Abstract
This chapter follows the development of Computing Education Research (CER) from how the CER community emerged from investigating teaching computer science (CS) as a tertiary education subject to becoming a research discipline of its own. Given the rapid growth of Computing as a discipline and the complexity of the research foci aligned with the educational transformation, it is clear that a single definition of CER is not possible. However, taking a historical perspective, including the development of a sense of scholarship, allows us to analyze the focus of CER over time. Furthermore, we will provide an environmental structure for CER that includes the components computing in general, learning and teaching computing, and educational research, to discuss the interaction and overlap between CER and the other aspects of the field of Computing. The concept of scholarship gives a common ground for valuing CER. To that end, we provide a short introduction to scholarship based on a framework developed by Glassick et al. (Scholarship assessed: evaluation of the professoriate. Jossey-Bass, San Francisco, 1997) as a basis for the CER community. Finally, we will reflect on the status of CER as a discipline. In this, we will use some criteria from Fensham (Defining an Identity: The Evolution of Science Education as a Field of Research. Springer Science & Business Media, 2004) for a discipline and provide our assessment of how well CER fulfills these criteria. We argue that CER has matured to be seen as a legitimate research discipline and conclude by relating CER to other examples of Discipline Based Education Research (DBER). The chapter lays the groundwork for some of the remaining chapters by presenting our perspective on influential contributions to the international dialogue concerning the content and structure of CER. The chapter also provides an overview of some attempts to define the field, including significant books about CER, panel sessions at major conferences, taxonomies, and structured literature reviews.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Center for Computing Education Research at the IT-University of Copenhagen. https://ccer.itu.dk/. Accessed: 2022-09-14
ACM/IEEE Taskforce: ACM curricula recommendations. https://www.acm.org/education/curricula-recommendations. Accessed: 2022-09-14
Aithal, P.S., Aithal, S.: Innovation in B.Tech. Curriculum as B.Tech. (Hons) by integrating STEAM, ESEP & IPR features. International Journal of Case Studies in Business, IT, and Education (2019). DOI https://doi.org/10.2139/ssrn.3406824. URL https://papers.ssrn.com/abstract=3406824
Ben-Ari, M., Berglund, A., Booth, S., Holmboe, C.: What Do We Mean by Theoretically Sound Research in Computer Science Education? In: Proceedings of the 9th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education, ITiCSE ’04, pp. 230–231. Association for Computing Machinery, New York, NY, USA (2004). URL https://doi.org/10.1145/1007996.1008059. Event-place: Leeds, United Kingdom
Brusilovsky, P., Edwards, S., Kumar, A., Malmi, L., Benotti, L., Buck, D., Ihantola, P., Prince, R., Sirkiä, T., Sosnovsky, S., et al.: Increasing adoption of smart learning content for computer science education. In: Proceedings of the Working Group Reports of the 2014 on Innovation & Technology in Computer Science Education Conference, pp. 31–57 (2014)
Carbone, A., de Raadt, M., Lister, R., Hamilton, M., Sheard, J.: Classifying computing education papers: process and results. In: Proceedings of the Fourth International Workshop on Computing Education Research, ICER, pp. 161–172 (2008)
Carter, A.S., Hundhausen, C.D., Adesope, O.: The normalized programming state model: predicting student performance in computing courses based on programming behavior. In: 11th International Computing Education Research Conference, ICER 2015, pp. 141–150 (2015). URL http://doi.acm.org/10.1145/2787622.2787710
Carter, A.S., Hundhausen, C.D., Adesope, O.: Blending measures of programming and social behavior into predictive models of student achievement in early computing courses. ACM Transactions on Computing Education (TOCE) 17(3), 12 (2017)
Dagiene, V., Stupuriene, G.: Informatics Concepts and Computational Thinking in K-12 Education: A Lithuanian Perspective. Journal of Information Processing 24(4), 732–739 (2016)
Dagienė Valentina, Jevsikova Tatjana, Stupurienė Gabrielė, Juškevičienė Anita: Teaching computational thinking in primary schools: Worldwide trends and teachers’ attitudes. Computer Science and Information Systems 19(1), 1–24 (2022).
Daniels, M., Pears, A.: Models and methods for computing education research. Australian Computer Science Communications 34(2), 95–102 (2012)
Daniels, M., Petre, M., Berglund, A.: Building a Rigorous Research Agenda into Changes to Teaching. In: Proceedings of Third Australasian Computer Science Education Conference ACE (1998)
Denning, P.J., Tedre, M.: Computational Thinking: A Disciplinary Perspective. Informatics in Education (2021). DOI https://doi.org/10.15388/infedu.2021.21. URL https://infedu.vu.lt/journal/INFEDU/article/701. Publisher: Vilnius University Institute of Data Science and Digital Technologies
Dorn, B., Elliott Tew, A.: Empirical validation and application of the computing attitudes survey. Computer Science Education 25(1), 1–36 (2015)
Fensham, P.J.: Defining an Identity: The Evolution of Science Education as a Field of Research. Springer Science & Business Media (2004)
Fincher, S., Petre, M.: Computer Science Education Research. Routledge Falmer (2004). URL http://www.cs.kent.ac.uk/pubs/2004/1819
Fincher, S.A., Robins, A.V.: The Cambridge handbook of computing education research. Cambridge University Press (2019)
Fincher, S., Tenenberg, J.: Using Theory to Inform Capacity-Building: Bootstrapping Communities of Practice in Computer Science Education Research. Journal of Engineering Education 95(4), 265–277 (2006). DOI https://doi.org/10.1002/j.2168-9830.2006.tb00902.x
Glassick, C.E., Huber, M.T., Maeroff, G.I., Boyer, E.L.: Scholarship assessed: evaluation of the professoriate. Jossey-Bass, San Francisco (1997)
Goldweber, M., Clark, M., Fincher, S., Pears, A.: The relationship between CS education research and the SIGCSE community. In: ITiCSE ’04: Proceedings of the 9th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education, pp. 228–229. ACM Press, Leeds, United Kingdom (2004). DOI http://doi.acm.org/10.1145/1007996.1008057
Goldweber, M., Clark, M., Fincher, S., Pears, A.: The Relationship between CS Education Research and the SIGCSE Community. In: Proceedings of the 9th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education, ITiCSE ’04, pp. 228–229. Association for Computing Machinery, New York, NY, USA (2004). URL https://doi.org/10.1145/1007996.1008057. Event-place: Leeds, United Kingdom
Grover, S., Korhonen, A.: Unlocking the potential of learning analytics in computing education. ACM Transactions on Computing Education (TOCE) 17(3), 1–4 (2017)
Grover, S., Fisler, K., Lee, I., Yadav, A.: Integrating Computing and Computational Thinking into K-12 STEM Learning. In: Proceedings of the 51st ACM Technical Symposium on Computer Science Education, pp. 481–482. Association for Computing Machinery, New York, NY, USA (2020). URL https://doi.org/10.1145/3328778.3366970
Gulliksen, J., Cajander, Å., Pears, A., Wiggberg, M.: Digital spetskompetens – den nya renässansmänniskan: Genomlysning, definition, prognosverktyg och rekommendationer för framtida utveckling. ISBN: 978-91-88961-58-7. Tillväxtverket (2020). Publication Title: https://digitalspetskompetens.se/wp-content/uploads/2020/06/DigitalSpetskompetens_Definition_Gulliksenetal.pdf
Hellas, A., Ihantola, P., Petersen, A., Ajanovski, V.V., Gutica, M., Hynninen, T., Knutas, A., Leinonen, J., Messom, C., Liao, S.N.: Predicting academic performance: a systematic literature review. In: Proceedings companion of the 23rd annual ACM conference on innovation and technology in computer science education, pp. 175–199 (2018)
Kirschner, P.A.: Do we need teachers as designers of technology enhanced learning? Instructional Science 43(2), 309–322 (2015). URL https://doi.org/10.1007/s11251-015-9346-9
Lishinski, A., Good, J., Sands, P., Yadav, A.: Methodological rigor and theoretical foundations of CS education research. In: Proceedings of the 2016 ACM conference on international computing education research, pp. 161–169 (2016)
Lister, R.: After the gold rush: Toward sustainable scholarship in computing (keynote address). In: Tenth Australasian Computing Education Conference, ACE 2008, pp. 3–17 (2008)
Lister, R., Adams, E.S., Fitzgerald, S., Fone, W., Hamer, J., Lindholm, M., McCartney, R., Moström, J.E., Sanders, K., Seppälä, O., Simon, B., Thomas, L.: A multi-national study of reading and tracing skills in novice programmers. In: ITiCSE-WGR ’04: Working group reports from ITiCSE on Innovation and technology in computer science education, pp. 119–150. ACM, Leeds, United Kingdom (2004). DOI http://doi.acm.org/10.1145/1044550.1041673
Luxton-Reilly, A., Albluwi, I., Becker, B.A., Giannakos, M., Kumar, A.N., Ott, L., Paterson, J., Scott, M.J., Sheard, J., Szabo, C.: Introductory programming: a systematic literature review. In: Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education, pp. 55–106 (2018)
Malmi, L., Sheard, J., Bednarik, R., Helminen, J., Korhonen, A., Myller, N., Sorva, J., Taherkhani, A.: Characterizing research in computing education: a preliminary analysis of the literature. In: Proceedings of the Sixth international workshop on Computing education research, pp. 3–12 (2010)
Malmi, L., Sheard, J., Simon, Bednarik, R., Helminen, J., Kinnunen, P., Korhonen, A., Myller, N., Sorva, J., Taherkhani, A.: Theoretical underpinnings of computing education research: what is the evidence? In: Tenth International Computing Education Research Conference, ICER 2014, pp. 27–34 (2014)
Malmi, L., Sheard, J., Kinnunen, P., Simon, Sinclair, J.: Computing education theories: what are they and how are they used? In: 15th International Computing Education Research Conference, ICER 2019, pp. 187–197 (2019)
Malmi, L., Sheard, J., Kinnunen, P., Simon, Sinclair, J.: Theories and models of emotions, attitudes, and self-efficacy in the context of programming education. In: 16th International Computing Education Research Conference, ICER 2020, p. 36–47 (2020)
Malmi, L., Sheard, J., Kinnunen, P., Sinclair, J.: Development and use of domain-specific learning theories, models and instruments in computing education. ACM Transactions on Computing Education (TOCE) (2022)
Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., Settle, A.: Computational Thinking in K-9 Education. In: Proceedings of the Working Group Reports of the 2014 on Innovation & Technology in Computer Science Education Conference, ITiCSE-WGR ’14, pp. 1–29. ACM, Uppsala, Sweden (2014). URL http://doi.acm.org/10.1145/2713609.2713610
Mannila, L., Nordén, L.å., Pears, A.: Digital Competence, Teacher Self-Efficacy and Training Needs. In: Proceedings of the 2018 ACM Conference on International Computing Education Research, pp. 78–85. ACM (2018). DOI https://doi.org/10.1145/3230977.3230993
Margulieux, L., Ketenci, T.A., Decker, A.: Review of measurements used in computing education research and suggestions for increasing standardization. Computer Science Education 29(1), 49–78 (2019)
Martín-Ramos, P., Lopes, M.J., Lima da Silva, M.M., Gomes, P.E.B., Pereira da Silva, P.S., Domingues, J.P.P., Ramos Silva, M.: First exposure to Arduino through peer-coaching: Impact on students’ attitudes towards programming. Computers in Human Behavior 76, 51–58 (2017). DOI https://doi.org/10.1016/j.chb.2017.07.007. URL https://www.sciencedirect.com/science/article/pii/S0747563217304193
McCracken, M., Almstrum, V., Diaz, D., Guzdial, M., Hagan, D., Kolikant, Y.B.D., Laxer, C., Thomas, L., Utting, I., Wilusz, T.: A multi-national, multi-institutional study of assessment of programming skills of first-year CS students. SIGCSE Bulletin 33(4), 125–180 (2001). DOI http://doi.acm.org/10.1145/572139.572181
McGill, M.M., Decker, A.: A gap analysis of statistical data reporting in K-12 computing education research: recommendations for improvement. In: Proceedings of 51st SIGCSE Technical Symposium on Computer Science Education, pp. 591–597 (2020)
Morrison, B.B., Dorn, B., Guzdial, M.: Measuring cognitive load in introductory cs: adaptation of an instrument. In: Proceedings of the tenth annual conference on International computing education research, pp. 131–138 (2014)
Munasinghe, B., Bell, T., Robins, A.: Teachers’ understanding of technical terms in a Computational Thinking curriculum. In: Australasian Computing Education Conference, ACE ’21, pp. 106–114. Association for Computing Machinery, New York, NY, USA (2021). URL https://doi.org/10.1145/3441636.3442311
Nelson, G.L., Ko, A.J.: On use of theory in computing education research. In: Proceedings of the 2018 ACM Conference on International Computing Education Research, pp. 31–39 (2018)
Niemelä, P., Pears, A., Dagienė, V., Laanpere, M.: Computational Thinking – Forces Shaping Curriculum and Policy in Finland, Sweden and the Baltic Countries. In: D. Passey, D. Leahy, L. Williams, J. Holvikivi, M. Ruohonen (eds.) Digital Transformation of Education and Learning - Past, Present and Future, IFIP Advances in Information and Communication Technology, pp. 131–143. Springer International Publishing, Cham (2022). DOI https://doi.org/10.1007/978-3-030-97986-7_11
Papert, S.: Mindstorms: Computers, children, and powerful ideas. NY: Basic Books (1980)
Pears, A., Daniels, M.: Developing Global Teamwork Skills: The Runestone Project. In: M. Castro, E. Tovar, M.E. Auer (eds.) IEEE EDUCON 2010 – The Future of Global Learning in Engineering Education (2010)
Pears, A., Daniels, M., Berglund: Describing Computer Science Education Research: An Academic Process View. In: Conference on Simulation and Multimedia in Engineering Education, ICSEE’2002, San Antonio, Texas, pp. 99–104. Society for Computer Simulation International (2002). URL PearICSEE2002.pdf
Pears, A., Seidman, S., Eney, C., Kinnunen, P., Malmi, L.: Constructing a Core Literature for Computing Education Research. ACM SIGCSE Bulletin 37(4), 152–161 (2005). DOI https://doi.org/10.1145/1113847.1113893
Pears, A., Dagiene, V., Jasute, E.: Baltic and Nordic K-12 Teacher Perspectives on Computational Thinking and Computing. In: V. Dagien∖.e, A. Hellas (eds.) Informatics in Schools: Focus on Learning Programming: 10th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2017, Helsinki, Finland, November 13–15, 2017, Proceedings, pp. 141–152. Springer International Publishing, Cham (2017). URL https://doi.org/10.1007/978-3-319-71483-7_12
Pears, A., Tedre, M., Valtonen, T., Vartiainen, H.: What Makes Computational Thinking so Troublesome? In: 2021 IEEE Frontiers in Education Conference (FIE), pp. 1–7 (2021). DOI https://doi.org/10.1109/FIE49875.2021.9637416. ISSN: 2377-634X
Petre, M., Fincher, S.: Bootstrapping Research in Computer Science Education. In: Tacoma and Port Townsend, Washington, USA (2002). URL http://depts.washington.edu/bootstrp/
Petre, M., Sanders, K., McCartney, R., Ahmadzadeh, M., Connolly, C., Hamouda, S., Harrington, B., Lumbroso, J., Maguire, J., Malmi, L., et al.: Mapping the landscape of peer review in computing education research. In: Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education, pp. 173–209. ACM (2020)
Porter, L., Zingaro, D., Liao, S.N., Taylor, C., Webb, K.C., Lee, C., Clancy, M.: BDSI: A validated concept inventory for basic data structures. In: Proceedings of the 2019 ACM Conference on International Computing Education Research, pp. 111–119 (2019)
Randolph, J.J., Julnes, G., Sutinen, E., Lehman, S.: A methodological review of computer science education research. Journal of Information Technology Education: Research 7(1), 135–162 (2008)
Robins, A.V.: Novice programmers and introductory programming. In: S. Fincher, A. Robins (eds.) The Cambridge handbook of computing education research, pp. 327–377. Cambridge University Press (2019)
Scheer, A., Noweski, C., Meinel, C.: Transforming Constructivist Learning into Action: Design Thinking in education. Design and Technology Education: an International Journal 17(3) (2012). URL https://ojs.lboro.ac.uk/DATE/article/view/1758
Simon: A Classification of Recent Australasian Computing Education Publications. Computer Science Education 17(3), 155 – 169 (2007). URL http://www.informaworld.com/10.1080/08993400701538021
Simon: Emergence of computing education as a research discipline. Ph.D. thesis, Aalto Univerity, Finland (2015)
Simon, Carbone, A., Raadt, M.d., Lister, R., Hamilton, M., Sheard, J.: Classifying Computing Education Papers: Process and Results. In: R. Lister, M. Caspersen, M. Clancy (eds.) Fourth International Computing Education Research Workshop (ICER 2008). ACM Press, Sydney, Australia (2008)
Singer, S.R., Nielsen, N.R., Schweingruber, H.A.: Discipline-Based Education Research: Understanding and Improving Learning in Undergraduate Science and Engineering. National Academies Press (2012)
Solomon, C., Harvey, B., Kahn, K., Lieberman, H., Miller, M.L., Minsky, M., Papert, A., Silverman, B.: History of Logo. Proceedings of the ACM on Programming Languages 4(HOPL), 1–66 (2020)
Soloway, E., Ehrlich, K.: Empirical studies of programming knowledge. IEEE Transactions on software engineering SE-10(5), 595–609 (1984)
Szabo, C., Sheard, J.: Learning theories use and relationships in computing education research. ACM Transactions on Computing Education (TOCE) p. in press (2022)
Szabo, C., Falkner, N., Petersen, A., Bort, H., Cunningham, K., Donaldson, P., Hellas, A., Robinson, J., Sheard, J.: Review and use of learning theories within computer science education research: primer for researchers and practitioners. In: ITiCSE 2019 Working Group Reports, ITiCSE WGR 2019, pp. 89–109. Association for Computing Machinery (2019)
Tedre, M., Toivonen, T., Kahila, J., Vartiainen, H., Valtonen, T., Jormanainen, I., Pears, A.: Teaching Machine Learning in K–12 Classroom: Pedagogical and Technological Trajectories for Artificial Intelligence Education. IEEE Access 9, 110558–110572 (2021). DOI https://doi.org/10.1109/ACCESS.2021.3097962. Conference Name: IEEE Access
Tenenberg, J., Malmi, L.: Conceptualizing and using theory in computing education research. ACM Transactions on Computing Education (2022)
Utting, I., Tew, A.E., McCracken, M., Thomas, L., Bouvier, D., Frye, R., Paterson, J., Caspersen, M., Kolikant, Y.B.D., Sorva, J., et al.: A fresh look at novice programmers’ performance and their teachers’ expectations. In: Proceedings of the ITiCSE working group reports conference on Innovation and technology in computer science education-working group reports, pp. 15–32 (2013)
Valentine, D.W.: CS educational research: a meta-analysis of SIGCSE technical symposium proceedings. In: SIGCSE ’04: Proceedings of the 35th SIGCSE Technical Symposium on Computer Science Education, pp. 255–259. ACM Press, Norfolk, Virginia, USA (2004). DOI http://doi.acm.org/10.1145/971300.971391
Wahyuningsih, S., Nurjanah, N.E., Rasmani, U.E.E., Hafidah, R., Pudyaningtyas, A.R., Syamsuddin, M.M.: STEAM Learning in Early Childhood Education: A Literature Review. International Journal of Pedagogy and Teacher Education 4(1), 33–44 (2020). DOI https://doi.org/10.20961/ijpte.v4i1.39855.
Weinberg, G.M.: The psychology of computer programming, vol. 29. Van Nostrand Reinhold New York (1971)
Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., Wilensky, U.: Defining Computational Thinking for Mathematics and Science Classrooms. Journal of Science Education and Technology (2016). DOI https://doi.org/10.1007/s10956-015-9581-5
Wiggberg, M., Gulliksen, J., Cajander, å., Pears, A.: Defining Digital Excellence: Requisite Skills and Policy Implications for Digital Transformation. IEEE Access 10, 52481–52507 (2022). DOI 10.1109/ACCESS.2022.3171924. Conference Name: IEEE Access
Wing, J.M.: Computational thinking. Communications of the ACM 49(3), 33–35 (2006)
Xie, B., Loksa, D., Nelson, G.L., Davidson, M.J., Dong, D., Kwik, H., Tan, A.H., Hwa, L., Li, M., Ko, A.J.: A theory of instruction for introductory programming skills. Computer Science Education 29(2–3), 205–253 (2019)
Yang, K., Liu, X., Chen, G.: The influence of robots on students’ computational thinking: A literature review. International Journal of Information and Education Technology 10(8), 5 (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Daniels, M., Malmi, L., Pears, A., Simon (2023). What is Computing Education Research (CER)?. In: Apiola, M., López-Pernas, S., Saqr, M. (eds) Past, Present and Future of Computing Education Research . Springer, Cham. https://doi.org/10.1007/978-3-031-25336-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-031-25336-2_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-25335-5
Online ISBN: 978-3-031-25336-2
eBook Packages: Computer ScienceComputer Science (R0)