thesis educational technology

• USF Research
• USF Libraries

Digital Commons @ USF > Theses and Dissertations

Instructional Technology Theses and Dissertations

Theses/dissertations from 2010 2010.

Evaluation of the Flicker Effect as a Generative Strategy in Enhancing ComputerBased Instruction (CBI) of Visual Recognition and Classification , Ping Luo

Theses/Dissertations from 2007 2007

The Effects of Goal Message and Goal Orientation on Learning in a Web-Based Tutorial , John M. Bunch

The Model-Based Systematic Development of LOGIS Online Graphing Instructional Simulator , Darrel R. Davis

The effectiveness and user perception of 3-dimensional digital human anatomy in an online undergraduate anatomy laboratory , Amy JoAnne Hilbelink

The relationship between technology integration and achievement using multi-level modeling , Tina N. Hohlfeld

Technology in low socio-economic K-12 schools: Examining student access and implementation , Katherine J. Kemker

Perceptions of Florida school library media specialists relative to the saliency of collaboration, leadership, and technology tasks outlined in Information Power: Changes since 1996 , Terrell M. Pace

Online delivery of career choice interventions: Preferences of first-year students in higher education , Melissa Venable

Theses/Dissertations from 2005 2005

A Comparison of Traditional Physical Laboratory and Computer Simulated Laboratory Experiences in Relation to Engineering Undergraduate Students’ Conceptual Understandings of a Communication Systems Topic , Giti Javidi

Theses/Dissertations from 2004 2004

Improving the Environment in Distance Learning Courses Through the Application of Aesthetic Principles , Darryl J. Hancock

Feedback In Distance Learning: Do Student Perceptions Of Corrective Feedback Affect Retention In Distance Learning? , Lori S. Kielty

Are Preservice Instructional Designers Adequately Prepared For Tomorrow’s Diverse Learning Audiences?—A Cultural Content Analysis Of Textbooks (1993-2003) Used For Instructional Design , Sujie Man

Theses/Dissertations from 2002 2002

The Effects Of Animated Textual Instruction On Learners' Written Production Of German Modal Verb Sentences , Elizabeth A. Caplan

Theses/Dissertations from 2001 2001

Effects of Deadline Contingencies in a Web-Based Course on HTML , Tina L. Majchrzak

Advanced Search

• Email Notifications and RSS
• All Collections
• USF Faculty Publications
• Open Access Journals
• Conferences and Events
• Theses and Dissertations
• Textbooks Collection

Useful Links

• Rights Information
• SelectedWorks
• Submit Research

Home | About | Help | My Account | Accessibility Statement | Language and Diversity Statements

Privacy Copyright

• Faculty of Arts and Sciences
• FAS Theses and Dissertations
• Communities & Collections
• By Issue Date
• FAS Department
• Quick submit
• Waiver Generator
• DASH Stories
• Accessibility
• COVID-related Research

Terms of Use

• Privacy Policy
• By Collections
• By Departments

Essays on Technology in Education

Citable link to this page

Collections.

• FAS Theses and Dissertations [6136]

Contact administrator regarding this item (to report mistakes or request changes)

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.

RELATED CONTENT

Podcast: How education technology can improve learning for all students

To make ed tech work, set clear goals, review the evidence, and pilot before you scale

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.

• Media Relations
• Terms and Conditions
• Privacy Policy

Home > Bagwell College of Education > Instructional Technology > Ed.D Instructional Technology Dissertations

Doctor of Education in Instructional Technology Dissertations

The Ed.D. in Instructional Technology is fully online and designed for educators who currently hold or aspire to hold a technology leadership position at the school, district, or state level. The Ed.D. is intended to deepen and broaden the educational technology leadership knowledge and skills of candidates. The program is based on the ISTE Standards for Technology Directors and the CoSN Framework of Essential Skills for K-12 CTOs.

Need to Submit Your Dissertation? Submit Here!

Dissertations from 2023 2023.

Cue the Paralinguistics: A Qualitative Case Study of Teacher Social Presence , Molly R. Bowden

Leading Online Professional Development for Instructional Technology Coaches with Effective Design Elements , Janet Cowart

Navigating the Digital Realm: Perceptions and Challenges of High School Educators in Fostering Digital Citizenship , Kristopher P. Daniels

AP Statistics Students’ Conceptions of Engagement and Technology in a Flipped Classroom: A Phenomenographical Study , Kimberly Gile

Upper Elementary Teacher, Instructional Technology Coach, and Administrator Experiences with Technology Integration During COVID-19 Related School Closures: A Phenomenography , Amber Gravitt

Digital Bridges: How Art Educators Build Professional Learning Networks on Twitter , Jennifer Heyser

Becoming an Effective Digital Educator: A Case Study of Technology Preparation in a Novel Preservice Teacher Internship Program , Stephanie Milner

Dissertations from 2022 2022

The Perceptions of High School Art Teachers on their Experiences with Digital Art , Chris Akins

The Evolving Roles of School Librarians in Diverse Instructional Settings , Kay Wright

Dissertations from 2021 2021

The Parent Role in Teen Digital Citizenship , Christi Harp

Secondary Mathematics Teachers’ Experiences with Technology Integration in a One-to-One School District During Face-to-Face and Remote Instruction: A Phenomenography , Safna Kalariparambil

Teacher Experiences with Multiple One-to-One Technology Integration Models: A Phenomenography , Tiffany Post

Teachers’ Perceptions of One-to-One Laptop Initiative for Increased Learner Communication and Collaboration Skills , Harry Saint Cyr

Student Engagement in the Honors Biology Flipped Learning Environment , Hillary M. Wilson

Dissertations from 2020 2020

Flexibility Matters: A Qualitative Look at Four Middle Grade Teachers’ Implementation of Personalized Learning , Christa Evans Heath

Teacher Perceptions of Personalized Teaching & Learning in an Instructional Technology Graduate Course: A Phenomenographical Case Study , Stephanee Stephens

Dissertations from 2019 2019

Hashtags and Pins in Education: Digital Native Educators in Digital Habitats. , Kelly Pilgrim Cassidy

K-12 Community of Inquiry: A Case Study of K-12 Online Social Studies Teacher Practice in a Virtual School , Kyle Sanders

Dissertations from 2017 2017

The Evolution of Pre-Service Teachers TPACK After Completing an Undergraduate Technology Integration Course , Sherri Booker

Dissertations from 2016 2016

A Comparison of Online and Face-to-Face Achievement in Physical Science , Lisa F. Mozer

Dissertations from 2015 2015

Administrators Using Technology to Increase Family Engagement , Ashley P. Beasley

Job Satisfaction, Organizational Commitment, and Turnover Intention of Online Teachers in the K-12 Setting , Ingle M. Larkin

Dissertations from 2014 2014

Perceptions of Blended Learning: A Case Study on Student Experiences in an Advanced Placement Macroeconomics Course , Daniel A. Gagnon

Advanced Search

• Notify me via email or RSS
• All Collections
• Disciplines
• Conferences
• Faculty Works
• Open Access
• Research Support
• Student Works
• Ed.D. in Instructional Technology Homepage

Useful Links

• Training Materials

Home | About | FAQ | My Account | Accessibility Statement

Privacy Copyright DigitalCommons@Kennesaw State University ISSN: 2576-6805

Home > USC Columbia > Education, College of > Educational Studies > Educational Studies Theses and Dissertations

Educational Studies Theses and Dissertations

Theses/dissertations from 2023 2023.

Centering the Teacher: How an Autonomy-Supportive Environment Impacts Arts Educators’ Sense of Agency and the Collaborative Culture of Their Education Networks , Kyle Andrew Anderson

Effects of a Self-Monitoring Tracking System Combined With Blended Learning Intervention Time on Students’ Self-Regulated Learning Skills And Academic Performance , Jennifer E. Augustine

Reading Strategies: Impact on Fifth Grade African American Males’ Reading Comprehension and Motivation to Read , Patrice Antoinette Barrett

Tip of the Iceberg in Changing School Culture: Acknowledging and Addressing Microaggressions , Nicole Lauren Becker

Impacts of Technology-Enhanced Dual Enrollment Mathematics Course on Rural High School Students’ Intentions of Going to College , Nicolae Bordieanu

Creating a Culturally Inclusive American Literature Classroom , Holly R. Bradshaw

The Impact of a Series of Professional Development Sessions on Culturally Responsive Pedagogy (CRP) on the Awareness Level of Seven Teachers at a Suburban High School , Charity Jo Brady

The Effects of Gamified Peer Feedback on Student Writing in High School English Language Arts , Kerise Amaris Broome

Evaluating the Impact of Personalized Professional Learning on Technology Integration in the Classroom , Angela Bishop Burgess

An Exploration of Perinatal Stress and Associated Mental Health of Transitioning First-Time Fathers , Timothy Reed Burkhalter

A Study of Computational Thinking Skills and Attitudes Towards Computer Science with Middle School Students , Lorien W. Cafarella

Mitigating Student Anxiety in the Secondary Classroom: A Culturally Sustaining Approach , Erin Hawley Cronin

Daily Activities and Routines: A Comparative Case Study of the Home Language and Literacy Environment of Spanish-Speaking Toddlers With and Without Older Siblings , Eugenia Crosby-Quinatoa

Online Professional Development’s Effect on Teachers’ Technology Self-Efficacy and Continuance Intention to Use Pear Deck , Katherine Shirley Degar

Empowering Teachers to Support MTSS Students: An Action Research Study , Sahalija Dentico

Multisensory Phonics Instruction in Struggling Readers , Amanda M. Dixon

Student Engagement Action Research a Focus on Culturally Relevant Instructional Methods , Amia Dixon

Instructional Coaching: A Support for Increasing Engagement in Middle School Mathematics , Christi Ritchie Edwards

A Holistic View of Integrated Care Within Counselor Education: A Multi-Manuscript Dissertation , Alexander McClain Fields

Faculty Perceptions of Readiness and Confidence for Teaching Online: An Evaluation of Online Professional Development , Kevin Brent Forman

Increasing Phonemic Awareness in Intellectually Impaired Students by Using Wilson’s Fundations Phonics Program in a Self-Contained Classroom , Theresa Lynne Garcia

A Causal Comparative Study of the Effects of Physical Activity Course Enrollment on College Students’ Perceived Wellness, Mental Health, and Basic Psychological Needs , Genee’ Regina Glascoe

The Effect of Computer-Based Learning Modules on Pre-Algebra Student Proficiency and Self-Efficacy in Manipulating Math Expressions Involving Negative Signs , Brian Charles Grimm

Exploring Literary Responses to Culturally Relevant Texts Through an AsianCrit Lens: A Collective Case Study of Chinese American Students in a Community-Based Book Club , Wenyu Guo

The Influence and Impacts of Critical Literacy Intervention in Preservice Teachers Culturally Responsive Teaching Self-Efficacy: A Mixed Methods Study , Heather Lynn Hall

Stories From North Carolina Teachers of Color: An Inquiry of Racialized Experiences in the Workplace. , Deborah Stephanie Harrison

Electronic Portfolios in a High School Community of Practice: Action Research Exploring Writing Experiences in an Advanced Placement Writing Course , Archibald Franklin Harrison IV

The Effects of Problem-Based Learning on Mathematics Motivation in a Flipped Classroom Instructional Environment , Joshua David Harrison

University, City, and Community: Athletics Urban Renewal Projects and the University of South Carolina’s Carolina Coliseum and Blatt Physical Education Center, 1964–1971 , Theresa M. Harrison

Stories from North Carolina Teachers of Color: An Inquiry of Racialized Experiences in the Workplace. , Deborah Stephanie Harrisson

Supporting Black Students in Sixth-Grade Science Through a Social Constructivist Approach: A Mixed-Methods Action Research Study , Kirk Anthony Heath

Effects of Choice Reading on Intrinsic Motivation in Underperforming Sixth-Grade Students , Heather M. Henderson

Academic Success and Student Development in the Health Professions: An Action Research Study , Molly Ellen Higbie

Deficit Thinking in Teacher Course Level Recommendations , Andrew Hogan

The Impact of Cognitive Coaching on High School English Teachers’ Implementation of Metacognitve Reading Strategies , Charrai Hunter

Digital Literacy Integrated Into Academic Content Through the Collaboration of a Librarian and a Core Content Teacher , Jeri Leann Jeffcoat

The Effects of Hip-Hop and Rap Music Intervention to Improve the Wellbeing of Black and African American Men , Lanita Michelle Jefferson

Examining the Relationship Between Multicultural Training and Cultural Humility Development in CACREP-Accredited Counselor Education Programs , Sabrina Monique Johnson

Multimodal Digital Literacy Practices: Perspectives of L2 Academic Writing Instructors , Priscila Jovazino Bastos Medrado Costa

Using Yoga, Meditation, and Art Therapy to Combat Complex Trauma and Promote Social–Emotional Learning in the Art Room , Karen Emory Kelly

STEM Educators’ Perceptions of Gender Bias and the Contributing Factors That Persist for Women in STEM Education , Haleigh Nicole Kirkland

A Qualitative Study Examining and Comparing Families’ and Teachers’ Perceptions of School Readiness , Shalonya Cerika Knotts

The Evolution of Contextualized, Discourse-based Professional Development to Support Elementary Teachers in the Implementation of Conceptual Mathematical Teaching Practices , Jennifer Aren Kueter

A Critical Examination Of An in Class Tabata Based Physical Fitness Protocol on Student Engagement Levels in a Sixth Grade Math Class , Justin R. Kulik

Mathematics Teachers’ Attitudes and Intentions Towards Instructional Videos as Part of a Flipped Learning Model , Jessica Lee Lambert

Increasing Math Knowledge in 3 rd Grade: Evaluating Student Use & Teacher Perceptions of Imagine Math , Paoze Lee

Utilizing Case Studies to Increase Critical Thinking in an Undergraduate Anatomy & Physiology Classroom , Sarah E. Lehman

Exploring Chinese International Students’ Motivational Factors in Non-Mandatory Event Participation , Aimin Liao

Preparing In-Service Elementary Teachers to Support English Language Learners: A Qualitative Case Study of a Job-Embedded Professional Development Using TPACK , Rachel Theresa Lopez

Impact of Virtual Models on Students’ Multilevel Understanding of an Organic Reaction , Eli Martin

Measuring the Impact of Peer Coaching on Teacher Effectiveness at Friendship County High School , Whittney Michele McPherson

The Effects of Technology Integration on Academic Performance and Engagement of Third Grade Social Studies Students: A Mixed Methods Study , Ashley Megregian

Supporting LGBTQ+ ELA Students Through Action Research , Nicole Mustaccio

What Are They Thinking?: A Qualitative Study of Secondary Students’ Critical Thinking in Online Classes , Scott Allan Nolt

Shakespeare in Virtual Reality: Social Presence of Students in a Virtual Reality Book Club , John Funchess Ott Jr.

Teacher Observations as Professional Development Opportunities , Ashton Carrie Padgett

Reading Motivation and Retrieval Practice of United States Undergraduates Aged 18 to 23 , Robyn M. Pernetti

A Descriptive Study of Factors That Support and Hinder Classroom Discourse With English Learners , Jillian Camille Plum

Implementing Meaningful Problem-Based Learning in a Middle School Science Classroom , Celestine Banks Pough

Coaching to Success: Moving From a Fixed Mindset to a Growth Mindset Through Positive Motivation , Shannon Dianna Ramirez

The Impact of a Literacy Program on Summer Reading Setback: Providing Access to Books and Project-Based Learning , Tiffany Gayle Robles

An Examination of Semester-Long Review of Behavior Referral Data at a High School in a Southeastern State , Shalanda L. Shuler

The Impact of the Flipped Classroom Model on Elementary Students’ Achievement and Motivation for Learning Geometry , Kimberly M. Smalls

If Not Me, Then Who? A Study of Racial and Cultural Competence in a High School English Department , DiAnna Sox

“So, the World Isn’t Just Old White Guys?”: Student and Teacher Experiences in a Culturally Relevant Advanced Placement Chemistry Class , James Thomas Sox

1, 2, 3: Counting on Problem Based Learning to Improve Mathematical Achievement in African American Students , Kelley P. Spahr

Implementation of Digital Flashcards to Increase Content-Specific Vocabulary Knowledge and Perceptions of Motivation and Self-Efficacy in an Eleventh-Grade U.S. History Course: An Action Research Study , Jill Lee Steinmeyer

Family Therapy, K-12 Public Education, and Discipline Risk: A Scoping Review and Relationship Analysis Multiple Manuscript Dissertation , Cara Melinda Thompson

The Impact of Extended Professional Development in Project-Based Learning on Middle School Science Teachers , Margrett Caroline Upchurch-Ford

A Qualitative Study on Mental Health Resource Utilization of Enlisted Airmen During the COVID-19 Pandemic , Hassahn Khali Wade

Where Race Has No Place: English Teachers’ Efforts to Maintain Space for Diversity in the ELA Classroom , Muzical D. Waite

Navigating Age of Majority-Related Issues in Special Education: The Current Needs and a Potential Means for Aligning Professional Values With Policy and Practice , Charles Blayne Walters

The Impact of Opendyslexic Font on the Reading Comprehension of Tier II and Tier III Reading Intervention Students , William David Whitmire

Theses/Dissertations from 2022 2022

Implementing a Technology-Based Instructional Module in An Introduction to Engineering Course: The Impact on Student’s Vocabulary Retention and Attitudes Towards Learning , Robin T. Amick

Effectively Integrating Technology to Engage Students and Meet Learning Objectives in Language Arts Classrooms , Jessica L. Austin

The Use of Social Justice Socioscientific Issues in Secondary Biology Classes: An Action Research , Stephanie Marilyn Bailey

The Effect of Explicit Vocabulary Instruction on Elementary Students’ Vocabulary Knowledge and Reading Comprehension: An Action Research Study , Tonia Bauer

A Holistic Approach to Culturally Relevant Education In Biology to Examine Student Engagement , Robyn Brooke Biery

A Descriptive Mixed-Methods Study Examining Teachers’ Needs and Preferences for Technology Integration Professional Development , Amber Birden

The Effects of the Online Remediation of Phonological Processing Deficits on Functional Reading Abilities in Students With Dyslexia , Fletcher Bowden

“Why Do I Have to Learn This Anyway?”: A Qualitative Investigative Action Research Study Into the Tension Between the Rural, Working-Class Masculine Student and the Formal Educative Structure , Joshua Matthew Bowers

White Blindness: An Investigation Into Teacher Whiteness and Racial Ignorance , Mary Katharine Brasche

Using Multimedia Vocabulary Games to Improve Newcomer ESOL Students Motivation and Vocabulary Acquisition , Elizabeth E. Brittingham

Incremental, Spaced Repetition and StudyMate Flashcards: The Impact on College Student Memorization of Measurement Conversion Standards , Patricia A. Bromer

At-Risk Students’ Perception of the Effectiveness of Alternative Schools , Tara D. Cunningham Cantey

Qualitative Action Research Into the Planning Between the Classroom Teacher and Reading Interventionist , Russell Derrial Clark

An Evaluation of the Impact of Academic Policies and Athletic Procedures for Student Athletes , Seanta Cleveland

Supervisory Allyship for University Custodial Staff , Daniel Colascione

Where Are the Girls? Exploring Influences on Female Eighth Grade Public School Students’ Choices of Technology Classes in Texas: A Mixed Method Action Research Study , Shasta Colon

Exploring the Impact of Social Emotional Learning to Support Motivation and Self-Efficacy in Text-Dependent Analysis Writing , Elizabeth N. Crocker

Impacts in the Classroom When Students Take Ownership Of Cellphone Usage Policies: An Investigation Using a Project-Based Learning Design , Melynda Elaine Diehl

Connecting Writing to Life: The Effects of Place-Conscious Education on Writing in a First Grade Classroom , Tara P. Dietrich

Examining the Influence of Argument Driven Inquiry Instructional Approach on Female Students of Color in Sixth Grade Science: Its Impact on Classroom Experience, Interest, And Self-Efficacy in Science, Written Argumentation Skills, and Scientific Voice , Paul Duggan

Identifying and Understanding Factors Which Affect Persistence In Academically At-Risk Minority Prelicensure Nursing Students: An Action Research Study , Christina L.K. Eaton

Collaborative Problem-Solving and Its Impact on Inclusive Practices, Confidence, and Beliefs of General Education Teachers in Colombia , Shannon Renee Elmore

Fostering the Development of Instructor Cultural Competence: A Mixed Methods Action Research Study , Jennifer Lilly Engle

The Power of Story in Developing a Cycle of Efficacy for Teachers and Students , Melissa Renee Ewing

“Even the Little Things Matter:” a Phenomenological Study On Factors Impacting Student Motivation During and After COVID-Related Disruptions in Education , Jennifer Ferris-Crisafulli

Co-Teaching at the High School: One School's Approach to Create a Sustainable Co-Teaching Program Using Collaborative Learning and Learner Centered Theories , John Kegan Flynn

Supporting Black Children Within a Eurocratic Educational System: Making Culturally Relevant Pedagogy Foundational to the Role of the Literacy Coach , Jennipher C.K. Frazier

Page 1 of 8

Advanced Search

• Notify me via email or RSS
• Collections
• Disciplines

Submissions

• Give us Feedback
• University Libraries

Home | About | FAQ | My Account | Accessibility Statement

Privacy Copyright

• Future Students
• Current Students
• Faculty/Staff

News and Media

• News & Media Home
• Research Stories
• School's In
• In the Media

You are here

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.”

More Stories

⟵ Go to all Research Stories

Get the Educator

Subscribe to our monthly newsletter.

Stanford Graduate School of Education

482 Galvez Mall Stanford, CA 94305-3096 Tel: (650) 723-2109

• Contact Admissions
• GSE Leadership
• Site Feedback
• Web Accessibility
• Career Resources
• Faculty Open Positions
• Explore Courses
• Academic Calendar
• Office of the Registrar
• Cubberley Library
• StanfordWho
• StanfordYou

Improving lives through learning

• Stanford Home
• Maps & Directions
• Search Stanford
• Emergency Info
• Terms of Use
• Non-Discrimination
• Accessibility

© Stanford University , Stanford , California 94305 .

Trends and Topics in Educational Technology, 2024 Edition

• Column: Editorial
• Published: 21 March 2024

Cite this article

• Bohdana Allman 1 ,
• Royce Kimmons 1 ,
• Wei Wang 2 ,
• Hanhui Bao 2 ,
• Joshua M. Rosenberg 2 &
• Matthew J. Koehler 3  

345 Accesses

Explore all metrics

Avoid common mistakes on your manuscript.

Introduction

This editorial continues to landscape the trends and popular educational technology topics for 2023. We used the public internet data mining approach from previous years (Allman et al., 2023b ; Kimmons, 2020 ; Kimmons & Rosenberg, 2022 ; Kimmons et al., 2021 ). This year, we extracted and analyzed data from the Scopus research article database, K-12 school and district Facebook pages, and the open publishing platform EdTech Books. We also looked closer at two key terms—“artificial intelligence” and “OER”—using Google Custom Search API to examine patterns in the higher education context and the description of resources from the Teachers Pay Teachers (TPT) website for insights in the K-12 context. This year, we no longer utilized the X (formerly Twitter) #EdTech affinity group as a data source because of the changes to the platform/accessibility of the data. Our analysis represents snapshots of 2023 trends in educational technology from these dataset angles, furthering our understanding of current EdTech community’s attitudes, behaviors, and leanings and underpinning a predictive vision of future trends in the field.

What Were Trends in EdTech Journals in 2023?

For insight into which research topics were trending in the field in 2023, we analyzed article titles published in the top educational technology journals during the year. We utilized a similar methodology as in previous years (Kimmons et al., 2021 ; Kimmons & Rosenberg, 2022 ; Allman et al., 2023b ) and compiled a list of 3,355 articles published in 2023 from the top educational technology journals (n = 18) as identified by Google Scholar and retrieved via the Scopus API. See Table  1 for the list of journals included in the analysis. Following this, we looked at the frequencies of each keyword and n-gram (multi-word phrase) appearing in the titles to identify potential trends.

We then manually categorized top keywords and n-grams into three information types suggested by the data: “Contexts,” “Methods,” and a broader category of “Topics, Tools, and Modalities” (see Table  2 ). Contexts included terms related to the research settings, such as “high school” or “university.” Methods included descriptors of the research methods, such as “systematic review” or “case study.” Topics, Tools, and Modalities included a more comprehensive array of terms, such as “online,” “learning analytics,” and “virtual reality.” Notably, in previous years, we had separated modalities into their own section, but this separation seemed to become increasingly arbitrary and unnecessary (e.g., is VR a topic or a modality?). So, we combined modalities and topics into a common category. We included all relevant n-grams above 0.5% and their comparatively ranked keywords in the table.

Table 2 suggests several noteworthy findings. Regarding contexts, higher education was far more common as a setting for educational technology studies than K-12, and secondary schools were more represented than elementary schools. This suggests an inverted pyramid representation of EdTech research being done at different educational levels, a trend that we saw in previous analyses (Allman et al., 2023b ). Referenced physical locations also focused on school settings, suggesting an emphasis on formal (rather than informal or non-formal) learning. As expected, references to COVID-19 declined from the previous year (3.6% to 2.4%). Relatively high on the list were also references to language learning. Specifically, search terms “language” (n = 169, 5.0%) and “EFL” (n = 95; 2.8%) and related n-grams “language learning” (n = 54; 1.6%), “EFL learner” (n = 37; 1.1%), and “foreign language” (n = 28, 0.8%). Additionally, references to “support” (n = 124, 3.7%), “professional,” and “preservice” (both n = 64; 1.9%) and n-grams “preservice teacher” (n = 49, 1.9%) and “professional development” (n = 22, 0.7%) might be worth noticing as important context keywords for studies carried out in 2023.

The most commonly referenced n-grams related to research methods mentioned in 2023 titles were secondary data analysis methods, specifically “systematic OR scoping OR literature reviews” (n = 194, 5.8%) and “meta-analyses” (n = 49, 1.9%). The most common primary data analysis method n-grams included “machine learning” (n = 43, 1.3%), “case study” (n = 43, 1.3%), “network analysis” (n = 23, 0.7%), and “mixed methods” (n = 24, 0.7%). Additionally, several keywords related to measuring educational success in the titles of 2023 journal articles are noteworthy. Specifically, search terms “effect” (n = 202, 6.0%), “performance” (n = 193, 5.8%), “impact” (n = 148, 4.4%), “evaluation” (n = 82, 2.4%), “effectiveness” and “achievement” (both n = 77, 2.3%), and “outcome” (n = 68, 2.0%).

Regarding modality, the dominant term continues to be “online” (n = 469, 14%) and the n-gram “online teaching OR online learning” (n = 150, 4.5%), outnumbering the next-highest n-gram, “blended learning” (n = 31, 0.9%), at a rate of 5-to-1. Although, from closer investigation of the titles, it appears that “online,” “distance,” “blended,” “remote,” and a variety of other terms are sometimes used interchangeably to describe a broad spectrum of internet-mediated synchronous or asynchronous learning situations. Immersive environments, in the form of “virtual,” “augmented,” and “mixed reality,” in that order, were also of interest. Specifically, the search term “virtual” appeared 188 times (5.6%), and n-grams “virtual reality” were seen 110 times (3.3%), “augmented reality” 63 times (1.9%), and “immersive virtual” 22 times (0.7%). Notably, references to “artificial intelligence” more than doubled from the previous year (n = 91, increase from 1.4% to 2.7%), and “learning analytics” also saw increased attention (n = 72, 1.6% to 2.1%).

What Was Trending among School and School District Facebook Groups in 2023?

The comprehensive analysis of hyperlinks shared on school and district Facebook pages revealed significant trends in technology adoption and usage within K-12 educational settings. Table 3 showcases the top fifteen domains by their prevalence and highlights the evolving landscape of digital tools in education from 2021 to 2023.

To identify the technologies shared on school and district Facebook pages, we scrutinized the domain names of all hyperlinks posted across 16,309 publicly accessible pages, totaling 10,597,076 posts. Executing this analysis involved exploring the homepages of all schools and school districts in the U.S. for links to Facebook pages. Subsequently, we uploaded the identified links to Facebook pages onto the CrowdTangle platform to access publicly available posts for the years 2021–2023 and identified the domains of websites linked within schools' and districts' posts. Additional details on the data collection approach can be found in Rosenberg et al. ( 2022 ). The top fifteen most-shared domains, delineated by year (2021, 2022, and 2023), are presented in Table  3 . The following explanation may help the reader interpret the table. For instance, in 2023, 7049, or 43% of schools or districts with publicly accessible Facebook pages, shared one or more links to docs.google.com , and the domain was shared on average 5.3 times.

Upon reviewing the years 2021 to 2023, we observed the continued dominance of Google services, with Google Docs maintaining its position as the most shared domain for three consecutive years, as highlighted in prior research (Allman et al., 2023b ). YouTube follows closely behind, indicating the sustained prevalence of Google services in the mainstream usage of schools and school districts, underscoring the stability of these technologies within educational institutions. Simultaneously, we noted a significant decline in the percentage of YouTube links from 44% in 2021 and 41% in 2022 to 33% in 2023. This shift might reflect a broader trend towards prioritizing the digital privacy and security of students within the educational community, influencing how schools and districts curate and share content on social media platforms. The trend in Zoom links continues to decline, with the proportion of districts sharing Zoom links decreasing from 21% in 2021 to 11% in 2022 and further dropping to 7% in 2023. This decline aligns with the reduced engagement in remote activities across various schools and school districts. Additionally, tools facilitating event sign-ups, exemplified by SignUpGenius and gofan.co , experienced steady increases, indicating a surge in posts promoting event registrations post-COVID-19 pandemic. Other domains, such as bookfairs.scholastic.com , smore.com , eventbrite.com , and surveymonkey.com , have consistently maintained their presence in the top ten over the past three years. Their similar frequency suggests the sustained importance of tools for school-parent communication, book sales, event management, and survey services within K-12 schools and districts.

What Were Trends in EdTech Open Educational Resources (OER) in 2023?

In addition to Scopus and social media trends, we also examined an EdTech-focused Open Educational Resource (OER) platform EdTech Books ( https://edtechbooks.org ). OER are “teaching, learning, and research materials that reside in the public domain or have been released under an open license that permits their free use and re-purposing by others” (Creative Commons, 2020 ). OER can take various forms and sizes, including textbooks, lessons, courses, learning activities, assessments, technologies, syllabi, images, presentations, videos, and graphics. Being ‘open’ means that OER is freely accessible to anyone with internet access and can be retained, reused, redistributed, revised, and remixed as needed (Wiley, n.d. ), providing significant opportunities for improving “the quality and affordability of education for learners everywhere” (Wiley & Hilton, 2018 , p. 144). Research has repeatedly shown that OER quality is comparable to commercial resources (Clinton & Khan, 2019 ; Kimmons, 2015 ), and their adoption does not negatively impact student learning (Hilton, 2016 , 2019 ) while saving students money (Clinton, 2018 ; Hilton, 2016 ; Ikahihifo et al., 2017 ) and providing a variety of other benefits (Kimmons, 2016 ). In 2023, almost two-thirds (64%) of U.S. higher education faculty are aware of OER, and 29% of faculty require OER in their courses (Seaman & Seaman, 2023b ).

For this year’s OER analysis, we again selected EdTech Books as the authors are most familiar with this platform and have ready access to data. In 2023, ETB provided free OER to more than 1.5 million users worldwide. We believe that as an EdTech-focused platform, EdTech Books analytics may provide valuable insights into user behavior and how OER are developed, adopted, and used in our field.

A perusal of the most popular books (Table  4 ) and chapters (Table  5 ) revealed that readers seemed to be drawn to these resources when they were seeking information on broad theoretical aspects of educational technology (e.g., behaviorism, constructivism, socioculturalism), technology-specific guidance (e.g., how to use a specific tool), or research and evaluation guidelines (e.g., mixed methods or sampling procedures). This is consistent with our findings from last year (Allman et al., 2023b ).

A closer analysis of the most popular books and chapters suggested that the top trending chapters are most influenced by organic traffic via search engines rather than direct links (such as from a course). This underscores the importance of indexing and optimizing OER resources to increase exposure and impact. On the other hand, EdTech books that were most accessed may have been influenced by OER adoption behaviors and instructors’ pedagogical decisions as part of formal access to instructional resources. For example, students might have been instructed to read carefully, which could mean accessing longer chapters several times or downloading them as PDF for annotation or later retrieval. Another instructor may encourage the use of social annotation tools, such as Hypothesis, to complete collaborative classroom assignments, encouraging students to return to a chapter several times and thus increasing overall book views. Additionally, ease of access or anticipation of fees to access may also explain why some books have higher PDF downloads than expected. For example, West’s Foundations of Learning and Instructional Design Technology (highest PDF downloads) is often sought out with search terms like “instructional design pdf,” which suggests that learners are intentionally seeking local copies of these particular resources.

We found that the United States (29.7%), the Philippines (14.1%), and India (6.2%) were again the heaviest users of the platform, with overall use of the platform becoming less centralized to the U.S. We also found an increase in overall mobile device access to the platform, with 39.7% of users accessing on a phone as opposed to 59% on a desktop or laptop. This reveals an increasing trend of globalization of educational-technology-related OER and the need to be attentive to their accessibility with various device configurations and bandwidth limitations.

References to Artificial Intelligence and OER on University Websites and Teachers Pay Teachers

Further exploring how large public data sources might help us identify patterns in the field, we used the Google Custom Search API to scrape data from university websites (cf., such as Kimmons & Veletsianos, 2021 and Veletsianos et al., 2023 ) and descriptions of resources uploaded to the popular curricular sharing site Teachers Pay Teachers (TPT) to understand the frequencies and nature of references to two key terms of particular interest to the authors: “artificial intelligence” and “OER”.

In considering Google indexing results of university websites, it is necessary to limit analyses to a few sets of interesting a priori terms. So, for this analysis, we limited our considerations to AI, given its current interest in the larger social context, and OER, given its attention in educational technology and the topic’s relationship to university missions as public caretakers of knowledge. Results showed that 66.4% of universities mentioned “generative artificial intelligence,” “generative AI,” or “ChatGPT,” and 47.7% referenced “open educational resource” or “open textbook,” with references to generative AI outnumbering references to OER at a rate of nearly 5-to-1 (see Table  6 ). In both cases, politically blue states (Democratic according to the most recent U.S. presidential election) were more likely to reference these technologies than were politically red (Republican) states. However, urban states were more likely to reference “AI,” and rural states were more likely to reference “OER.” Rhode Island, Utah, and Idaho were among the most likely to mention both, and Wyoming was the least likely to mention either. Interestingly, Hawaii was the most likely to mention artificial intelligence but was among the least likely to mention OER. This pattern suggests sociopolitical and economic differences in how educators pay attention to these technologies. Also, it suggests that universities may be more actively playing into the hype of new technologies (e.g., “AI”) in their communication efforts than serving as public distributors of valuable knowledge to their communities (e.g., “OER”).

In a similar vein, data extracted from the TPT website spanning from 2021 to 2023, encompassing 3,936,779 entries, were explored. Specific details regarding the data collection method can be found in (Shelton et al., 2022 ). The analysis revealed a total of 3,303 instances referencing AI-related keywords, including "generative artificial intelligence," "generative AI," "artificial intelligence," "DALL-E," and "ChatGPT." In contrast, mentions of "open educational resource" or "open textbook" numbered 4,285 (see Table  7 for details).

The analysis of the data suggested a growing trend of references to AI-related educational resources on the TPT platform from 2021 to 2023. Notably, despite the proportion of AI-related resources being low before 2023, there has been a remarkable uptick in interest. The number of AI-related resources in 2021 and 2022 were less than 0.05%. Specifically, in 2021, only 521 out of 1,060,241 or 0.049% of total resources and 528 out of 1,268,771 (0.042%) resources in 2022 were related to AI. In 2023, the mentions of AI surged to 2,254 out of 1,607,767 or 0.14% resources, representing almost a threefold increase from the 2022 figures, indicating a burgeoning interest in AI within K-12 educational resources. This surge aligns with the rising interest and integration of AI in educational settings, particularly following the release of generative artificial intelligence tools like ChatGPT in November 2022, reflecting educators' growing curiosity and the pressing need to incorporate AI into their teaching resources.

Compared to the mentions of Open Educational Resources (OER), AI references are fewer in number. However, the ratio of nearly 1-to-1.3 (AI to OER) suggests that AI is also becoming a topic of significant interest within educational resources in the K-12 setting. This is particularly noteworthy given that OERs have been a mainstay in educational discussions for a longer period, emphasizing the rapid ascension of AI as a key area of focus. The increasing mention of specific AI tools like "DALL-E" and "ChatGPT" possibly indicates a shift in the educational resource landscape, where innovative AI tools are starting to play a central role in creating and disseminating educational content. This shift could be attributed to the capabilities of generative AI, offering novel approaches to personalized learning, automated content generation, and interactive learning experiences. The disparity between the growth of AI vs. OER references could also reflect the evolving nature of educational technology, where there is a move from traditional open resources to more dynamic, adaptive, and personalized learning experiences AI offers. Integrating AI in educational resources can represent a transformative step in educational technology, potentially reshaping how educational content is created, distributed, and consumed. However, as AI online educational resources rapidly expand, concerns like academic fraud, information bias, and ethical dilemmas arise and deserve closer attention. Recommendations from educational technology experts are especially relevant and needed since markets often lack the motivation to regulate content under platform capitalism (Rodríguez et al., 2020 ).

Discussion and Conclusion

The analyses of the data from Scopus, Facebook, and EdTech Books, as well as the examination of AI and OER-related terms using Google Custom Search API and Teachers Pay Teachers, represent snapshots from different angles and offer valuable insights into the current state of the educational technology field. Moreover, by comparing some of the 2023 results to previous years, we observed several developmental directions and trends that may guide educational researchers and practitioners for future work.

The Scopus data suggested that studies published in the top EdTech journals in 2023 were predominantly conducted in higher education contexts, and among K-12 studies, secondary contexts were more common than elementary. Not surprisingly, references to COVID-19 declined from previous years. Interestingly, although COVID-19 was less referenced, the terms “online teaching” and “online learning” were frequently mentioned, remaining a dominant learning modality. Secondary data analysis methods, such as literature reviews and meta-analyses, were the most common research methods. However, it is important to mention that this year’s analysis included only titles, not abstracts, as was done in previous years, which may typically include fewer references to primary research methods. Keywords related to emerging technologies, including virtual reality, augmented reality, artificial intelligence, and learning analytics, were also frequently mentioned in the titles.

Through analyzing the hyperlinks on school and school district Facebook pages, we observed that Google-provided services, such as Google Docs, YouTube, and Google search engine, were the most included external links, which seems to be consistent with our findings from previous years (Allman et al., 2023b ; Kimmons et al., 2021 ; Kimmons & Rosenberg, 2022 ). A trend worth mentioning is the consistent decline of Zoom links and increased links to school event planning and registration sites between 2021 and 2023. This suggests a return to in-person learning and an increased school social event activity post-COVID-19.

The analysis of EdTechBooks data as a proxy for OER behavior in the field of educational technology revealed that, similar to last year’s findings, readers continue seeking resources related to theory, educational technology topics, and research and evaluation methods. Closer analysis suggested that chapter access might be more influenced by the organic traffic from search engines. In contrast, book access may be more tied to OER adoption and formal educational setting behaviors, such as course instructional material choices and instructor pedagogical decisions. The increase in global and mobile OER access further emphasizes the importance of technical and design decisions related to accessibility, flexibility, and social justice issues during OER design and development (Allman et al., 2023a ).

Finally, the results of further examining AI and OER-related terms on university websites and Teachers Pay Teachers were intriguing. One interesting finding was that universities in politically blue states were more likely to refer to both technologies than universities in politically red states. Additionally, universities in urban states typically referenced AI more often, while rural state universities more likely referenced OER. This suggests that EdTech attention may be associated with social, political, and economic factors, such as available capital and resources. The analysis of resources on the Teachers Pay Teachers platform emphasized a rising interest in AI in K-12 educational resources while the interest in OER resources remained steady. Among the AI tools, references to generative AI tools such as ChatGPT increased the most, suggesting interest in applying these tools in education and educational content creation.

This year’s analyses indicated that the field of educational technology continues to be influenced by the past pandemic as well as emerging technologies. Even though COVID-19 has gradually faded out in people’s lives, online learning has become a widely accepted way of learning, and technology-mediated instruction has become a norm in all educational settings. Digital educational resources replaced, for the most part, traditional print materials both in higher education and K-12 settings (Seaman & Seaman, 2023a , 2023b ). Mobile and digital learning platforms make learning more accessible and facilitate collaboration through cloud-based services across modalities. OER remain an interest in K-12 and higher ed, particularly in rural states. Immersive technologies continue transforming the EdTech landscape, integrating VR, AR, and gamification elements into learning environments for more engaging experiences. We found that AI and generative AI, in particular, are topics that are notably raising interest in the educational technology field. Utilizing generative AI to produce content and instructional resources, provide adaptive and personalized learning experiences, and automate assessment and evaluation are only a few potential applications that could transform the field of educational technology in the near future. Although the inclusion of AI is relevant at the university and K-12 level, social, political, and economic influences and implications need to be considered. Recognizing that many across educational sectors feel unprepared for AI-related changes (Cengage, 2023 ), we should embrace these new technologies with optimistic caution, carefully considering potentials balanced against security, privacy, and other concerns.

Data Availability

Data is available upon request.

Allman, B., Bozkurt, A., Dickson-Deane, C., Kimmons, R., Stefaniak, J., & Warr, M. C. (2023a, October 15–19). EdTechnica: Open educational resource and open educational practice [Panel discussion]. AECT International Convention. Retrieved January 15, 2024, from https://www.youtube.com/watch?v=8GB0V1CGvZY

Allman, B., Kimmons, R., Rosenberg, J., & Dash, M. (2023b). Trends and topics in educational technology, 2023 edition. TechTrends, 67 , 583–591. https://doi.org/10.1007/s11528-023-00840-2

Article   Google Scholar  

Cengage. (2023). Examining higher ed’s digital future: Infographic of 2023–2024 digital learning pulse survey. Retrieved February 8, 2024, from https://www.bayviewanalytics.com/reports/pulse/infographic-fall2023.pdf

Clinton, V. (2018). Savings without sacrifices: A case study of open-source textbook adoption. Open Learning: The Journal of Distance and Open Learning, 33 (3), 177–189. https://doi.org/10.1080/02680513.2018.1486184

Clinton, V., & Khan, S. (2019). Efficacy of open textbook adoption on learning performance and course withdrawal rates: A meta-analysis. AERA Open, 5 (3), 1–20. https://doi.org/10.1177/2332858419872212

Creative Commons. (2020). Open education. Retrieved December 6, 2023, from https://creativecommons.org/about/program-areas/education-oer

Hilton, J. (2016). Open educational resources and college textbook choices: A review of research on efficacy and perceptions. Educational Technology Research and Development, 64 (4), 573–590. https://doi.org/10.1007/s11423-016-9434-9

Hilton, J. (2019). Open educational resources, student efficacy, and user perceptions: A synthesis of research published between 2015–2018. Educational Technology Research and Development, 68 (3), 853–876. https://doi.org/10.1007/s11423-019-09700-4

Ikahihifo, T. K., Spring, K. J., Rosecrans, J., & Watson, J. (2017). Assessing the savings from open educational resources on student academic goals. The International Review of Research in Open and Distance Learning, 18 (7). https://doi.org/10.19173/irrodl.v18i7.2754

Kimmons, R. (2020). Current trends (and missing links) in educational technology research and practice. TechTrends, 64 (6), 803–809. https://doi.org/10.1007/s11528-020-00549-6

Kimmons, R., & Rosenberg, J. M. (2022). Trends and topics in educational technology, 2022 edition. TechTrends, 66 (2), 134–140. https://doi.org/10.1007/s11528-022-00713-0

Kimmons, R., Rosenberg, J., & Allman, B. (2021). Trends in educational technology: What Facebook, twitter, and Scopus can tell us about current research and practice. TechTrends, 65 (2), 125–136. https://doi.org/10.1007/s11528-021-00589-6

Kimmons, R., & Veletsianos, G. (2021). Proctoring software in higher ed: Prevalence and patterns. Educause Review . Retrieved December 8, 2023, from https://er.educause.edu/articles/2021/2/proctoring-software-in-higher-ed-prevalence-and-patterns

Kimmons, R. (2015). OER quality and adaptation in K-12: Comparing teacher evaluations of copyright-restricted, open, and open/adapted textbooks. The International Review of Research in Open and Distributed Learning, 16 (5). https://doi.org/10.19173/irrodl.v16i5.2341

Kimmons, R. (2016). Expansive openness in teacher practice. Teachers College Record, 118 (9). https://doi.org/10.1177/016146811611800901

Rodríguez, N., Brown, M., & Vickery, A. (2020). Pinning for profit? Examining elementary preservice teachers’ critical analysis of online social studies resources about Black history. Contemporary Issues in Technology and Teacher Education, 20 (3), 497–528. Retrieved January 5, 2024, from https://www.learntechlib.org/primary/p/216743/

Rosenberg, J. M., Borchers, C., Stegenga, S. M., Burchfield, M. A., Anderson, D., & Fischer, C. (2022). How educational institutions reveal students’ personally identifiable information on Facebook. Learning, Media and Technology, 1–17. https://doi.org/10.1080/17439884.2022.2140672

Seaman, J.E., & Seaman J. (2023a). Curricula of many sources: Educational resources in U.S. K-12 education, 2023 . Bay View Analytics. Retrieved February 8, 2024, from https://www.bayviewanalytics.com/reports/curricula-of-many-sources-2023.pdf

Seaman, J.E., & Seaman, J. (2023b). Digitally established: Educational resources in U.S. higher education, 2023 . Bay View Analytics. Retrieved February 8, 2024, from https://www.bayviewanalytics.com/reports/digitallyestablished-2023.pdf

Shelton, C. C., Koehler, M. J., Greenhalgh, S. P., & Carpenter, J. P. (2022). Lifting the veil on TeachersPayTeachers.com: an investigation of educational marketplace offerings and downloads. Learning, Media and Technology , 22(2), 268–287. https://doi.org/10.1080/17439884.2021.1961148

Veletsianos, G., Kimmons, R., & Bondah, F. (2023). ChatGPT and higher education: Initial prevalence and areas of interest. Educause Review . Retrieved February 12, 2024, from https://er.educause.edu/articles/2023/3/chatgpt-and-higher-education-initial-prevalence-and-areas-of-interest

Wiley, D. (n.d.). Defining the “open” in open content and open educational resources. Retrieved February 10, 2024, from https://opencontent.org/definition/

Wiley, D., & Hilton, J. L., III. (2018). Defining OER-enabled pedagogy. The International Review of Research in Open and Distributed Learning, 19 (4). https://doi.org/10.19173/irrodl.v19i4.3601

Download references

Author information

Authors and affiliations.

Brigham Young University, Provo, UT, USA

Bohdana Allman & Royce Kimmons

University of Tennessee, Knoxville, TN, USA

Wei Wang, Hanhui Bao & Joshua M. Rosenberg

Michigan State University, East Lansing, MI, USA

Matthew J. Koehler

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Bohdana Allman .

Additional information

Publisher's note.

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

Rights and permissions

Reprints and permissions

About this article

Allman, B., Kimmons, R., Wang, W. et al. Trends and Topics in Educational Technology, 2024 Edition. TechTrends (2024). https://doi.org/10.1007/s11528-024-00950-5

Download citation

Published : 21 March 2024

DOI : https://doi.org/10.1007/s11528-024-00950-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Find a journal
• Publish with us
• Track your research