Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-848d4c4894-2xdlg Total loading time: 0 Render date: 2024-06-22T09:26:06.609Z Has data issue: false hasContentIssue false

18 - Schools (K–12)

from New Milieux

Published online by Cambridge University Press:  15 February 2019

By
Jan Vahrenhold ,
Quintin Cutts  and
Katrina Falkner
Edited by
Sally A. Fincher  and
Anthony V. Robins
Sally A. Fincher
Affiliation:
University of Kent, Canterbury
Anthony V. Robins
Affiliation:
University of Otago, New Zealand
Get access

Summary

In recent years, there has been a growing focus on computer science at the K-12 level, both from an educational and research perspective. This chapter briefly surveys some of these developments and describes areas where research in K-12 classrooms is being conducted. Our survey shows that the majority of empirical research in K-12 classrooms is focused on introductory programming, computational thinking, and attitudes towards the discipline but that a surprisingly large variety of other topics, ranging from software engineering to professional ethics has been taught and researched as well. In the light of recent initiatives directed towards implementing computer science as a regular or even mandatory subject in secondary schools, we summarize curricular designs that have been implemented and evaluated in K-12 classrooms. We discuss the importance of recognising the significant differences between national education systems when attempting transfer and revalidation studies.
Type
Chapter
Information
The Cambridge Handbook of Computing Education Research , pp. 547 - 583
Publisher: Cambridge University Press
Print publication year: 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aggarwal, A., Touretzky, D. S., & Gardner-McCune, C. (2018). Demonstrating the ability of elementary school students to reason about programs. Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE 2018) (pp. 735–740). New York: ACM Press.Google Scholar
Al Sabbagh, A., Gedawy, H., Alshikhabobakr, H., & Razak, S. (2017). Computing curriculum in middle schools: An experience report. Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘17) (pp. 230–235). New York: ACM Press.Google Scholar
Alexandron, G., Armoni, M., Gordon, M., & Harel, D. (2013). On teaching programming with nondeterminism. Proceedings of the 8th Workshop in Primary and Secondary Computing Education (WiPSCE 2013) (pp. 71–74). New York: ACM Press.Google Scholar
Araujo, L. G. J., Bittencourt, R. A., & Santos, D. M. B. (2018). An analysis of a media-based approach to teach programming to middle school students. Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE 2018) (pp. 1005–1010). New York: ACM Press.Google Scholar
Armoni, M., Meerbaum-Salant, O., & Ben-Ari, M. (2015). From Scratch to “real” programming. ACM Transactions on Computing Education (TOCE), 14(4), 25.1–25.15.Google Scholar
Australian Curriculum, Assessment and Reporting Authority (ACARA) (2015). Australian Curriculum: Digital Technologies. Retrieved from www.australiancurriculum.edu.auGoogle Scholar
Basawapatna, A. R., Koh, K. H., & Repenning, A. (2010). Using scalable game design to teach computer science from middle school to graduate school. Proceedings of the Fifteenth Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘10) (pp. 224–228). New York: ACM Press.Google Scholar
Bell, T., Andreae, P., & Robins, A. (2014). A case study of the introduction of computer science in NZ schools. ACM Transactions on Computing Education (TOCE), 14(2), 10.1–10.31.Google Scholar
Bell, T., Newton, H., Andreae, P., & Robins, A. (2012a). The introduction of computer science to NZ high schools – An analysis of student work. Proceedings of the 7th Workshop in Primary and Secondary Computing Education (WiPSCE 2012) (pp. 5–15). New York: ACM Press.CrossRefGoogle Scholar
Bell, T., Rosamond, F., & Casey, N. (2012b) Computer science unplugged and related projects in math and computer science popularization. In Bodlaender, H. L., Downey, R., Fomin, F. V., & Marx, D. (Eds.), The Multivariate Algorithmic Revolution and Beyond. Lecture Notes in Computer Science 7370 (pp. 398–456). Berlin, Germany: Springer.Google Scholar
Benacka, J., & Reichel, J. (2013). Computer modeling with Delphi – Constructionism and IBL in practice and motivation for studying STEM. In Proceedings of the 6th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (ISSEP 2013), Lecture Notes in Computer Science 7780 (pp. 136–46). Berlin, Germany: Springer.Google Scholar
Ben-Bassat Levry, R., & Ben-Ari, M. (2015). Robotics – Is the investment worthwhile? In Proceedings of the 8th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (ISSEP 2015), Lecture Notes in Computer Science 9378 (pp. 22–31). Berlin, Germany: Springer.Google Scholar
Ben-David Kolikant, Y. (2001). Gardeners and cinema tickets: High school students’ preconceptions of concurrency. Computer Science Education, 11(3), 221–245.Google Scholar
Ben-David Kolikant, Y., & Pollack, S. (2004). Establishing computer science professional norms among high-school students. Computer Science Education, 14(1), 21–35.Google Scholar
Benner, A. D., Boyle, A. E., & Sadler, S. (2016). Parental involvement and adolescent’s educational success: The roles of prior achievement and socioeconomic status. Journal of Youth and Adolescence, 45(6), 1053–1064.CrossRefGoogle ScholarPubMed
Benotti, L., Martínez, M. C., & Schapachnik, F. (2014). Engaging high school students using chatbots. In Proceedings of the 2014 Conference on Innovation & Technology in Computer Science Education (ITiCSE ‘14) (pp. 63–68). New York: ACM Press.Google Scholar
Bischof, E., & Sabitzer, B. (2011). Computer science in primary schools – Not possible, but necessary?! In Proceedings of the 5th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (ISSEP 2011), Lecture Notes in Computer Science 7013 (pp. 95–105). Berlin, Germany: Springer.Google Scholar
Brackmann, C. P., Román-González, M., Robles, G., Moreno-León, J., Casali, , , A., & Barone, D. (2017). Development of computational thinking skills through unplugged activities in primary school. In Proceedings of the 12th Workshop in Primary and Secondary Computing Education (WiPSCE 2017) (pp. 65–72). New York: ACM Press.Google Scholar
Brinda, T., Puhlmann, H., & Schulte, C. (2009). Bridging ICT and CS: Educational standards for computer science in lower secondary education. In Proceedings of the 14th Annual ACM SIGCSE Conference on Innovation and Technology in Computer Science Education (ITiCSE 2009) (pp. 289–292). New York: ACM Press.Google Scholar
Brinda, T., & Terjung, Th. (2017). A database is like a dresser with lots of sorted drawers: Secondary school learners’ conceptions of relational databases. In Proceedings of the 12th Workshop in Primary and Secondary Computing Education (WiPSCE 2017) (pp. 39–48). New York: ACM Press.CrossRefGoogle Scholar
Brinkmeier, M., & Kalbreyer, D. (2016). A case study of physical computing in computer science education. In Proceedings of the 11th Workshop in Primary and Secondary Computing Education (WiPSCE 2016) (pp. 54–59). New York: ACM Press.CrossRefGoogle Scholar
Brown, N. C. C., Sentance, S., Crick, T., & Humphreys, S. (2014). Restart: The resurgence of computer science in UK schools. ACM Transactions on Computing Education (TOCE), 14(2), 9.1–9.22.Google Scholar
Bruner, J. (1960). The Process of Education. Cambridge, MA: Harvard University Press.Google Scholar
Buffum, P. S., Frankorsky, M. H., Boyer, K. E., Wiebe, E. N., Mott, B. W., & Lester, J. C. (2016). Empowering all Sstudents: Closing the CS confidence gap with an in-school initiative for middle school students. In Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE 2016) (pp. 382–387). New York: ACM Press.Google Scholar
Burke, Q., & Kafai, Y. (2012). The writers’ workshop for youth programmers: Digital storytelling with scratch in middle school classrooms. In Proceedings of the 43rd ACM Technical Symposium on Computer Science Education (SIGCSE 2012) (pp. 433–438). New York: ACM Press.Google Scholar
Carruthers, S., Milford, T., Pelton, T., & Stege, U. (2011). Draw a social network. In Proceedings of the 16th Annual Joint Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘11) (pp. 178–182). New York: ACM Press.Google Scholar
Carter, E., Blank, G., & Walz, J. (2012). Bringing the breadth of computer science to middle schools. In Proceedings of the 43rd ACM Technical Symposium on Computer Science Education (SIGCSE 2012) (pp. 203–208). New York: ACM Press.Google Scholar
Castro, B., Diaz, T., Gee, M., Justice, R., Kwan, D., Seshadri, P., & Dodds, Z. (2016). MyCS at 5: Assessing a middle-years CS curriculum. In Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE 2016) (pp. 558–563). New York: ACM Press.Google Scholar
Cateté, V., Snider, , , E., & Barnes, T. (2016). Developing a rubric for a creative CS principles lab. In Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE 2016) (pp. 290–295). New York: ACM Press.Google Scholar
Catrambone, R. (1998). The subgoal learning model: Creating better examples so that students can solve novel problems. Journal of Experimental Psychology: General, 127(4), 355–376.Google Scholar
Cheong, Y. F., Pajares, F., & Oberman, P. S. (2004). Motivation and academic help-seeking in high school computer science. Computer Science Education, 14(1), 3–19.Google Scholar
Chiprianov, V., & Gallon, L. (2016). Introducing computational thinking to K–5 in a French context. In Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE 2016) (pp. 112–117). New York: ACM Press.Google Scholar
Chun, S. Y., & Ryoo, J. (2010). Development and application of a web-based programming learning system with LED display kits. In Proceedings of the 41st ACM Technical Symposium on Computer Science Education (SIGCSE 2010) (pp. 310–314). New York: ACM Press.Google Scholar
Corradini, I., Lodi, M., & Nardelli, E. (2017). Computational thinking in Italian schools: Quantitative data and teachers’ sentiment analysis after two years of “Programma il Futuro”. In Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘17) (pp. 224–229). New York: ACM Press.Google Scholar
Cutts, Q., Connor, R., Donaldson, P., & Michaelson, G. (2014). Code or (not code) – Separating formal and natural language in CS education. In Proceedings of the 9th Workshop in Primary and Secondary Computing Education (WiPSCE 2014) (pp. 20–28). New York: ACM Press.Google Scholar
Deitrick, E., Wilkerson, M., & Simoneau, E. (2017). Understanding student collaboration in interdisciplinary computing activities. In Proceedings of the 2017 ACM Conference on International Computing Education Research (ICER 2017) (pp. 118–126). New York: ACM Press.Google Scholar
DeLyser, L. A. (2014). Software engineering students in the city. In Proceedings of the 9th Workshop in Primary and Secondary Computing Education (WiPSCE 2014) (pp. 37–42). New York: ACM Press.Google Scholar
Duncan, C., & Bell, T. (2015). A pilot computer science and programming course for primary school students. In Proceedings of the 10th Workshop in Primary and Secondary Computing Education (WiPSCE 2015) (pp. 39–48). New York: ACM Press.Google Scholar
Dwyer, H. A., Hill, C., Hansen, A., Iveland, A., Franklin, D., & Harlow, D. (2015). Fourth grade students reading block-based programs: Predictions, visual cues, and affordances. In Proceedings of the Eleventh International Computing Education Research Conference (ICER 2015) (pp. 111–119). New York: ACM Press.Google Scholar
Dwyer, H. A., Hill, C., Carpenter, S., Harlow, D., & Franklin, D. (2014). Identifying elementary students’ pre-instructional ability to develop algorithms and step-by-step instructions. In Proceedings of the 45th ACM Technical Symposium on Computer Science Education (SIGCSE 2014) (pp. 511–516). New York: ACM Press.Google Scholar
Eglash, R., Krishnamoorthy, M., Sanchez, J., & Woodbridge, A. (2011). Fractal simulations of African design in pre-college computing education. ACM Transactions on Computing Education (TOCE), 11(3), 17.1–17.14.Google Scholar
Epstein, R. G., Aiken, R. M., Snelbecker, G., & Potosky, J. (1987). Retraining high school teachers to teach computer science – Observations on the first course. In Proceedings of the 18th SIGCSE Technical Symposium on Computer Science Education (SIGCSE 1987) (pp. 136–140). New York: ACM Press.Google Scholar
Esterhues, J. (Ed.) (1984) Johann Friedrich Herbart. Band I. Umriß pädagogischer Vorlesungen. Paderborn, Germany: Schöningh. In German.Google Scholar
Falkner, K., Vivian, R., & Falkner, N. (2014). The Australian digital technologies curriculum: Challenge and opportunity. In Proceedings of the Australasian Computing Education Conference (ACE 2014) (pp. 3–12). Sydney, Australia: Australian Computer Society.Google Scholar
Feaster, Y., Ali, F., Zhai, J., & Hallstrom, J. O. (2014). Serious toys: Three years of teaching computer science concepts in K–12 classrooms. In Proceedings of the 2014 Conference on Innovation & Technology in Computer Science Education (ITiCSE ‘14) (pp. 69–74). New York: ACM Press.Google Scholar
Feaster, Y., Segars, L., Wahba, S. K., & Hallstrom, J. O. (2011). Teaching CS Unplugged in the high school (with limited success). In Proceedings of the 16th Annual Joint Conference on Innovation and Technology in Computer Science Education (ITiCSE 2011) (pp. 248–252). New York: ACM Press.Google Scholar
Felleisen, M., Findler, R. B., Flatt, M., & Krishnamurthi, S. (2000). How to Design Programs: An Introduction to Programming and Computing. Cambridge, MA: MIT Press.Google Scholar
Felleisen, M., Findler, R. B., Flatt, M., & Krishnamurthi, S. (2004). The TeachScheme! Project: Computing and programming for every student. Computer Science Education, 14(1), 55–77.Google Scholar
Fraillon, J., Ainley, J., Schulz, W., Friedman, T., & Gebhardt, E. (2014). Preparing for Life in a Digital Age: The IEA International Computer and Information Literacy Study International Report. Cham, Switzerland: Springer.Google Scholar
Franklin, D., Hill, C., Dwyer, H. A., Hansen, A. K., Iveland, A., & Harlow, D. B. (2016). Initialization in Scratch: Seeking Knowledge transfer. In Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE 2016) (pp. 217–222). New York: ACM Press.Google Scholar
Franklin, D., Skifstad, G., Rolock, R., Mehrotra, I., Ding, V., Hansen, A., Weintrop, D., & Harlow, D. (2017). Using upper-elementary student performance to understand conceptual sequencing in a blocks-based curriculum. In Proceedings of the 48th ACM Technical Symposium on Computer Science Education (SIGCSE 2017) (pp. 231–236). New York: ACM Press.Google Scholar
Fronza, I., El Ioini, N., & Corral, L. (2017). Teaching computational thinking using agile software engineering methods: A framework for middle schools. ACM Transactions on Computing Education (TOCE), 17(4), 19.1–19.28.Google Scholar
Frost, D. (2007). Fourth grade computer science. In Proceedings of the 38th ACM Technical Symposium on Computer Science Education (SIGCSE 2007) (pp. 302–306). New York: ACM Press.Google Scholar
Funke, A., & Geldreich, K. (2017). Gender differences in Scratch programs of primary school children. In Proceedings of the 12th Workshop in Primary and Secondary Computing Education (WiPSCE 2017) (pp. 57–64). New York: ACM Press.Google Scholar
Gal-Ezer, J., & Stephenson, C. (2014). A tale of two countries: Successes and challenges in K–12 computer science education in Israel and the United States. ACM Transactions on Computing Education (TOCE), 14(2), 8.1–8.18.Google Scholar
Gander, W., Petit, A., Berry, G., Demo, B., Vahrenhold, J., McGettrick, A., Boyle, R., Drechsler, M., Stephenson, C., Ghezzi, C., & Meyer, B. (2013). Informatics Education: Europe Cannot Afford to Miss the Boat. Informatics Europe & Association for Computing Machinery. Retrieved from www.informatics-europe.org/images/documents/informatics-education-acm-ie.pdfGoogle Scholar
Gärtig-Daugs, A., Weitz, , Wolking, K., , M., & Schmid, U. (2016). Computer science experimenter’s kit for use in preschool and primary school. In Proceedings of the 11th Workshop in Primary and Secondary Computing Education (WiPSCE 2016) (pp. 66–71). New York: ACM Press.Google Scholar
Giannakos, M. N., Hubwieser, P., & Ruf, A. (2012). Is self-efficacy in programming decreasing with the level of programming skills? In Proceedings of the 7th Workshop in Primary and Secondary Computing Education (WiPSCE 2012) (pp. 16–21). New York: ACM Press.Google Scholar
Gibson, J. P. (2012). Teaching graph algorithms to children of all ages. In Proceedings of the 17th ACM Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘12) (pp. 34–39). New York: ACM Press.Google Scholar
Ginat, D., & Alankry, R. (2012). Pseudo abstract composition: The case of language concatenation. In Proceedings of the 17th ACM Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘12) (pp. 28–33). New York: ACM Press.Google Scholar
Ginat, D., Menashe, E., & Taya, A. (2013). Novice difficulties with interleaved pattern composition. In Proceedings of the 6th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (ISSEP 2013), Lecture Notes in Computer Science 7780 (pp. 56–67). Berlin, Germany: Springer.Google Scholar
Goode, J., Chapman, G., & Margolis, J. (2012). Beyond curriculum: The Exploring Computer Science Program. ACM Inroads, 3(2), 47–53.CrossRefGoogle Scholar
Gordon, M., Marron, A., & Meerbaum-Salant, O. (2012) Spaghetti for the main course?: Observations on the naturalness of scenario-based programming. In Proceedings of the 17th ACM Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘12) (pp. 198–203). New York: ACM Press.Google Scholar
Grover, S., & Basu, S. (2017). Measuring student learning in introductory block-based programming: Examining misconceptions of loops, variables, and boolean logic. In Proceedings of the 48th ACM Technical Symposium on Computer Science Education (SIGCSE 2017) (pp. 267–272). New York: ACM Press.Google Scholar
Grover, S., Basu, S., & Schank, P. (2018) What we can learn about student learning from open-ended programming projects in middle school computer science. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE 2018) (pp. 999–1004). New York: ACM Press.Google Scholar
Grover, S., Cooper, S., & Pea, R. (2014a). Assessing computational learning in K–12. In Proceedings of the 2014 Conference on Innovation & Technology in Computer Science Education (ITiCSE ‘14) (pp. 57–62). New York: ACM Press.Google Scholar
Grover, S., Pea, R., & Cooper, S. (2014b). Remedying misperceptions of computer science among middle school students. In Proceedings of the 45th ACM Technical Symposium on Computer Science Education (SIGCSE 2014) (pp. 343–348). New York: ACM Press.Google Scholar
Grover, S., Pea, R., & Cooper, S. (2015). Designing for deeper learning in a blended computer science course for middle school students. Computer Science Education, 25(2), 199–237.Google Scholar
Grover, S., Pea, R., & Cooper, S. (2016a). Factors influencing computer science learning in middle school. In Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE 2016) (pp. 552–557). New York: ACM Press.Google Scholar
Grover, S., Rutstein, D., & Snow, E. (2016b). “What is a computer”: What do secondary school students think? In Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE 2016) (pp. 564–569). New York: ACM Press.Google Scholar
Gujberova, M., & Kalas, I. (2013). Designing productive gradations of tasks in primary programming education. In Proceedings of the 8th Workshop in Primary and Secondary Computing Education (WiPSCE 2013) (pp. 108–117). New York: ACM Press.Google Scholar
Guzdial, M. (2003). A media computation course for non-majors. In Proceedings of the 8th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE 2003) (pp. 104–108). New York: ACM Press.Google Scholar
Haberman, B. (2004). How learning logic programming affects recursion comprehension. Computer Science Education, 14(1), 37–53.Google Scholar
Hansen, A. K., Hansen, E. R., Dwyer, H. A., Harlow, D. B., & Franklin, D. (2016). Differentiating for diversity: Using universal design for learning in elementary computer science education. In Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE 2016) (pp. 376–381). New York: ACM Press.Google Scholar
Hazzan, O. (1999). Reducing abstraction level when learning abstract algebra concepts. Education Studies in Mathematics, 44, 71–90.Google Scholar
Heimann, P. (1962). Didaktik als Theorie und Lehre. Die Deutsche Schule, 54(9), 407–427. In German.Google Scholar
Heiner, C. (2018). A robotics experience for all the students in an elementary school. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE 2018) (pp. 729–34). New York: ACM Press.Google Scholar
Heintz, F., Mannila, L., Nygårds, K., Parnes, , , P., & Regnell, B. (2015). Computing at school in Sweden – Experiences from introducing computer science within existing subjects. In Proceedings of the 8th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (ISSEP 2015), Lecture Notes in Computer Science 9378 (pp. 118–130). Berlin, Germany: Springer.Google Scholar
Hermans, F., & Aivaloglo, E. (2017). To Scratch or not to Scratch?: A controlled experiment comparing plugged first and unplugged first programming lessons. In Proceedings of the 12th Workshop in Primary and Secondary Computing Education (WiPSCE 2017) (pp. 49–56). New York: ACM Press.Google Scholar
Hildebrandt, C., & Diethelm, I. (2012). The school experiment InTech: How to influence interest, self-concept of ability in informatics and vocational orientation. In Proceedings of the 7th Workshop in Primary and Secondary Computing Education (WiPSCE 2012) (pp. 30–39). New York: ACM Press.CrossRefGoogle Scholar
Hubwieser, P. (2013). The Darmstadt Model: A first step towards a research framework for computer science education in schools. In Proceedings of the 6th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (ISSEP 2013), Lecture Notes in Computer Science 7780 (pp. 1–14). Berlin, Germany: Springer.Google Scholar
Hubwieser, P., Armoni, M., Brinda, T., Dagiene, V., Diethelm, I., Giannakos, M. N., Knobelsdorf, M., Magenheim, J., Mittermeir, R. T., & Schubert, S. (2011). Computer science/informatics in secondary schools. In ITICSE-WGR ‘11: Proceedings of the 16th Annual Conference Reports on Innovation and Technology in Computer Science Education – Working Group Reports (pp. 18–38). New York: ACM Press.Google Scholar
Hubwieser, P., Armoni, M., & Giannakos, M. N. (2015a). How to implement rigorous computer science education in K–12 schools? Some answers and many questions. ACM Transactions on Computing Education (TOCE), 15(2), 5.1–5.12.Google Scholar
Hubwieser, P., Armoni, M., Giannakos, M. N., & Mittermeir, R.T. (2014). Perspectives and visions of computer science education in primary and secondary (K–12) schools. ACM Transactions on Computing Education (TOCE), 14(2), 7.1–7.9.Google Scholar
Hubwieser, P., Giannakos, M. N., Berges, M., Brinda, T., Diethelm, I., Magenheim, J., Pal, Y., Jackova, J., & Jasute, E. (2015b). A global snapshot of computer science education in K–12 schools. In ITICSE-WGR ‘15: Proceedings of the 2015 ITiCSE Working Group Reports (pp. 65–83). New York: ACM Press.CrossRefGoogle Scholar
Hug, S., Guenther, R., & Wenk, M. (2013). Cultivating a K12 computer science community: A case study. In Proceedings of the 44th ACM Technical Symposium on Computer Science Education (SIGCSE 2013) (pp. 275–280). New York: ACM Press.Google Scholar
Ioannou, I., & Angeli, C. (2014). Examining the effects of an instructional intervention on destabilizing learners’ misconceptions about the central processing unit. In Proceedings of the 9th Workshop in Primary and Secondary Computing Education (WiPSCE 2014) (pp. 93–99). New York: ACM Press.Google Scholar
Isayama, D., Ishiyama, M., Relator, R., & Yamazaki, K. (2017). Computer science education for primary and lower secondary school students: Teaching the concept of automata. ACM Transactions on Computing Education (TOCE), 17(1), 2.1–2.28.Google Scholar
Israel, M., Wherfel, Q. M., Shehab, S., Melvin, O., & Lash, T. (2017). Describing elementary students’ interactions in K–5 puzzle-based computer science environments using the Collaborative Computing Observation Instrument (C-COI). InProceedings of the 2017 ACM Conference on International Computing Education Research (ICER 2017) (pp. 110–117). New York: ACM Press.Google Scholar
Joentausta, J., & Hellas, A. (2018). Subgoal labeled worked examples in K–3 education. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE 2018) (pp. 616–621). New York: ACM Press.Google Scholar
Kafai, Y. B., Lee, E., Searle, K., Fields, D., Kaplan, E., & Lui, D. (2014). A crafts-oriented approach to computing in high school: Introducing computational concepts, practices, and perspectives with electronic Textiles. ACM Transactions on Computing Education (TOCE), 14(1), 1.1–1.20.Google Scholar
Kaila, E., Lindén, R., Lokkila, , , E., & Laakso, M. (2017). About programming maturity in Finnish high schools: A comparison between high school and university students’ programming skills. In Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘17) (pp. 122–127). New York: ACM Press.Google Scholar
Kallia, M. (2017). Assessment in Computer Science Courses: A Literature Review. London, UK: The Royal Society.Google Scholar
Kastl, P., KIesmüller, U., & Romeike, R. (2016). Starting out with projects – Experiences with agile software development in high schools. In Proceedings of the 11th Workshop in Primary and Secondary Computing Education (WiPSCE 2016) (pp. 60–65). New York: ACM Press.Google Scholar
Kiesmüller, U. (2009). Diagnosing learners’ problem-solving strategies using learning environments with algorithmic problems in secondary education. ACM Transactions on Computing Education (TOCE), 9(3), 17.1–17.26.Google Scholar
King-Sears, P. (2014). Introduction to Learning Disability Quarterly special series on universal design for learning: Part one of two. Learning Disability Quarterly, 37(2), 68–70.Google Scholar
Knobelsdorf, M., Magenheim, J., Brinda, T., Engbring, D., Humbert, L., Pasternak, A., Schroeder, U., Thomas, M., & Vahrenhold, J. (2015). Computer science education in North-Rhine Westphalia, Germany – A case study. ACM Transactions on Computing Education (TOCE), 15(2), 9.1–9.22.Google Scholar
Kohn, T. (2017). Variable evaluation: An exploration of novice programmers’ understanding and common misconceptions. In Proceedings of the 48th ACM Technical Symposium on Computer Science Education (SIGCSE 2017) (pp. 345–350). New York: ACM Press.Google Scholar
Lamprou, A., Repenning, A., & Escherle, N. A. (2017). The Solothurn Project: Bringing computer science education to primary schools in Switzerland. In Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘17) (pp. 218–223). New York: ACM Press.Google Scholar
Lang, C., Craig, A., & Casey, G. (2014). Unblocking the pipeline by providing a compelling computing experience in secondary schools: Are the teachers ready? In Proceedings of the Australasian Computing Education Conference (ACE 2014) (pp. 149–158). Sydney, Australia: Australian Computer Society.Google Scholar
Lemov, D. (2015). Teach Like a Champion 2.0: 62 Techniques That Put Students on the Path to College, 2nd edn. San Francisco, CA: Jossey-Bass.Google Scholar
Lemov, D., Hernandez, J., & Kim, J. (2016). Teach Like a Champion Field Guide 2.0: A Practical Resource to Make the 62 Techniques Your Own, 2nd edn. San Francisco, CA: Jossey-Bass.Google Scholar
Lewis, C. M., Khayarallah, H., & Tsai, A. (2013). Mining data from the AP CS A exam: Patterns, non-patterns, and replication failure. In Proceedings of the International Computing Education Research Conference (ICER 2013) (pp. 115–122). New York: ACM Press.Google Scholar
Lewis, D. W., Kohne, L., Mechlinski, T., & Schmalstig, M. (2015). The exploring computer science course, attendance and math achievement. In Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘15) (pp. 147–152). New York: ACM Press.Google Scholar
Liebenberg, J., Mentz, E., & Breed, B. (2012). Pair programming and secondary school girls’ enjoyment of programming and the subject information technology (IT). Computer Science Education, 22(3), 219–236.Google Scholar
Liu, A., Schunn, C., Flot, J., & Shoop, R. (2013). The role of physicality in rich programming environments. Computer Science Education, 23(4), 315–331.Google Scholar
Magerko, B., Freeman, J., McKlin, T., Reilly, M., Livingston, E., McCoid, S., & Crews-Brown, A. (2016). EarSketch: A STEAM-based approach for underrepresented populations in high school computer science education. ACM Transactions on Computing Education (TOCE), 16(4), 14.1–14.25.Google Scholar
Margolis, J., & Fisher, A. (2001). Unlocking the Clubhouse: Women in Computing. Cambridge, MA: MIT Press.Google Scholar
Martinez, C., Gomez, M. J., & Benotti, L. (2015). A comparison of preschool and elementary school children learning computer science concepts through a multilanguage robot programming platform. In Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘15) (pp. 159–164). New York: ACM Press.Google Scholar
McCabe, T. J. (1976). A complexity measure. IEEE Transactions on Software Engineering, SE-2(4), 308–320.Google Scholar
Meerbaum-Salant, O., Armoni, M., & Ben-Ari, M. (2013). Learning computer science concepts with Scratch. Computer Science Education, 23(3), 239–264.Google Scholar
Meerbaum-Salant, O., & Hazzan, O. (2010). An agile constructionist mentoring methodology for software projects in the high school. ACM Transactions on Computing Education (TOCE), 9(4), 21.1–21.29.Google Scholar
Meerbaum-Salant, O., & Hazzan, O. (2009). Challenges in mentoring software development projects in the high school: Analysis according to Shulman’s teacher knowledge base model. Journal of Computers in Mathematics and Science Teaching, 28(1), 23–43.Google Scholar
Merkouris, A., Chorianopoulos, K., & Kameas, A. (2017). Teaching programming in secondary education through embodied computing platforms: Robotics and wearables. ACM Transactions on Computing Education (TOCE), 17(2), 9.1–9.22.Google Scholar
Montessori, M. (1909). Il Metodo della Pedagogia Scientifica Applicato All’educazione Infantile Nelle Case dei Bambini. Città di Castello, Italy: S. Lafi.Google Scholar
Mühling, A., Ruf, , , A., & Hubwieser, P. (2015). Design and first results of a psychometric test for measuring basic programming abilities. In Proceedings of the 10th Workshop in Primary and Secondary Computing Education (WiPSCE 2015) (pp. 2–10). New York: ACM Press.Google Scholar
Musicant, D., & Selcen Guzey, S. (2015). Engaging high school students in modeling and simulation through educational media. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education (SIGCSE 2015) (pp. 464–469). New York: ACM Press.Google Scholar
Nishida, T., Idosaka, Y., Hofuku, Y., Kanemune, S., & Kuno, Y. (2008). New methodology of information education with “computer science unplugged”. In Proceedings of the 3rd International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (ISSEP 2008), Lecture Notes in Computer Science 5090 (pp. 241–252). Berlin, Germany: Springer.Google Scholar
Pasternak, A. (2016). Contextualized teaching in the lower secondary education: Long-term evaluation of a CS course from Grade 6 to 10. In Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE 2016) (pp. 657–662). New York: ACM Press.Google Scholar
Pasternak, A., & Vahrenhold, J. (2012). Design and evaluation of a braided teaching course in sixth grade computer science education. In Proceedings of the 43rd ACM Technical Symposium on Computer Science Education (SIGCSE 2012) (pp. 45–50). New York: ACM Press.Google Scholar
Peters, A. K., & Rick, D. (2014). Identity development in computing education: Theoretical perspectives and an implementation in the classroom. In Proceedings of the 9th Workshop in Primary and Secondary Computing Education (WiPSCE 2014) (pp. 70–79). New York: ACM Press.Google Scholar
Poirot, J. L. (1979). Computer education in the secondary school: Problems and solutions. In Proceedings of the Tenth SIGCSE Technical Symposium on Computer Science Education (SIGCSE 1979) (pp. 101–104). New York: ACM Press.Google Scholar
Reges, S. (2008). The mystery of “b:= (b = false)”. In Proceedings of the 39th ACM Technical Symposium on Computer Science Education (SIGCSE 2008) (pp. 21–25). New York: ACM Press.Google Scholar
Robertson, J. (2013). The influence of a game-making project on male and female learners’ attitudes to computing. Computer Science Education, 23(1), 58–83.Google Scholar
Rodriguez, B., Kennicutt, S., Rader, C., & Camp, T. (2017). Assessing computational thinking in CS Unplugged activities. In Proceedings of the 48th ACM Technical Symposium on Computer Science Education (SIGCSE 2017) (pp. 501–506). New York: ACM Press.Google Scholar
Rodriguez, B., Rader, C., & Camp, T. (2016). Using student performance to assess CS Unplugged activities in a classroom environment. In Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education (SIGCSE 2016) (pp. 95–100). New York: ACM Press.Google Scholar
Ruf, A., Mühling, A., & Hubwieser, P. (2014). Scratch vs. Karel – Impact on learning outcomes and motivation. In Proceedings of the 9th Workshop in Primary and Secondary Computing Education (WiPSCE 2014) (pp. 50–59). New York: ACM Press.Google Scholar
Sahami, M., Danyluk, A., Fincher, S., Fisher, K., Grossman, D., Hawthorne, E., Katz, R., LeBlanc, R., Reed, D., Roach, S., Cuadros-Vargas, E., Dodge, R., France, R., Kumar, A., Robinson, B., Seker, R., & Thompson, A. (2013). Computer Science Curricula 2013 – Final Report. Association for Computing Machinery & IEEE-Computer Society. Retrieved from http://dx.doi.org/10.1145/2534860Google Scholar
Sakhnini, V., & Hazzan, O. (2008). Reducing abstraction in high school computer science education: The case of definition, implementation, and use of abstract data types. Journal of Educational Resources in Computing, 8(2), 5.Google Scholar
Schanzer, E., Fisler, K., & Krishnamurthi, S. (2018). Assessing Bootstrap: Algebra students on scaffolded and unscaffolded word problems. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE 2018) (pp. 8–13). New York: ACM Press.Google Scholar
Schanzer, E., Fisler, K., Krishnamurthi, S., & Felleisen, M. (2015). Transferring skills at solving word problems from computing to algebra through Bootstrap. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education (SIGCSE 2015) (pp. 616–621). New York: ACM Press.Google Scholar
Schofield, E., Erlinger, M., & Dodds, Z. (2014). MyCS: CS for middle-year students and their teachers. In Proceedings of the 45th ACM Technical Symposium on Computer Science Education (SIGCSE 2014) (pp. 337–342). New York: ACM Press.Google Scholar
Schollmeyer, M. (1996). Computer programming in high school vs. college. In Proceedings of the 27th SIGCSE Technical Symposium on Computer Science Education (SIGCSE 1996) (pp. 378–382). New York: ACM Press.Google Scholar
Schulte, C., & Magenheim, J. (2005). Novices’ expectations and prior knowledge of software development: Results of a study with high school students. In Proceedings of the International Computing Education Research Workshop (ICER 2005) (pp. 143–153). New York: ACM Press.Google Scholar
Searle, K. A., Fields, D. A., Lui, D. A., & Kafai, Y. (2014). Diversifying high school students’ views about computing with electronic textiles. In Proceedings of the International Computing Education Research Conference (ICER 2014) (pp. 75–82). New York: ACM Press.Google Scholar
Seehorn, D., Carey, S., Fuschetto, B., Lee, I., Moix, D., O’Grady-Cunniff, D., Boucher Owens, B., Stephenson, C., & Verno, A. (2011). K–12 Computer Science Standards – Revised 2011. New York: Computer Science Teachers Association & Association for Computing Machinery.Google Scholar
Seidel, T., Prenzel, M., & Kobarg, M. (Eds.) (2005). How to Run a Video Study. Technical Report of the IPN Video Study. Münster, Germany: Waxmann.Google Scholar
Seiter, L. (2015). Using SOLO to classify the programming responses of primary grade students. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education (SIGCSE 2015) (pp. 540–545). New York: ACM Press.Google Scholar
Seiter, L., & Foreman, B. (2013). Modeling the learning progressions of computational thinking of primary grade students. In Proceedings of the International Computing Education Research Conference (ICER 2013) (pp. 59–66). New York: ACM Press.Google Scholar
Sentance, S., & Czismadia, A. (2017). Computing in the curriculum: Challenges and strategies from a teacher’s perspective. Education and Information Technologies, 22(2), 469–495.Google Scholar
Sentance, S., Waite, J., Hodges, S., MacLeod, E., & Yeomans, L. (2017). “Creating cool stuff”: Pupils’ experience of the BBC micro:bit. In Proceedings of the 48th ACM Technical Symposium on Computer Science Education (SIGCSE 2017) (pp. 531–536). New York: ACM Press.Google Scholar
Serafini, G. (2011). Teaching programming at primary schools: Visions, experiences, and long-term research prospects. In Proceedings of the 5th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (ISSEP 2011), Lecture Notes in Computer Science 7013 (pp. 143–154). Berlin, Germany: Springer.Google Scholar
Settle, A., Franke, B., Hansen, R., Spaltro, F., Jurisson, C., Rennert-May, C., & Wildeman, B. (2012). Infusing computational thinking into the middle- and high-school curriculum. In Proceedings of the 17th ACM Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘12) (pp. 22–27). New York: ACM Press.Google Scholar
Siegel, A. A., & Zarb, M. (2016). Student concerns regarding transition into higher education CS. In Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE 2016) (pp. 23–28). New York: ACM Press.Google Scholar
Shah, P., Capovilla, D., & Hubwieser, P. (2015). Searching for barriers to learning iteration and runtime in computer science. In Proceedings of the 10th Workshop in Primary and Secondary Computing Education (WiPSCE 2015) (pp. 73–75). New York: ACM Press.Google Scholar
Shulman, L. E. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57(1), 1–22.Google Scholar
Smetsers-Weeda, R., & Smetsers, S. (2017). Problem solving and algorithmic development with flowcharts. In Proceedings of the 12th Workshop in Primary and Secondary Computing Education (WiPSCE 2017) (pp. 25–34). New York: ACM Press.Google Scholar
Snow, E., Rutstein, D., Bienkowski, M., & Xu, Y. (2017). Principled assessment of student learning in high school computer science. In Proceedings of the 2017 ACM Conference on International Computing Education Research (ICER 2017) (pp. 209–216). New York: ACM Press.Google Scholar
Statter, D., & Armoni, M. (2016). Teaching abstract thinking in introduction to computer science for 7th graders. In Proceedings of the 11th Workshop in Primary and Secondary Computing Education (WiPSCE 2016) (pp. 80–83). New York: ACM Press.Google Scholar
Statter, D., & Armoni, M. (2017). Learning abstraction in computer science: A gender perspective. In Proceedings of the 12th Workshop in Primary and Secondary Computing Education (WiPSCE 2017) (pp. 5–14). New York: ACM Press.Google Scholar
Steiner, R. (1984). Erziehungskunst. Seminarbesprechungen und Lehrplanvorträge. Dornach, Germany: Rudolf Steiner Verlag. In German.Google Scholar
Sysło, M. M. (2014) The first 25 years of computers in education in Poland: 1965–1990. In Tatnall, A. & Davey, B. (Eds.), Reflections on the History of Computers in Education. IFIP Advances in Information and Communication Technology, Vol. 424 (pp. 266–290). Berlin, Germany: Springer.Google Scholar
Sysło, M. M., & Kwiatkowska, A. B. (2015). Introducing a new computer science curriculum for all school levels in Poland. In Proceedings of the 8th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (ISSEP 2015), Lecture Notes in Computer Science 9378 (pp. 141–154). Berlin, Germany: Springer.Google Scholar
Tabet, N., Gedawy, H., Alshikhabobakr, H., & Razak, S. (2016). From Alice to Python. Introducing text-based programming in middle schools. In Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE 2016) (pp. 124–129). New York: ACM Press.Google Scholar
Taub, R., Armoni, M., & Ben-Ari, M. (2012). CS Unplugged and middle-school students’ views, attitudes, and intentions regarding CS. ACM Transactions on Computing Education (TOCE), 12(2), 8.1–8.29.Google Scholar
Tessler, J., Beth, B., & Lin, C. (2013). Using Cargo-Bot to provide contextualized learning of recursion. In Proceedings of the International Computing Education Research Conference (ICER 2013) (pp. 161–168). New York: ACM Press.Google Scholar
The Royal Society (2012). Shut Down or Restart – The Way Forward for Computing in UK Schools. Retrieved from https://royalsociety.org/~/media/education/computing-in-schools/2012-01-12-computing-in-schools.pdfGoogle Scholar
Thies, R., & Vahrenhold, J. (2013). On plugging “Unplugged” into CS classes. In Proceedings of the 44th ACM Technical Symposium on Computer Science Education (SIGCSE 2013) (pp. 365–370). New York: ACM Press.Google Scholar
Thies, R., & Vahrenhold, J. (2016). Back to school: Computer science unplugged in the wild. In Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE 2016) (pp. 118–123). New York: ACM Press.Google Scholar
Tsan, J., Boyer, K. E., & Lynch, C. F. (2016). How early does the CS gender gap emerge?: A study of collaborative problem solving in 5th grade computer science. In Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE 2016) (pp. 288–293). New York: ACM Press.Google Scholar
Tsan, J., Rodriguez, F. J., Boyer, K. E., & Lynch, C. (2018). “I think we should…”: Analyzing elementary students’ collaborative processes for giving and taking suggestions. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE 2018) (pp. 622–627). New York: ACM Press.Google Scholar
Vahrenhold, J. (2012). On the importance of being earnest: Challenges in computer science education. In Proceedings of the 7th Workshop in Primary and Secondary Computing Education (WiPSCE 2012) (pp. 3–4). New York: ACM Press.Google Scholar
Vahrenhold, J., Nardelli, E., Pereira, C., Berry, G., Caspersen, M. E., Gal-Ezer, J., Kölling, M., McGettrick, , , A., & Westermeier, M. (2017). Informatics Education in Europe: Are We All in The Same Boat? Association for Computing Machinery & Informatics Europe. Retrieved from http://dx.doi.org/10.1145/3106077Google Scholar
Vaníček, J. (2015). Programming in Scratch using inquiry-based approach. In Proceedings of the 8th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (ISSEP 2015), Lecture Notes in Computer Science 9378 (pp. 82–93). Berlin, Germany: Springer.Google Scholar
Waite, J. (2017). Pedagogy in Teaching Computer Science in Schools: A Literature Review. London, UK: The Royal Society.Google Scholar
Webb, M., Davis, N., Bell, T., Katz, Y.J., Reynolds, N., Chambers, D. P., & Sysło, M. M. (2017). Computer science in K–12 school curricula of the 21st century: Why, what and when? Education and Information Technologies, 22(2), 445–468.Google Scholar
Weintrop, D., & Wilensky, U. (2018). Comparing block-based and text-based programming in high school computer science classrooms. ACM Transactions on Computing Education (TOCE), 18(1), 3.1–3.20.Google Scholar
Werner, L., Campe, S., & Denner, J. (2012a). Children learning computer science concepts via Alice game-programming. In Proceedings of the 43rd ACM Technical Symposium on Computer Science Education (SIGCSE 2012) (pp. 427–432). New York: ACM Press.Google Scholar
Werner, L., Denner, J., Campe, S., & Kawamoto, D. C. (2012b). The Fairy Performance Assessment: Measuring computational thinking in middle school. In Proceedings of the 43rd ACM Technical Symposium on Computer Science Education (SIGCSE 2012) (pp. 215–220). New York: ACM Press.Google Scholar
White House Office of the Press Secretary (2016). FACT SHEET: President Obama Announces Computer Science For All Initiative. Retrieved from https://obamawhitehouse.archives.gov/the-press-office/2016/01/30/fact-sheet-president-obama-announces-computer-science-all-initiative-0Google Scholar
Whitherspoon, E. B., Higashi, R. M., Schunn, C. D., Baehr, E. C., & Shoop, R. (2018). Developing computational thinking through a virtual robotics programming curriculum. ACM Transactions on Computing Education (TOCE), 18(1), 4.1–4.20.Google Scholar
Wilson, C., Sudol, L.A., Stephenson, C., & Stehlik, M. (2010). Running on Empty: The Failure to Teach K–12 Computer Science in the Digital Age. New York: Association for Computing Machinery & Computer Science Teachers Association.Google Scholar
Wolz, U., Stone, M., Pearson, K., Pulimood, S. M., & Switzer, M. (2011). Computational thinking and expository writing in the middle school. ACM Transactions on Computing Education (TOCE), 11(2), 9.1–9.22.Google Scholar
Wong-Villacres, M., Ehsan, U., Solomon, A., Pozo Buil, M., & DiSalvo, B. (2017). Design guidelines for parent-school technologies to support the ecology of parental engagement. In Proceedings of the 2017 Conference on Interaction Design and Children (pp. 73–83). New York: ACM Press.Google Scholar
Woszczynski, A. B. (2006). CyberTech I: Online introduction to computer science course for high school students. In Proceedings of the 36th ACM Technical Symposium on Computer Science Education (SIGCSE 2006) (pp. 153–157). New York: ACM Press.Google Scholar
Wood, Z. J., Muhl, P., & Hicks, K. (2016). Computational art: Introducing high school students to computing via art. In Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE 2016) (pp. 261–266). New York: ACM Press.Google Scholar
Wu, C.-C., Tseng, I.-C., & Huang, S.-L. (2008). Visualization of program behaviors: Physical robots versus robot simulators. In Proceedings of the 3rd International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (ISSEP 2008), Lecture Notes in Computer Science 5090 (pp. 53–62). Berlin, Germany: Springer.Google Scholar
Xu, D., Cadle, A., Thompson, D., Wolz, U., Greenberg, I., & Kumar, D. (2016). Creative computation in high school. In Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE 2016) (pp. 273–278). New York: ACM Press.Google Scholar
Zur-Bargury, I., Pârv, B., & Lanzberg, D. (2013). A nationwide exam as a tool for improving a new curriculum. In Proceedings of the 18th ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE ‘13) (pp. 267–272). New York: ACM Press.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×