Computer science education

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Elementary school children coding in a robotics programme

Computer science education or computing education is the field of teaching and learning the discipline of computer science, [1] [2] [3] [4] [5] [6] and computational thinking. [7] [8] [9] The field of computer science education encompasses a wide range of topics, from basic programming skills to advanced algorithm design and data analysis. It is a rapidly growing field that is essential to preparing students for careers in the technology industry and other fields that require computational skills. [10]

Contents

Computer science education is essential to preparing students for the 21st century workforce. As technology becomes increasingly integrated into all aspects of society, the demand for skilled computer scientists is growing. According to the Bureau of Labor Statistics, employment of computer and information technology occupations is projected to "grow 21 percent from 2021 to 2031", much faster than the average for all occupations. [11]

In addition to preparing students for careers in the technology industry, computer science education also promotes computational thinking skills, which are valuable in many fields, including business, healthcare, and education. By learning to think algorithmically and solve problems systematically, students can become more effective problem solvers and critical thinkers.

Background

The history of computer science education can be traced back to the early days of computing, when programming was primarily done by scientists and mathematicians. As computers became more widely used in industry and government, the need for skilled programmers grew, and universities began to offer courses in computer science.

In comparison to science education and mathematics education, computer science (CS) education is a much younger field. [12] In the history of computing, digital computers were only built from around the 1940s – although computation has been around for centuries since the invention of analog computers. [13]

Another differentiator of computer science education is that it has primarily only been taught at university level until recently, with some notable exceptions in Israel, Poland and the United Kingdom with the BBC Micro in the 1980s as part of Computer science education in the United Kingdom. [6] [14] Computer science has been a part of the school curricula from age 14 or age 16 in a few countries for a few decades, but has typically as an elective subject.

Primary and secondary computer science education is relatively new in the United States with many K-12 CS teachers facing obstacles to integrating CS instruction such as professional isolation, limited CS professional development resources, and low levels of CS teaching self-efficacy. [15] [16] [17] According to a 2021 report, only 51% of high schools in the US offer computer science. [18] Elementary CS teachers in particular have lower CS teaching efficacy and have fewer chances to implement CS into their instruction than their middle and high school peers. [15] Connecting CS teachers to resources and peers using methods such as Virtual Communities of Practice has been shown to help CS and STEM teachers improve their teaching self-efficacy and implement CS topics into student instruction. [15] [16]

Curriculum

The curriculum for computer science education varies depending on the level of education and country. At the elementary and middle school level, computer science education usually focuses on block or visual programming languages such as Scratch or python (in India For higher Secondary level)using basic programming concepts, such as loops, conditionals, and variables. [19] At the high school level, students may learn more advanced programming concepts and algorithms, as well as web development, networking, and data analysis.

In college and graduate school, computer science education may include courses in topics such as artificial intelligence, machine learning, data science, and computer graphics. Many computer science programs also offer courses in computer architecture, operating systems, and computer networks.

Teaching methods

Teaching methods in computer science education vary depending on the level of education and the goals of the program. At the elementary and middle school level, computer science education may focus on interactive games and puzzles to teach programming concepts. In high school and college, computer science education may involve lectures, labs, and hands-on projects that allow students to apply their knowledge to real-world problems.

Online learning platforms and coding bootcamps have also become popular methods of teaching computer science skills. These programs offer self-paced learning and can be accessed from anywhere with an internet connection. As computer science is more about practicality and real-world application.

Computing education research

Computing education research (CER) or Computer science education research is an interdisciplinary field that focuses on studying the teaching and learning of computer science. [5] [20] It is a subfield of both computer science and education research, and is concerned with understanding how computer science is taught, learned, and assessed in a variety of settings, such as K-12 schools, colleges and universities, and online learning environments.

Background

Computer science education research emerged as a field of study in the 1970s, when researchers began to explore the effectiveness of different approaches to teaching computer programming. Since then, the field has grown to encompass a wide range of topics related to computer science education, including curriculum design, assessment, pedagogy, and diversity and inclusion.

Topics of study

One of the primary goals of computer science education research is to improve the teaching and learning of computer science. To this end, researchers study a variety of topics, including:

Curriculum design

Researchers in computer science education seek to design curricula that are effective and engaging for students. This may involve studying the effectiveness of different programming languages, or developing new pedagogical approaches that promote active learning.

Assessment

Computer science education researchers are interested in developing effective ways to assess student learning outcomes. This may involve developing new measures of student knowledge or skills, or evaluating the effectiveness of different assessment methods.

Pedagogy

Researchers in computer science education are interested in exploring different teaching methods and instructional strategies. This may involve studying the effectiveness of lectures, online tutorials, or peer-to-peer learning.

Diversity and inclusion

Computer science education researchers are interested in promoting diversity and inclusion in computer science education. This may involve studying the factors that contribute to under representation of certain groups in computer science, and developing interventions to promote inclusivity and equity.

Research communities

The Association for Computing Machinery (ACM) runs a Special Interest Group (SIG) on Computer science education known as SIGCSE which celebrated its 50th anniversary in 2018, making it one of the oldest and longest running ACM Special Interest Groups. [21] An outcome of computing education research are Parsons problems.[ citation needed ]

Conferences

Gender perspectives in computer science education

In many countries, there is a significant gender gap in computer science education. In 2015, 15.3% of computer science students graduating from non-doctoral granting institutions in the US were women while at doctoral granting institutions, the figure was 16.6%. [22] The number of female PhD recipients in the US was 19.3% in 2018. [23] In almost everywhere in the world, less than 20% of the computer science graduates are female. [24]

This problem mainly arises due to the lack of interests of girls in computing starting from the primary level. Despite numerous efforts by programs specifically designed to increase the ratio of women in this field, no significant improvement has been observed. Furthermore, a declining trend has been noticed in the involvement of women in past decades. [25]

The main reason for the failure of these programs is because almost all of them focused on girls in high school or higher levels of education. Researchers argue that by then women have already made up their mind and stereotypes start to form about computer scientists. Computer Science is perceived as a male dominated field, pursued by people who are nerdy and lack social skills. [25] All these characteristics seem to be more damaging for a woman as compared to a man. Therefore, in order to break these stereotypes and to engage more women in computer science, it is crucial that there are special outreach programs designed to develop interest in girls starting at the middle school level and prepare them for a academic track towards the hard sciences. [24]

Evidently, there are a few countries in Asia and Africa where these stereotypes do not exist and women are encouraged for a career in science starting at the primary level, thus resulting in a gender gap that is virtually nonexistent. In 2011, women earned half of the computer science degrees in Malaysia. [26] In 2001, 55 percent of computer science graduates in Guyana were women. [27]

Related Research Articles

The Association for Computing Machinery (ACM) is a US-based international learned society for computing. It was founded in 1947 and is the world's largest scientific and educational computing society. The ACM is a non-profit professional membership group, reporting nearly 110,000 student and professional members as of 2022. Its headquarters are in New York City.

<span class="mw-page-title-main">Computer science</span> Study of computation

Computer science is the study of computation, information, and automation. Computer science spans theoretical disciplines to applied disciplines. Though more often considered an academic discipline, computer science is closely related to computer programming.

<span class="mw-page-title-main">PL/C</span> Programming language developed at Cornell University

PL/C is an instructional dialect of the programming language PL/I, developed at the Department of Computer Science of Cornell University in the early 1970s in an effort headed by Professor Richard W. Conway and graduate student Thomas R. Wilcox. PL/C was developed with the specific goal of being used for teaching programming. The PL/C compiler, which implemented almost all of the large PL/I language, had the unusual capability of never failing to compile a program, through the use of extensive automatic correction of many syntax errors and by converting any remaining syntax errors to output statements. This was important because, at the time, students submitted their programs on IBM punch cards and might not get their output back for several hours. Over 250 other universities adopted PL/C; as one late-1970s textbook on PL/I noted, "PL/C ... the compiler for PL/I developed at Cornell University ... is widely used in teaching programming." Similarly, a mid-late-1970s survey of programming languages said that "PL/C is a widely used dialect of PL/I."

<span class="mw-page-title-main">Peter J. Denning</span> American computer scientist and writer

Peter James Denning is an American computer scientist and writer. He is best known for pioneering work in virtual memory, especially for inventing the working-set model for program behavior, which addressed thrashing in operating systems and became the reference standard for all memory management policies. He is also known for his works on principles of operating systems, operational analysis of queueing network systems, design and implementation of CSNET, the ACM digital library, and codifying the great principles of computing. He has written numerous influential articles and books, including an overview of fundamental computer science principles, computational thinking, and his thoughts on innovation as a set of learnable practices.

<span class="mw-page-title-main">David Gries</span> American computer scientist

David Gries is an American computer scientist at Cornell University, United States mainly known for his books The Science of Programming (1981) and A Logical Approach to Discrete Math.

<span class="mw-page-title-main">Michael Kölling</span> German computer scientist

Michael Kölling is a German computer scientist, currently working at King's College London, best known for the development of the BlueJ and Greenfoot educational development environments and as author of introductory programming textbooks. In 2013 he received the SIGCSE Award for Outstanding Contribution to Computer Science Education for the development of the BlueJ.

<span class="mw-page-title-main">Mark Guzdial</span>

Mark Joseph Guzdial is a Professor in the College of Engineering at the University of Michigan. He was formerly a professor in the School of Interactive Computing at the Georgia Institute of Technology affiliated with the College of Computing and the GVU Center. He has conducted research in the fields of computer science education and the learning sciences and internationally in the field of Information Technology. From 2001–2003, he was selected to be an ACM Distinguished Lecturer, and in 2007 he was appointed Vice-Chair of the ACM Education Board Council. He was the original developer of the CoWeb, one of the earliest wiki engines, which was implemented in Squeak and has been in use at institutions of higher education since 1998. He is the inventor of the Media Computation approach to learning introductory computing, which uses contextualized computing education to attract and retain students.

Computational thinking (CT) refers to the thought processes involved in formulating problems so their solutions can be represented as computational steps and algorithms. In education, CT is a set of problem-solving methods that involve expressing problems and their solutions in ways that a computer could also execute. It involves automation of processes, but also using computing to explore, analyze, and understand processes.

Owen Astrachan is an American computer scientist and professor of the practice of computer science at Duke University, where he is also the department's director of undergraduate studies. He is known for his work in curriculum development and methods of teaching computer science. He was one of the first National Science Foundation CISE Distinguished Education Fellows, and is a recipient of the ACM Outstanding Educator Award. He was the principal investigator on the multi-year NSF/College Board project that led to the release of the AP Computer Science Principles course and exam.

<span class="mw-page-title-main">Alexander Repenning</span> American computer programmer

Alexander Repenning is the Director of the Scalable Game Design project, a computer science professor adjunct, a founder of AgentSheets Inc., and a member of the Center for Lifelong Learning and Design at the University of Colorado in Boulder. Repenning is the inventor of drag and drop blocks programming. His research interests include computer science education, end-user programmable agents, human-computer interaction, and artificial intelligence.

Susan Beth Horwitz was an American computer scientist noted for her research on programming languages and software engineering, and in particular on program slicing and dataflow-analysis. She had several best paper and an impact paper award mentioned below under awards.

<span class="mw-page-title-main">David J. Malan</span> American computer scientist and professor

David Jay Malan is an American computer scientist and professor. Malan is a Gordon McKay Professor of Computer Science at Harvard University, and is best known for teaching the course CS50, which is the largest open-learning course at Harvard University and Yale University and the largest Massive Open Online Course (MOOC) at EdX, with lectures being viewed by over a million people on the edX platform up to 2017.

<span class="mw-page-title-main">Gender disparity in computing</span> Imbalance

Gender disparity in computing concerns the disparity between the number of men in the field of computing in relation to the lack of women in the field. Originally, computing was seen as a female occupation. As the field evolved, so too did the demographics, and the gender gap shifted from female dominated to male dominated. The believed need for more diversity and an equal gender gap has led to public policy debates regarding gender equality. Many organizations have sought to create initiatives to bring more women into the field of computing.

Valerie Barr is an American computer scientist, and is the Margaret Hamilton Distinguished Professor of Computer Science at Bard College. She formerly held the Jean Sammet endowed chair in the department of Computer Science at Mount Holyoke College in South Hadley, Massachusetts. She is known for her work with women in computing.

Amber Settle is an American computer scientist and professor of education and theory in the department of Computer Science at DePaul University in Chicago, Illinois. She is known for her work in computer science education and her continuing service and leadership in Association for Computing Machinery (ACM) Special Interest Group on Computer Science Education (SIGCSE). She is also known for her work on computational thinking.

Daniel Zingaro is an associate professor at the University of Toronto Mississauga. His main areas of research are in evaluating Computer science education and online learning. He has co-authored over 80 articles in peer-reviewed journals and conferences; and also authored a textbook, "Invariants: a Generative Approach to Programming.

Susan Sentance is a British computer scientist, educator and director of the Raspberry Pi Foundation Computing Education Research Centre at the University of Cambridge. Her research investigates a wide range of issues computer science education, teacher education and the professional development of those teaching computing. In 2020 Sentance was awarded a Suffrage Science award for her work on computing education.

Alicia Nicki Washington is an American computer scientist, author, and professor at Duke University. She is the author of the book Unapologetically Dope. She was the first Black woman to earn a Doctor of Philosophy in Computer Science from North Carolina State University in 2005.

The International Bebras Challenge on Informatics is an annual computer science competition for primary and secondary school students around the world. With 54 member countries and more than 2.5 million participating students in 2021, the competition is the largest computer science competition in the world.

<span class="mw-page-title-main">Michael E. Caspersen</span> Danish computer scientist

Danish computer scientist Michael Edelgaard Caspersen has spent his academic life furthering computer science education, at all levels. His research interests are computing education, programming didactics, programming methodology, and object-oriented programming. He is best known for his work on computing education research and development, particularly his work to promote informatics as a fundamental discipline for all.

References

  1. Fincher, Sally; Petre, Marian (2004). Computer Science Education Research. London: Taylor & Francis. ISBN   90-265-1969-9. OCLC   54455019.
  2. Sentance, Sue; Barendsen, Erik; Schulte, Carsten (2018). Computer science education : perspectives on teaching and learning in school. London: Bloomsbury. ISBN   978-1-350-05711-1. OCLC   999588195.
  3. Bruckman, Amy; Biggers, Maureen; Ericson, Barbara; McKlin, Tom; Dimond, Jill; DiSalvo, Betsy; Hewner, Mike; Ni, Lijun; Yardi, Sarita (2009). "Georgia computes! Improving the computing education pipeline". ACM SIGCSE Bulletin. 41 (1): 86. doi:10.1145/1539024.1508899. ISSN   0097-8418.
  4. Anon (2017). "Computing education". royalsociety.org.
  5. 1 2 Fincher, Sally A.; Robins, Anthony V. (2019). The Cambridge Handbook of Computing Education Research (PDF). Cambridge University Press. doi:10.1017/9781108654555. ISBN   9781108654555. OCLC   1090781199. S2CID   243000064.
  6. 1 2 Furber, Steve (2017). After the reboot: computing education in UK schools (PDF). London: Royal Society. ISBN   9781782522973.
  7. Guzdial, Mark (2008). "Education: Paving the way for computational thinking". Communications of the ACM. 51 (8): 25–27. doi:10.1145/1378704.1378713. ISSN   0001-0782. S2CID   35737830.
  8. Wing, Jeanette M. (2006). "Computational thinking" (PDF). Communications of the ACM . 49 (3): 33–35. doi:10.1145/1118178.1118215. hdl: 10818/29866 . S2CID   1693513.
  9. Wing, Jeanette M. (2008). "Computational thinking and thinking about computing". Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 366 (1881): 3717–3725. Bibcode:2008RSPTA.366.3717W. doi:10.1098/rsta.2008.0118. PMC   2696102 . PMID   18672462.
  10. Fincher, Sally; Petre, Marian, eds. (2005-09-26). Computer Science Education Research. Taylor & Francis. doi:10.1201/9781482287325. ISBN   978-1-4822-8732-5.
  11. "Computer and Information Research Scientists : Occupational Outlook Handbook: : U.S. Bureau of Labor Statistics". www.bls.gov. Retrieved 2023-04-13.
  12. Tedre, Matti; Simon; Malmi, Lauri (2018). "Changing aims of computing education: a historical survey". Computer Science Education. 28 (2): 158–186. Bibcode:2018CSEd...28..158T. doi:10.1080/08993408.2018.1486624. S2CID   52884221.
  13. Tedre, Matti (2015). The science of computing : shaping a discipline. Boca Raton. ISBN   978-1-4822-1769-8. OCLC   870289913.{{cite book}}: CS1 maint: location missing publisher (link)
  14. Rogers, Yvonne; Shum, Venus; Marquardt, Nic; Lechelt, Susan; Johnson, Rose; Baker, Howard; Davies, Matt (2017). "From the BBC micro to micro:bit and beyond". Interactions. 24 (2): 74–77. doi:10.1145/3029601. ISSN   1072-5520. S2CID   24258819.
  15. 1 2 3 Schwarzhaupt, Robert; Liu, Feng; Wilson, Joseph; Lee, Fanny; Rasberry, Melissa (2021-10-08). "Teachers' Engagement and Self-Efficacy in a PK–12 Computer Science Teacher Virtual Community of Practice". Journal of Computer Science Integration. 4 (1): 1. doi: 10.26716/jcsi.2021.10.8.34 . ISSN   2574-108X. S2CID   240864514.
  16. 1 2 Kelley, Todd R.; Knowles, J. Geoffery; Holland, Jeffrey D.; Han, Jung (2020-04-16). "Increasing high school teachers self-efficacy for integrated STEM instruction through a collaborative community of practice". International Journal of STEM Education. 7 (1): 14. doi: 10.1186/s40594-020-00211-w . ISSN   2196-7822. S2CID   216034569.
  17. Yadav, Aman; Gretter, Sarah; Hambrusch, Susanne; Sands, Phil (2016-12-08). "Expanding computer science education in schools: understanding teacher experiences and challenges". Computer Science Education. 26 (4): 235–254. Bibcode:2016CSEd...26..235Y. doi:10.1080/08993408.2016.1257418. ISSN   0899-3408. S2CID   33792019.
  18. "2021 State of computer science education: Accelerating action through advocacy" (PDF). Code.org, CSTA, & ECEP Alliance. 2021.
  19. Snider, Johan; Bokstrom, Erik; Davidsson, Kasper; Eckerdal, Anna; Kastberg, Robin (2022-10-08). "Block and Text Programming in Swedish High School: What do students know on their first dayƒ". 2022 IEEE Frontiers in Education Conference (FIE). Uppsala, Sweden: IEEE. pp. 1–5. doi:10.1109/FIE56618.2022.9962696. ISBN   978-1-6654-6244-0. S2CID   254101531.
  20. Cooper, Steve; Grover, Shuchi; Guzdial, Mark; Simon, Beth (2014). "A future for computing education research". Communications of the ACM. 57 (11): 34–36. doi:10.1145/2668899. ISSN   0001-0782. S2CID   34034556.
  21. Morrison, Briana; Settle, Amber (2018). "Celebrating SIGCSE's 50th anniversary!". ACM SIGCSE Bulletin. 50 (1): 2–3. doi:10.1145/3183559.3183560. ISSN   0097-8418. S2CID   19169248.
  22. "The Mixed News on Diversity and the Enrollment Surge". CRA. 2017-02-10. Retrieved 2020-05-05.
  23. 2018 Taulbee Survey, Computing Research Association. https://cra.org/wp-content/uploads/2019/05/2018_Taulbee_Survey.pdf
  24. 1 2 Happe, Lucia; Buhnova, Barbora; Koziolek, Anne; Wagner, Ingo (2021-05-01). "Effective measures to foster girls' interest in secondary computer science education". Education and Information Technologies. 26 (3): 2811–2829. doi: 10.1007/s10639-020-10379-x . ISSN   1573-7608. S2CID   228817008.
  25. 1 2 Vitores, Anna; Gil-Juárez, Adriana (2016-11-01). "The trouble with 'women in computing': a critical examination of the deployment of research on the gender gap in computer science". Journal of Gender Studies. 25 (6): 666–680. doi:10.1080/09589236.2015.1087309. ISSN   0958-9236. S2CID   146570525.
  26. "what [sic!] gender is science" (PDF). Archived from the original (PDF) on September 24, 2015. Retrieved July 20, 2015.
  27. James, Justin (19 September 2023). "IT gender gap: Where are the female programmers?". TechRepublic.