research paper on technology in the classroom

Impact of Implementing New Technology Into K-12 Classrooms on Teacher Well-Being During the COVID-19 Pandemic

• Original Paper
• Published: 15 April 2024

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• Madeline Dunfee   ORCID: orcid.org/0000-0003-2134-8105 1 ,
• Heather Bush 1 ,
• Kate A. Leger 2 ,
• Timothy J. Hilbert 3 ,
• Candace Brancato 1 &
• Erin N. Haynes 1  

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At the start of the COVID-19 pandemic, K-12 teachers rapidly implemented new technologies to provide remote education, often with limited technological training and support. We tested whether teachers’ satisfaction with their technology training was associated with their perceived stress, depression, anxiety, well-being and sleep. The School Staff Health and Wellness Study has surveyed school staff about their experiences throughout the COVID-19 pandemic. A priori analyses included comparisons of well-being scores among teachers who were satisfied with their technology training, dissatisfied with their technology training and those who had not received technology training. We also explore qualitatively what additional technology-related responsibilities teachers had throughout Fall 2020. Participants included 5,873 K-12 teachers who identified predominately as female, White and Non-Hispanic. Most K-12 teachers (88%) had to learn new technology, and 54% reported being “not at all” or only “a little bit” satisfied with the technology training they received. Teachers who were satisfied with their training in new technology were less anxious, depressed, stressed, scored lower on measures of sleep disturbance and higher on measures of well-being compared to other groups. Understanding the association between training in new technology and teachers’ well-being will help school leaders support teachers amid future challenging circumstances.

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Acknowledgements

Thank you to all participants for their time and contributions. Thank you also to our School Staff Advisory Board for their valuable insights and assistance.

This research was supported by the Center for Clinical Translational Science and the NIH National Center for Advancing Translational Sciences through grant number 5TL1TR001997. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

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Madeline Dunfee, Heather Bush, Candace Brancato & Erin N. Haynes

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Conceptualization, M.D., E.H. and H.B.; methodology, M.D., E.H. and H.B.; formal analysis, M.D.; resources, M.D., E.H. and H.B.; data curation C.B. and M.D.; writing—original draft preparation M.D.; writing—review and editing, E.H., H.B., C. B., T.H., and K.L.; supervision, E.H.; project administration, C.B.; funding acquisition, E.H. and H.B. All authors have read and agreed to the final version of the manuscript.

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The study was conducted in accordance with the Declaration of Helsinki and was approved by the (blinded for review) Office of Research Integrity (Procedure #62619, 2020).

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Dunfee, M., Bush, H., Leger, K.A. et al. Impact of Implementing New Technology Into K-12 Classrooms on Teacher Well-Being During the COVID-19 Pandemic. TechTrends (2024). https://doi.org/10.1007/s11528-024-00957-y

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Accepted : 22 March 2024

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Learning through technology in middle school classrooms: Students’ perceptions of their self-directed and collaborative learning with and without technology

Chantal labonté.

Department of Educational Psychology, Faculty of Education, The University of Alberta, Edmonton, Alberta T6G 2G5 Canada

Veronica R. Smith

Associated data.

A copy of the questionnaire used in the study can be accessed by emailing the first author.

In the present study, students’ perceptions of their self-directed and collaborative learning with and without technology were examined in ICT-supported middle school classrooms. Three hundred and twenty middle school students from eight schools across Alberta, Canada participated in the study by completing a questionnaire. Descriptive statistics, independent sample t-test, one-way ANOVA and correlational analysis were used to analyse the questionnaire responses. Descriptive statistics revealed that middle school students perceive themselves as readily engaging in self-directed and collaborative learning within their classrooms. Students’ self-directed learning with and without technology was significantly related to the instructional quality in their classroom with lower instructional quality classrooms having a significant small effect on self-directed learning. Gender was also found to have a small effect, with girls more readily engaging in self-directed learning, although this difference was not sustained when using technology. When learning with technology, while indicating that they engage in self-directed learning within their classrooms, students reported less engagement in collaborative activities with their peers, particularly in earlier middle school grades. Students may benefit from additional support to engage in collaborative activities while using technology. Likewise, teachers may benefit from professional development to support their facilitation of self-directed learning and collaborative learning as well as implementation of technology within the classroom.

Introduction

Increased access to information communication technologies (ICT) in classrooms across the world over the last two decades has transformed pedagogical practices (Collins & Halverson, 2010 ). Most recently, the COVID-19 pandemic has necessitated the use of ICT, transforming student learning further, as students began home-based online learning at an unprecedented rate (Wen et al., 2021 ). As students return to in-person learning, emphasis remains on preparing students to enter our complex technology and media-driven environment where devices and applications change rapidly, information is readily accessible, and there are increasing opportunities for large-scale collaborations. Collaborative learning (CL) and self-directed learning (SDL) have been recognized as necessary competencies to prepare students for the current global knowledge society (Henry, 2015 ; Partnership for 21st Century Skills, 2011 ; Voogt & Roblin, 2012 ).

ICT has been recognized for its potential in supporting the development of SDL (Morris & Rohs, 2021 ) and CL (Akhigbe, 2021 ; Resta & Laferriere, 2007 ). With emphasis placed on fully utilizing ICT in the classroom, there is a need to understand how the development of SDL and CL can be promoted in ICT-supported learning environments, particularly within K-12 classrooms where research has been lacking (Morris & Rohs, 2021 ). Teachers’ positive perceptions and attitudes towards ICT have been identified as a significant factor in the successful integration of ICT in the classroom (Arkoful et al., 2021 ; Bas & Bastug, 2021 ; Khlaif, 2017 ; Semerci & Aydin, 2018 ; Xie et al., 2021 ). Students themselves also play a role in the success of ICT-supported learning and skill acquisition. Students’ perceptions of their learning affect motivation and the ability to succeed academically (Bandura, 1993 ; Schwartz et al., 2016 ). Therefore, there is a need to understand students’ perceived ability to engage in SDL and CL both with and without technology in order to better understand how to support students’ ability to take full advantage of their learning opportunities. The present study examines middle school students’ perceptions of their SDL and CL with and without technology.

Self-directed and collaborative learning

SDL has become an essential learning process for achieving meaningful educational outcomes. SDL occurs when knowledge, skills, or personal development are attained by an individual through his or her own efforts (Gibbons, 2002 ). During SDL, learners take initiative and responsibility for the planning, completion and review of their learning process and outcomes (Bolhuis, 2003 ; Garrison, 1997 ; Morris & Rohs, 2021 ). By doing so, they are able to customize their approach to learning tasks (Gibbons, 2002 ). Readiness towards SDL has been associated with a variety of meaningful learning skills and outcomes, including critical and logical thinking skills (Willett et al., 1983 ), academic achievement (Stewart, 2007 ), and an increase in students’ engagment and understanding of course content (Findlater et al., 2012 ).

SDL is often viewed as implying a purely individual pursuit of knowledge and learning goals (Bolhuis, 2003 ). However, students who are engaged in SDL may receive a variety of support from teachers and peers to complete their learning goals (Robertson, 2011 ). The quality of these interactions with teachers and peers has an influence on the student’s motivation to persist with their SDL goals (Sze-yeng & Hussain, 2010 ). Self-directed learners work closely with other students and adults (Gibbons, 2002 ). As such, SDL goes hand in hand with CL. CL refers to two or more students working towards a goal (Dillenbourg, 1999 ). When students are engaged in CL, they develop and work towards a shared learning goal (Clark, 2001 ; Dillenbourg, 1999 ), and take on the perspective that others are a source of expertise and knowledge (Henry, 2015 ). In the classroom, CL occurs during tasks that encourage students to assist each other in such a way that the less competent members will benefit from the assistance that they receive from the more skillful peers whose learning is advantaged in return by their role as teacher (Bjorklund, 2012 ). CL has been associated with greater conceptual understanding (O'Donnell, 2006 ), greater academic achievement (Hussain et al., 2011 ; Springer et al., 1999 ), great content knowledge and skills (Hussain et al., 2011 ; Terenzini et al., 2001 ), and greater critical thinking skills (Gokhale, 1995 ).

ICT-supported self-directed learning and collaborative learning

Within an ICT-supported learning environment, students learn in an environment that blends face-to-face and technology-based activities. ICT provides instructional affordances to facilitate both SDL (Morris & Rohs, 2021 ) and CL (Akhigbe, 2021 ; Resta & Laferriere, 2007 ). Students in K-12 classrooms perceived the use of technology in their classroom to be important for their learning (Quaddumi et al., 2021 ). While ICT can support the acquisition and use of these skills, technology itself cannot have an impact on students who have not developed collaborative and self-directed learning processes (Lee et al., 2014 ).

When adult learners used web platforms, such as Moodle, Google Classroom, and Wikispaces , researchers have found that the use of technology empowers students’ ability to engage in SDL, although participants experienced an initial learning curve (Sze-yeng & Hussain, 2010 ). Within the higher education setting, students with higher perceptions of their ICT-supported learning tended to be more engaged and demonstrated greater outcomes (Cole et al., 2021 ). In university students, SDL skills were associated with ICT-supported learning, while gender and age were not related to ICT use (Lee et al., 2017 ). Among high school students, students’ ICT-supported SDL did not differ across gender (Eroglu & Ozbek, 2018 ; Gokcearslan, 2017 ). Among a sample of Grade 8 students, Dwiyanti et al. ( 2020 ) found that, while students were generally ready to engage in online learning, students continued to require support to develop their SDL skills and online communication self-efficacy (Dwiyanti et al., 2020 ). Within K-12 learning, Bartholomew et al. ( 2017 ) found that access to mobile devices was significantly related to higher student performance, although it was not significantly related to SDL processes. Students often require support and guidance on how to use ICT in order to effectively engage in SDL (Morris & Rohs, 2021 ).

When technology is introduced within CL, the CL processes have been found to be similar to when learning without technology (Garris et al., 2018 ). ICT tools can be used to mediate access to shared content and the quick and efficient exchange of ideas (Shamir-Inbal & Blau, 2021 ). When engaging in CL in online environments, some students may feel less intimidated to participate in group discussions than in a face-to-face context, affording those students equal access to participation (O'Donnell, 2006 ). Among higher education students, students’ use of social media and interactions with their peers and teachers influence students’ engagement in CL and their learning performance (Qureshi et al., 2021 ). Male higher education students have demonstrated greater readiness and aptitude towards technology-supported CL (Khalifeh et al., 2020 ). When higher-education students engaged in CL within online networks, students experience higher academic achievement, greater mastery of subject matter, and increased success during problem-solving tasks, compared to students who engage in computer-mediated learning independently (Resta & Laferriere, 2007 ). Higher education students also perceived ICT-supported CL to enhance their learning outcomes (Tanrikulu, 2020 ).

Present study

With the increased access to ICTs and a push towards developing SDL and CL competencies within classrooms, there is a need to understand students’ perceived ability to engage in SDL and CL both with and without technology in order to better understand how to support students’ ability to take full advantage of their learning. Given the relationship between students’ SDL and CL in non-technological settings and their ability to engage in SDL and CL with technology (Lee et al., 2014 ), the assessment of students’ perceptions of their learning skills is of a particular interest as students’ perceptions and beliefs about their learning have an effect on their ability to succeed academically (Bandura, 1993 ; Schwartz et al., 2016 ). By examining the extent that students apply SDL and CL across settings, the development of pedagogical practices that foster and facilitate SDL and CL in ICT-supported classrooms can be developed and bolstered. Despite the importance of SDL and CL, the development of these learning processes are not yet fully understood in the K-12 setting, with research lacking in many areas (Morris & Rohs, 2021 ). The present study examines middle school students’ perceptions of their SDL and CL with and without technology. The research is guided by the following question: To what extent do middle school students perceive themselves to be engaged in SDL and CL in their ICT-supported classrooms?

The study was conducted in Alberta, Canada where technology is readily available and accessible in K to 12 classrooms through provincial governmental policies. Alberta Education’s Learning and Technology Policy Framework (Alberta Education, 2013 ) articulates the commitment to ICT-supported SDL and CL within the province, and calls for technology to be used as a means tor provide students with a variety of ways to “learn, communicate, collaborate, ask important questions, solve problems, and demonstrate what they know and can do”, (Alberta Education, 2013 ; p. 21) allowing for students the choice of how they wish to engage in their learning. To facilitate the implementation of ICTs within classrooms, Alberta Education provided infrastructure (i.e., Internet connectivity, technological tools such as computers and tablets) for schools and resources for teachers (Pich & Kim, 2004 ). Given the emerging use of technology in Alberta classrooms, we hypothesize that students will perceive themselves to readily engage in SDL and CL with and without technology in their classrooms.

Research design

This study employed a survey design with descriptive analyses, correlational analyses and an analysis of variance used to explore the extent that middle school students perceive themselves to engage in SDL and CL with and without technology. A survey design allows for a quantitative description of trends within a population by studying a sample drawn from the population (Cresswell, 2014 ).

Participants

Three hundred and twenty-five students (52.6% male) from 8 schools and 19 classrooms across 5 school jurisdictions were asked to participate by completing a questionnaire. Of these students, five students did not complete all the items in the questionnaire. Results of Little’s ( 1988 ) missing completely at random (MCAR) test were non-significant (chi-square = 9.82, df = 26, sig = 0.998), suggesting that the missing items were missing at random. Given that only a few cases had missing values and they were found to be missing at random, all 5 participants with missing values were deleted from the data set (Tabachnick & Fidell, 2014 ). A total of 320 students enrolled in grades 5 to 9 were retained. The total population of students in these grades in Alberta was 236,268 at the time of data collection according to available Alberta Education data. (Alberta Education, n.d. ). Students were enrolled in grades 5 to 9. The majority of students were in Grade 8 (55.3% of the sample). Table  1 provides the distribution of students in each grade per school. All students were in inclusive ICT-supported classrooms where students with mild to moderate learning needs ranged from 10 to 85% per classroom. 64.4% (n = 206) of the participants came from English speaking families.

Distribution of students in each grade per school

Participating schools were part of a larger study. All school jurisdictions across Alberta were invited to participate in the study. Eight schools across five school jurisdictions participated based on expressed interest and availability of teaching staff. Participating schools were located in both rural and population centers across various regions of Alberta, Canada. A rural centre refers to areas outside of population centers, defined as areas with a population of at least 1000 and a population density of at least 400 people per square kilometre. Small population centres have a population between 1000 and 29,999, whereas medium population centres have a population between 30,000 and 99,999. Four schools were located in areas classified as small population centers and 2 schools were located in areas classified as medium population centers based on the 2011 Canadian census population estimates (Statistics Canada, 2011 ).

ICT was integrated into students’ classrooms across subject areas. A variety of technological devices (e.g. laptops, tablets, smartphones) were used in participating classrooms to complete assigned tasks, access learning management systems, create reports and presentations, access information using the Internet, and use a variety of applications for multimedia creations. Student technology use varied by classroom but, on average, students actively used technology for educational purposes 71.22% of the time. Observations of teacher technology use revealed that the majority of the time (66.63%) teachers used technology indirectly as a means to support their practice.

Teachers all provided a similar quality of instruction in their classroom. The quality of classroom instructional across students was measured using the Classroom Assessment Scoring System-Secondary (CLASS-S), an observational protocol used to examine the quality of classroom practice across the domains of emotional support, classroom organization and instructional support (Pianta et al., 2012 ). Using the CLASS-S, coders assign a score along a scale from one to seven where a score of 1 or 2 falls within the low range, a score of 3 to 5 falls within the mid-range, and a score of 6 to 7 falls within the high range. Teachers were observed across at least two complete classroom sessions. Across all 19 teachers, aggregated across observational periods, the average quality of instruction fell within the mid-range at 4.75, with a minimum score of 4.14 and a maximum score of 5.80 (SD = 0.39). Across aggregated observations, teachers provided instruction that was of mid-range in quality based on the CLASS-S.

Data were collected and managed using REDCap electronic data capture tools (Harris et al., 2009 ). The study questionnaire was administered, via REDCap, to students mid-school year. Students completed the questionnaire within their respective classrooms. A research assistant provided instructions via video embedded within the online platform to help students complete the questionnaire. The computer read each item aloud to the student.

Students’ perceptions of their SDL and CL with and without technology within ICT-supported classroom environments was assessed using a 14-item questionnaire found to be reliable and valid with middle school students in Canada (Labonté & Smith, 2019 ). The questionnaire is adapted from Lee et al. ( 2014 ) who initially developed the questionnaire in order to understand high school students’ SDL and CL in ICT-supported classrooms in Singapore (Lee et al., 2014 ). The questionnaire was selected based on its evidence of validity for use with our sample (Labonté & Smith, 2019 ) and its alignment with the purpose of the research (Lee et al., 2014 ). The questionnaire assesses students’ perceptions of their learning across four scales:

• self-directed learning without technology (SDL) scale; this scale is comprised of 3 items and measures students’ perceptions of the extent of their ability to direct their learning in face-to-face non-technological settings and includes items such as ‘In this class, I try to determine the best way to work on the assignments.’,
• collaborative learning without technology (CL) scale; this 4-item scale assesses students’ perceptions of their participation in CL opportunities such as group discussions within face-to-face non-technological settings and includes items such as ‘In this class, my classmates and I actively work together to help each other understand the material.’,
• self-directed learning with technology (SDLT) scale; which is made up of 4 items and measures student’s perceptions of their role in directing their learning in ICT-supported learning environments including items like ‘In this class, I use the computer to keep track of my learning progress.’, and
• collaborative learning with technology (CLT) scale; this 3-item scale assesses student’s perceptions of their participation in CL opportunities such as group discussions in ICT-supported learning environments and includes items such as ‘In this class, my classmates and I actively communicate via online platforms (e.g. Forum, MSN, wiki) to learn new things together.’.

Each item required a response on a 7-point Likert scale (i.e., 1- strongly disagree, 7-strongly agree). The average ratings of items within a scale was used as the scale score.

Examination of the mean and standard deviations, found in Table  2 , reveals that, overall, students in our sample report their SDL, CL, and SDLT as slightly more agreeable (means over 5). The mean score for CLT is 4.27 on the 7-point Likert scale. The SDL scale had the highest mean scale, and the CLT scale is the lowest scale, on average. An examination of the range of students’ responses revealed that for all questionnaire items students endorsed the full range of Likert response possibilities (i.e., strongly disagree to strongly agree).

Descriptive statistics for SDL, CL, SDLT, and CLT scales and their corresponding items

Correlation analysis revealed a significant relationship ( p  = 0.04) between instructional quality and ratings of SDL. No other significant relationships between overall instructional quality and students’ perceptions of their learning were found. When students’ ratings were examined based on whether they were in a classroom with high or low levels of instructional quality (groups separated by the median score of 4.697), t-test analysis revealed a significant difference among the ratings of students on SDL ( p  = 0.008) and SDLT ( p  = 0.001). Students who were in classrooms with lower ratings (n = 163) of instructional quality reported an average rating of 5.46 (SD = 1.03) for SDL and an average rating of 5.44 (SD = 1.01) on SDLT, whereas students who were in classrooms with higher ratings of instructional quality (n = 157) reported an average rating of 5.15 (SD = 1.03) on SDL and an average rating of 4.98 (SD = 1.34) on SDLT. The effect of the quality of instructional was found to be small, with a Cohen’s d of 0.30 SD.

Students’ perceptions of their learning were examined across gender and grade. Correlation analysis revealed a significant relationship between gender and SDL ( p  = 0.05). No significant relationships were found among the other scales and gender. A one-way analysis of variance revealed a significant gender difference ( p  = 0.05) on the SDL scale. Girls reported a mean score of 5.43 (SD = 1.06) on the SDL scale, whereas males reported a mean score of 5.20 (SD = 1.02). The effect of gender was found to be small, with a Cohen’s d of 0.22 SD. No significant difference was found among the other scales across genders. When the difference between gender was examined based on the students’ respective grades, only a significant difference between boys (M = 5.10, SD = 1.11) and girls (M = 5.50, SD = 1.11) was found among grade 8 students. Grade 8 students make up the largest subset of the sample, with 177 grade 8 students included.

Correlation analyses did not find any significant relationships between grades and the four scales measured. However, a one-way analysis of variance revealed that students’ CLT varied across grades (F (4,315) = 2.93, p  = 0.02). Despite reaching a level of statistical significance, the actual difference in mean scores across grades for CLT was small (eta squared of 0.04). Post-hoc comparisons using the Tukey HSD test indicated that the perception of grade 5 students’ CLT (M = 2.7, SD = 1.49) was significantly different from that of grade 7 students (M = 4.38, SD = 1.18), grade 8 students (M = 4.30, SD = 1.57), and from that of grade 9 students (M = 4.33, SD = 1.42) at a 0.05 level.

Twenty-first century learners need to be prepared for the global knowledge society. CL and SDL have been recognized as necessary competencies that students need to acquire (Henry, 2015 ; Partnership for 21st Century Skills, 2011 ; Voogt & Roblin, 2012 ). Despite a focus on these skills, their development is not fully undestood within a K-12 setting (Morris & Rohs, 2021 ). The aim of the present study was to explore middle school students’ perceptions of their CL and SDL with and without technology. The assessment of students’ learning skills both with and without technology is of particular interest to educators as students’ who have not developed collaborative and self-directed ways of learning may not be able to take full advantage of the benefits of ICT-supported learning. Additionally, the assessment of students’ perceptions of the extent of their ability to engage in SDL and CL is an important consideration as students’ perceptions and beliefs about their learning have a direct effect on their ability to learn and succeed (Bandura, 1993 ; Schwartz et al., 2016 ).

Our results suggest that students readily engage in SDL and CL during non-technology supported learning. On average, no student in the sample strongly disagreed in their ability to engage in some degree of SDL and CL in their classrooms. Middle school students are indeed readily engaging with both SDL and CL. Students perceived engagement in SDL and CL in non-technology supported learning environments suggests that they are using and acquiring CL and SDL skills. Lee et al. ( 2014 ) found a positive relationship exists between SDL and CL use without technology and with technology among high school students in Singapore, in such a way that students’ ability to engage in SDL and CL without technology predicted their ability to do with technology (Lee et al., 2014 ). The finding that students are engaging in SDL and CL without technology holds promise for their ability to do so when learning with technology, and suggests that students are acquiring necessary learning skills to allow them to take full advantage of learning in technology-supported environments.

When asked about their perceived engagement in SDL in technology-supported learning environments, students, on average, reported readily engaging in SDL, although the range of scale scores suggest that some students strongly disagree with the notion that they engage in SDL with technology to any extent. When asked about their perceived engagement in CL in technology-supported learning environments, students reported less engagement, on average, in collaborative activites with technology in their classrooms. The range of scale scores suggest that some students are readily engaging (i.e, agree and strongly agree) in such tasks while other students are not (i.e., ratings of disagree and strongly disagree). The results suggest that although students have the skills to engage in CL when not using technology, they may require additonal support and opportunitity to engage in CL with technology in their classrooms. Students may benefit from additional support to use technology in collaborative tasks. Tools such as email, online chat forums, blogs, wikis, videoconferencing systems, and course management systems have all been used to support online CL (Resta & Laferriere, 2007 ). These Internet tools and technologies allow for an active rather than a passive process of receiving and evaluating information (Domalewska, 2014 ). Additionally, CL with technology does not only occur within online networks, it can also occur when peers engage in the use of ICT together collaboratively (Blaye et al., 1991 ). Teachers might benefit from additional professional development to support their ability to integrate technology for various uses in their classrooms.

Are students’ perception of their learning influenced by the instructional quality in their classroom? Our results suggest that the instructional quality experienced in the classroom did not have a significant impact on students perceived ability to engage in CL and CLT. However, the quality of instruction in the classroom did influence students’ perception of their engagement in SDL and SDLT. Students who were in classrooms with lower levels of instructional quality perceived themselves to be more engaged in SDL processes with and without technology compared to students who received a higher quality instructional support. It appears that in classrooms where teachers were observed to provide lower levels of direct instructional support that students were able to be more independent in their learning resulting in more students taking initiative and responsibility over their learning. Further research is required to better understand the relationship between SDL and teacher’s instructional quality and pedagogical approaches in ICT-supported classrooms.

Students’ perception of their engagement in SDL and CL with and without technology differ across both gender and grades. Overall, girls reported more perceived ability to engage in SDL compared to boys. However, the effect size of the differences in means across gender was small. When gender was covaried by graded, a statistically significant difference on SDL only remained for grade 8 students who make up the largest subset of the sample. An effect of gender has not been found within older samples of higher education students (Lee et al., 2017 ) or high school students (Eroglu & Ozbek, 2018 ). From a maturation perspective, grade 8 girls undergo developmental changes associated with puberty that may allow them to more easily engaged in self-directed processes compared to boys of the same age. Neuropsychological research into the development of executive functioning skills has demonstrates that task performance dips at the onset of puberty but then improves again after puberty (Blakemore & Choudhury, 2006 ). Executive functioning refers to a set of basic information-processing abilities used to regulate attention and goal-oriented behaviour. Children rely on executive functioning abilities to engage in complex social and cognitive activities (Bjorklund, 2012 ). When engaging in SDL, students must be able to prepare and plan their learning, to carry out learning independently, and to adjust their behaviour in order to reach their learning goal (Robertson, 2011 ). Executive functioning is one psychological function that allows students to carry out SDL (Simons, 2000 ). The onset of puberty decreases performance on tasks requiring executive functioning, which may result in less engagement in SDL. The onset of puberty occurs earlier for girls (10 to 11 years of age) compared to boys (11 to 12 years of age) (Blakemore & Choudhury, 2006 ). Given that students are typically 12 to 13 years of age in grade 8, girls, whose onset of puberty occurs earlier than boys, may be more able to engage in SDL. While this maturation view of executive functioning is well documented in neuropsychological literature, the pattern of difference in SDL engagement between girls and boys was not found for Grade 6 and 7 students which is when we would expect the onset of puberty to occur for girls. Further research is required to better understand the role of the development of executive function, and other cognitive skills, related to SDL.

Limitations and future research

The sample was a non-probabilistic convenience sample. Although convenience samples are commonly used in research, a non-random sample limits the generalization of the results (Elfil & Negida, 2017 ). Further research among middle school students is required. Within our sample, a significant limitation is that students were not equally distributed across grades. Students in grade 5 made up only a small percentage (3.1%) of the overall sample of students, whereas grade 8 students made up the largest percentage of the overall sample (55.3%). The uneven distribution of students may have limited our ability to detect statistical differences across grades. Additional research is needed to examine difference in SDL and CL in ICT-supported classroom across the middle school grades.

Based on the individual items in the questionnaire, it is impossible to conclude whether the variance in students’ perceived engagement in SDL and CL is due to individual differences in students’ proficiency in engaging in SDL and CL, or if the difference in students’ perceived ability to engage in SDL and CL is due to variation in pedagogical appproaches to using ICT in their respective classrooms. Across Alberta, a variety of technology implementation strategies have been adopted by schools. Jurisdiction technology implementation strategies may influence pedagogical practices surrounding the use of ICT for SDL and CL. Furthermore, pedagogical differences across grade level may also influence the opportunities for students to engage in SDL and CL. For example, grade 5 students report less perceived engagement in CL with technology than grade 7, 8, and 9 students. Pedagogical differences may allow grade 7, 8, and 9 students more opportunities to engage in CL with technology than grade 5 students. Additionally, differences in the approaches of integrating ICT for SDL and CL may differ across subject areas. Although students in our sample experienced the use of ICT across subject areas, some subject areas may more easily and effectively lend themselves to certain pedagogical approaches over others. Futher research is needed to better understand the factors that contribute to the variation in students’ engagement with SDL and CL in their ICT-supported classrooms.

Practical implications

SDL and CL skills are recognized for their importance in preparing students for the current global knowledge society (Henry, 2015 ; Partnership for 21st Century Skills, 2011 ; Voogt & Roblin, 2012 ). Students in our sample are engaging in SDL and CL within their classrooms, although teachers who offer less instructional support tended to have students who are more engaged in SDL compared to teachers with higher instructional quality. In order for SDL to occur, teachers must provides students with the opportunities to take initiative, planning and responsibility over their learning (Morris & Rohs, 2021 ).

When learning with ICTs, middle school students require more support and opportunity to engage in ICT-supported learning, particularly in the area of CL. Teachers may benefit from additional professional development and support to facilitated ICT-supported CL, particularly in early grades as CLT was less common among Grade 5 students in our sample. Within our middle school sample, girls appear to be more developmentally prepared to engage in SDL compared to boys. However, this effect disappears when using technology. Students continue to require support to develop SDL and CL skills, even when readily engaged in ICT-supported learning. This is consisent with prior research in both K-12 and higher education settings (Bartholomew et al., 2017 ; Dwiyanti et al., 2020 ; Lee et al., 2014 ; Morris & Rohs, 2021 ).

The present study examined middle school students’ perceptions of their CL and SDL with and without technology. To our knowledge, this is the first study to examine middle school students’ perceptions of both SDL and CL with and without technology, contributing to a limit body of literature on students’ perceptions of their ICT-supported learning. The results revealed that students are engaging in SDL and CL in their classrooms. Students indicated that they engage less in collaborative activities (i.e., sharing ideas, discussion, working with peers) with technology. Girls tend to more readily engage in SDL but this gender-based difference disappears when learning with technology.

Acknowledgements

Parts of this paper were developed as a Masters of Education thesis by the first author. Funds received by Veronica R. Smith from Alberta Education “Flexible Pathways to Success: Technology to Design for Diversity” grant supported this study.

Code availability

Not applicable.

Funds from Alberta Education “Flexible Pathways to Success: Technology to Design for Diversity” grant supported this study.

Data availability

Declarations.

The authors declare that they do not have any conflict of interest. The Research Ethics Board at the University of Alberta approved all study procedures.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Chantal Labonté, Email: ac.atreblau@etnobalc .

Veronica R. Smith, Email: ac.atreblau@2sv .

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REALIZING THE PROMISE:

Leading up to the 75th anniversary of the UN General Assembly, this “Realizing the promise: How can education technology improve learning for all?” publication kicks off the Center for Universal Education’s first playbook in a series to help improve education around the world.

It is intended as an evidence-based tool for ministries of education, particularly in low- and middle-income countries, to adopt and more successfully invest in education technology.

While there is no single education initiative that will achieve the same results everywhere—as school systems differ in learners and educators, as well as in the availability and quality of materials and technologies—an important first step is understanding how technology is used given specific local contexts and needs.

The surveys in this playbook are designed to be adapted to collect this information from educators, learners, and school leaders and guide decisionmakers in expanding the use of technology.  

Introduction

While technology has disrupted most sectors of the economy and changed how we communicate, access information, work, and even play, its impact on schools, teaching, and learning has been much more limited. We believe that this limited impact is primarily due to technology being been used to replace analog tools, without much consideration given to playing to technology’s comparative advantages. These comparative advantages, relative to traditional “chalk-and-talk” classroom instruction, include helping to scale up standardized instruction, facilitate differentiated instruction, expand opportunities for practice, and increase student engagement. When schools use technology to enhance the work of educators and to improve the quality and quantity of educational content, learners will thrive.

Further, COVID-19 has laid bare that, in today’s environment where pandemics and the effects of climate change are likely to occur, schools cannot always provide in-person education—making the case for investing in education technology.

Here we argue for a simple yet surprisingly rare approach to education technology that seeks to:

• Understand the needs, infrastructure, and capacity of a school system—the diagnosis;
• Survey the best available evidence on interventions that match those conditions—the evidence; and
• Closely monitor the results of innovations before they are scaled up—the prognosis.

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The framework.

Our approach builds on a simple yet intuitive theoretical framework created two decades ago by two of the most prominent education researchers in the United States, David K. Cohen and Deborah Loewenberg Ball. They argue that what matters most to improve learning is the interactions among educators and learners around educational materials. We believe that the failed school-improvement efforts in the U.S. that motivated Cohen and Ball’s framework resemble the ed-tech reforms in much of the developing world to date in the lack of clarity improving the interactions between educators, learners, and the educational material. We build on their framework by adding parents as key agents that mediate the relationships between learners and educators and the material (Figure 1).

Figure 1: The instructional core

Adapted from Cohen and Ball (1999)

As the figure above suggests, ed-tech interventions can affect the instructional core in a myriad of ways. Yet, just because technology can do something, it does not mean it should. School systems in developing countries differ along many dimensions and each system is likely to have different needs for ed-tech interventions, as well as different infrastructure and capacity to enact such interventions.

The diagnosis:

How can school systems assess their needs and preparedness.

A useful first step for any school system to determine whether it should invest in education technology is to diagnose its:

• Specific needs to improve student learning (e.g., raising the average level of achievement, remediating gaps among low performers, and challenging high performers to develop higher-order skills);
• Infrastructure to adopt technology-enabled solutions (e.g., electricity connection, availability of space and outlets, stock of computers, and Internet connectivity at school and at learners’ homes); and
• Capacity to integrate technology in the instructional process (e.g., learners’ and educators’ level of familiarity and comfort with hardware and software, their beliefs about the level of usefulness of technology for learning purposes, and their current uses of such technology).

Before engaging in any new data collection exercise, school systems should take full advantage of existing administrative data that could shed light on these three main questions. This could be in the form of internal evaluations but also international learner assessments, such as the Program for International Student Assessment (PISA), the Trends in International Mathematics and Science Study (TIMSS), and/or the Progress in International Literacy Study (PIRLS), and the Teaching and Learning International Study (TALIS). But if school systems lack information on their preparedness for ed-tech reforms or if they seek to complement existing data with a richer set of indicators, we developed a set of surveys for learners, educators, and school leaders. Download the full report to see how we map out the main aspects covered by these surveys, in hopes of highlighting how they could be used to inform decisions around the adoption of ed-tech interventions.

The evidence:

How can school systems identify promising ed-tech interventions.

There is no single “ed-tech” initiative that will achieve the same results everywhere, simply because school systems differ in learners and educators, as well as in the availability and quality of materials and technologies. Instead, to realize the potential of education technology to accelerate student learning, decisionmakers should focus on four potential uses of technology that play to its comparative advantages and complement the work of educators to accelerate student learning (Figure 2). These comparative advantages include:

• Scaling up quality instruction, such as through prerecorded quality lessons.
• Facilitating differentiated instruction, through, for example, computer-adaptive learning and live one-on-one tutoring.
• Expanding opportunities to practice.
• Increasing learner engagement through videos and games.

Figure 2: Comparative advantages of technology

Here we review the evidence on ed-tech interventions from 37 studies in 20 countries*, organizing them by comparative advantage. It’s important to note that ours is not the only way to classify these interventions (e.g., video tutorials could be considered as a strategy to scale up instruction or increase learner engagement), but we believe it may be useful to highlight the needs that they could address and why technology is well positioned to do so.

When discussing specific studies, we report the magnitude of the effects of interventions using standard deviations (SDs). SDs are a widely used metric in research to express the effect of a program or policy with respect to a business-as-usual condition (e.g., test scores). There are several ways to make sense of them. One is to categorize the magnitude of the effects based on the results of impact evaluations. In developing countries, effects below 0.1 SDs are considered to be small, effects between 0.1 and 0.2 SDs are medium, and those above 0.2 SDs are large (for reviews that estimate the average effect of groups of interventions, called “meta analyses,” see e.g., Conn, 2017; Kremer, Brannen, & Glennerster, 2013; McEwan, 2014; Snilstveit et al., 2015; Evans & Yuan, 2020.)

*In surveying the evidence, we began by compiling studies from prior general and ed-tech specific evidence reviews that some of us have written and from ed-tech reviews conducted by others. Then, we tracked the studies cited by the ones we had previously read and reviewed those, as well. In identifying studies for inclusion, we focused on experimental and quasi-experimental evaluations of education technology interventions from pre-school to secondary school in low- and middle-income countries that were released between 2000 and 2020. We only included interventions that sought to improve student learning directly (i.e., students’ interaction with the material), as opposed to interventions that have impacted achievement indirectly, by reducing teacher absence or increasing parental engagement. This process yielded 37 studies in 20 countries (see the full list of studies in Appendix B).

Scaling up standardized instruction

One of the ways in which technology may improve the quality of education is through its capacity to deliver standardized quality content at scale. This feature of technology may be particularly useful in three types of settings: (a) those in “hard-to-staff” schools (i.e., schools that struggle to recruit educators with the requisite training and experience—typically, in rural and/or remote areas) (see, e.g., Urquiola & Vegas, 2005); (b) those in which many educators are frequently absent from school (e.g., Chaudhury, Hammer, Kremer, Muralidharan, & Rogers, 2006; Muralidharan, Das, Holla, & Mohpal, 2017); and/or (c) those in which educators have low levels of pedagogical and subject matter expertise (e.g., Bietenbeck, Piopiunik, & Wiederhold, 2018; Bold et al., 2017; Metzler & Woessmann, 2012; Santibañez, 2006) and do not have opportunities to observe and receive feedback (e.g., Bruns, Costa, & Cunha, 2018; Cilliers, Fleisch, Prinsloo, & Taylor, 2018). Technology could address this problem by: (a) disseminating lessons delivered by qualified educators to a large number of learners (e.g., through prerecorded or live lessons); (b) enabling distance education (e.g., for learners in remote areas and/or during periods of school closures); and (c) distributing hardware preloaded with educational materials.

Prerecorded lessons

Technology seems to be well placed to amplify the impact of effective educators by disseminating their lessons. Evidence on the impact of prerecorded lessons is encouraging, but not conclusive. Some initiatives that have used short instructional videos to complement regular instruction, in conjunction with other learning materials, have raised student learning on independent assessments. For example, Beg et al. (2020) evaluated an initiative in Punjab, Pakistan in which grade 8 classrooms received an intervention that included short videos to substitute live instruction, quizzes for learners to practice the material from every lesson, tablets for educators to learn the material and follow the lesson, and LED screens to project the videos onto a classroom screen. After six months, the intervention improved the performance of learners on independent tests of math and science by 0.19 and 0.24 SDs, respectively but had no discernible effect on the math and science section of Punjab’s high-stakes exams.

One study suggests that approaches that are far less technologically sophisticated can also improve learning outcomes—especially, if the business-as-usual instruction is of low quality. For example, Naslund-Hadley, Parker, and Hernandez-Agramonte (2014) evaluated a preschool math program in Cordillera, Paraguay that used audio segments and written materials four days per week for an hour per day during the school day. After five months, the intervention improved math scores by 0.16 SDs, narrowing gaps between low- and high-achieving learners, and between those with and without educators with formal training in early childhood education.

Yet, the integration of prerecorded material into regular instruction has not always been successful. For example, de Barros (2020) evaluated an intervention that combined instructional videos for math and science with infrastructure upgrades (e.g., two “smart” classrooms, two TVs, and two tablets), printed workbooks for students, and in-service training for educators of learners in grades 9 and 10 in Haryana, India (all materials were mapped onto the official curriculum). After 11 months, the intervention negatively impacted math achievement (by 0.08 SDs) and had no effect on science (with respect to business as usual classes). It reduced the share of lesson time that educators devoted to instruction and negatively impacted an index of instructional quality. Likewise, Seo (2017) evaluated several combinations of infrastructure (solar lights and TVs) and prerecorded videos (in English and/or bilingual) for grade 11 students in northern Tanzania and found that none of the variants improved student learning, even when the videos were used. The study reports effects from the infrastructure component across variants, but as others have noted (Muralidharan, Romero, & Wüthrich, 2019), this approach to estimating impact is problematic.

A very similar intervention delivered after school hours, however, had sizeable effects on learners’ basic skills. Chiplunkar, Dhar, and Nagesh (2020) evaluated an initiative in Chennai (the capital city of the state of Tamil Nadu, India) delivered by the same organization as above that combined short videos that explained key concepts in math and science with worksheets, facilitator-led instruction, small groups for peer-to-peer learning, and occasional career counseling and guidance for grade 9 students. These lessons took place after school for one hour, five times a week. After 10 months, it had large effects on learners’ achievement as measured by tests of basic skills in math and reading, but no effect on a standardized high-stakes test in grade 10 or socio-emotional skills (e.g., teamwork, decisionmaking, and communication).

Drawing general lessons from this body of research is challenging for at least two reasons. First, all of the studies above have evaluated the impact of prerecorded lessons combined with several other components (e.g., hardware, print materials, or other activities). Therefore, it is possible that the effects found are due to these additional components, rather than to the recordings themselves, or to the interaction between the two (see Muralidharan, 2017 for a discussion of the challenges of interpreting “bundled” interventions). Second, while these studies evaluate some type of prerecorded lessons, none examines the content of such lessons. Thus, it seems entirely plausible that the direction and magnitude of the effects depends largely on the quality of the recordings (e.g., the expertise of the educator recording it, the amount of preparation that went into planning the recording, and its alignment with best teaching practices).

These studies also raise three important questions worth exploring in future research. One of them is why none of the interventions discussed above had effects on high-stakes exams, even if their materials are typically mapped onto the official curriculum. It is possible that the official curricula are simply too challenging for learners in these settings, who are several grade levels behind expectations and who often need to reinforce basic skills (see Pritchett & Beatty, 2015). Another question is whether these interventions have long-term effects on teaching practices. It seems plausible that, if these interventions are deployed in contexts with low teaching quality, educators may learn something from watching the videos or listening to the recordings with learners. Yet another question is whether these interventions make it easier for schools to deliver instruction to learners whose native language is other than the official medium of instruction.

Distance education

Technology can also allow learners living in remote areas to access education. The evidence on these initiatives is encouraging. For example, Johnston and Ksoll (2017) evaluated a program that broadcasted live instruction via satellite to rural primary school students in the Volta and Greater Accra regions of Ghana. For this purpose, the program also equipped classrooms with the technology needed to connect to a studio in Accra, including solar panels, a satellite modem, a projector, a webcam, microphones, and a computer with interactive software. After two years, the intervention improved the numeracy scores of students in grades 2 through 4, and some foundational literacy tasks, but it had no effect on attendance or classroom time devoted to instruction, as captured by school visits. The authors interpreted these results as suggesting that the gains in achievement may be due to improving the quality of instruction that children received (as opposed to increased instructional time). Naik, Chitre, Bhalla, and Rajan (2019) evaluated a similar program in the Indian state of Karnataka and also found positive effects on learning outcomes, but it is not clear whether those effects are due to the program or due to differences in the groups of students they compared to estimate the impact of the initiative.

In one context (Mexico), this type of distance education had positive long-term effects. Navarro-Sola (2019) took advantage of the staggered rollout of the telesecundarias (i.e., middle schools with lessons broadcasted through satellite TV) in 1968 to estimate its impact. The policy had short-term effects on students’ enrollment in school: For every telesecundaria per 50 children, 10 students enrolled in middle school and two pursued further education. It also had a long-term influence on the educational and employment trajectory of its graduates. Each additional year of education induced by the policy increased average income by nearly 18 percent. This effect was attributable to more graduates entering the labor force and shifting from agriculture and the informal sector. Similarly, Fabregas (2019) leveraged a later expansion of this policy in 1993 and found that each additional telesecundaria per 1,000 adolescents led to an average increase of 0.2 years of education, and a decline in fertility for women, but no conclusive evidence of long-term effects on labor market outcomes.

It is crucial to interpret these results keeping in mind the settings where the interventions were implemented. As we mention above, part of the reason why they have proven effective is that the “counterfactual” conditions for learning (i.e., what would have happened to learners in the absence of such programs) was either to not have access to schooling or to be exposed to low-quality instruction. School systems interested in taking up similar interventions should assess the extent to which their learners (or parts of their learner population) find themselves in similar conditions to the subjects of the studies above. This illustrates the importance of assessing the needs of a system before reviewing the evidence.

Preloaded hardware

Technology also seems well positioned to disseminate educational materials. Specifically, hardware (e.g., desktop computers, laptops, or tablets) could also help deliver educational software (e.g., word processing, reference texts, and/or games). In theory, these materials could not only undergo a quality assurance review (e.g., by curriculum specialists and educators), but also draw on the interactions with learners for adjustments (e.g., identifying areas needing reinforcement) and enable interactions between learners and educators.

In practice, however, most initiatives that have provided learners with free computers, laptops, and netbooks do not leverage any of the opportunities mentioned above. Instead, they install a standard set of educational materials and hope that learners find them helpful enough to take them up on their own. Students rarely do so, and instead use the laptops for recreational purposes—often, to the detriment of their learning (see, e.g., Malamud & Pop-Eleches, 2011). In fact, free netbook initiatives have not only consistently failed to improve academic achievement in math or language (e.g., Cristia et al., 2017), but they have had no impact on learners’ general computer skills (e.g., Beuermann et al., 2015). Some of these initiatives have had small impacts on cognitive skills, but the mechanisms through which those effects occurred remains unclear.

To our knowledge, the only successful deployment of a free laptop initiative was one in which a team of researchers equipped the computers with remedial software. Mo et al. (2013) evaluated a version of the One Laptop per Child (OLPC) program for grade 3 students in migrant schools in Beijing, China in which the laptops were loaded with a remedial software mapped onto the national curriculum for math (similar to the software products that we discuss under “practice exercises” below). After nine months, the program improved math achievement by 0.17 SDs and computer skills by 0.33 SDs. If a school system decides to invest in free laptops, this study suggests that the quality of the software on the laptops is crucial.

To date, however, the evidence suggests that children do not learn more from interacting with laptops than they do from textbooks. For example, Bando, Gallego, Gertler, and Romero (2016) compared the effect of free laptop and textbook provision in 271 elementary schools in disadvantaged areas of Honduras. After seven months, students in grades 3 and 6 who had received the laptops performed on par with those who had received the textbooks in math and language. Further, even if textbooks essentially become obsolete at the end of each school year, whereas laptops can be reloaded with new materials for each year, the costs of laptop provision (not just the hardware, but also the technical assistance, Internet, and training associated with it) are not yet low enough to make them a more cost-effective way of delivering content to learners.

Evidence on the provision of tablets equipped with software is encouraging but limited. For example, de Hoop et al. (2020) evaluated a composite intervention for first grade students in Zambia’s Eastern Province that combined infrastructure (electricity via solar power), hardware (projectors and tablets), and educational materials (lesson plans for educators and interactive lessons for learners, both loaded onto the tablets and mapped onto the official Zambian curriculum). After 14 months, the intervention had improved student early-grade reading by 0.4 SDs, oral vocabulary scores by 0.25 SDs, and early-grade math by 0.22 SDs. It also improved students’ achievement by 0.16 on a locally developed assessment. The multifaceted nature of the program, however, makes it challenging to identify the components that are driving the positive effects. Pitchford (2015) evaluated an intervention that provided tablets equipped with educational “apps,” to be used for 30 minutes per day for two months to develop early math skills among students in grades 1 through 3 in Lilongwe, Malawi. The evaluation found positive impacts in math achievement, but the main study limitation is that it was conducted in a single school.

Facilitating differentiated instruction

Another way in which technology may improve educational outcomes is by facilitating the delivery of differentiated or individualized instruction. Most developing countries massively expanded access to schooling in recent decades by building new schools and making education more affordable, both by defraying direct costs, as well as compensating for opportunity costs (Duflo, 2001; World Bank, 2018). These initiatives have not only rapidly increased the number of learners enrolled in school, but have also increased the variability in learner’ preparation for schooling. Consequently, a large number of learners perform well below grade-based curricular expectations (see, e.g., Duflo, Dupas, & Kremer, 2011; Pritchett & Beatty, 2015). These learners are unlikely to get much from “one-size-fits-all” instruction, in which a single educator delivers instruction deemed appropriate for the middle (or top) of the achievement distribution (Banerjee & Duflo, 2011). Technology could potentially help these learners by providing them with: (a) instruction and opportunities for practice that adjust to the level and pace of preparation of each individual (known as “computer-adaptive learning” (CAL)); or (b) live, one-on-one tutoring.

Computer-adaptive learning

One of the main comparative advantages of technology is its ability to diagnose students’ initial learning levels and assign students to instruction and exercises of appropriate difficulty. No individual educator—no matter how talented—can be expected to provide individualized instruction to all learners in his/her class simultaneously . In this respect, technology is uniquely positioned to complement traditional teaching. This use of technology could help learners master basic skills and help them get more out of schooling.

Although many software products evaluated in recent years have been categorized as CAL, many rely on a relatively coarse level of differentiation at an initial stage (e.g., a diagnostic test) without further differentiation. We discuss these initiatives under the category of “increasing opportunities for practice” below. CAL initiatives complement an initial diagnostic with dynamic adaptation (i.e., at each response or set of responses from learners) to adjust both the initial level of difficulty and rate at which it increases or decreases, depending on whether learners’ responses are correct or incorrect.

Existing evidence on this specific type of programs is highly promising. Most famously, Banerjee et al. (2007) evaluated CAL software in Vadodara, in the Indian state of Gujarat, in which grade 4 students were offered two hours of shared computer time per week before and after school, during which they played games that involved solving math problems. The level of difficulty of such problems adjusted based on students’ answers. This program improved math achievement by 0.35 and 0.47 SDs after one and two years of implementation, respectively. Consistent with the promise of personalized learning, the software improved achievement for all students. In fact, one year after the end of the program, students assigned to the program still performed 0.1 SDs better than those assigned to a business as usual condition. More recently, Muralidharan, et al. (2019) evaluated a “blended learning” initiative in which students in grades 4 through 9 in Delhi, India received 45 minutes of interaction with CAL software for math and language, and 45 minutes of small group instruction before or after going to school. After only 4.5 months, the program improved achievement by 0.37 SDs in math and 0.23 SDs in Hindi. While all learners benefited from the program in absolute terms, the lowest performing learners benefited the most in relative terms, since they were learning very little in school.

We see two important limitations from this body of research. First, to our knowledge, none of these initiatives has been evaluated when implemented during the school day. Therefore, it is not possible to distinguish the effect of the adaptive software from that of additional instructional time. Second, given that most of these programs were facilitated by local instructors, attempts to distinguish the effect of the software from that of the instructors has been mostly based on noncausal evidence. A frontier challenge in this body of research is to understand whether CAL software can increase the effectiveness of school-based instruction by substituting part of the regularly scheduled time for math and language instruction.

Live one-on-one tutoring

Recent improvements in the speed and quality of videoconferencing, as well as in the connectivity of remote areas, have enabled yet another way in which technology can help personalization: live (i.e., real-time) one-on-one tutoring. While the evidence on in-person tutoring is scarce in developing countries, existing studies suggest that this approach works best when it is used to personalize instruction (see, e.g., Banerjee et al., 2007; Banerji, Berry, & Shotland, 2015; Cabezas, Cuesta, & Gallego, 2011).

There are almost no studies on the impact of online tutoring—possibly, due to the lack of hardware and Internet connectivity in low- and middle-income countries. One exception is Chemin and Oledan (2020)’s recent evaluation of an online tutoring program for grade 6 students in Kianyaga, Kenya to learn English from volunteers from a Canadian university via Skype ( videoconferencing software) for one hour per week after school. After 10 months, program beneficiaries performed 0.22 SDs better in a test of oral comprehension, improved their comfort using technology for learning, and became more willing to engage in cross-cultural communication. Importantly, while the tutoring sessions used the official English textbooks and sought in part to help learners with their homework, tutors were trained on several strategies to teach to each learner’s individual level of preparation, focusing on basic skills if necessary. To our knowledge, similar initiatives within a country have not yet been rigorously evaluated.

Expanding opportunities for practice

A third way in which technology may improve the quality of education is by providing learners with additional opportunities for practice. In many developing countries, lesson time is primarily devoted to lectures, in which the educator explains the topic and the learners passively copy explanations from the blackboard. This setup leaves little time for in-class practice. Consequently, learners who did not understand the explanation of the material during lecture struggle when they have to solve homework assignments on their own. Technology could potentially address this problem by allowing learners to review topics at their own pace.

Practice exercises

Technology can help learners get more out of traditional instruction by providing them with opportunities to implement what they learn in class. This approach could, in theory, allow some learners to anchor their understanding of the material through trial and error (i.e., by realizing what they may not have understood correctly during lecture and by getting better acquainted with special cases not covered in-depth in class).

Existing evidence on practice exercises reflects both the promise and the limitations of this use of technology in developing countries. For example, Lai et al. (2013) evaluated a program in Shaanxi, China where students in grades 3 and 5 were required to attend two 40-minute remedial sessions per week in which they first watched videos that reviewed the material that had been introduced in their math lessons that week and then played games to practice the skills introduced in the video. After four months, the intervention improved math achievement by 0.12 SDs. Many other evaluations of comparable interventions have found similar small-to-moderate results (see, e.g., Lai, Luo, Zhang, Huang, & Rozelle, 2015; Lai et al., 2012; Mo et al., 2015; Pitchford, 2015). These effects, however, have been consistently smaller than those of initiatives that adjust the difficulty of the material based on students’ performance (e.g., Banerjee et al., 2007; Muralidharan, et al., 2019). We hypothesize that these programs do little for learners who perform several grade levels behind curricular expectations, and who would benefit more from a review of foundational concepts from earlier grades.

We see two important limitations from this research. First, most initiatives that have been evaluated thus far combine instructional videos with practice exercises, so it is hard to know whether their effects are driven by the former or the latter. In fact, the program in China described above allowed learners to ask their peers whenever they did not understand a difficult concept, so it potentially also captured the effect of peer-to-peer collaboration. To our knowledge, no studies have addressed this gap in the evidence.

Second, most of these programs are implemented before or after school, so we cannot distinguish the effect of additional instructional time from that of the actual opportunity for practice. The importance of this question was first highlighted by Linden (2008), who compared two delivery mechanisms for game-based remedial math software for students in grades 2 and 3 in a network of schools run by a nonprofit organization in Gujarat, India: one in which students interacted with the software during the school day and another one in which students interacted with the software before or after school (in both cases, for three hours per day). After a year, the first version of the program had negatively impacted students’ math achievement by 0.57 SDs and the second one had a null effect. This study suggested that computer-assisted learning is a poor substitute for regular instruction when it is of high quality, as was the case in this well-functioning private network of schools.

In recent years, several studies have sought to remedy this shortcoming. Mo et al. (2014) were among the first to evaluate practice exercises delivered during the school day. They evaluated an initiative in Shaanxi, China in which students in grades 3 and 5 were required to interact with the software similar to the one in Lai et al. (2013) for two 40-minute sessions per week. The main limitation of this study, however, is that the program was delivered during regularly scheduled computer lessons, so it could not determine the impact of substituting regular math instruction. Similarly, Mo et al. (2020) evaluated a self-paced and a teacher-directed version of a similar program for English for grade 5 students in Qinghai, China. Yet, the key shortcoming of this study is that the teacher-directed version added several components that may also influence achievement, such as increased opportunities for teachers to provide students with personalized assistance when they struggled with the material. Ma, Fairlie, Loyalka, and Rozelle (2020) compared the effectiveness of additional time-delivered remedial instruction for students in grades 4 to 6 in Shaanxi, China through either computer-assisted software or using workbooks. This study indicates whether additional instructional time is more effective when using technology, but it does not address the question of whether school systems may improve the productivity of instructional time during the school day by substituting educator-led with computer-assisted instruction.

Increasing learner engagement

Another way in which technology may improve education is by increasing learners’ engagement with the material. In many school systems, regular “chalk and talk” instruction prioritizes time for educators’ exposition over opportunities for learners to ask clarifying questions and/or contribute to class discussions. This, combined with the fact that many developing-country classrooms include a very large number of learners (see, e.g., Angrist & Lavy, 1999; Duflo, Dupas, & Kremer, 2015), may partially explain why the majority of those students are several grade levels behind curricular expectations (e.g., Muralidharan, et al., 2019; Muralidharan & Zieleniak, 2014; Pritchett & Beatty, 2015). Technology could potentially address these challenges by: (a) using video tutorials for self-paced learning and (b) presenting exercises as games and/or gamifying practice.

Video tutorials

Technology can potentially increase learner effort and understanding of the material by finding new and more engaging ways to deliver it. Video tutorials designed for self-paced learning—as opposed to videos for whole class instruction, which we discuss under the category of “prerecorded lessons” above—can increase learner effort in multiple ways, including: allowing learners to focus on topics with which they need more help, letting them correct errors and misconceptions on their own, and making the material appealing through visual aids. They can increase understanding by breaking the material into smaller units and tackling common misconceptions.

In spite of the popularity of instructional videos, there is relatively little evidence on their effectiveness. Yet, two recent evaluations of different versions of the Khan Academy portal, which mainly relies on instructional videos, offer some insight into their impact. First, Ferman, Finamor, and Lima (2019) evaluated an initiative in 157 public primary and middle schools in five cities in Brazil in which the teachers of students in grades 5 and 9 were taken to the computer lab to learn math from the platform for 50 minutes per week. The authors found that, while the intervention slightly improved learners’ attitudes toward math, these changes did not translate into better performance in this subject. The authors hypothesized that this could be due to the reduction of teacher-led math instruction.

More recently, Büchel, Jakob, Kühnhanss, Steffen, and Brunetti (2020) evaluated an after-school, offline delivery of the Khan Academy portal in grades 3 through 6 in 302 primary schools in Morazán, El Salvador. Students in this study received 90 minutes per week of additional math instruction (effectively nearly doubling total math instruction per week) through teacher-led regular lessons, teacher-assisted Khan Academy lessons, or similar lessons assisted by technical supervisors with no content expertise. (Importantly, the first group provided differentiated instruction, which is not the norm in Salvadorian schools). All three groups outperformed both schools without any additional lessons and classrooms without additional lessons in the same schools as the program. The teacher-assisted Khan Academy lessons performed 0.24 SDs better, the supervisor-led lessons 0.22 SDs better, and the teacher-led regular lessons 0.15 SDs better, but the authors could not determine whether the effects across versions were different.

Together, these studies suggest that instructional videos work best when provided as a complement to, rather than as a substitute for, regular instruction. Yet, the main limitation of these studies is the multifaceted nature of the Khan Academy portal, which also includes other components found to positively improve learner achievement, such as differentiated instruction by students’ learning levels. While the software does not provide the type of personalization discussed above, learners are asked to take a placement test and, based on their score, educators assign them different work. Therefore, it is not clear from these studies whether the effects from Khan Academy are driven by its instructional videos or to the software’s ability to provide differentiated activities when combined with placement tests.

Games and gamification

Technology can also increase learner engagement by presenting exercises as games and/or by encouraging learner to play and compete with others (e.g., using leaderboards and rewards)—an approach known as “gamification.” Both approaches can increase learner motivation and effort by presenting learners with entertaining opportunities for practice and by leveraging peers as commitment devices.

There are very few studies on the effects of games and gamification in low- and middle-income countries. Recently, Araya, Arias Ortiz, Bottan, and Cristia (2019) evaluated an initiative in which grade 4 students in Santiago, Chile were required to participate in two 90-minute sessions per week during the school day with instructional math software featuring individual and group competitions (e.g., tracking each learner’s standing in his/her class and tournaments between sections). After nine months, the program led to improvements of 0.27 SDs in the national student assessment in math (it had no spillover effects on reading). However, it had mixed effects on non-academic outcomes. Specifically, the program increased learners’ willingness to use computers to learn math, but, at the same time, increased their anxiety toward math and negatively impacted learners’ willingness to collaborate with peers. Finally, given that one of the weekly sessions replaced regular math instruction and the other one represented additional math instructional time, it is not clear whether the academic effects of the program are driven by the software or the additional time devoted to learning math.

The prognosis:

How can school systems adopt interventions that match their needs.

Here are five specific and sequential guidelines for decisionmakers to realize the potential of education technology to accelerate student learning.

1. Take stock of how your current schools, educators, and learners are engaging with technology .

Carry out a short in-school survey to understand the current practices and potential barriers to adoption of technology (we have included suggested survey instruments in the Appendices); use this information in your decisionmaking process. For example, we learned from conversations with current and former ministers of education from various developing regions that a common limitation to technology use is regulations that hold school leaders accountable for damages to or losses of devices. Another common barrier is lack of access to electricity and Internet, or even the availability of sufficient outlets for charging devices in classrooms. Understanding basic infrastructure and regulatory limitations to the use of education technology is a first necessary step. But addressing these limitations will not guarantee that introducing or expanding technology use will accelerate learning. The next steps are thus necessary.

“In Africa, the biggest limit is connectivity. Fiber is expensive, and we don’t have it everywhere. The continent is creating a digital divide between cities, where there is fiber, and the rural areas.  The [Ghanaian] administration put in schools offline/online technologies with books, assessment tools, and open source materials. In deploying this, we are finding that again, teachers are unfamiliar with it. And existing policies prohibit students to bring their own tablets or cell phones. The easiest way to do it would have been to let everyone bring their own device. But policies are against it.” H.E. Matthew Prempeh, Minister of Education of Ghana, on the need to understand the local context.

2. Consider how the introduction of technology may affect the interactions among learners, educators, and content .

Our review of the evidence indicates that technology may accelerate student learning when it is used to scale up access to quality content, facilitate differentiated instruction, increase opportunities for practice, or when it increases learner engagement. For example, will adding electronic whiteboards to classrooms facilitate access to more quality content or differentiated instruction? Or will these expensive boards be used in the same way as the old chalkboards? Will providing one device (laptop or tablet) to each learner facilitate access to more and better content, or offer students more opportunities to practice and learn? Solely introducing technology in classrooms without additional changes is unlikely to lead to improved learning and may be quite costly. If you cannot clearly identify how the interactions among the three key components of the instructional core (educators, learners, and content) may change after the introduction of technology, then it is probably not a good idea to make the investment. See Appendix A for guidance on the types of questions to ask.

3. Once decisionmakers have a clear idea of how education technology can help accelerate student learning in a specific context, it is important to define clear objectives and goals and establish ways to regularly assess progress and make course corrections in a timely manner .

For instance, is the education technology expected to ensure that learners in early grades excel in foundational skills—basic literacy and numeracy—by age 10? If so, will the technology provide quality reading and math materials, ample opportunities to practice, and engaging materials such as videos or games? Will educators be empowered to use these materials in new ways? And how will progress be measured and adjusted?

4. How this kind of reform is approached can matter immensely for its success.

It is easy to nod to issues of “implementation,” but that needs to be more than rhetorical. Keep in mind that good use of education technology requires thinking about how it will affect learners, educators, and parents. After all, giving learners digital devices will make no difference if they get broken, are stolen, or go unused. Classroom technologies only matter if educators feel comfortable putting them to work. Since good technology is generally about complementing or amplifying what educators and learners already do, it is almost always a mistake to mandate programs from on high. It is vital that technology be adopted with the input of educators and families and with attention to how it will be used. If technology goes unused or if educators use it ineffectually, the results will disappoint—no matter the virtuosity of the technology. Indeed, unused education technology can be an unnecessary expenditure for cash-strapped education systems. This is why surveying context, listening to voices in the field, examining how technology is used, and planning for course correction is essential.

5. It is essential to communicate with a range of stakeholders, including educators, school leaders, parents, and learners .

Technology can feel alien in schools, confuse parents and (especially) older educators, or become an alluring distraction. Good communication can help address all of these risks. Taking care to listen to educators and families can help ensure that programs are informed by their needs and concerns. At the same time, deliberately and consistently explaining what technology is and is not supposed to do, how it can be most effectively used, and the ways in which it can make it more likely that programs work as intended. For instance, if teachers fear that technology is intended to reduce the need for educators, they will tend to be hostile; if they believe that it is intended to assist them in their work, they will be more receptive. Absent effective communication, it is easy for programs to “fail” not because of the technology but because of how it was used. In short, past experience in rolling out education programs indicates that it is as important to have a strong intervention design as it is to have a solid plan to socialize it among stakeholders.

Beyond reopening: A leapfrog moment to transform education?

On September 14, the Center for Universal Education (CUE) will host a webinar to discuss strategies, including around the effective use of education technology, for ensuring resilient schools in the long term and to launch a new education technology playbook “Realizing the promise: How can education technology improve learning for all?”

file-pdf Full Playbook – Realizing the promise: How can education technology improve learning for all? file-pdf References file-pdf Appendix A – Instruments to assess availability and use of technology file-pdf Appendix B – List of reviewed studies file-pdf Appendix C – How may technology affect interactions among students, teachers, and content?

About the Authors

Alejandro j. ganimian, emiliana vegas, frederick m. hess.

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• Published: 15 March 2018

A critical review of mobile learning integration in formal educational contexts

• Luís Francisco Mendes Gabriel Pedro   ORCID: orcid.org/0000-0003-1763-8433 1 ,
• Cláudia Marina Mónica de Oliveira Barbosa 1 &
• Carlos Manuel das Neves Santos 1  

International Journal of Educational Technology in Higher Education volume  15 , Article number:  10 ( 2018 ) Cite this article

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The use of digital technology in the learning process and teaching practices in formal teaching is highly dependent on the ability of teachers of introducing it without jeopardizing the richness of the classroom environment, namely the attention that students need to follow the flow of argumentation and to guarantee the quality of the inquiring.

Although several studies value the importance of technologies in our media-enriched world and the "learn anytime and anywhere" motto associated with mobile learning, we argue that the classroom dynamics are becoming more and more at risk with the addictive dimension brought about by the ubiquitous presence of digital devices and social media in students’ lives.

In this article, we will make a critical review of the literature related to mobile learning because there is still a need of more extensive research on the interference of technology in the classroom, especially on how multitasking affects the teacher role in-class as a media orchestrator and learning facilitator.

Finally, we will discuss the use of technology in the formal classroom environment, mainly to stimulate a much-needed discussion about the bright-not-so-bright impacts of technology in the teaching and learning process.

Introduction

The introduction of digital technologies in the teaching and learning process is a theme that spans the literature on Educational Technology since the 1980s. Highly associated with the emergence and more consensual acceptance of new pedagogies and a renewed epistemological approach about the nature of knowledge and of its construction, technologies are often depicted as a set of tools that bear in themselves several solutions to the problems of education.

This optimistic view of digital technology came about with the introduction of the personal computer, then the Internet mainly in the 1990s and is still echoed and very much amplified with the possibilities brought by the pervasive and ubiquitous access to mobile devices and social media platforms in the 2000s.

These latter devices and media frame the emergence of a new learning modality, mobile-learning (m-learning), that was defined as “the processes of coming to know through conversations across multiple contexts among people and personal interactive technologies” (Sharples, Taylor, & Vavoula, 2007 : 224).

The definition of m-learning has evolved in different ways and directions since the first decade of the 2000s. According to Baran ( 2014 : 18), the evolution of these definitions has mainly highlighted m-learning positive characteristics such as “mobility (Sharples et al., 2009 ), access (Parsons & Ryu, 2006 ), immediacy (Kynäslahti, 2003 ), situativity (Cheon, Lee, Crooks, & Song, 2012 ), ubiquity (Kukulska-Hulme et al., 2009 ), convenience (Kynäslahti, 2003 ), and contextuality (Kearney, Schuck, Burden, & Aubusson, 2012 )”.

These different emphases reflect the expected but also the unexpected impacts of the introduction of these digital technologies in the learning process. In the history of m-learning, initial definitions were more device-driven (focusing in immediacy, convenience, access and mobility) while the latter ones are more personal and social-driven, exploring affordances that relate to new technological features of mobile devices such as location awareness, motion detection and augmented reality (Baran, 2014 : 18).

Although, theoretically, these definitions encompass the formal, non-formal and informal contexts in which learning occurs, Cheon et al. ( 2012 ) argue that they reinforce the learning that occurs in real settings, i.e., that are not limited to classrooms contexts. But is m--learning supporting or jeopardizing learning in classrooms?

To be able to critically explore these issues is the main aim of this article. We will begin by a brief review of the literature about m-learning research in order to try to understand the undeniable positiveness related to the use of these devices (Al-Zahrani & Laxman, 2016 ; Wu et al., 2012 ). Following, we will discuss the place and value of mobile devices and social media applications in today’s learning, confronting our optimism about this issue with other opinions which question the fit of mobile devices in some educational contexts.

In the following section, we will present some of the teaching and learning impacts associated with the use of these devices in classroom contexts, namely the issues that result from multitasking and that may be troublesome for the students but also the orchestration issues that arise for the teacher in a multidevice and multimedia classroom. Finally, we will discuss different perspectives related to digital technologies integration in the classroom, trying to provoke a necessary and reality-based discussion about these issues.

Mobile learning research overview

This integrative literature review follows some of our previous work in this area, namely developed by Aresta, Pedro & Santos ( 2015 ) but in this one we focused our analysis on the review of meta-analytical studies about m-learning published since 2010 in order to present a snapshot of the existing research in this field. The keywords used in searching articles in the SCOPUS database were m-learning and meta-analy* and we limited the search to articles from 2010 to 2017. A staged review was conducted, beginning with an initial review of all the abstracts, followed by an in-depth review of selected articles according to the relevance of the journals in which they were published. This review shows that the m-learning is an emerging field of research, showing a steady increase in terms of number of publications since the beginning of the 2000 decade. Some meta-analytical papers in the past years (Chee, Yahaya, Ibrahim, & Noor Hassan, 2017 ; Al-Zahrani & Laxman, 2016 ; Hung & Zhang, 2012 ; Wu et al., 2012 ; Hwang & Tsai, 2011 ) show this progression and reveal the focus on studies related to the effectiveness of m-learning followed by m-learning system design (Chee et al., 2017 ).

These trends and foci are somewhat expected, as pointed out by Hung and Zhang ( 2012 ), because they reveal a predictable path since the introduction of a technology to its adoption and integration. According to these authors, “e-learning research is at the early majority stage and foci have shifted from comparing the effectiveness of e-learning to developing models for e-learning environments and for teaching and learning strategies within various e-learning environments. If m-learning articles follow a similar path, we may expect more research studies on strategies and framework (...) in the near future.” (Hung & Zhang, 2012 : 13).

However, one of the first issues that pretty much every study in this field tries to establish is a stable definition of m-learning. Being a relative new field of study and witnessing some technological breakthroughs in its early existence, several definitions have been suggested since the early 2000s. For instance, some authors identified m-learning as a natural consequence of the e-learning evolution (Georgiev et al., 2004 ), but more recent definitions position m-learning as a method that intersects mobile computing and e-learning (Chee et al., 2017 ), that adopts the use of mobile technology to achieve anytime, anywhere, ubiquitous learning (Hung & Zhang, 2012 ) and that emphasizes learners’ mobility and personalized learning (Vázquez-Cano, 2014 ).

In terms of simple bibliometric data, Hwang and Tsai ( 2011 ) reviewed studies about m-learning published in six major research journals related to technology-enhanced learning from 2001 to 2010 and reported that from 2006 to 2010 the number of articles related to MUL (Mobile and Ubiquitous Learning) almost quadrupled in relation to the 2001–2005 period. These figures can be supplemented by the ones developed by Hung and Zhang ( 2012 ) and Chee et al. ( 2017 ) that conducted meta-analytical reviews of m-learning trends from 2003 to 2008 and from 2010 to 2015. Although these authors used different journal databases, the results also present a parallel evolution pattern in the case of the Hung and Zhang ( 2012 ) study and a more modest but still evolutional pattern in terms of number of publications in the time period reported in the Chee et al. ( 2017 ) literature review.

In terms of sample groups, both Hwang and Tsai ( 2011 ) and Wu et al. ( 2012 ) report that published papers show a high prevalence of studies with Higher Education students, followed by elementary school students and K-12 students. Oddly (or perhaps not, as we will argue further) only a few studies in both meta-analyses were related with the use of m-learning from the professors or teachers’ standpoint.

Regarding the educational contexts of m-learning studies, Chee et al. ( 2017 ) report that when those contexts are revealed, informal learning contexts are predominant, followed by formal contexts and a combination of both. This result is consistent with results reported by other authors, namely by Vázquez-Cano ( 2014 ).

Together with the predominance of informal educational contexts in m-learning published research, Hwang and Tsai ( 2011 ) also report that most studies do not focus on a particular learning domain but rather present results related to motivation, perceptions and attitudes of students towards m-learning. Once again, the perceptions and attitudes of teachers are seldom found. These results are aligned with the ones also reported by Chee et al. ( 2017 ) in a more recent analysis.

Finally, in terms of outcomes, Wu et al. ( 2012 ) report that 86% of the studies on m-learning present positive outcomes. This kind of result is also found in Chee et al. ( 2017 : 123) article, which report that “most of the 144 M-Learning studies present positive outcomes. (...) Neutral outcome ranked next and negative outcome ranked the least.”

These results are very representative of a general positive attitude towards m-learning that crosses much of the literature in this field.

The not-so-glamorous issues missing in m-learning research

The brief snapshot of m-learning research of the last decade gave us some important clues about the major topics of research in this field but, more importantly, about the issues that are seldom if not considered at all.

Among the latter, we would like to stress two particular ones: the use of m-learning in formal educational contexts and the integration of m-learning from the professor/teacher standpoint which will be developed in the following sections.

M-learning and formal education contexts

Regarding digital devices use in education, Gikas & Grant ( 2013 : 18) acknowledge that “(...) there is little applied research into how these tools are actually being used to support teaching and learning with few descriptions of how mobile computing devices and social media are used by university students”.

Being widely regarded as both a formal and informal method or set of practices, it is curious that only a few studies report the use of mobile devices or m-learning strategies in formal educational contexts. We noticed that some authors prefer to see m-learning as a shot to bridge formal and informal learning opportunities, valuing, among others, its context-awareness and situated features. Obviously, we also share this opinion and some of our previous work is precisely related to that (Pedro, Aresta, Santos & Almeida, 2015 ). We also agree with Gikas and Grant ( 2013 ) claim whereas much of the literature has been focusing on the affordances of mobile devices to replicate old methods, strategies, and practices that are mainly teacher-centered and transmission-oriented. We find it very difficult to disagree with these findings. As mentioned by Tess ( 2013 ), we also believe that bringing more scholarship into the implementation of technology as a learning resource is necessary.

Nevertheless, it is curious that apparently only a few studies report the results of the use of these devices in the context of class-activities such as a lecture, for instance. Gikas & Grant ( 2013 : 23) report in their study that “(...) traditional college-aged students (...) felt that at times the device could be distracting. The allure of social networking applications that were not being used for class potentially threatened their concentration” but don’t elaborate further on that, presenting next a claim that “(...) older students (...) emphatically stated that the devices were not distracting.” Could this issue be related to the age of students? These authors also report a finding that “(...) while there is not a preponderance of data to support this final implication, there were data to suggest that the student participants also blurred the lines between their personal identity and their mobile computing device. The student participants recognized their need to be constantly near their device.” The tone used on the discussion of this result is, again, very positive. Gikas & Grant ( 2013 , 25) report that being always connected with their mobile devices allowed students to access course information and also gave them the opportunity to interact with the content, potentially contributing to tear apart the existing barrier between learning and real life. Could it be the case that we may be missing something? According to Lepp, Barkley, and Karpinski ( 2015 ), some recent findings suggest a careful consideration of the relationship between cell phone use, and foremost the use of social media, and academic performance.

And what about the overall suitability of mobile devices and social media applications in formal education? Friesen and Lowe ( 2011 : 184), for instance, are outsiders in this optimism game, questioning the suitability of social media for education, claiming that just as “commercialism ultimately render television beyond the reach of education, we conclude that commercial pressures threaten to limit the potential of the social Web for education and learning.”

Reflecting on the commercial priorities of most social media applications, Friesen and Lowe ( 2011 ) argue that the use of these applications could harm education, precisely because they are positively bounded to likeness and agreement, possibly jeopardizing important learning strategies that imply critical inquiry, confrontation, disagreement and dissent. They argue that the “adoption of these platforms would threaten educational dialogue as a process that is central to collaborative learning. The sequence, rhythm, and flow functions of commercial social media present, to use Raymond Williams ( 1974 ) phrasing, ‘a formula of communication, an intrinsic setting of priorities’. The difference separating these priorities (in new social technology) from those of education is clear in the form of social networks, if not also in some aspects of its content.” (Friesen and Lowe, 2011 : 193).

M-learning integration from the teacher’s standpoint

As mentioned before, although many teachers are looking up to technological devices and applications to enhance their classes and promote active learning practices in their students, there are not so many studies that try to understand the integration and the actual results of m-learning practices from the teacher standpoint.

Baran ( 2014 ), for instance, reports on the use of m-learning in teacher education which is a good sign but, still, reports more on preservice teacher’s perceptions and attitudes and not on the integration of m-learning by real practitioners on the field. As argued by Tess ( 2013 : 66), a “(...) reason that may explain the paucity of studies is that SNS (social networking sites) integration is a choice made at the instructor level rather than an institutional decision. As a result, the implementation may be more of a trial that lends itself to action research and ultimately to more questions.”

However, we think that besides the real implementation issues that come about in practice there is an underlying problem to be solved related to the lack of theoretical and pedagogical foundations regarding the implementation of mobile-learning in educational contexts.

Although many authors frame this method on socioconstructivist approaches deriving from the work of Vygotsky and in the appeal of the communication features of mobile devices to set up communities of practice and inquiry and foster collaboration, the fact is that what is participatory and collaborative in any human endeavour is people and not devices or media (Jenkins, Ito & Boyd, 2016 ). Therefore, it seems that, beginning in the teachers themselves but also encompassing students and the overall learning community, there is a lack of true and meaningful participatory culture of mobile devices users that can propel the full promise of technology.

Eijkman ( 2008 ) proposes the term ‘non-foundational network-centric learning spaces’ precisely to define this conundrum. He argues that the use of technology in education is still pretty much centered on an information-driven paradigm and that to fulfill the promise of new media and the devices that support them it is needed, from the part of the teacher and students, a novel approach, centered on collaborative knowledge construction and on a participatory-driven paradigm. This is a major problem because, as reported by Tess’ ( 2013 ) review of literature, the former kind of perception and attitude is still dominant in our schools.

This conundrum has obvious effects in practice. Tess ( 2013 ) reports several studies which suggest that training and guidance is needed for teachers to feel secure to implement this method. Accordingly, Baran ( 2014 : 23) curiously goes a step back and proposes that the problem really begins before, with teachers’ educators, stating that “(...) the literature needs to establish pedagogical and theoretical models that can guide teacher educators in designing mobile learning experiences for preservice and in-service teachers. These models need to present strategies for equipping teachers and teacher educators with methods for integrating mobile learning into classrooms as well as supporting professional learning with mobile tools.”

These are major problems and, in the regular teaching and learning process, we still have not reached the classroom. There, these problems increase in magnitude and several studies report that students rarely used social media for educational purposes (Jones et al., 2010 ), communication regarding coursework was least on the list (Roblyer, McDaniel, Webb, Herman, & Witty, 2010 ) and only 24% of the faculty used SNSs in their courses (Ajjan & Hartshorne, 2008 ).

As stated before, the discussion of the challenges of real integration of m-learning in classrooms is minimal (Baran, 2014 ) and, for instance, there are studies that alert to the fact that the integration of certain practices in classrooms can run, for instance, into a non-existent or incompatible curriculum (Price et al., 2014 ).

Challenges of mobile devices use in the classroom

Digital devices as a distraction in the classroom.

Shirky ( 2014 ), in a lengthy essay on Medium, argued that, although he is an advocate of the use of technology in the classroom, he asked his students to put their laptops, tablets and phones away in classes. The author claims that this decision was made considering that the levels of distraction is his classes were growing despite the existence of two constants: the teacher and the students, which were selected using approximately the same criteria each year. Shirky, then, attributed the cause of this increase of distraction to the pervasive and ubiquitous presence of technological devices in his classroom.

However, this line of thought is not new. Almost 10 years ago, Fried reported this concern referring laptops as likely sources of cognitive overload and distraction and referencing a set of studies that suggested that “[t]he orientation and visual nature of laptops, along with pop-ups, instant messages, movement and lighting of text, and even things like low-battery warnings, make laptops inherently distracting” (Fried, 2008 : 908 for more information).

Although some authors (Selwyn, 2010 ; Siemens, 2006 ) argue that there is, apparently, a new student in our higher education classrooms that is highly connected, collective, and creative and that social and communicative connections may constitute a new form of knowledge that is no more merely instrumental to the learning process (see Friesen & Lowe, 2011 for an entertaining and thoughtful discussion about these topics), there are also other authors (Warschauer, Zheng, Niiya, Cotten, & Farkas, 2014 ) that are questioning the benefits of using mobile devices in the classroom, mainly because of the yet to study effects resulting from its integration.

One of those effects is reported by Shirky ( 2014 ) and by Sana, Weston, and Cepeda ( 2013 ) and it is related with the potential harmful effects on learning resulting from using mobile devices for nearby peers.

According to these authors this effect is particularly serious and Shirky argues that “[t]here is no laissez-faire attitude to take when the degradation of focus is social.”

As a matter of fact, this may be an irreversible and ever-worst problem if, as claimed by Shirky ( 2014 ), digital devices and applications continue to be designed for competing for our attention. In the past years, we witnessed the emergence of very creative forms of notifications in digital environments, beginning in pop-ups and banners, to the most recent badges, roll-ups, and push notifications. These kinds of effects have been suggested in some studies as a possible cause to a negative correlation between electronic media use (including mobile devices) and academic performance as Lepp et al. ( 2015 ) suggest in a thorough review on this issue. Some of these studies also suggest that these effects are not only visible in classrooms but also in homeworking tasks and in the overall quality of time spent studying.

Lepp et al. ( 2015 : 7) argue that more research is needed in these topics because relationship between these variables has been proved but relationship does not mean, necessarily, causality: “[f]uture research should examine the many potential underlying reasons for the negative relationship identified here, including time spent studying and multitasking”.

In the next section, we will present and discuss one of these topics - multitasking - and its effects in educational contexts.

Multitasking and its negative effects on learning

An aspect that is commonly presented as a downside of the introduction of mobile devices in the classroom is the possibility of students engaging in multitasking behaviors with (and within) said devices.

Multitasking has been defined by the American Psychological Association as occurring in those situations “when someone tries to perform two tasks simultaneously, switch from one task to another, or perform two or more tasks in rapid succession”. When multitasking with the use of one medium or more media is considered, the term evolves to “media multitasking”, characterized by Wallis ( 2010 ) as a possible threefold event: (a) between medium and face-to-face interaction; (b) between two or more media; and (c) within a single medium. Baumgartner, Weeda, van der Heijden, and Huizinga ( 2014 ), on the other hand, define it as an activity involving interaction with two different types of media or between one type of media and a non-media related activity, while a bare bones definition by Wang and Tchernev ( 2012 ) presents media multitasking as “multitasking involving at least one media-based stimulus or response”.

A more recent take on media multitasking offered by Patterson ( 2017 ) indicates that “media multitasking can take on many forms, such as multiscreen media multitasking with two or more media devices at once, such as using a smartphone or tablet while other digital media is simultaneously consumed” on a single device. The author differentiates between the terms “digital media” and “digital device” pointing out that “many different modalities of digital media can be consumed on most digital devices”.

Not being a new phenomenon, multitasking has been highly potentiated by the development of digital - especially mobile – devices (Brasel & Gips, 2011 ; Wang & Tchernev, 2012 ; Cardoso-Leite, Green, & Bavelier, 2015 ; Schutten, Stokes, & Arnell, 2017 ). While the behavior itself is, as mentioned, not novel, “what is new are the number and types of digitally based activities in which people can now engage in simultaneously” (Wood et al., 2012 ).

Most of the current university students belong to one of the two highly technological generations: the “Millennials” (the first generation to grow up with digital technology) and the “Centennials” (who have never known a world without computers and cell phones, which they were able to fully integrate into their daily lives), both usually described as tech-savvy and highly engaged with digital technologies which they use for long periods of time and in different combinations. Therefore, digital media consumption and the use of multiple devices apparently does not represent a problem in terms of students’ digital literacy. However, the problem seems to reside in the multitasking effect that results from these multiple uses.

Ophir, Nass, and Wagner ( 2009 ) recorded an average use of four digital media at a given time by the study-participating Stanford students. Patterson ( 2017 ) reports a median level of five different technologies used by students while preparing for an exam. Students also engage in prolonged multitasking behavior for long sittings: in a study conducted by Judd ( 2013 ), 3372 computer sessions of students engaged in self-directed study within an open-access computer laboratory were captured, segmented and analyzed, with the author stating that “multitasking was much more common than focused or sequential behaviors” and was “present in more than 70%, was most frequent in over 50% and occurred exclusively in around 35% of all sessions”.

These are high values but it is worth noting that respondents tend to underestimate the amount of multitasking they engage in (Brasel & Gips, 2011 ), usually self-reporting less multitasking than the recorded through observation, so one can wonder whether these values are still underrepresenting an extensive phenomenon.

While the ability to multitask has traditionally been viewed as a positive attribute and multitasking behavior seems to be on the rise in terms of popularity, several studies have been questioning how multitasking impact learning in a higher education context, taking into consideration that “doing more than one task at a time, especially more than one complex task, takes a toll on productivity” (APA, 2006 ). Distraction – or shared attention – is key in this assessment, since “when we talk about multitasking, we are really talking about attention: the art of paying attention, the ability to shift our attention, and, more broadly, to exercise judgment about what objects are worthy of our attention” (Rosen, 2008 ), which can be affected when new digital technologies are introduced in the classroom.

A reduced efficiency in task completion has been reported when one multitasks in the classroom, with several studies pointing out that tasks performed concurrently require more time for completion and are conducted less accurately than tasks performed sequentially. Bowman, Levine, Waite, and Gendron ( 2010 ) conducted a reading experiment involving undergraduates asked to read a 3828-word passage on a computer monitor, split in three groups: one engaged in instant messaging (IM) before reading the passage, a second group engaged in IM while reading the passage and a third group who did not engage in IM at all. The students who engaged in IM while reading took between 22% and 59% longer to read the passage than the other groups, even after deducting the time spent messaging. The underlying concept is that there is an added time needed to switch back and forth between the tasks. Subrahmanyam et al. ( 2013 ) conducted one experimental study focused on the exploration of the effect of medium and opportunities to multitask while reading two different passages (on paper, tablet, or laptop) and while multitasking or not. The authors report that while the reading medium did not have a significant statistical impact, “those who multitasked took longer to read” and “it may simple be less disruptive if one multitasks on a medium/device that is separate from the reading medium”.

Therefore, multitasking with digital devices (mobile phones, tablets or laptops) can have negative impacts on the learning outcomes, leading to a poorer academic performance, while further studies have highlighted how a high use of social media has negative impacts on academic engagement. Wood et al. ( 2012 ) tried to assess the learning outcomes of 145 University students, divided into 3 groups (paper-and-pencil note-taking, word processing note-taking and a natural use of technology condition) following off-task multitasking with social media and communication tools (Facebook, MSN, email and texting) when learning from classroom lectures. The authors concluded that the participants who chose not to use technology or used minimal amounts outperformed the participants who opted to engage in intensive multitasking. Furthermore, the participants involved with off-task activities with both Facebook and MSN engaged in more off-task activities than the two tasks assigned to them and more than the other participants, which the authors link with the somewhat attractive, engaging and interactive character of the activities provided by both platforms. Junco ( 2012 ) investigated the relationship between the frequency of multitasking with some ICTs and academic performance measure by semester grade point average (GPA), concluding that while multitasking with Facebook and text messaging with cell phones negatively predicted overall semester GPA, multitasking with other ICTs (such as email, information search, or instant messaging) did not. The author links this to either the "characteristics of the technologies themselves or by qualitative differences in how the technologies were used by the students", with Facebook, messaging and texting being used mostly for social purposes and emailing and searching for academic ones.

However, multitasking behaviors with media devices have the potential to affect not only users but also nearby peers. In a couple of experiments, Sana et al. ( 2013 ) investigated whether multitasking with a laptop would hinder learning of both multitaskers and their peers. In the first experiment, 44 undergraduates were asked to attend a university lecture and take notes with their laptop and further instructed to complete a series of non-related online tasks at any point during the lecture, mimicking the typical student web browsing habits. A post-lecture comprehension test containing 20 questions to evaluate simple knowledge and a further set of 20 question to evaluate application of knowledge was conducted with the purpose to measure learning. The authors concluded that participants who multitasked on the laptop scored significantly lower in the post-lecture comprehension test than the ones who did not multitask. In a second experiment, a new set of participants (38) was asked to take notes of the lecture using paper and pencil, some seated in view of multitasking peers and others with a distraction-free view of the lecture. The participants who were in view of multitasking peers scored significantly lower in the comprehension test, than the ones who were not. All these detrimental effects associated with multitasking - affecting not only students who willingly multitask but also those nearby - raise a significant challenge for instructors: can the advantages brought about by the inclusion of mobile devices in a classroom setting still be harnessed, while avoiding the potential for distraction they may pose, and how? The aforementioned studies report also on multitasking practices with non-digital devices. Therefore, more research is needed in order to find if these results are transferable to m-learning cases and if, as Selwyn ( 2009 : 368) puts it, “(…) digital technologies may be contributing to an increased disengagement, disenchantment and alienation of young people from formal institutions and activities. For example, young people are derided as being more interested in using digital technologies such as the internet or mobile telephony for self-expression and self-promotion than for actually listening to and learning from others”.

Orchestration: The need of a new skill for the teachers’ role

When discussing the effects of integrating mobile devices with teaching and learning on students’ learning performance, Sung et al. ( 2016 : 266) bring about the concept of orchestration as an important topic. They define it as “the efforts of building harmonious relationships among components to enable compatible, efficient, and effective technology-enhanced teaching and learning environments”. The components mentioned by Sung et al. ( 2016 ) were previously proposed by Dillenbourg ( 2013 ) and Dimitriadis, Prieto, and Asensio-Pérez ( 2013 ) and include technological components (hardware and software), educational context components (for instance, learning and teaching processes in different settings) and finally components related to users (teachers and students).

This is an old discussion. Many technological implementations in the past were not very successful because of a lack of attention to one or more of those components. One of the causes that is traditionally suggested for this problem is the lack of preparation of teachers. Solutions, therefore, point to the inclusion of mobile-enhanced instruction modules in teacher education programs (Sung et al., 2016 ).

While we agree with this claim it is our opinion that, perhaps once again, we may be overlooking the complexity of this issue by overvaluing technological issues. Theoretical, pedagogical and methodological issues related to the integration of these devices in educational contexts should be more valued. Educational contexts are ecological by nature and the addition of one more element does not mean that we have the old environment plus one element. The whole environment changes so all the elements of the ecosystem must adapt to the new conditions (see Gibson, 1986 for a thorough discussion of this topic). When this new element is technological this ecological nature is even more visible. Media devices are very powerful in terms of its appeal and bring about new spaces, times and geographies to the classroom. Teachers, but also students and the overall community, must be prepared to integrate these devices to extend learning opportunities but not forgetting that, in order to learn, along with discovery learning methods there must be inquiry, debate but also explanation and lecturing.

Regarding the role of the teacher, as stated by Shirky ( 2014 ), “[t]his is, for me, the biggest change — not a switch in rules, but a switch in how I see my role. Professors are at least as bad at estimating how interesting we are as the students are at estimating their ability to focus. Against oppositional models of teaching and learning, both negative - Concentrate, or lose out! - and positive - Let me attract your attention! - I’m coming to see student focus as a collaborative process.”

Dimitriadis et al., 2013 : 497) sum up this discussion with a definition of orchestration that encompasses both the ecological nature of technology in the teaching and learning process and the new skill of the teachers’ role: “From these discussions we can see a new trend raising, which we believe lies in the heart of the use of the orchestration term: that of how teachers (and/or students) appropriate and integrate in their practice the different technologies at their disposal (either digital or paper-based, generic or intended for orchestration).”

The orchestration of devices, methods and the constant adaptation to the reality of students and the class dynamic is an ongoing and collaborative process. Maybe teacher education programs should also be.

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DigiMedia, Department of Communication and Arts of the University of Aveiro, University of Aveiro, Campus Universitário de Santiago, 3810-193, Aveiro, Portugal

Luís Francisco Mendes Gabriel Pedro, Cláudia Marina Mónica de Oliveira Barbosa & Carlos Manuel das Neves Santos

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LP conceived the study, developed the paper and conducted the literature review and reflection on mobile learning. CB conducted the literature review and reflection on multitasking. Both authors read and approved the final manuscript. CS developed the first draft of the paper.

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Luis Pedro holds a PhD in Educational Technology (2005, University of Aveiro, Portugal). He currently is an Assistant Professor at the Department of Communication and Arts, University of Aveiro, Portugal. His research interests are related with social media development, integration and assessment in educational and training contexts, which have been developed in several MSc and PhD supervisions and through the coordination and participation in externally funded research projects.

Cláudia Barbosa has a graduate degree in Teaching of English and German, from the University of Aveiro, where she is currently working towards a PhD in Multimedia in Education. She has been involved as project manager in several FP7, H2020 and other international and national funded projects. Her current research interests lie in the use of technologies to support language teaching and learning and media multitasking.

Carlos Santos is an Assistant Professor at University of Aveiro, and holds a PhD in Information and Communication in Digital Platforms. Since 2009, he is the coordinator of the SAPO Campus research project ( http://campus.sapo.pt ). Since 2016, he is the technical lead researcher of the Global Portuguese Scientists (GPS) platform ( http://gps.pt ). His research interests are related with Personal Learning Environments, promotion of Web 2.0 tools in educational contexts, gamification, recommendation systems and technology for building communities.

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Pedro, L.F.M.G., Barbosa, C.M.M.d. & Santos, C.M.d. A critical review of mobile learning integration in formal educational contexts. Int J Educ Technol High Educ 15 , 10 (2018). https://doi.org/10.1186/s41239-018-0091-4

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• Devices in the Classroom

Digital devices, such as laptops, tablets, and smartphones, are ubiquitous in society, across college campuses, and in college classrooms. A vast majority of college students bring and/or use a laptop in the classroom ( Patterson and Patterson, 2017 ; Elliot-Dorans, 2018 ). In many ways, the ubiquity of these devices has been a boon to higher education—students can now respond instantaneously to online polls, collaborate in real time on written work, and engage with a range of media more flexibly than ever before. Using digital devices to teach remotely for a year and a half helped further demonstrate some of the ways they might be used in-person to promote learning.

Given this tension, how do you create a classroom and course where technology is used to engage, rather than distract, students? Looking at the research and our experiences using technology both in-person and remotely, we’ve found that using technology well involves being intentional, flexible, and transparent. Below you’ll find some advice about how you might use technology to support your learning objectives, supplemented by research on how to prevent technology from becoming a distraction.

Distraction, not the device, is the problem

Let's be clear: the presence of electronic devices in the classroom is not, in and of itself, the problem. Rather, it's the way we incorporate electronic devices into situations in which we are already inclined to pay attention to too many things. Broadly, we are not wired to multitask well (e.g. Mayer and Moreno, 2003 ), which is precisely the temptation that many students report experiencing when they are in the classroom. Let’s take a moment to look at what the research on in-class device usage tells us about multitasking; or, you may wish to jump directly to our recommendations below.

Studies of individual class sessions

A growing number of studies have found that off-topic device usage—whether on a phone or on a laptop—impedes academic performance (e.g. Glass and Kang, 2019 ; Felisoni and Godoi, 2018 ; Bjornsen and Archer, 2015 ; Demirbilek and Talan, 2018 ). Several studies have compared students who texted during a lecture versus those who did not. Those who texted typically took lower quality notes, retained less information, and did worse on tests about the material (e.g. Kuznekoff and Titsworth, 2013 , and Rosen et al, 2011 ; Lee et al, 2017 ). Students themselves are aware that in-class multitasking does not promote learning; in one survey, 80% of students agreed that multitasking in class decreases their ability to pay attention ( Sana et al, 2013 ).

Studies of semester-long courses

Much of the above data comes from simulated class situations, correlational studies, or studies of a single class session. What happens when students are not allowed to use computers in class for an entire semester? Two studies comparing actual college classrooms in which students were or were not allowed to use computers over the course of the semester found that students who bring a laptop to class earned lower grades than those who do not ( Patterson and Patterson, 2017 ; Carter et al, 2017 ).

However, the evidence is not uniformly against laptops. Elliot-Dorans compared different sections of the same course that either banned or allowed laptops, and found that banning laptops led to lower quality of written work, lower attendance, and lower exam scores ( Elliot-Dorans, 2018 ). The author surmised that students’ note taking was worse without a laptop, which impeded their learning.

Our recommendations

Maintaining focus.

Boredom is one of the main reasons that students report using a digital device during class ( McCoy, 2016 ). By keeping your students engaged, thinking, and doing activities during class, they are less likely to be tempted by digital distractions. Two studies, one that asked students to use clickers to report lapses in attention ( Bunce et al, 2010 ) and one that tracked students’ eye gaze patterns during lectures ( Rosengrant et al, 2012 , summarized here ), found that students’ attention is highest during and immediately after a change in pedagogy or behavior of the instructor. Some examples of changes that can help students maintain focus include:

Variety in pedagogical activities. If you want students to pay attention to you, then you have to offer them something more interesting than your slides (which they’re perfectly capable of reading for themselves). Look for opportunities to change up the interaction in the classroom. If you're lecturing, why not ask your students to provide examples of the concept you’re describing? If you are leading a discussion seminar, why not design activities for students to talk to each other in small groups instead of just answering your questions for the duration of the class? For example, prompt students turn and talk to each other about a question or challenge you’ve posed. Technology can help promote engagement and collaboration during an activity like this; students could write and respond to each other in a shared Google Doc.

Proximity to the instructor. You are not a prisoner of the podium, or the front of the table, or however your classroom is set up. Of course, you can't be proximate to each student all the time—so move around! You can use your position in the classroom to change the flow of the conversation and the way that students direct their attention.

Humor. You probably already knew that students typically pay attention to jokes. But there's a lot more behind that surface observation: laughter in the classroom can make students more comfortable, lower their affective filter , encourage intellectual risk-taking, decrease anxiety, and establish a more productive student-teacher relationship.

Using technology for learning and engagement

Furthermore, students may prefer taking notes on their computer rather than by hand. In one survey of college students, 70% of students report that having a laptop in class is helpful for their academic performance, with note-taking cited as the most important benefit ( Kay and Lauricella, 2014 ). Additional reported benefits include engagement with in-class academic activities, and communication and collaboration with peers ( Kay and Lauricella, 2014 ; Fried, 2008 ).

Technology as a technology of inclusion

While for many students banning devices from the classroom may seem like a minor inconvenience, students with dyslexia, ADHD, or visual impairments use computers to take notes and to access cloud-based assistive technologies. People with invisible disabilities are enrolling in higher education settings in increasing numbers, and require access to technologies that assist with their learning. Allowing all students access to a device in class avoids singling out students who have important reasons for using one.

To allow or not allow devices?

Faculty are often hesitant to allow students to use devices in the classroom due to the potential for distraction. However, we note that the challenge with digital devices is not the device per se, but off-topic usage. We can decrease the temptation by ensuring that the class itself is interactive and engaging, and that any use of technology is relevant.

We recommend being intentional, transparent, and flexible about use of digital devices in the classroom.

Start by thinking carefully about your learning objectives , and identify activities that align with your objectives and enhance learning. Sometimes the most appropriate activity might not involve technology, but instead might include students talking to a neighbor, drawing a diagram on paper, or solving a problem on a white board. In other cases, you might see an ideal use case for electronic devices. For example, you might incorporate online tools that provide insight into student understanding (such as polls) or that allow collaborative work.

During some portions of a class, you might encourage students not to use their devices, but to instead maintain their attention on the conversation, for example. (You may wish to apply these directions flexibility, with the understanding that some students rely on digital tools for learning.)

Communicate clearly—and frequently—about when and why to use a device, as well as why not to use a device. Share the research about how off-topic device usage impedes learning.

Include a technology policy on your syllabus. In addition to letting students know what they can and cannot use, it is important to let them know why.

Share advice about good practices for using digital devices. Guidance about turning off extraneous applications and notifications, and closing the device when an activity is completed, will help students not only in your class, but also in their future work environments.

For more information...

Beth McMurtrie, " Should You Allow Cellphones in Class? "  The Chronicle of Higher Education  (20 October 2022).

James M. Lang, Distracted: Why Students Can't Focus and What You Can Do about It  (Hachette, 2020).

J. Weinberg, " Why To Discourage Laptops In Class (With Slides You Can Show Your Students) ," Daily Nous (15 August 2018). [These slides provide an overview of research surrounding using laptops in class; additionally, the comments provide some nuance as to why a ban can be problematic.]

Zhu, E., Kaplan, M., Dershimer, R. C., & Bergom, I. (2011). Use of laptops in the classroom: Research and best practices . CRLT Occasional Papers, 30(6).

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How technology is reinventing education.

New advances in technology are upending education, from the recent debut of new artificial intelligence (AI) chatbots like ChatGPT to the growing accessibility of virtual-reality tools that expand the boundaries of the classroom. For educators, at the heart of it all is the hope that every learner gets an equal chance to develop the skills they need to succeed. But that promise is not without its pitfalls.

“Technology is a game-changer for education – it offers the prospect of universal access to high-quality learning experiences, and it creates fundamentally new ways of teaching,” said Dan Schwartz, dean of  Stanford Graduate School of Education  (GSE), who is also a professor of educational technology at the GSE and faculty director of the  Stanford Accelerator for Learning . “But there are a lot of ways we teach that aren’t great, and a big fear with AI in particular is that we just get more efficient at teaching badly. This is a moment to pay attention, to do things differently.”

For K-12 schools, this year also marks the end of the Elementary and Secondary School Emergency Relief (ESSER) funding program, which has provided pandemic recovery funds that many districts used to invest in educational software and systems. With these funds running out in September 2024, schools are trying to determine their best use of technology as they face the prospect of diminishing resources.

Here, Schwartz and other Stanford education scholars weigh in on some of the technology trends taking center stage in the classroom this year.

AI in the classroom

In 2023, the big story in technology and education was generative AI, following the introduction of ChatGPT and other chatbots that produce text seemingly written by a human in response to a question or prompt. Educators immediately  worried  that students would use the chatbot to cheat by trying to pass its writing off as their own. As schools move to adopt policies around students’ use of the tool, many are also beginning to explore potential opportunities – for example, to generate reading assignments or  coach  students during the writing process.

AI can also help automate tasks like grading and lesson planning, freeing teachers to do the human work that drew them into the profession in the first place, said Victor Lee, an associate professor at the GSE and faculty lead for the  AI + Education initiative  at the Stanford Accelerator for Learning. “I’m heartened to see some movement toward creating AI tools that make teachers’ lives better – not to replace them, but to give them the time to do the work that only teachers are able to do,” he said. “I hope to see more on that front.”

He also emphasized the need to teach students now to begin questioning and critiquing the development and use of AI. “AI is not going away,” said Lee, who is also director of  CRAFT  (Classroom-Ready Resources about AI for Teaching), which provides free resources to help teach AI literacy to high school students across subject areas. “We need to teach students how to understand and think critically about this technology.”

Immersive environments

The use of immersive technologies like augmented reality, virtual reality, and mixed reality is also expected to surge in the classroom, especially as new high-profile devices integrating these realities hit the marketplace in 2024.

The educational possibilities now go beyond putting on a headset and experiencing life in a distant location. With new technologies, students can create their own local interactive 360-degree scenarios, using just a cell phone or inexpensive camera and simple online tools.

“This is an area that’s really going to explode over the next couple of years,” said Kristen Pilner Blair, director of research for the  Digital Learning initiative  at the Stanford Accelerator for Learning, which runs a program exploring the use of  virtual field trips  to promote learning. “Students can learn about the effects of climate change, say, by virtually experiencing the impact on a particular environment. But they can also become creators, documenting and sharing immersive media that shows the effects where they live.”

Integrating AI into virtual simulations could also soon take the experience to another level, Schwartz said. “If your VR experience brings me to a redwood tree, you could have a window pop up that allows me to ask questions about the tree, and AI can deliver the answers.”

Gamification

Another trend expected to intensify this year is the gamification of learning activities, often featuring dynamic videos with interactive elements to engage and hold students’ attention.

“Gamification is a good motivator, because one key aspect is reward, which is very powerful,” said Schwartz. The downside? Rewards are specific to the activity at hand, which may not extend to learning more generally. “If I get rewarded for doing math in a space-age video game, it doesn’t mean I’m going to be motivated to do math anywhere else.”

Gamification sometimes tries to make “chocolate-covered broccoli,” Schwartz said, by adding art and rewards to make speeded response tasks involving single-answer, factual questions more fun. He hopes to see more creative play patterns that give students points for rethinking an approach or adapting their strategy, rather than only rewarding them for quickly producing a correct response.

Data-gathering and analysis

The growing use of technology in schools is producing massive amounts of data on students’ activities in the classroom and online. “We’re now able to capture moment-to-moment data, every keystroke a kid makes,” said Schwartz – data that can reveal areas of struggle and different learning opportunities, from solving a math problem to approaching a writing assignment.

But outside of research settings, he said, that type of granular data – now owned by tech companies – is more likely used to refine the design of the software than to provide teachers with actionable information.

The promise of personalized learning is being able to generate content aligned with students’ interests and skill levels, and making lessons more accessible for multilingual learners and students with disabilities. Realizing that promise requires that educators can make sense of the data that’s being collected, said Schwartz – and while advances in AI are making it easier to identify patterns and findings, the data also needs to be in a system and form educators can access and analyze for decision-making. Developing a usable infrastructure for that data, Schwartz said, is an important next step.

With the accumulation of student data comes privacy concerns: How is the data being collected? Are there regulations or guidelines around its use in decision-making? What steps are being taken to prevent unauthorized access? In 2023 K-12 schools experienced a rise in cyberattacks, underscoring the need to implement strong systems to safeguard student data.

Technology is “requiring people to check their assumptions about education,” said Schwartz, noting that AI in particular is very efficient at replicating biases and automating the way things have been done in the past, including poor models of instruction. “But it’s also opening up new possibilities for students producing material, and for being able to identify children who are not average so we can customize toward them. It’s an opportunity to think of entirely new ways of teaching – this is the path I hope to see.”

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6 Ways to Unplug From Classroom Technology in Our Digital Age

There are a lot of great ways to use tech in the classroom, but challenging students to sometimes work without it has benefits for creativity, critical thinking, and engagement.

I recently spoke with several tech coaches who had done audits of digital tools in their buildings—they found more than 400 tools being used in their schools! I know a lot about technology, yet I still find myself struggling to strike the right balance of technology in the classroom. Avoiding overreliance on technology in our highly digital world can be challenging. One solution is to “unplug.”

Integrating into your classroom unplugged activities that do not require technology can offer many benefits, including helping students develop a variety of skill sets. Although each of these ideas can also be implemented with technology, there are ways to use these without the tech and that help amplify the learning experience for students. Having an unplugged classroom does not always require a lot of planning or materials. In my classroom, when I notice a decrease in student engagement, I shift to trying new methods and mixing up the activities to promote student choice and more active learning. 

6 Ways to Unplug

1. Genius hour. Students select a topic of interest and have time to develop a presentation. They may refer to resources such as books, videos, or internet research, but their presentation must be done without the use of technology. Students can create a visual display, such as a poster, a replica, or a demo of their topic, and then deliver a presentation to their classmates.

2. Place-based learning. Opportunities to explore the community while connecting content to the real world make learning experiences more valuable and meaningful for students. One year, my students did an outdoor project about childhood, and they visited a local park and playground for research.

Students in a history class could visit local historical sites to better understand the content they are learning. Science classes such as biology or ecology can have students explore local areas, learn about the ecosystem, and participate in projects to clean up the community or learn about and present solutions to environmental concerns. Place-based learning boosts student engagement, fosters student agency, and helps students develop a greater understanding of their impact on the community and even the world.

3. Project-based learning (PBL). Through PBL, students have many opportunities to build essential skills that are in demand for future work. It boosts engagement and makes learning more relevant, which also helps with motivation. Whether PBL is done through a grade-level focus, cross-curricular collaboration, or individually, students and teachers benefit from it.

For example, my Spanish class focused on the United Nations Sustainable Development Goals one year. Students created different products by hand to represent their learning. One of my students made a watercolor project to display land regions and plants, another student used clay to create different structures related to her topic of housing, and several students designed visuals to represent their learning. Beyond the research, helping students find ways to share learning that builds confidence and promotes creativity and problem-solving will benefit them as they consider skills needed in the future.

4. Sketchnoting. A few years ago, I decided to dive into sketchnoting as a way to engage students in a more creative way. Sketchnoting is visual note-taking, the process of using drawings to represent words or concepts. It has been referred to as doodling with a specific purpose: to represent complex topics. For students who enjoy doodling, sketchnoting has been a great option. One year, we created PSAs to inform classmates and the school community about digital citizenship. For teachers who may use tools to have students create word clouds, sketchnoting is a great option to move away from the tech.

5. Skits. Skits and role-playing boost creativity, collaboration, and student engagement in lessons. Some students may hesitate to be involved, but providing some structure and ongoing support and check-ins can help students become more confident and comfortable when working with classmates. There are many tools available for creating videos; however, performing live in class can be fun. For students who prefer not to perform in front of classmates, this could be a time when technology is used to record the skit to then be played in class. Some students have more confidence when they have prepared, recorded, and then shared their skit. 

6. Station rotations. Several years ago, I was dealing with a decrease in student engagement in my own classroom, and I wanted to provide more opportunities for students to collaborate, engage in more hands-on learning, and be more active. I decided to try stations. Some unplugged activities can include having students create flash cards, asking students to make up a game, or giving students the option to select from a variety of materials (markers, paper, sticky notes) and then come up with their own way to practice with the content at their station. 

There are a variety of benefits of unplugging in the classroom. Digital tools are quite useful, but we need to find some balance and avoid overreliance on technology in the classroom. Without clearly defined objectives or lessons delivered in an interactive or game-based learning platform, students have to work together. Reducing the use of technology promotes more active learning and interactions that help build relationships. Students can build essential skills such as collaboration, creativity, critical thinking, and problem-solving by learning in different ways.

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Embracing technology in today's classrooms

Second-grade teacher and Liberty University alumna Angie Kraje (’00) assists her students as they work on iPads.

It is 9 a.m. at Boonsboro Elementary School in Bedford County, Va. Second-grade teacher and Liberty University alumna Angie Kraje (’00) hands each of her students an iPad and instructs them to open a math application. The students independently complete problems designed for their grade level on their high-tech tool and raise their hands if they have a question.

Tablets and smartboards are common sights in classrooms now. These devices have ushered in a new era of teaching methods. Teachers who once stood in front of a classroom in a cloud of chalk dust and amidst the grinding sound of pencils being sharpened are now using digital tools to engage their students in the learning process.

While some may think this modern trend is a disadvantage — causing too much screen time and not enough hands-on learning — many in education are finding that these cutting-edge tools are helping pupils better prepare to succeed in the 21st century.

Last April, Project Tomorrow — a national educational nonprofit that researches technological resources for K-12 schools — released a report on digital learning, focusing specifically on student experience in a blended classroom, where the teacher integrates technology with traditional teaching methods. The results from over 430,000 K-12 students representing over 8,000 schools in the U.S. showed that 63 percent of teachers use tablets; 58 percent of principals have implemented technology in the classroom; 63 percent of students in grades 6-12 prefer a blended learning environment; and 51 percent of parents want their children in a blended learning environment.

“The ability to use technology within a school or class environment engages students in active learning and establishes a foundation for the development of independent learning,” the report concluded.

With the wave of technology carrying so many school systems into the future, Liberty University’s School of Education is at the forefront, training students to become the future generation of teachers who will employ this new technology and innovation in the most effective ways.

Dr. Karen Parker, dean of the School of Education, said that Liberty is preparing its students for “real-world K-12 settings” by actively training and preparing them to use technology as a valuable tool in their future classrooms. She noted that 90 percent of graduates from Liberty’s program are employed upon graduation.

“To me, this is the highest testament (to our success) — that we are training our teacher candidates to adapt to what is current,” she said. “Educators view our students as the ones bringing new ideas and expertise in using these technologies, which is what we want to maintain.”

Kraje, who earned her B.S. in General Studies with an elementary K-8 teaching licensure, is one of thousands of teachers across America using new technology in their classrooms. She said the courses she took at Liberty prepared her to embrace new experiences and new trends in education.

“To be an educator is also to be a lifelong learner. And with ever-changing technologies, it is necessary to keep current with what’s new,” she said.

School systems nationwide are investing in the latest software and Web apps for all ages, starting in kindergarten, some even assigning tablets and laptops to students for use year-round. Educators everywhere are debating whether or not technology assists with different learning styles, whether it makes school more exciting for the students, and whether or not it is beneficial as a whole.

“There are many ways that technology plays a positive role in student learning,” Kraje said. “Many educational programs have apps and websites designed for hands-on practice, where students have personal logins and applications that are on their level. Many of these programs also provide students’ results immediately so that teachers are able to adapt their instruction to meet the needs of all students.”

Teachers are using creative applications to keep their students excited about their learning. Randall Dunn, associate professor and chair of innovation and technology in the School of Education, recently observed a Liberty student doing his student teaching requirement in a local classroom. The student used a popular Web app that allowed everyone in the room to compete in a trivia game. (These Web apps are becoming popular in restaurants and other public places). He watched as all the students raced to beat each other to the answer.

Parker said technology is effective because it allows students to “individually engage.”

“It appeals to their current interests, and it is meeting them where they are,” she said. “It allows for students to learn actively, and when they are active, they are engaged. When students are using a tablet or laptop in a classroom, they are actively selecting answers.”

A second-grade student at Boonsboro Elementary School works on a smartboard, a digital projector that allows students to go to the front of the classroom and interact with the entire class while the teacher is presenting the lesson.

Taking the place of whiteboards now are smartboards, a digital projector that allows students to go to the front of the classroom and interact with the entire class while the teacher is presenting the lesson.

Parker said that technology courses are “infused” throughout Liberty’s curriculum. The university has active learning classrooms that are outfitted with these technologies, where students can learn how to integrate the use of smartboards and tablets into their future learning environments. 

Dunn teaches courses that focus on using technology in the classroom, and he keeps up-to-date with what the School of Education should implement into its own curriculum.

When Liberty students go to teach in local schools, according to Dunn, they have the opportunity to present new ideas to the teachers.

“In the world of educational research, we usually say five years is the maximum time for something to be current,” he said. “In the world of technology, we say two years because it changes so quickly. We cannot possibly train a sophomore on technology that will be in the classroom when they are finally entering their first year of teaching three years later. We have to train them with the mindset, the approach, and the knowledge in order to be effective using whatever is out there.”

He said one of the newest trends in teaching is not only technology, but also the idea of “flip classrooms” — where the learning environment “flips” from the classroom to the student’s own home. The teacher works to ensure that the content presented to the student that day at school is placed on YouTube, which makes the lesson available to the student at home when they are working on a homework assignment with their parents.

“If your child is learning at home with a parent, then when he or she goes to school the next day, they are able to progress further in the classroom because of the direct instruction that happened at home,” Dunn said.

When students bring their devices home, technology allows parents to be more effective in helping them with homework.

“If a parent does not understand their child’s homework, they can pull up the lesson on the tablet or laptop and learn with their child immediately,” he said.

Liberty utilizes Horizon Reports to stay up-to-date on technology trends. These reports chart emerging technologies for teaching and learning. The 2015 edition showed research indicating that in one to two years, there will be an increased use of flip classrooms and technological devices in the classroom. 

“Online learning and classroom learning have now turned into a blended learning environment,” Dunn said. “A long time ago they were separated; however, now they are here to stay, and it is important to keep up with these trends.”

Parker said that technology use in the classroom is an example of “differentiated instruction,” a buzzword in education.

“When we say we ‘differentiate the curriculum,’ we are saying that we are not just teaching a particular subject, but we are learning to adapt our lessons to our students’ needs,” she said.

It feeds into another buzzword: accountability.

“Technology allows for teachers to see how an individual student is participating in an assignment,” she said. “When they use technology in the classroom, teachers are seeing which students are engaged, allowing them to measure a student’s progress immediately. This sets a higher standard not only for the teacher, but also for the student.”

Parker said that technology also helps teachers maintain records.

“Many classrooms are set up to help teachers measure a student’s progress from the beginning of the year, showing where he or she needs to improve,” she said. “Teachers are also responsible for keeping a log of how many students understood what was taught and what they did as an educator to improve understanding. This helps school systems know how effective a teacher is with their students.”

Beth Ackerman, the School of Education’s assistant dean for assessment, said that Liberty’s education students are shown that teaching is a toolbox. 

“You have your different tools that you use at different times to make sure your students are learning from all aspects,” she said. “Teaching is not just lecturing, not just group activity, not just essays, and it is not just technology. We teach our students to use every tool in their toolbox in order to speak to 100 percent of their students.” 

Ackerman said that “old-school” teaching was giving a student a lesson, then a test, and asking them if they understood a particular subject.

“Now, with the use of technology, educators can assess and constantly engage their students to find out if they understand the material at the beginning of a lesson and if they better understand it by the end of the lesson,” she said. “Technology gives us a tool — a hammer — for constant assessment.”

Parker said that as an educator, it is important to be aware of what is new and how to translate that to your students.

“One great rule in teaching is to not only show a student how to do something, but also to allow them to do it themselves,” she said. “It is important to us that our students learn to walk away from our program knowing there is a method to teaching that engages technology to be effective. Our graduates have that mindset, and they will continue to impress educators for years to come.”

Liberty offers a B.S. in Elementary Education, with specializations in English, math, science, or social science. Students can also add a dual endorsement in special education, which requires them to take two additional courses. A secondary licensure is available for students interested in teaching at the high school level.

Those interested in furthering their degree can earn licensure online through Liberty’s Master of Arts in Teaching (M.A.T.) program. Licensure and non-licensure options are available through the school’s Master of Education (M.Ed.), Education Specialist (Ed.S.), and Doctor of Education (Ed.D.) course offerings.

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Jessica Grose

Most teachers know they’re playing with fire when they use tech in the classroom.

By Jessica Grose

Opinion Writer

A few years ago, when researchers at Boston College and Harvard set out to review all of the existing research on educational apps for kids in preschool through third grade, they were surprised to find that even though there are hundreds of thousands of apps out there that are categorized as educational, there were only 36 studies of educational apps in the databases they searched. “That is not a strong evidence base on which to completely redesign an entire schooling system,” Josh Gilbert, one of the co-authors of the study, told me over the phone.

That said, their meta-analysis of the effects of educational app use on children’s literacy and math skills, published in 2021, found that well-designed apps can make a positive difference when it comes to “constrained skills” — things like number recognition or times tables in math, or letter sounds in literacy. Unconstrained skills are more complex ones that develop over a lifetime of learning and can deepen over the years. (It’s worth noting that many popular educational apps are not high-quality .)

Gilbert said that overall, “the range of effects was gigantic.” Because they were all over the place, “we have to go beyond the average effect and say, OK, for whom does the app work? Under what conditions? On what types of measures? And I think those are the questions that researchers, policymakers, school leaders, teachers and principals should be asking,” he said. “What are the best use cases for this digital technology in the classroom?”

In last week’s newsletter , I came in pretty hot about the pitfalls of educational technology in American classrooms. I’m convinced that since students returned to in-person school after the disruptions of 2020-21, there are too many schools that haven’t been taking a thoughtful or evidence-based approach to how they’re using screens and apps, and that it’s time for a pause and a rethink. But that doesn’t mean there are no benefits to any use of educational technology.

So for the second part of this series, I wanted to talk to people who’ve seen real upsides from using tech in their classrooms. Their experiences back up some of the available research , which shows that ed tech can help teachers differentiate their material to meet the needs of students with a wide range of proficiencies. Further, teachers report that students with disabilities can really benefit from the assistive technologies that screens and apps can provide.

Debbie Marks, who teaches third grade in Oklahoma, told me that her students’ school-issued laptops allow them “to participate in differentiated reading interventions designed specifically for them” during the school day. That differentiation allows her to better assess how each student has progressed and tailor her instruction to each student.

“So for example, we could be working on story elements and we’re working on characters,” she explained to me when we spoke. “One student might be at the point where they’re just trying to identify who the main character is. Another student might be trying to identify character traits while a higher-level student would be comparing characters or would be identifying how the character changes throughout the story based on the plot. So it really allows me to develop one-on-one lessons for every kid in my classroom.”

Marks works in a rural district, about 90 minutes away from Tulsa, and some of her students may be traveling 45 minutes to an hour just to get to class. She said that the use of devices allows her to better connect with her students’ parents and to get them more involved in what’s going on in a classroom that is physically far from them. Marks also said that screens enable her to do things like virtual author visits, which she says get the kids really excited and engaged in reading.

I also heard from several teachers who said that assistive technology has been a game changer for students with special needs. Duncan Law, who works as a special education support teacher in an elementary school in Oregon, put it this way: “Technology can be a necessity for students with special needs in accessing core curriculum/standards, as well as for fluency practice. In the best case scenario, learning via tech is guided and closely monitored by teachers, and students are actively engaged with feedback. For students with dysgraphia and dyslexia, word processing tools offer a meaningful way to demonstrate/assess their writing skills.”

Several middle school and high school teachers who said that tech was helpful in their classrooms seemed to be using it as an efficient way to teach students more rote tasks, allowing more class time to be spent helping build those “unconstrained” skills.

Doug Showley, a high school English teacher in Indiana who’s been teaching since 1996, gave me the example of how he has changed his quizzes over time by integrating technology. He used to just give straight-up vocabulary quizzes where students had to define words; now he and his colleagues have moved toward “diction quizzes,” requiring students to understand the nuances of using specific words in sentences.

Showley noted that it’s easier to quickly look up words than it was in the hard-copy dictionary days, and that his students “have access to online dictionaries” during these quizzes. They’re given four synonyms and are asked to figure out which synonym best fits into a sentence. “To determine that, they have to go beyond just that basic definition. They’ve got to get into the connotative meaning of the word and the common usage of the word,” he explained.

But Showley also said that he monitors the kids quite closely. When they’re doing a task that involves their laptops, he’ll have them set up so all of their screens are facing him. He estimates that usually only one or two kids out of a class of 25 really aren’t able to stay on task when they’re on the screens.

He also told me that his school has made the decision not to block A.I., including ChatGPT, though it is a hot topic of discussion. The challenge of dealing with A.I. is something that came up a lot among teachers in the upper grades, and the overall vibe I got was that no one quite knows what to do with it yet.

After we spoke, Showley emailed me to say that “we should carefully gauge to what degree and in what way tech is used at each level of education.” And he wrote something that I think really sums up both the promise and the peril of ed tech (and is also such a classic English teacher passage):

I couldn’t help but think of Prometheus defying the Olympic gods by sharing the first-ever technological advancement with humankind: fire. Fire, as with every other significant advancement since, both propelled society forward and burnt it to the ground. It enlightened our minds and souls, and it tormented them, just as Prometheus was perpetually tormented through his punishment for sharing too much of the gods’ power.

Perhaps deliberately, one of the popular digital whiteboards is the Promethean board.

The technology isn’t going away. We need to start creating better frameworks to think about how students and teachers are using technology in our schools, because the tech companies won’t stop pushing their products, whether or not there’s evidence that shows educational gains. CNN’s Clare Duffy reports that later this year, Meta “will launch new software for educators that aims to make it easier to use its V.R. headsets in the classroom,” though “it remains unclear just how useful virtual reality is in helping students learn better.”

In next week’s newsletter, I’ll write about solutions to some of the problems posed by ed tech, and how we might create a future where we can minimize some of the most egregious hazards of distraction and invasion of privacy, and realize some of the potential of technology’s most fantastic educational promises.

Jessica Grose is an Opinion writer for The Times, covering family, religion, education, culture and the way we live now.

Edtech in Elementary Schools

Take a look at some great examples of technology in the elementary classroom and how these tools are changing the way young children learn.

Technology has disrupted everything from healthcare and banking to transportation and printing. Now it’s gunning for that staple of childhood: blocks. 

For a lot of kids, blocks on the floor have been replaced by virtual blocks on a screen. And instead of using them to build castles, they’re using them to learn coding courtesy of a LEGO-inspired programming language called Scratch . 

Designed for kids ages eight to 16, Scratch was created by the Lifelong Kindergarten Lab at MIT and originally released in 2007. (A simpler version,  Scratch Jr. , caters to younger users.) Its mission: to facilitate earlier and more in-depth tech education.

“We need to expand the notion of ‘digital fluency’ to include designing and creating, not just browsing and interacting,” Scratch’s inventors  wrote in 2009 .

Over the past decade, that view has gained mainstream traction, as evidenced by the company's more than 40 million registered users in and out of schools.

Over at UC Irvine’s Digital Learning Lab,  Dr. Mark Walschauer and his team are using funding from the National Science Foundation to design a Scratch curriculum for early elementary-age kids. Walschauer is particularly fond of Scratch’s user-friendly language. Its block structure, he says, makes typos (common in kid coding) impossible. On top of that, its media-friendly interface lets kids incorporate cat photos and their own voices in programming projects.

More broadly, Walschauer appreciates that teachers increasingly employ technology in elementary classrooms.

“I’m a firm believer in developing computational thinking in schools,” he told Built In, “because I think computation is such an important part of all careers.”

7 Edtech Companies to Know

Houghton mifflin harcourt.

• Mind Research Institute

Flocabulary

The screentime conundrum.

Edtech is a multi-billion-dollar industry, and the growing preK-12 software market is currently worth more than $8 billion . Digital tools abound to help kids with reading, writing, basic math and other subjects. In Southern California schools, especially, Dr. Walschauer often sees tablet and laptop carts in elementary classrooms. 

But the combo of elementary-age kids and screentime is a fraught subject for many. Detractors say it’s unhealthy. And it’s true that researchers have scant data on how screens impact kids’ highly malleable brains in the long term. In the spirit of caution , the World Health Organization recently recommended an hour or less of daily screentime for kids under five. “Less,” the group added, “is better.”

Dr. Marilyn Price-Mitchell , a developmental psychologist who studies the impact of technology on young people, seconds the WHO’s sentiments. As technology has become more prevalent over the past few decades, she notes, robust longitudinal studies have found a decline in empathy among college students. 

“We don’t really know what the cause of that decline is,” Dr. Price-Mitchell told Built In, “but we know that children are spending less face-to-face time with humans.”

But their face-to-screen bonding has greatly intensified.

Elementary educators, then, must deal with a conundrum: preparing kids for a hyper-connected world while simultaneously encouraging healthy human development. The latter requires in-person interaction, not coding savvy.

Price-Mitchell and Walschauer agree, however, that tech can play an important role in elementary classrooms by augmenting educational toolkits rather than dominating the curriculum. 

We’ve rounded up 7 companies finding creative ways to integrate technology in the elementary classroom.

Location: Montreal, Quebec

Paper, a remote-first edtech platform, partners with elementary schools throughout the U.S. and Canada to provide tutoring services at no cost to families. Paper tutors can help students in a variety of languages from English and Spanish to French or Mandarin. Tutors are also available to students 24/7 using the company’s live help chat feature. The company also offers a number of online tools to help elementary-school students with reading and math proficiency. 

Location: Boston

How it’s shaping elementary edtech:  The storied textbook publisher also developed  iRead , a digital literacy program designed to get every student reading by third grade. As part of the program, which is backed by a multi-school-district study , kids send digital avatars to virtual classes that automatically adapt to their strengths and weaknesses. 

MIND Education

Location: Irvine, CA

How it’s shaping elementary edtech: This non-profit organization makes ST Math , a math-instruction program whose vibrant world teems with penguins and rainbow balloons. Reportedly used by 1.2 million elementary-age students, the program promotes deep conceptual understanding over mere memorization. 

More in Education and Technology Companies That Hire Former Teachers

Lexia Learning

Location: Concord, MA

How it’s shaping elementary edtech: Designed in accordance with the latest pedagogical research, Lexia’s CORE5 literacy platform cuts testing out of the reading process. Instead, the interface assesses K-5 students as they read, and the adaptive lessons—focused on building blocks like phonetics and comprehension—find and fill in competency gaps as they appear.

Location: New York City

How it’s shaping elementary edtech: Amplify has helped modernize elementary school instruction and assessment for a couple of decades now. Its teacher-friendly tech tools cover a variety of subjects, including reading to science. The company also offers course sequences on more specific topics like fractions and English-language acquisition.

Location: Brooklyn, NY

How it’s shaping elementary edtech: Kids use Flocabulary to learn new vocabulary words from video lessons that feature hip-hop-style songs. The catalog covers K-12 science, math and English terminology, and teachers can reinforce new lingo with worksheets and other app-based assessments.

Location: Berkeley, CA

How it’s shaping elementary edtech: Enuma’s signature app, Todo Math , features more than 40 multi-level math games in which kids master Common Core concepts and earn cyber-stars for correct answers. Like all of the company’s apps, Todo Math welcomes kids of all abilities. It even has a special font for dyslexic readers and tools for circumventing fine motor skill challenges.

The Future of Elementary School

Walschauer, for one, sees a few especially promising elementary edtech tools on the horizon. There’s formative assessment technology, which Lexia and other edtech companies use to assess learning as it happens. By making summative assessments (like testing) redundant, it could help decrease the stress and shame that often accompanies them. 

In a similar vein, Walschauer is excited about the surge of personalized tech tools for kids with special needs. Even the mere presence of a computer, he says, can foster an atmosphere of greater inclusion. As one example, he refers to the time he witnessed an autistic 10-year-old bond with a classmate on a laptop-based project.

“To just to sit there and talk was too painful and too difficult,” he says, “but when they were working together on the computer, showing each what they had done, [the screen] provided a nice bridge for the [autistic] student to communicate a lot more.”

For her part, Price-Mitchell wants edtech companies to incorporate holistic measures like empathy in addition to the narrow numerical measures they already focus on – like the number of fraction-based math problems a child correctly solves. Without empathy, she says, kids can’t apply their mechanical skills — such as those sharpened by video games — to the “social and environmental problems of the world” in an exciting or meaningful way. 

But empathy grows from meaningful human connection and face-to-face interaction. Which isn’t to say every glance at an app is a step towards sociopathy, but both Price-Mitchell and Walschauer agree: No online elementary schools, please. 

“When we eliminate the human interaction, particularly in young people’s learning,” Price-Mitchell says, “we have to ask ourselves the question: how will it affect these children in their development of broader, much more important human characteristics like curiosity or creativity or empathy or resilience?”

Learning First, Gadgets Second

There’s at least one thing on which both Price-Mitchell and Walschauer agree when it comes to the future of elementary education: “blended learning.” A mix of in-person traditional instruction and independent work with technology, it is most effectively implemented by tech-savvy teachers who ensure that edtech serves academics and not vice versa.

“I remember one class where teachers assigned students to do a PowerPoint,” Walschauer said, “and [the students] got a grade based on how many transitions, colors and different formats they used. In other words, [the assignment] was: Create a PowerPoint from hell.”

That’s exactly the wrong way to combine education and tech, he says. The students learned about the tool itself, PowerPoint, but didn’t use it to meet their academic or developmental needs.

When it’s deployed smartly, though, edtech can meet a variety of elementary educational needs. Snapping together Scratch's blocks, for instance, teaches kids more than how to use Scratch — it teaches them modes of reasoning relevant to every programming language.

And just as she hopes edtech companies will focus more on holistic measures, Price-Mitchell also wants schools to take a more holistic approach by incorporating technology “into the other things that we know humans need, like time to reflect and discuss with their peers and teachers. Kids could also use tech to reflect on the feeling of learning, or to catalog what sparks their curiosity.” 

Despite a flood of untested edtech gadgets, however, Walschauer says there's a trend toward familiar and versatile basics like Google docs and spreadsheets — “the kinds of things that you and I use to share, to write, to do research, to share work together.” 

In edtech as in all tech, sometimes less is more. 

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