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What is Computer Literacy? Benefits, History, Skills & Assessing Your Level

Introduction

Computer literacy is the ability to understand and use computers and other technology. In today’s world, having a basic understanding of computers is essential for almost all aspects of life, from finding a job to engaging with online communities. In this article, we will explore what computer literacy is, the benefits of being computer literate, the history of computer literacy, tips and strategies for developing computer literacy skills, and how to assess your computer literacy level.

The Benefits of Being Computer Literate

Having a basic understanding of computers can open up many doors in terms of job opportunities and other life skills. Here are some of the main benefits of being computer literate:

Increased Job Opportunities

In today’s job market, having a basic understanding of computers is essential. Most employers expect their employees to be able to use computers and other technology, so having a good grasp of computer literacy can give you an edge when applying for jobs. Even if the job you’re applying for doesn’t require you to use a computer, having computer literacy skills can still be beneficial as it shows potential employers that you have the ability to learn new skills quickly.

Improved Communication

Being computer literate also makes it easier to communicate with others. Whether you’re using email, video conferencing, or social media, having a good understanding of computers can help you stay connected with friends, family, and colleagues. Additionally, having a basic understanding of computers can make it easier to search for information online and keep up with the latest news and trends.

Enhanced Problem-Solving Skills

Having a basic understanding of computers can also help you develop problem-solving skills. By learning how to troubleshoot computer issues and research solutions online, you can become more adept at solving problems both on and off the computer.

History of Computer Literacy: How We Got Here

Computer literacy has come a long way since its beginnings in the early days of computing. Let’s take a look at how we got here.

Early Days of Computing

The first computers were large and complex machines that required highly skilled operators. These machines were mainly used for scientific and military purposes, and only a small number of people had access to them. As such, there was no need for widespread computer literacy.

Emergence of Personal Computers

The emergence of personal computers in the 1980s changed the landscape of computing. These machines made computers more accessible to the general public, and people began to realize the potential of computers for everyday tasks. This led to the development of computer education courses and the rise of computer literacy.

Growth of the Internet

The growth of the internet in the 1990s further increased the need for computer literacy. With the internet came a whole new range of possibilities, from shopping online to researching topics and communicating with people around the world. This led to the creation of more computer literacy courses and resources.

Developing Computer Literacy Skills: Tips and Strategies

If you want to become computer literate, there are several things you can do to improve your skills. Here are some tips and strategies for developing your computer literacy skills:

Learn the Basics

The first step to becoming computer literate is to learn the basics. You should familiarize yourself with the different components of a computer (such as the monitor, keyboard, and mouse) and understand how they work together. Additionally, you should learn how to use the operating system and common software programs such as word processors, spreadsheets, and web browsers.

Practice, Practice, Practice

Once you’ve learned the basics, it’s time to start practicing. The best way to learn is by doing, so try out different tasks on the computer and see how they work. This will help you get a better understanding of the different functions and features of a computer.

Utilize Online Resources

There are also plenty of online resources available to help you learn computer literacy. From online tutorials to forums and discussion groups, you can find a wealth of information online to help you become more comfortable with computers.

Exploring the Different Types of Computer Literacy

When it comes to computer literacy, there are three main types: basic computer literacy, digital literacy, and information literacy. Let’s take a look at each one in more detail.

Basic Computer Literacy

Basic computer literacy refers to the ability to understand and use technology. This includes being able to use a computer’s operating system, performing basic tasks such as sending emails or using a word processor, and troubleshooting basic computer issues.

Digital Literacy

Digital literacy is the ability to use technology to create and share content. This includes creating websites, writing blog posts, and using social media. It also involves understanding how to protect yourself online, such as avoiding scams and phishing attempts.

Information Literacy

Information literacy is the ability to find and evaluate information from a variety of sources. This includes knowing how to search for information online and being able to critically evaluate the reliability of a source.

Assessing Your Computer Literacy Level

Once you’ve developed your computer literacy skills, you may want to assess your level. Here are some tools you can use to do so:

Self-Assessment Tools

Many websites offer self-assessment tools that allow you to gauge your computer literacy level. These tools ask you questions about your knowledge and experience with computers, and then provide you with an overall score.

Online Tests and Quizzes

You can also take online tests and quizzes to assess your computer literacy level. These tests usually cover a wide range of topics, from understanding computer hardware to using common software programs.

Teaching Computer Literacy in the Classroom

Computer literacy is an important skill for students to have, and schools are beginning to recognize this. Here are some ways schools are incorporating computer literacy into their curriculums:

Implementing Technology Into the Curriculum

Many schools are incorporating technology into their curriculums, such as teaching students how to use computers and software programs. This helps prepare students for the future and gives them a better understanding of how to use technology in their everyday lives.

Offering Computer Literacy Courses

Some schools are now offering dedicated computer literacy courses, which teach students the basics of computers and how to use them. These courses can be beneficial for those who don’t have much experience with computers.

Utilizing Technology to Enhance Learning

Technology can also be used to enhance learning in the classroom. For example, teachers can use interactive whiteboards and tablets to engage students and make lessons more interesting. Additionally, students can use computers to research topics, write papers, and collaborate with classmates.

Computer literacy is an important skill to have in today’s world. Having a basic understanding of computers can open up many doors, from increased job opportunities to improved communication and enhanced problem-solving skills. To become computer literate, you should learn the basics, practice, and utilize online resources. Additionally, you can assess your computer literacy level with self-assessment tools and online tests and quizzes. Finally, schools are beginning to recognize the importance of computer literacy and are implementing technology into their curriculums and offering dedicated computer literacy courses.

Students and Their Computer Literacy: Evidence and Curriculum Implications

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For a number of years, education authorities have responded to the importance of school students developing computer literacy by including it as part of the school curriculum, directly as a cross-curriculum capability, and by assessing the extent to which students are computer literate. Computer literacy and related concepts, such as ICT literacy, are defined so as to include both technological expertise and information literacy. Assessments of computer literacy, even though they vary, indicate that there are substantial variations in levels of computer literacy among students in the lower years of secondary school. In technologically developed countries, approximately one half of Year 8 students demonstrate proficiency, or advanced proficiency, in computer literacy, but up to 10% have very limited computer literacy. Assessments of computer literacy can also provide the basis for progression maps that could be used to inform curriculum development. Those progression maps will be more valuable if the frameworks on which they are based become more strongly integrated with each other. In addition, computer literacy appears to be influenced by student background, including familiarity with computers, as well as the emphases placed on it in classrooms and schools and the support provided by ICT in education systems. At present, there is less information about school and classroom influences on computer literacy than there is about student background influences. In the immediate future, the construct of computer literacy may need to accommodate increasingly to changes in software and hardware contexts in which it is manifested.

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Aesaert, K., van Nijlen, D., Vanderlinde, R., & van Braak, J. (2014). Direct measures of digital information processing and communication skills in primary education: Using item response theory for the development and validation of an ICT competence scale. Computers & Education, 76 , 168–181. https://doi.org/10.1016/j.compedu.2014.03.013 .

Article Google Scholar

Aesaert, K., van Braak, J., van Nijlen, D., & Vanderlinde, R. (2015). Primary school pupils ICT competences: Extensive model and scale development. Computers & Education, 81 , 326–344. https://doi.org/10.1016/j.compedu.2014.10.021 .

Ainley, J., Schulz, W., Fraillon, J., & Gebhardt, E. (2016). Conceptualizing and measuring computer and information literacy in cross-national contexts. Applied Measurement in Education, 29 (4), 291–309. https://doi.org/10.1080/08957347.2016.1209205 .

Australian Council for Educational Research (ACER). (2016). A global measure of digital and ICT literacy skills. Background paper prepared for the 2016 Global Education Monitoring Report: Education for people and planet: Creating sustainable futures for all . Paris: UNESCO. ED/GEMR/MERT/2016/P1/4. http://unesdoc.unesco.org/images/0024/002455/245577e.pdf .

Australian Curriculum and Reporting Authority (ACARA). (2012). National Assessment Program – ICT literacy years 6 & 10 2011 report . Sydney: Australian Curriculum and Reporting Authority (ACARA). Available: http://www.nap.edu.au/_resources/NAP_ICTL_2011_Public_Report_Final.pdf .

Google Scholar

Australian Curriculum and Reporting Authority (ACARA). (2015). National Assessment Program – ICT literacy years 6 & 10 2014 report . Sydney: Australian Curriculum and Reporting Authority (ACARA). Available: http://www.nap.edu.au/_resources/D15_8761__NAP-ICT_2014_Public_Report_Final.pdf .

Australian Curriculum and Reporting Authority (ACARA). (2017). Information and communication technology (ICT) capability . Sydney: Australian Curriculum and Reporting Authority (ACARA). Available: http://v7-5.australiancurriculum.edu.au/GeneralCapabilities/Pdf/ICT .

Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: A digital age skill for everyone. Learning and Leading with Technology, 38 (6), 20–23.

Bennett, S., Maton, K., & Kervin, L. (2008). The “digital natives” debate: A critical review of the evidence. British Journal of Educational Technology, 39 (5), 775–786.

Binkley, M., Erstad, E., Herman, J., Raizen, S., Ripley, M., Miller-Ricci, M., et al. (2012). Defining 21st century skills. In P. Griffin, B. McGaw, & E. Care (Eds.), Assessment and teaching of 21st century skills . Dordrecht: Springer.

Catts, R., & Lau, J. (2008). Towards information literacy indicators . Paris: UNESCO.

Claro, M., Preiss, D., San Martin, E., Jara, I., Hinostraoza, J. E., Valenzuela, S., Cortes, F., & Nussbaum, M. (2012). Assessment of 21st century ICT skills in Chile: Test design and results from high school level students. Computers and Education, 59 , 1042–1053. https://doi.org/10.1016/j.compedu.2012.04.004 .

De Bortoli, L., Buckley, S., Underwood, C., O’Grady, E., & Gebhardt, E. (2014). ICILS 2013: Australian students’ readiness for study, work and life in the digital age . Melbourne: ACER. http://research.acer.edu.au/ict_literacy/6 .

Dexter, S. (2008). Leadership for IT in schools. In J. Voogt & G. Knezek (Eds.), International handbook of information technology in primary and secondary education (Vol. 2, pp. 543–554). New York: Springer.

Chapter Google Scholar

Educational Testing Service (ETS), International ICT Literacy Panel. (2002). Digital transformation – A framework for ICT literacy . Princeton: Educational Testing Service.

E-learning Nordic. (2006). E-learning Nordic 2006: The impact of ICT on education . Denmark: Ramboll Management.

European Commission. (2008). Digital Literacy European Commission working paper and recommendations from Digital Literacy High-Level Expert Group . Retrieved 21 Oct 2010 from http://www.ifap.ru/library/book386.pdf .

European Commission. (2010). Digital competence: Identification and European-wide validation of its key components for all levels of learners (DIGCOMP) . Retrieved 26 Nov 2012, from http://is.jrc.ec.europa.eu/pages/EAP/DIGCOMP.html .

European Commission, Joint Research Centre-IPTS on behalf of DG Education and culture. (2013). DIGCOMP: A framework for developing and understanding digital competence in Europe . Retrieved from http://ftp.jrc.es/EURdoc/JRC83167.pdf .

Ferrari, A. (2012). Digital competence in practice: An analysis of frameworks . Institute for Prospective Technological Studies. Retrieved 5 Feb 2013 from http://ipts.jrc.ec.europa.eu/publications/pub.cfm?id=5099 .

Fraillon, J., Schulz, W., & Ainley, J. (2013). International computer and information literacy study assessment framework . Amsterdam: International Association for the Evaluation of Educational Achievement (IEA). Retrieved from http://www.iea.nl/fileadmin/user_upload/Publications/Electronic_versions/ICILS_2013_Framework.pdf .

Fraillon, J., Ainley, J., Schulz, W., Friedman, T., & Gebhardt, E. (2014). Preparing for life in a digital age. The IEA international computer and literacy information study international report . Heidelberg: Springer Cham.

Griffin, P., McGaw, B., & Care, E. (2012). Assessment and teaching of 21st century skills . Dordrecht: Springer.

Book Google Scholar

Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42 (1), 38–43. https://doi.org/10.3102/0013189X12463051 .

Hatlevik, O. E., Ottestad, G., & Throndsen, I. (2015). Predictors of digital competence in 7th grade: A multilevel analysis. Journal of Computer Assisted Learning, 31 , 220–231.

Helsper, E., & Eynon, R. (2010). Digital natives: Where is the evidence? British Educational Research Journal, 36 (3), 503–520. https://doi.org/10.1080/01411920902989227 .

Hinostroza, J. E., Hepp, P., & Cox, C. (2008). Policies and practices on ICT in education in Chile: Enlaces. In T. Plomp, R. E. Anderson, N. Law, & A. Quale (Eds.), Cross-national policies and practices on information and communication technology in education (Revised ed.). Greenwich: Information Age Publishing.

Institute of Education Sciences, National Center for Education Statistics. (2012). National Assessment of Educational Progress (NAEP) technology and engineering literacy (TEL) assessment . Retrieved on 8 Feb 2013 from http://nces.ed.gov/nationsreportcard/tel/ .

Katz, I. R. (2007). Testing information literacy in digital environments: ETS’s iSkills assessment. Information Technology and Libraries, 26 (3), 3–12.

Kim, J., & Lee, W. (2013). Meanings of criteria and norms: Analyses and comparisons of ICT literacy competencies of middle school students. Computers & Education, 64 , 81–94. https://doi.org/10.1016/j.compedu.2012.12.018 .

Kim, H. S., Kil, H. J., & Shin, A. (2014). An analysis of variables affecting the ICT literacy level of Korean elementary school students. Computers & Education, 77 , 29–38. https://doi.org/10.1016/j.compedu.2014.04.009 .

Koutropoulos, A. (2011). Digital natives: Ten years after. MERLOT Journal of Online Learning and Teaching, 7 (4). Retrieved from http://jolt.merlot.org/vol7no4/koutropoulos_1211.htm .

Kozma, R. (Ed.). (2003). Technology, innovation, and educational change: A global perspective . Eugene: ISTE.

Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41 , 51–61. https://doi.org/10.1016/j.chb.2014.09.012 .

Madaus, G., & O’Dwyer, L. M. (1999). A short history of performance assessment: Lessons learned. The Phi Delta Kappan, 89 (9), 688–695.

Markauskaite, L. (2006). Towards an integrated analytical framework of information and communications technology literacy: From intended to implemented and achieved dimensions. Information Research, 11 (3) paper 252. Available at http://InformationR.net/ir/11-3/paper252.html .

McDougall, A., Murnane, J. S., & Wills, S. (2014). The educational programming language logo: Its nature and its use in Australia. In A. Tatnall & B. Davey (Eds.), Reflections on the history of computers in education (IFIP advances in information and communication technology, Vol. 424). Berlin: Springer.

Ministerial Council on Education, Employment, Training and Youth Affairs (MCEETYA). (2005). National Assessment Program Information and Communication Technology literacy years 6 and 10 an assessment domain for ICT literacy . Carlton: Curriculum Corporation.

Ministerial Council on Education, Employment, Training and Youth Affairs (MCEETYA). (2007). National Assessment Program – ICT literacy years 6 & 10 2005 report . Carlton: Curriculum Corporation.

Ministerial Council on Education, Employment, Training and Youth Affairs (MCEETYA). (2008). Melbourne declaration on educational goals for young Australians . Carlton: Curriculum Corporation.

Moos, D., & Azevedo, R. (2009). Learning with computer-based learning environments: A literature review of computer self-efficacy. Review of Educational Research, 79 (2), 576–600.

National Center for Educational Statistics (NCES). (2016a). 2014 Abridged technology and engineering literacy framework for the 2014 National Assessment of educational progress . Washington, DC: National Assessment Governing Board.

National Center for Educational Statistics (NCES). (2016b). 2014 Nations Report Card: Technology & Engineering Literacy (TEL). https://www.nationsreportcard.gov/tel_2014/ .

Organisation for Economic Cooperation and Development (OECD). (2011). PISA 2009 results: Students on-line digital technologies and performance . Paris: OECD.

Peyton Jones, S. (2011). Computing at school: International comparisons . London: Microsoft Research.

Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9 (5), 1–6.

Qualifications and Curriculum Authority. (2007). About information and communication technology: Assessment guidance. Retrieved 7 Apr 2007 from http://www.qca.org.uk/7889.html .

Rohatgi, A., Scherer, R., & Hatlevik, O. (2016). The role of ICT self-efficacy for students’ ICT use and their achievement in a computer and information literacy test. Computers & Education, 102 , 103–116.

Sánchez, J., & Salinas, A. (2008). ICT & learning in Chilean schools: Lessons learned. Computers & Education, 51 (4), 1621–1633.

Selwyn, N. (2009). The digital native – myth and reality. Aslib Proceedings: New Information Perspectives, 61 (4), 364–379.

Senkbeil, M., Ihme, J. M., & Wittwer, J. (2013). The Test of Technological and Information Literacy (TILT) in the National Educational Panel Study: Development, empirical testing, and evidence for validity. Journal for Educational Research Online, 5 (2), 139–161.

Siddiq, F., Hatlevik, O. E., Olsen, R. V., Throndsen, I., & Scherer, R. (2016). Taking a future perspective by learning from the past - A systematic review of assessment instruments that aim to measure primary and secondary school students’ ICT literacy. Educational Research Review, 19 , 58–84.

Sturman, L., & Sizmur, J. (2011). International comparison of computing in schools . Slough: NFER.

United States Department of Education Office of Educational Technology. (2010). Transforming American education powered by technology: National Education Technology Plan 2010 . Washington, DC: United States Department of Education Office of Educational Technology.

Van Deursen, A. J., & Van Dijk, J. A. (2016). Modelling traditional literacy, internet skills and internet usage: An empirical study. Interacting with Computers, 28 (1), 13–26. https://doi.org/10.1093/iwc/wu027 .

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Ainley, J. (2018). Students and Their Computer Literacy: Evidence and Curriculum Implications. In: Voogt, J., Knezek, G., Christensen, R., Lai, KW. (eds) Second Handbook of Information Technology in Primary and Secondary Education . Springer International Handbooks of Education. Springer, Cham. https://doi.org/10.1007/978-3-319-71054-9_4

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Chapter 6: 21st-century media and issues

6.14.2 Literacy in computer science (research essay)

John Parker

English 102, April 2021

Introduction.

Computer Science is one of the fastest growing fields as the world transitions to increased automation. Schools of all levels are putting a greater emphasis on educating the younger generation on programming. This suggests that schools are growing their STEM departments, which house the fields of science, technology, engineering, and mathematics. In order to understand why many educators are approaching the field of Computer Science in this way, it must be understood what Computer Science is. It is most commonly defined as the study of computer software and computing systems. More specifically, it deals with creating, reading, and error-checking programming or code. While it is true that STEM is very important within the field of programming, there are other important aspects of coding that are not frequently considered by many educators. Coding includes being able to read, write, and communicate in a unique way, which implies that literacy involved in the field. Any form of literacy that is not directly learning how to read, write, or communicate in standard English is often not considered to be literacy, which is a major reason that its importance within programming is not recognized. The fact that many educators within the field of Computer Science do not realize the importance of literacy alludes to the idea that the teaching of programming may be flawed in its methods and implementation.

Computer Science is very important in my life, as I am currently pursuing a degree in the field. I have been programming for just over a year now and have experience in Python and Java programming languages. I have taken three courses on programming/computer science in college, in which I have learned so much about programming and Computer Science in general. In addition to coursework, I frequently work on coding projects for my own entertainment and read/watch articles and videos on programming. Any knowledge that I gain on the most effective ways to learn programming is very important to my future. Even more important than gaining this knowledge for myself, being able to spread this knowledge to grow the field is paramount. Although I am not an expert in programming, I have had many learning experiences with programming that qualify me to discuss my personal experiences with learning how to program. Since the focus of this essay deals with the teaching methods and learning experiences of programming, the relative freshness of my learning experiences with programming provides me with an advantage over industry professionals in this discussion.

Writing in Computer Science

Although it may be somewhat difficult to discover the parallels between computer programming and literacy, the literacy aspect of writing can be understood very easily. When thinking of what a programmer does, one of the simplest and high-level descriptions could be “someone who writes code.” The main similarity between the two practices is the exist in the process of creating a finalized piece of work, whether it be a novel for an application. In Felienne Hermans and Marlies Aldewereld’s article, “Programming is Writing is Programming,” the authors describe the beginning of the writing process and programming workflow to include a high-level plan (1). The next step in both processes is to convert these high-level designs into low-level, workable steps. For writers, these low-level steps include sentences and words; for programmers, they include methods, functions, and lines of code. For both practices, intermediate steps are needed manage the organization of the work, such as chapters in writing and classes and objects in programming (Hermans and Marlies 2). In the programming course that I am currently enrolled in, every coding assignment that is submitted must be accompanied by pseudocode, which is essentially a plan for how the final code will look. This pseudocode, which is written in a mix of English and Java syntax, begins with high-level plans that are broken down into smaller, more manageable steps. The process of writing pseudocode was not all that difficult to me when I realized that it was just like the outlines that I have been writing for English courses for years. These outlines broke up the goal of the essay into manageable portions and consisted of some wording that would be directly added to the essay and some rough ideas that would need to be converted into cohesive writing.

In Ziva R. Hassenfeld’s et al article, “If you can Program you can Write,” explores the constructs shared by computer programming and writing in great detail. The authors discuss the similar constructs between the two practices as, “planning and prewriting, creating and drafting, testing and evaluating, and debugging and editing and revising” (Hassenfeld et al. 68). The study described in this article, which focuses on the correlation between elementary student’s ability to write and ability to learn programming, showed that these similarities between the two practices produce a correlation between students’ ability to write and their ability to program (Hassenfeld et al. 75). In the section titled “Programming as Literacy” of Annette Vee’s novel, “Coding Literacy: How Computer Programming is Changing Writing,” she discusses an extremely interesting way to observe the similarities between writing and programming. Vee dives into exploring the ways in which programming is treated like writing within United States law. The United States Congress amended the 1976 Copywrite Act in 1980 to categorize computer code as a “literary work” and a “form of writing” (Vee 450). Since a law protecting writing and forms of creative expression, it can be alluded that the United States law views computer programming as a form of writing.

Reading in Computer Science

Reading is also extremely prevalent within the world of programming and Computer Science in general. Peg Grafwallner’s article, “Encoding Literacy in Computer Science,” examines an instructional coach and computer science teacher’s attempt to implement literacy lessons into a computer science class. The article states that reading within Computer Science requires students to focus on one specific area at a time, thinking in a linear and conceptual manner (Grafwallner). The computer science class discussed in this article was taught with an emphasis on literacy through directions, ultimately proving to boost the success of the students’ ability to program. The ability to read instructions was determined to be the most vital skill in programming (Grafwallner).

In Marthie Schoeman’s article, “Reading Skills Can Predict the Programming Performance of Novices,” the relationship between reading and ability to code is discussed extensively. In the study described in the article, the reading level of students were determined using eye-tracking technology. The students then took an introductory course in computer programming that would be followed by a final examination (Schoeman 44). The results of the study show that students with low reading skills failed the programming component, while those with higher reading skills did better overall. These results depict the fact that reading skills do play a role in one’s ability to learn programming (Schoeman 48). This relation can be attributed to the fact that programming is a form high-level written language in its own sense. In my own experiences, reading programming has proved to be one of the most vital skills that a computer programmer can possess. One of the main points of emphasis within Computer Science classes is being able to read and debug others’ code. Since there are so many different ways that a program can be created, I initially struggled with reading others’ code. The skill of reading code is very similar to reading literary works, as some authors are naturally easier to follow along with than others. Reading code is a vital aspect of computer programming and is a skill that I am still working on improving.

Communication in Computer Science

Although communication is not necessarily involved in the creation of all computer programs, communication in vital within the professional setting of Computer Science, in addition to engaging in programming within a team environment. In Gilles Dubochet’s article, “Computer Code as a Medium for Human Communication,” it is stated that communication between a human and a computer is the main objective of computer programming. The article goes on to state that computer programming itself has become a channel for human communication (Dubochet 1). The article explores the increase in team usage in the field of computer science, suggesting that the ability to understand the code that other’s write is extremely important (2). Understanding the code that others write is not only dependent on one’s ability to read and understand coding syntax and standards, but also the ability of the person reading the code and the person who wrote the code to communicate effectively with one another. The article suggests that communication is not only prevalent through oral dialect, but that programming languages are becoming a channel for communication between programmers (Dubochet 13). In other words, programmers are able to convey their thoughts through a programming language.

At the start of my college career, I did not expect for communication to be as prevalent as it was within my Computer Science courses. Throughout the entire Fall Semester of my introduction to programming course, a team of students that we were assigned to were required to code a robot. Due to the business of the group members’ schedules, we often had to do portions of the project on our own. This meant that I would often log in to add a portion to the code and would be confused by the code that was just written above. Through a simple phone call or text, all of the team members were able to understand the others’ work. The communication between our team was extremely important for this reason, as the project would have fallen apart without it. Throughout the semester, our team began to “comment” our code, which is simply inserting explanation within the code that do not affect how the code runs. If “//” is used before a line, the programming software environment understands that this is just for programmers to read. This simple addition to our code meant that we were actually able to communicate directly through the code, without having to text, call, or talk at all.

Marc Riemer breaks down the importance of communication and language skills in a broader field of engineering in the article titled, “Communication Skills for the 21st Century Engineer.” Riemer discusses the importance of communication skills in engineering, primarily focusing on the English language. He states that English is the most widespread language in the world and that effective communication in English is a skill that develops more successful engineers (91). Riemer examines the importance of communication between engineers and stakeholders (95). After engineers’ years of education in upper-level concepts, it can be difficult to decipher what stakeholders are familiar and not familiar with. Being able to effectively break down the concepts into more common terminology plays a major role in one’s success within the field of Computer Science as well as all other engineering disciplines. The findings of this article suggest that an increase in communication and language courses in college curriculums will produce more successful engineers (Riemer 98). Although this article focuses more broadly on engineering, Computer Science is a major branch of engineering that shares in the same challenges of communication as all other major fields of engineering.

Computer Programming as a Language in Itself

Computer Programming is much more than a computational practice, as learning programming languages comes with many of the same challenges as learning human languages, uncovering the fact that computer programming is its own unique form of literacy or language. When I was applying for colleges and deciding on a major, I honestly did not know what I wanted to do. I knew that I loved math and problem solving and would want to pursue a career in math-based field. The reason that I chose to pursue a career in Computer Science was purely for this reason, as I have never taken a coding course or had any prior experience. Once I began coding in my collegiate level courses, I fell in love with the problem-solving aspect. I was grasping the various coding techniques and problem-solving methods, but found that the portion I was struggling with the most was syntax and coding conventions. I thought that learning to program would be like learning Calculus, but, in reality, it was actually like learning a new language.

The world of programming is extremely complex, with syntax and grammar of its own, comparable to the grammar and structure used in human languages. The article, “Classifying Programming languages,” is an excellent source for understanding how programming languages are classified and the many similarities and differences between. The authors state that there are eight major categories of programming languages, categorized by “linguistic structure, expressive features, possibility of efficient implementation, direct support for certain programming models, and similar concerns” (“Classifying Programming Languages”). This practice of categorizing languages based on various features is used extensively in human languages also. For example, the Romance Languages are all rooted in Latin and have similar sounds, sentence structure, etc. The article goes on to explain there are many styles of programming that can be used within one language (“Classifying Programming Languages”). This is also a construct that is common throughout human languages, as there are many styles of writing within the English language. Programming languages also have their own grammar and syntax. The grammar portion of coding could be described through common code standards, such as camel case being used for variable names or uppercase being used for constant names. The syntax portion of coding is slightly different than in English, as errors in syntax within programming will cause the program to crash, losing functionality.

In Ana Harris’ article, “Human Languages vs. Programming Languages,” she breaks down the criteria for something to be considered a language. Harris states that the main function of language is communication. She goes on to explain that the function of programming languages is to communicate a series of an instructions to a computer or machine, alluding to the idea that programming languages are indeed unique forms of literacy/language. Harris zooms in on another major similarity between human languages and programming languages, being structure. She discusses the concepts of semantics (meaning connected to a certain concept) and syntax (rules for aligning words and phrases) from the perspective of a linguist. She states that programming uses semantics, as every program has a specific intention, and syntax, which includes following rules for the use of variables, functions, parenthesis, colons, etc. (Harris). These many similarities allow for programming to be considered its own unique form of literacy or language.

Connection between Literacy Skills and Programming Ability

Due to the many parallels between computer programming and literacy, it can be gathered that programming ability and literacy skills benefit one another. Although I enjoy and excel in mathematics and problem solving more-so, I have always loved reading and writing. Throughout my journey of learning programming, this love and ability has helped to excel in the field. Although many of my peers are more advanced than myself in mathematics, this ability has proved to give me a slight upper hand in some aspects of coding. Many of my peers who lack in this ability often have trouble with their code simply because they missed a portion of the instruction when reading, misunderstood what was being asked of them, or they had trouble recalling the semantics and syntax required for the program.

In Sharin Jacob and Mark Warschauer’s article, “Computational Thinking and Literacy,” the authors discuss how literary skills can lead to stronger computational skills. The authors describe in detail how computational thinking (computer programming) is a form of literacy, which was discussed earlier extensively (Jacob and Warschauer 3). The authors then switch gears to focus on how literacy skills can improve programming ability. The article describes the importance of verbal analysis of game architecture to their implementation of game design. The example that the authors use to back up this statement is as follows: The statement “the hunter killed the monkey” is implemented into the coding as “the monkey disappears when it touches the hunter” (Jacob and Warschauer 8). This example shows the importance of one literary element, transitive verb structures, to the success of a game developer. Jacob and Warschauer state, “students cannot master programming syntax without understanding the semantic meaning of commands if they cannot produce correct linguistic forms without considering their corresponding meanings” (10). The authors are saying that students are required to use the same skills within literacy courses that they are required to use within programming, just manifest in different ways. Therefore, skills that are taught in literacy primarily can assist in improving programming ability.

Marthie Schoeman’s article discussed above, “Reading Skills Can Predict the Programming Performance of Novices,” further displays how literacy skill can affect programming performance. This article discusses a study of the relationship between reading skills and the ability to code. The method of the study involved performing an initial eye tracking test on participants as they were reading to determine their reading proficiency. The participants were then given a short introductory course in programming, which would be followed by a knowledge exam (Schoeman 42). The results of the study displayed that those students with low reading skills failed the programming component, while students with higher reading skills did better overall (Shoeman 48). These results suggest that the literary skill of reading does indeed play a role in one’s ability to learn programming.

All of the findings discussed throughout the entirety of this essay display the fact that teaching programming to young people more similarly to the ways in which that literacy is taught may be more effective than just the typical STEM approach. Marina Bers’ article, “Coding as Another Language,” discusses a new method of teaching computer science to young children starting in kindergarten called “Coding as Another Language” (499). The method of teaching coding described in this article deviates from the typical STEM approach, offering the proposition that computer science teaching can be enhanced by incorporating the design of literacy instruction, due to the parallels that exists between natural languages and programming languages (Bers 504). According to Bers, research shows that teaching children how to read and write artificial languages in the same way as natural languages leads to a greater cognitive understanding of programming (503).

In Ziva R. Hassenfeld’s et al. article, “If you can Program you can Write,” the authors examine a study of elementary students learning through the “Coding as Another Language” curriculum. The article discusses results from a test on literacy and an assessment of students’ understanding of an introductory program language, drawing conclusions based upon their correlation (Hassenfeld et al. 73). The results of this study show that there is a connection between students’ literacy levels and their height of achievement in grasping an introductory programming language (Hassenfeld et al. 75). This indicates that there are fundamental understandings and constructs that are shared by literacy and computer programming, which are described in detail earlier. All of these articles suggest that the instruction of programming in early years is more effective when taught more similarly to literacy instruction than just being taught in the typical STEM approach.

The future of Computer Science is limitless, due to the increase in automation throughout societies. As the field continues to grow, programming education will become more and more prevalent within elementary and high schools across the country. The ways in which programming is taught needs to transition to a more literacy-based approach for younger children to improve the effectiveness of the education. If the instruction of programming evolves according to the findings displayed in this essay, so will the growth of the field of Computer Science. Just as most people hold the belief that literacy is not involved in the field of Computer Science, many people are unaware of its presence within all STEM fields, whether it be biology, nursing, or engineering. If the style of teaching programming is holding back the future of programming so drastically by ignoring literacy approaches, imagine how much the world is being held back by this issue.

Although approaching the instruction of computer programming from a literacy point of view is more effective than just the STEM approach overall, there are still many individuals that have disadvantages in learning programming no matter what teaching method that is used. According to Antonio Byrd’s article, “Between Learning and Opportunity: A Study of African American Coders’ Networks of Support,” racially marginalized individuals are not as likely to develop coding literacy skills for problem-solving applications (Byrd 31). A core issue for these marginalized communities gaining access to programming knowledge and experience is financial stability. Computer Programming boot camps and college education are both very expensive investments, which is often not an option for individuals from marginalized communities. Byrd expands on this by stating that even those that do not need to pay tuition for coding bootcamps are required to give of their emotional and physical labor (34). Since coding bootcamps require many hours of work a week, many individuals often have to take time away from their jobs and/or their families. This is something that many marginalized people can simply not afford. The study described in this article takes place at Clearwater Academy, where marginalized students do not pay tuition, which taught courses on programming languages such as JavaScript, HTML, and CSS (Byrd 35). The results of this confirm that African American adult’s access to coding literacy is limited by the social, emotional, and economic repercussions of white supremacy (Byrd 49). Unfortunately, there is no one easy solution that completely resolves this issue, as it stems from years of oppression and discrimination. In order to best combat this issue, universities, training centers, and employers need to take steps to accommodate the needs of marginalized groups. Taking steps in this direction will cultivate the field of Computer Science to grow exponentially and move towards equality.

Works Cited

Bers, Marina Umaschi. “Coding as another language: a pedagogical approach for teaching computer science in early childhood.” Journal of Computers in Education 6.4 (2019): 499-528.

Byrd, Antonio. “Between learning and opportunity: A study of African American coders’ networks of support.” Literacy in Composition Studies 7.2 (2019): 31-56.

Cencelj, Zvonka, et al. “Role and meaning of functional science, technological and engineering literacy in problem-based learning.” Journal of Baltic Science Education 18.1 (2019): 132-146.

“Classifying Programming Languages.” Pltypes, Loyola Marymount University,

cs.lmu.edu/~ray/notes/pltypes/.

Dubochet, Gilles. “Computer Code as a Medium for Human Communication: Are Programming Languages Improving?” Proceedings of the 21st Working Conference on the Psychology of Programmers Interest Group. No. CONF. University of Limerick, 2009.

Grafwallner, Peg. “Encoding Literacy in Computer Science.” Edutopia , George Lucas Educational Foundation, 10 Jan. 2018, www.edutopia.org/article/encoding-literacy-computer-science.

Harris, Ana. “Human Languages vs. Programming Languages.” Medium , Medium, 1 Nov. 2018, medium.com/@anaharris/human-languages-vs-programming-languages-c89410f13252.

Hermans, Felienne, and Marlies Aldewereld. “Programming is writing is programming.” Companion to the first International Conference on the Art, Science and Engineering of Programming . 2017.

Jacob, Sharin Rawhiya, and Mark Warschauer. “Computational thinking and literacy.” Journal of Computer Science Integration 1.1. 2018.

Riemer, Marc J. “Communication skills for the 21st century engineer.” Global J. of Engng. Educ 11.1 (2007): 89-100.

R Hassenfeld, Ziva, et al. “If You Can Program, You Can Write: Learning Introductory Programming Across Literacy Levels.” Journal of Information Technology Education: Research , vol. 19, 2020, pp. 065–085., doi:10.28945/4509.

Schoeman, Marthie. “Reading skills can predict the programming performance of novices: an eye-tracking study.” Perspectives in Education 37.2 (2019): 35-52.

Vee, Annette. “Computer Programming as Literacy.” Coding Literacy , 2017, pp. 445–452., doi:10.7551/mitpress/10655.003.0003.

Understanding Literacy in Our Lives by John Parker is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License , except where otherwise noted.

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International Study Finds Major Inequities in Computer Literacy

Having access to a computer or tablet doesn’t necessarily make students computer literate, according to a study released Tuesday that looked at computer literacy rates across a dozen countries.

The study also found greater variation in achievement levels within each nation than it found between countries, said Dirk Hastedt, the executive director of the by the International Association for the Evaluation of Educational Achievement, which released the analysis. That points to a major equity issue, he explained.

For instance, students in the 95 th percentile when it comes to computer literacy skills in one of the highest-scoring countries who participated in the study, South Korea scored an average of 682 on the assessment. (The scale was 1 to 700.)

That’s only 118 points higher than those in one of the lowest scoring countries, Kazakshstan. But it’s a whopping 312 points higher than the lowest 5 percent of students in South Korea.

On average, students of higher socio-economic status, as measured by family conditions such as parental occupation and education, and the number of books in the home, had significantly higher computer literacy scores.

For instance, students who reported that their parents had a bachelor’s degree or higher scored an average of 518. Those whose parents did not hold a bachelor’s degree scored an average of 487. And those who reported having a parent with high occupational status scored an average of 522, compared to 485 for those with parents of low-to-medium occupational status.

The countries and states that participated in the study include Chile, Denmark, Finland, France, Germany, Italy, Kazakhstan, South Korea, Luxembourg, Portugal, Uruguay, and the United States. Other parts of those countries—including Moscow in the Russia Federation and North Rhine-Westphalia in Germany, joined so they could benchmark their results against other nations. The U.S did not meet the participation threshold for the study, so its results aren’t as considered as comparable.

Middling Performance From U.S. Students

Denmark and South Korea were the top performaers on the assessment. The United States scored in the middle of the pack. Researchers conducted a 40-minute assessment for a sample group of students, and a background questionnaire for teachers, principals, and technical coordinators. The IEA assessed more than 46,000 students, 26,000 teachers, and 2,200 schools in 14 countries and territories for the study.

In evaluating students’ computer literacy, the study considered students’ ability to do things like edit digital photographs, create a database using Microsoft or Access, write or edit text for a school assignment, search for relevant information for a school project on the internet, creating a multimedia presentation, or judge whether you can trust information you find on the internet.

The study found that if a student doesn’t learn such skills at home, it’s unlikely that their teacher will be able to fill in the gaps, Hastedt said.

“Certain things you need to know in today’s world are not taught in school,” Hastedt said. “Teachers think students already know it, and this is not true.”

What’s more, teachers themselves may not be proficient at some computer-literacy skills. While 95 percent of teachers said they were comfortable using the internet to find resources, just 57 percent said they were confident in using digital tools for online collaboration.

“Teachers don’t feel self-confident in using computers,” Hastedt said. “We make sure that there are devices in schools but we don’t necessarily make sure that the teachers” understand how to help students learn to use them effectively. In part it’s a generational issue, he added. The study saw a huge difference between younger teachers—defined as those younger than 40 and older teachers when it comes to how comfortable educators were in helping students learn to use devices.

“There’s a clear need to get all of our teachers up-to-speed,” Hastedt said.

Strong Showing for Girls

And overall, girls outperformed boys on computer literacy skills. They scored an average of 505, compared with 498 for boys. That tracks with the results of the National Assessment for Educational Progress in Technology and Engineering Literacy (TEL), which also found girls significantly outpacing boys . It’s also consistent with the last time the study was conducted, in 2013.

“Most people think boys are better in computers and tech, but this is not what we found,” Hastedt said. “It’s actually the girls who do better.”

The biggest surprise of the report? Not much has changed since the last survey in 2013.

“Computers are used in very old fashioned ways,” Hastedt said. “Basic computer literacy skills are not taught to all students.”

Image: Getty

A version of this news article first appeared in the Digital Education blog.

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Importance of computer literacy in the modern world

Do i really need computer literacy you may ask.

Its shocking that some people still wonder if computer literacy is really important in this 21st century. The fact is that the use of computers has become a way of life in the modern world and this makes it important for just about everyone to learn basic computer skills .

A few decades ago, computer use was mostly relegated to a handful of professions. Not many people owned their own computers, and most computers were used as a tool on the job. These days, there is at least one computer in every household, and most people have active accounts on Facebook or Twitter or at least an email address. Computers are ubiquitous in our society, so it stands to reason that more importance has been placed on computer literacy.

Being computer literate is important as it opens up more job opportunities , helps in staying up to date, it is a cheap way to communicate, it enhances professionalism, helps in better record keeping and makes transactions more convenient. Almost all workplaces and businesses have embraced the use of computers in one way or another meaning it is almost impossible not to encounter a computer in everyday life

There are many clear advantages to being computer literate in the 21st century. Here are just a few of them:

IMPORTANCE OF COMPUTER LITERACY IN THE MODERN WORLD

Benefits of computer literacy in the modern world

More job opportunities:.

since almost all workplaces use computers, employers are likely to favor people that are computer literate over those with no computer skills. For many people, it’s easier to find an office job that involves the use of a computer if they are already computer literate .

Naturally, being able to use a computer will put you at a distinct advantage when you apply for these kinds of positions. Not only can computer literacy make you more desirable to employers for office jobs, it may allow you to find ways to work from home if you have a reliable Internet connection.

Staying up to date:

Although there are still plenty of people who read them, newspapers are quickly becoming relics of the past. People are now choosing to read the news online, and these sites can be updated instantly as stories develop.

Best ICT and Computer Training School and institute in Nigeria Africa Bizmarrow (1)

Being computer literate enough to access these sites means being able to better keep up with current events. in the modern world, it is easier to hear or read about the latest news through computer websites.

Being Prepared for the Future:

Computer technology is advancing faster than ever before, and it’s very easy to be left behind if you don’t take the time to become at least semi-literate when it comes to computers.

The communication technology you use now will most likely be very different from what you will be using in five years, but it will still provide you with a solid foundation of computer literacy that will serve you for years to come.

Cheap and Better communication :

the cost of using computers for communication is quite reasonable making them ideal for those running businesses or people who wish to save more.A significant part of communication in the 21st century is done remotely over computer networks.

Email is more convenient than traditional mail-in many ways, and people who might otherwise never be able to speak to each other regularly exchange messages even though they may be on opposite sides of the world. Whether you are keeping in touch with old friends or emailing your resume to employers, communication via the Internet is vital in the modern age.

Computer literacy enhances professionalism:

A person using a computer is likely to be more organized when compared with someone who does not use a computer. Programs like word processors and bookkeeping software help in keeping a person professional.

Computer literacy training office productivity training in Abuja Nigeria

Better Connectivity:

Connectivity has become the order of the day in this digital age.

It does not matter where you live or what you do, the Internet provides you with the ability to connect to people in any part of the world who are interested in what you are producing or what you are doing. You can develop bonds for collaboration, and you can enhance and grow whatever you do through the power of the Internet.

Computer literacy, which allows you to make use of this incredible resource, is fundamental. Just having even the most basic computer skills will begin your journey. You can then build on those skills to take them to whatever level you want.

It is an exciting time. Computer literacy will help you use this tool to take part in the excitement and opportunity to transform your own life and the lives of others.

Why not start learning a new computer skill.

Here are different computer literacy skills you can start learning today .

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Computer Science Essay Examples

Explore 15+ Brilliant Computer Science Essay Examples: Tips Included

Published on: May 5, 2023

Last updated on: Jan 30, 2024

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Do you struggle with writing computer science essays that get you the grades you deserve?

If so, you're not alone!

Crafting a top-notch essay can be a daunting task, but it's crucial to your success in the field of computer science.

For that, CollegeEssay.org has a solution for you!

In this comprehensive guide, we'll provide you with inspiring examples of computer science essays. You'll learn everything you need to know to write effective and compelling essays that impress your professors and get you the grades you deserve.

So, let's dive in and discover the secrets to writing amazing computer science essays!

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Computer Science Essays: Understanding the Basics

A computer science essay is a piece of writing that explores a topic related to computer science. It may take different forms, such as an argumentative essay, a research paper, a case study, or a reflection paper.

Just like any other essay, it should be well-researched, clear, concise, and effectively communicate the writer's ideas and arguments.

Computer essay examples encompass a wide range of topics and types, providing students with a diverse set of writing opportunities.

Here, we will explore some common types of computer science essays:

Middle School Computer Science Essay Example

College Essay Example Computer Science

University Computer Science Essay Example

Computer Science Extended Essay Example

Uiuc Computer Science Essay Example [

Computer Science Essay Examples For Different Fields

Computer science is a broad field that encompasses many different areas of study. For that, given below are some examples of computer science essays for some of the most popular fields within the discipline.

By exploring these examples, you can gain insight into the different types of essays within this field.

College Application Essay Examples Computer Science

The Future of Computers Technology

Historical Development of Computer Science

Young Children and Technology: Building Computer Literacy

Computer Science And Artificial Intelligence

Looking for more examples of computer science essays? Given below are some additional examples of computer science essays for readers to explore and gain further inspiration from.

Computer Science â My Choice for Future Career

My Motivation to Pursue Undergraduate Studies in Computer Engineering

Abstract Computer Science

Computer Science Personal Statement Example

Sop For Computer Science

Computer Science Essay Topics

There are countless computer science essay topics to choose from, so it can be challenging to narrow down your options.

However, the key is to choose a topic that you are passionate about and that aligns with your assignment requirements.

Here are ten examples of computer science essay topics to get you started:

The impact of artificial intelligence on society: benefits and drawbacks
Cybersecurity measures in cloud computing systems
The Ethics of big data: privacy, bias, and Transparency
The future of quantum computing: possibilities and challenges
The Role of computer hardware in Healthcare: current applications and potential innovations
Programming languages: a comparative analysis of their strengths and weaknesses
The use of machine learning in predicting human behavior
The challenges and solutions for developing secure and reliable software
The Role of blockchain technology in improving supply chain management
The use of data analytics in business decision-making.

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Tips to Write an Effective Computer Science Essay

Writing an effective computer science essay requires a combination of technical expertise and strong writing skills. Here are some tips to help you craft a compelling and well-written essay:

Understand the Requirements: Make sure you understand the assignment requirements, including the essay type, format, and length.

Choose a Topic: Select a topic that you are passionate about and that aligns with your assignment requirements.
Create an Outline: Develop a clear and organized outline that highlights the main points and subtopics of your essay.
Use Appropriate Language and Tone: Use technical terms and language when appropriate. But ensure your writing is clear, concise, and accessible to your target audience.
Provide Evidence: Use relevant and credible evidence to support your claims, and ensure you cite your sources correctly.
Edit and Proofread Your Essay: Review your essay for clarity, coherence, and accuracy. Check for grammatical errors, spelling mistakes, and formatting issues.

By following these tips, you can improve the quality of your computer science essay and increase your chances of success.

In conclusion, writing a computer science essay can be a challenging yet rewarding experience.

It allows you to showcase your knowledge and skills within the field and develop your writing and critical thinking abilities. By following the examples provided in this blog, you can create an effective computer science essay, which will meet your requirements.

If you find yourself struggling with the writing process, consider seeking essay writing help online from CollegeEssay.org.

Our AI essay writer can provide guidance and support in crafting a top-notch computer science essay.

So, what are you waiting for? Hire our computer science essay writing service today!

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As a Digital Content Strategist, Nova Allison has eight years of experience in writing both technical and scientific content. With a focus on developing online content plans that engage audiences, Nova strives to write pieces that are not only informative but captivating as well.

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Essays on Computer Literacy

4 samples on this topic

The mixture of written assignments you might be tasked with while studying Computer Literacy is stunning. If some are too challenging, an expertly crafted sample Computer Literacy piece on a related topic might lead you out of a deadlock. This is when you will definitely recognize WowEssays.com ever-widening collection of Computer Literacy essay samples meant to ignite your writing enthusiasm.

Our directory of free college paper samples showcases the most vivid instances of top-notch writing on Computer Literacy and relevant topics. Not only can they help you develop an interesting and fresh topic, but also display the effective use of the best Computer Literacy writing practices and content organization techniques. Also, keep in mind that you can use them as a trove of authoritative sources and factual or statistical information processed by real masters of their craft with solid academic backgrounds in the Computer Literacy field.

Alternatively, you can take advantage of effective write my essay assistance, when our authors provide a unique model essay on Computer Literacy tailored to your individual requirements!

Computer Literacy Problem In Turkey And Solutions From Other Countries Essays Example

Computer Literacy Problem in Turkey

Computer Literacy Essay

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World Computer Literacy Day: Date, Theme, History, Significance

Updated on
Nov 29, 2023

With the invention of computers, the functioning of the entire world has changed. Digital learning is introduced at primary and secondary levels to make kids familiar with computers. A specific day is dedicated to celebrating World Computer Literacy Day . The World Computer Literacy Day is celebrated on 2 December every year since 2001. It is celebrated to drive digital literacy among women and children and encourage people towards a digital future. However, to date, there are certain sections of who are deprived of digital access so WCLD supports and promotes computer literacy in all sections of society. Keep reading and explore the date, theme, history, and significance of World Computer Literacy Day!

World Computer Literacy Day Theme 2023

Every year a specific theme is decided to celebrate WCLD. This day is celebrated to spread awareness in society about the importance of computer literacy. The theme for this year’s WCLD has not been announced yet.

Previous Year Theme of World Computer Literacy Day

Following is a list of themes that were used on the in the previous years

Also Read: What is the Full Form of PC in Computer?

History: When is World Computer Literacy Day Celebrated?

World Computer Literacy Day was an initiative by an Indian company NIIT National Institute of Information Technology. It was started on 2 December 2001 to mark the 20th anniversary of its establishment. In 2002, World Computer Literacy Day was celebrated together with many members of the Parliament. They were also provided computer training to spread awareness about computer literacy in the Presence of then Prime Minister of India Atal Bihari Vajpayee .

The main aim behind celebrating this day is to surpass the issue of the global digital divide. It has affected millions of people to whom computer literacy is inaccessible. Therefore, this day fuels the need to bridge the digital divide among the people.

Significance of the Day

On this day, people emphasise the importance of computers in day-to-day life. Computer is a basic necessity nowadays because everything is digital. It also focuses on eradicating the digital divide between different sectors of society.

This day holds a significant role in the adoption of digital technologies, mainly by women and children.

Kajal Thareja

Hi, I am Kajal, a pharmacy graduate, currently pursuing management and is an experienced content writer. I have 2-years of writing experience in Ed-tech (digital marketing) company. I am passionate towards writing blogs and am on the path of discovering true potential professionally in the field of content marketing. I am engaged in writing creative content for students which is simple yet creative and engaging and leaves an impact on the reader's mind.

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Submit at: https://openreview.net/group?id=NeurIPS.cc/2024/Conference

The site will start accepting submissions on Apr 22, 2024

Subscribe to these and other dates on the 2024 dates page .

The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024) is an interdisciplinary conference that brings together researchers in machine learning, neuroscience, statistics, optimization, computer vision, natural language processing, life sciences, natural sciences, social sciences, and other adjacent fields. We invite submissions presenting new and original research on topics including but not limited to the following:

Applications (e.g., vision, language, speech and audio, Creative AI)
Deep learning (e.g., architectures, generative models, optimization for deep networks, foundation models, LLMs)
Evaluation (e.g., methodology, meta studies, replicability and validity, human-in-the-loop)
General machine learning (supervised, unsupervised, online, active, etc.)
Infrastructure (e.g., libraries, improved implementation and scalability, distributed solutions)
Machine learning for sciences (e.g. climate, health, life sciences, physics, social sciences)
Neuroscience and cognitive science (e.g., neural coding, brain-computer interfaces)
Optimization (e.g., convex and non-convex, stochastic, robust)
Probabilistic methods (e.g., variational inference, causal inference, Gaussian processes)
Reinforcement learning (e.g., decision and control, planning, hierarchical RL, robotics)
Social and economic aspects of machine learning (e.g., fairness, interpretability, human-AI interaction, privacy, safety, strategic behavior)
Theory (e.g., control theory, learning theory, algorithmic game theory)

Machine learning is a rapidly evolving field, and so we welcome interdisciplinary submissions that do not fit neatly into existing categories.

Authors are asked to confirm that their submissions accord with the NeurIPS code of conduct .

Formatting instructions: All submissions must be in PDF format, and in a single PDF file include, in this order:

The submitted paper
Technical appendices that support the paper with additional proofs, derivations, or results
The NeurIPS paper checklist

Other supplementary materials such as data and code can be uploaded as a ZIP file

The main text of a submitted paper is limited to nine content pages , including all figures and tables. Additional pages containing references don’t count as content pages. If your submission is accepted, you will be allowed an additional content page for the camera-ready version.

The main text and references may be followed by technical appendices, for which there is no page limit.

The maximum file size for a full submission, which includes technical appendices, is 50MB.

Authors are encouraged to submit a separate ZIP file that contains further supplementary material like data or source code, when applicable.

You must format your submission using the NeurIPS 2024 LaTeX style file which includes a “preprint” option for non-anonymous preprints posted online. Submissions that violate the NeurIPS style (e.g., by decreasing margins or font sizes) or page limits may be rejected without further review. Papers may be rejected without consideration of their merits if they fail to meet the submission requirements, as described in this document.

Paper checklist: In order to improve the rigor and transparency of research submitted to and published at NeurIPS, authors are required to complete a paper checklist . The paper checklist is intended to help authors reflect on a wide variety of issues relating to responsible machine learning research, including reproducibility, transparency, research ethics, and societal impact. The checklist forms part of the paper submission, but does not count towards the page limit.

Please join the NeurIPS 2024 Checklist Assistant Study that will provide you with free verification of your checklist performed by an LLM here . Please see details in our blog

Supplementary material: While all technical appendices should be included as part of the main paper submission PDF, authors may submit up to 100MB of supplementary material, such as data, or source code in a ZIP format. Supplementary material should be material created by the authors that directly supports the submission content. Like submissions, supplementary material must be anonymized. Looking at supplementary material is at the discretion of the reviewers.

We encourage authors to upload their code and data as part of their supplementary material in order to help reviewers assess the quality of the work. Check the policy as well as code submission guidelines and templates for further details.

Use of Large Language Models (LLMs): We welcome authors to use any tool that is suitable for preparing high-quality papers and research. However, we ask authors to keep in mind two important criteria. First, we expect papers to fully describe their methodology, and any tool that is important to that methodology, including the use of LLMs, should be described also. For example, authors should mention tools (including LLMs) that were used for data processing or filtering, visualization, facilitating or running experiments, and proving theorems. It may also be advisable to describe the use of LLMs in implementing the method (if this corresponds to an important, original, or non-standard component of the approach). Second, authors are responsible for the entire content of the paper, including all text and figures, so while authors are welcome to use any tool they wish for writing the paper, they must ensure that all text is correct and original.

Double-blind reviewing: All submissions must be anonymized and may not contain any identifying information that may violate the double-blind reviewing policy. This policy applies to any supplementary or linked material as well, including code. If you are including links to any external material, it is your responsibility to guarantee anonymous browsing. Please do not include acknowledgements at submission time. If you need to cite one of your own papers, you should do so with adequate anonymization to preserve double-blind reviewing. For instance, write “In the previous work of Smith et al. [1]…” rather than “In our previous work [1]...”). If you need to cite one of your own papers that is in submission to NeurIPS and not available as a non-anonymous preprint, then include a copy of the cited anonymized submission in the supplementary material and write “Anonymous et al. [1] concurrently show...”). Any papers found to be violating this policy will be rejected.

OpenReview: We are using OpenReview to manage submissions. The reviews and author responses will not be public initially (but may be made public later, see below). As in previous years, submissions under review will be visible only to their assigned program committee. We will not be soliciting comments from the general public during the reviewing process. Anyone who plans to submit a paper as an author or a co-author will need to create (or update) their OpenReview profile by the full paper submission deadline. Your OpenReview profile can be edited by logging in and clicking on your name in https://openreview.net/ . This takes you to a URL "https://openreview.net/profile?id=~[Firstname]_[Lastname][n]" where the last part is your profile name, e.g., ~Wei_Zhang1. The OpenReview profiles must be up to date, with all publications by the authors, and their current affiliations. The easiest way to import publications is through DBLP but it is not required, see FAQ . Submissions without updated OpenReview profiles will be desk rejected. The information entered in the profile is critical for ensuring that conflicts of interest and reviewer matching are handled properly. Because of the rapid growth of NeurIPS, we request that all authors help with reviewing papers, if asked to do so. We need everyone’s help in maintaining the high scientific quality of NeurIPS.

Please be aware that OpenReview has a moderation policy for newly created profiles: New profiles created without an institutional email will go through a moderation process that can take up to two weeks. New profiles created with an institutional email will be activated automatically.

Venue home page: https://openreview.net/group?id=NeurIPS.cc/2024/Conference

If you have any questions, please refer to the FAQ: https://openreview.net/faq

Abstract Submission: There is a mandatory abstract submission deadline on May 15, 2024, six days before full paper submissions are due. While it will be possible to edit the title and abstract until the full paper submission deadline, submissions with “placeholder” abstracts that are rewritten for the full submission risk being removed without consideration. This includes titles and abstracts that either provide little or no semantic information (e.g., "We provide a new semi-supervised learning method.") or describe a substantively different claimed contribution. The author list cannot be changed after the abstract deadline. After that, authors may be reordered, but any additions or removals must be justified in writing and approved on a case-by-case basis by the program chairs only in exceptional circumstances.

Ethics review: Reviewers and ACs may flag submissions for ethics review . Flagged submissions will be sent to an ethics review committee for comments. Comments from ethics reviewers will be considered by the primary reviewers and AC as part of their deliberation. They will also be visible to authors, who will have an opportunity to respond. Ethics reviewers do not have the authority to reject papers, but in extreme cases papers may be rejected by the program chairs on ethical grounds, regardless of scientific quality or contribution.

Preprints: The existence of non-anonymous preprints (on arXiv or other online repositories, personal websites, social media) will not result in rejection. If you choose to use the NeurIPS style for the preprint version, you must use the “preprint” option rather than the “final” option. Reviewers will be instructed not to actively look for such preprints, but encountering them will not constitute a conflict of interest. Authors may submit anonymized work to NeurIPS that is already available as a preprint (e.g., on arXiv) without citing it. Note that public versions of the submission should not say "Under review at NeurIPS" or similar.

Dual submissions: Submissions that are substantially similar to papers that the authors have previously published or submitted in parallel to other peer-reviewed venues with proceedings or journals may not be submitted to NeurIPS. Papers previously presented at workshops are permitted, so long as they did not appear in a conference proceedings (e.g., CVPRW proceedings), a journal or a book. NeurIPS coordinates with other conferences to identify dual submissions. The NeurIPS policy on dual submissions applies for the entire duration of the reviewing process. Slicing contributions too thinly is discouraged. The reviewing process will treat any other submission by an overlapping set of authors as prior work. If publishing one would render the other too incremental, both may be rejected.

Anti-collusion: NeurIPS does not tolerate any collusion whereby authors secretly cooperate with reviewers, ACs or SACs to obtain favorable reviews.

Author responses: Authors will have one week to view and respond to initial reviews. Author responses may not contain any identifying information that may violate the double-blind reviewing policy. Authors may not submit revisions of their paper or supplemental material, but may post their responses as a discussion in OpenReview. This is to reduce the burden on authors to have to revise their paper in a rush during the short rebuttal period.

After the initial response period, authors will be able to respond to any further reviewer/AC questions and comments by posting on the submission’s forum page. The program chairs reserve the right to solicit additional reviews after the initial author response period. These reviews will become visible to the authors as they are added to OpenReview, and authors will have a chance to respond to them.

After the notification deadline, accepted and opted-in rejected papers will be made public and open for non-anonymous public commenting. Their anonymous reviews, meta-reviews, author responses and reviewer responses will also be made public. Authors of rejected papers will have two weeks after the notification deadline to opt in to make their deanonymized rejected papers public in OpenReview. These papers are not counted as NeurIPS publications and will be shown as rejected in OpenReview.

Publication of accepted submissions: Reviews, meta-reviews, and any discussion with the authors will be made public for accepted papers (but reviewer, area chair, and senior area chair identities will remain anonymous). Camera-ready papers will be due in advance of the conference. All camera-ready papers must include a funding disclosure . We strongly encourage accompanying code and data to be submitted with accepted papers when appropriate, as per the code submission policy . Authors will be allowed to make minor changes for a short period of time after the conference.

Contemporaneous Work: For the purpose of the reviewing process, papers that appeared online within two months of a submission will generally be considered "contemporaneous" in the sense that the submission will not be rejected on the basis of the comparison to contemporaneous work. Authors are still expected to cite and discuss contemporaneous work and perform empirical comparisons to the degree feasible. Any paper that influenced the submission is considered prior work and must be cited and discussed as such. Submissions that are very similar to contemporaneous work will undergo additional scrutiny to prevent cases of plagiarism and missing credit to prior work.

Plagiarism is prohibited by the NeurIPS Code of Conduct .

Other Tracks: Similarly to earlier years, we will host multiple tracks, such as datasets, competitions, tutorials as well as workshops, in addition to the main track for which this call for papers is intended. See the conference homepage for updates and calls for participation in these tracks.

Experiments: As in past years, the program chairs will be measuring the quality and effectiveness of the review process via randomized controlled experiments. All experiments are independently reviewed and approved by an Institutional Review Board (IRB).

Financial Aid: Each paper may designate up to one (1) NeurIPS.cc account email address of a corresponding student author who confirms that they would need the support to attend the conference, and agrees to volunteer if they get selected. To be considered for Financial the student will also need to fill out the Financial Aid application when it becomes available.

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CVPR Technical Program Features Presentations on the Latest AI and Computer Vision Research

LOS ALAMITOS, Calif., 16 May 2024 – Co-sponsored by the IEEE Computer Society (CS) and the Computer Vision Foundation (CVF), the 2024 Computer Vision and Pattern Recognition (CVPR) Conference is the preeminent event for research and development (R&D) in the hot topic areas of computer vision, artificial intelligence (AI), machine learning (ML), augmented, virtual and mixed reality (AR/VR/MR), deep learning, and related fields. Over the past decade, these areas have seen significant growth, and the emphasis on this sector by the science and engineering community has fueled an increasingly competitive technical program.

This year, the CVPR Program Committee received 11,532 paper submissions—a 26% increase over 2023—but only 2,719 were accepted, resulting in an acceptance rate of just 23.6%. Of those accepted papers, only 3.3% were slotted for oral presentations based on nominations from the area chairs and senior area chairs overseeing the program.

“CVPR is not only the premiere conference in computer vision, but it’s also among the highest-impact publication venues in all of science,” said David Crandall, Professor of Computer Science at Indiana University, Bloomington, Ind., U.S.A., and CVPR 2024 Program Co-Chair. “Having one’s paper accepted to CVPR is already a major achievement, and then having it selected as an oral presentation is a very rare honor that reflects its high quality and potential impact.”

Taking place 17-21 June at the Seattle Convention Center in Seattle, Wash., U.S.A., CVPR offers oral presentations that speak to both fundamental and applied research in areas as diverse as healthcare applications, robotics, consumer electronics, autonomous vehicles, and more. Examples include:

Pathology: Transcriptomics-guided Slide Representation Learning in Computational Pathology *– Training computer systems for pathology requires a multi-modal approach for efficiency and accuracy. New work from a multi-disciplinary team at Harvard University (Cambridge, Mass., U.S.A.), the Massachusetts Institute of Technology (MIT; Cambridge, Mass., U.S.A.), Emory University (Atlanta, Ga., U.S.A.) and others employs modality-specific encoders, and when applied on liver, breast, and lung samples from two different species, they demonstrated significantly better performance when compared to current baselines.
Robotics: SceneFun3D: Fine-Grained Functionality and Affordance Understanding in 3D Scenes – Creating realistic interactions in 3D scenes has been troublesome from a technology perspective because it has been difficult to manipulate objects in the scene context. Research from ETH Zürich (Zürich, Switzerland), Google (Mountainview, Calif., U.S.A.), Technical University of Munich (TUM; Munich, Germany), and Microsoft (Redmond, Wash., U.S.A.) has begun bridging that divide by creating a large-scale dataset with more than 14.8k highly accurate interaction annotations for 710 high-resolution real-world 3D indoor scenes. This work, as the paper concludes, has the potential to “stimulate advancements in embodied AI, robotics, and realistic human-scene interaction modeling.”
Virtual Reality: URHand: Universal Relightable Hands – Teams from Codec Avatars Lab at Meta (Menlo Park, Calif., U.S.A.) and Nanyang Technological University (Singapore) unveil a hand model that generalizes to novel viewpoints, poses, identities, and illuminations, which enables quick personalization from a phone scan. The resulting images make for a more realistic experience of reaching, grabbing, and interacting in a virtual environment.
Human Avatars: Semantic Human Mesh Reconstruction with Textures – Working to create realistic human models, teams at Nanjing University (Nanjing, China) and Texas A&M University (College Station, Texas, U.S.A.) designed a method of 3-D human mesh reconstruction that is capable of producing high-fidelity and robust semantic renderings that outperform state-of-the-art methods. The paper concludes, “This approach bridges existing monocular reconstruction work and downstream industrial applications, and we believe it can promote the development of human avatars.”
Text-to-Image Systems: Ranni: Taming Text-to-Image Diffusion for Accurate Instruction – Existing text-to-image models can misinterpret more difficult prompts, but now, new research from Alibaba Group (Hangzhou, Zhejiang, China) and Ant Group (Hangzhou, Zhejiang, China) has made strides in addressing that issue via a middleware layer. This approach, which they have dubbed Ranni, supports the text-to-image generator in better following instructions. As the paper sums up, “Ranni shows potential as a flexible chat-based image creation system, where any existing diffusion model can be incorporated as the generator for interactive generation.”
Autonomous Driving: Producing and Leveraging Online Map Uncertainty in Trajectory Prediction – To enable autonomous driving, vehicles must be pre-trained on the geographic region and potential pitfalls. High-definition (HD) maps have become a standard part of a vehicle’s technology stack, but current approaches to those maps are siloed in their programming. Now, work from a research team from the University of Toronto (Toronto, Ontario, Canada), Vector Institute (Toronto, Ontario, Canada), NVIDIA Research (Santa Clara, Calif., U.S.A.), and Stanford University (Palo Alto, Calif., U.S.A.) enhances current methodologies by incorporating uncertainty, resulting in up to 50% faster training convergence and up to 15% better prediction performance.

“As the field’s leading event, CVPR introduces the latest research in all areas of computer vision,” said Crandall. “In addition to the oral paper presentations, there will be thousands of posters, dozens of workshops and tutorials, several keynotes and panels, and countless opportunities for learning and networking. You really have to attend the conference to get the full scope of what’s next for computer vision and AI technology.”

Digital copies of all final technical papers* will be available on the conference website by the week of 10 June to allow attendees to prepare their schedules. To register for CVPR 2024 as a member of the press and/or request more on a specific paper, visit https://cvpr.thecvf.com/Conferences/2024/MediaPass or email [email protected]. For more information on the conference, visit https://cvpr.thecvf.com/ .

*Papers linked in this press release refer to pre-print publications. Final, citable papers will be available just prior to the conference.

About the CVPR 2024 The Computer Vision and Pattern Recognition Conference (CVPR) is the preeminent computer vision event for new research in support of artificial intelligence (AI), machine learning (ML), augmented, virtual and mixed reality (AR/VR/MR), deep learning, and much more. Sponsored by the IEEE Computer Society (CS) and the Computer Vision Foundation (CVF), CVPR delivers the important advances in all areas of computer vision and pattern recognition and the various fields and industries they impact. With a first-in-class technical program, including tutorials and workshops, a leading-edge expo, and robust networking opportunities, CVPR, which is annually attended by more than 10,000 scientists and engineers, creates a one-of-a-kind opportunity for networking, recruiting, inspiration, and motivation.

CVPR 2024 takes place 17-21 June at the Seattle Convention Center in Seattle, Wash., U.S.A., and participants may also access sessions virtually. For more information about CVPR 2024, visit cvpr.thecvf.com .

About the Computer Vision Foundation The Computer Vision Foundation (CVF) is a non-profit organization whose purpose is to foster and support research on all aspects of computer vision. Together with the IEEE Computer Society, it co-sponsors the two largest computer vision conferences, CVPR and the International Conference on Computer Vision (ICCV). Visit thecvf.com for more information.

About the IEEE Computer Society Engaging computer engineers, scientists, academia, and industry professionals from all areas and levels of computing, the IEEE Computer Society (CS) serves as the world’s largest and most established professional organization of its type. IEEE CS sets the standard for the education and engagement that fuels continued global technological advancement. Through conferences, publications, and programs that inspire dialogue, debate, and collaboration, IEEE CS empowers, shapes, and guides the future of not only its 375,000+ community members, but the greater industry, enabling new opportunities to better serve our world. Visit computer.org for more information.

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Essay On Computer Literacy. 1000 Words4 Pages. Computer literacy is the ability to self-teach and learn arbitrary new programs or tasks as they are encountered (Oni, 2000), to highly focused, computer literacy is the computer knowledge and skills of individuals in different professions. Childers (2003) viewed computer literacy as basic computer ...
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