Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter Oldenbourg March 22, 2018

Instructional methods in computing education judged by computer science teachers and educational experts

  • Andreas Zendler

    Andreas Zendler studied psychology and computer science at the University of Regensburg and the University of Potsdam. 1988 Dr phil. in experimental psychology. 1997 Dr rer. nat. in computer science. 2000 habilitation in computer science. From 1988 until 2004 consultant for software engineering with Softlab. Since 2005 professor for computer science education at the University of Education Ludwigsburg. Research areas: Empirical computer science education, experimental designs in educational studies, data science.

    EMAIL logo

Abstract

Answers to the questions of which instructional methods are suitable for school, what instructional methods should be applied in teaching individual subjects and how instructional methods support the act of learning represent challenges to general education and education in individual subjects. This article focuses on empirical examinations of instructional methods for computer science education supporting knowledge processes in the act of learning and their integration into the context of significant learning theories. The results of this article show that certain instructional methods are especially predestined for computer science education. They can also be attributed to behavioristic, cognitivist and constructivist learning theories; they are thereby localized and can profit from the empirical findings of the learning theories, especially in practical use on teaching computer science.

About the author

Andreas Zendler

Andreas Zendler studied psychology and computer science at the University of Regensburg and the University of Potsdam. 1988 Dr phil. in experimental psychology. 1997 Dr rer. nat. in computer science. 2000 habilitation in computer science. From 1988 until 2004 consultant for software engineering with Softlab. Since 2005 professor for computer science education at the University of Education Ludwigsburg. Research areas: Empirical computer science education, experimental designs in educational studies, data science.

References

1. S. K. Abell and N. G. Lederman, Handbook of research on science education. Lawrence Erlbaum, 2007.Search in Google Scholar

2. Association for Computing Machinery. Computer science curriculum 2013. ACM, 2013.Search in Google Scholar

3. C. Agneli, D. Kadijevich, and C. Schulte. Improving computer science education. Routledge Chapman & Hall, 2013.10.4324/9780203078723Search in Google Scholar

4. J. R. Anderson. Cognitive psychology. Worth Publishers, 2013.Search in Google Scholar

5. R. Andersson and L. Bendix. eXtreme teaching: a framework for continuous improvement. Comp. Sci. Educ., 16(3):175–184, 2006.10.1080/08993400600912335Search in Google Scholar

6. M. Baer and M. Paradiso. Neuroscience: Exploring the brain. Lippincott Williams & Wilk, 2015.Search in Google Scholar

7. K. Benoit and N. Wiesehomeier. Expert judgment. In S. Pickel, G. Pickel, H.-J. Lauth, and D. Jahn, editors, Methoden der vergleichenden Politik- und Sozialwissenschaften, pages 479–516, Wiesbaden: Verlag für Sozialwissenschaften, 2009.Search in Google Scholar

8. J. S. Bruner. The process of education. Harvard University Press, 1966.Search in Google Scholar

9. J. K. Burton, D. M. Moore, and S. G. Magliaro. Behaviorism and instructional design. In D. H Jonassen, editor, Handbook of Research on Educational Communications and Technology, pages 3–35, Lawrence Erlbaum, 2004.Search in Google Scholar

10. R. K. Canton. Programmed Instruction in online learning. Cambia Press, 2007.Search in Google Scholar

11. M. Carro, A. Herranz, and J. Mariño. A model-driven approach to teaching concurrency. ACM Trans. on Comp. Educ., 13(1): Article No. 5, 2013.10.1145/2414446.2414451Search in Google Scholar

12. A. Collins, D. Brown, and E. E. Newman. Cognitive apprenticeship. Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick, editor, Knowing, Learning and Instruction, pages 453–494, Erlbaum, 1989.10.4324/9781315044408-14Search in Google Scholar

13. S. Collins Neuroscience for learning and development: How to apply neuroscience and psychology for improved learning and training. Kogan Page, 2015.Search in Google Scholar

14. Cornelson. Methodik. www.cornelsen.de/lehrkraefte/suche?such_quelle=servicebox&freitext=Methodik. Accessed: 2017-08-01.Search in Google Scholar

15. B. G. Davis. Tools for teaching. Jossey-Bass, 2009.Search in Google Scholar

16. D. A. Dillman, J. Smyth, and L. Christian. Internet, mail, and mixed-mode designs: The tailored design method. Wiley & Sons, 2009.Search in Google Scholar

17. A. de Freitas and M. M. de Freitas. Classroom live: a software-assisted gamification tool. Comp. Sci. Educ., 23(2):186–206, 2013.10.1080/08993408.2013.780449Search in Google Scholar

18. R. M. Gagné, W. W. Wagner, K. Golas, and J. M. Keller. Principles of instructional design. Wadsworth Publishing, 2004.Search in Google Scholar

19. A. Gartner, M. C. Kohler, and F. Riessman. Children teach children. Learning by teaching. Harper & Row, 1971.Search in Google Scholar

20. GI. Bildungsstandards Informatik SI und SII. http://www.informatik-standards.de. Accessed: 2017-08-01.Search in Google Scholar

21. P. Ginnis. The teacher’s toolkit. Classroom achievement. Crown House Publishing, 2001.Search in Google Scholar

22. M. J. van Gorp and S. Grissom. An empirical evaluation of using constructive classroom activities to teach introductory programming. Comp. Sci. Educ., 11(3):247–260, 2001.10.1076/csed.11.3.247.3837Search in Google Scholar

23. N. S. Gowda. Learning and the learner: Insights into the processes of learning and teaching. PHI Learning, 2001.Search in Google Scholar

24. J. Grzega and M. Schöner. The didactic model LdL (Lernen durch Lehren) as a way of preparing students for communication in a knowledge society. J. of Edu. for Teach., 34(3):167–175, 2008.10.1080/02607470802212157Search in Google Scholar

25. G. Gugel. 2000 Methoden für Schule und Lehrebildung. Beltz, 2001.Search in Google Scholar

26. K. L. Gwet. Handbook of inter-rater-reliability. Advanced Analytics, 2014.10.1002/9781118445112.stat06882Search in Google Scholar

27. W. Hartmann, M. Näf, and R. Reichert. Informatikunterricht planen und durchführen. Springer, 2006.Search in Google Scholar

28. J. Hattie. Visible learning. Routledge, 2009.10.4324/9780203887332Search in Google Scholar

29. O. Hazzan, T. Lapidot, and N. Ragonis. Guide to teaching computer science: an activity-based approach. Springer, 2011.10.1007/978-0-85729-443-2Search in Google Scholar

30. S. G. Huber and S. Hader-Popp. Unterrichtsentwicklung durch Methodenvielfalt im Unterricht fördern: das Methodenatelier als schulinterne Fortbildung. In A. Bartz, J. Fabian, S. G. Huber, C. Kloft, H. Rosenbusch, and H. Sassenscheidt, editors, PraxisWissen Schulleitung, pages 30–31, Wolters Kluwer, 2007.Search in Google Scholar

31. P. Hubwieser. Didaktik der Informatik: Grundlagen, Konzepte, Beispiele. Springer, 2007.Search in Google Scholar

32. L. Humbert. Didaktik der Informatik. Teubner, 2006.10.1007/978-3-322-93427-7Search in Google Scholar

33. Y.-C. Hung. The effect of teaching methods and learning style on learning program design in webbased education systems. J. of Educ. Comp. R., 47(4):409–427, 2012.10.2190/EC.47.4.dSearch in Google Scholar

34. S. Iron, S. Alexander, and S. Alexander. Improving computer science education. Routledge Chapman & Hall, 2004.Search in Google Scholar

35. P. Kilpeläinen. Do all roads lead to Rome? (Or reductions for dummy travelers). Comp. Sci. Edu., 20(3):181–199, 2010.10.1080/08993408.2010.501226Search in Google Scholar

36. E. Koffmann and T. Brinda. Teaching programming and problems solving. In L. Cassel and R. A. Reis, editors, Informatics curricula and teaching methods, pages 125–130, Kluwer Academic Publishers, 2003.10.1007/978-0-387-35619-8_13Search in Google Scholar

37. LOG IN. Unterrichtsmaterialien für den Informatikunterricht. http://www.log-in-verlag.de/informatikunterricht. Accessed: 2017-08-01.Search in Google Scholar

38. D. Mareschal and B. Butterworth. Educational neuroscience. Wiley & Sons, 2013.Search in Google Scholar

39. M. D. Merill. First Principles. Educ. Technology, Res. and Dev., 50(3):43–59, 2002.10.1007/BF02505024Search in Google Scholar

40. S. B. Merriam and R. S. Caffarella. Learning in adulthood: A comprehensive guide. Bass, 2006.Search in Google Scholar

41. H. Meyer. Unterrichtsmethoden. In H. Kiper, H. Meyer, and W. Topsch, editors, Einführung in die Schulpädagogik, pages 109–121, Cornelsen, 2012.Search in Google Scholar

42. C. Mitchell and L. Sackney. Profound improvement building capacity for learning communities. Routledge, 2011.10.4324/9780203826027Search in Google Scholar

43. D. R. Olson. Jerome Bruner: The cognitive revolution in educational theory. Continuum, 2007.Search in Google Scholar

44. S. Petrina Advanced teaching methods for the technology classroom. Information Science Publishing, 2006.10.4018/978-1-59904-337-1Search in Google Scholar

45. G. Petty. Teaching today: a practical guide. Nelson Thornes, 2009.Search in Google Scholar

46. B. Sabitzer. Neurodidactics – a new stimulus in ICT and computer science education. In L. Gómez Chova, I. Candel Torres and A. López Martìnez, editors, INTED 2011 Proceedings CD. International Association of Technology, Education and Development (IATED), March 2011.Search in Google Scholar

47. S. D. Sala and M. Anderson. Neuroscience in education: The good, the bad, and the ugly. Oxford University Press, 2011.Search in Google Scholar

48. J. W. Santrock. Educational psychology. Mcgraw-Hill, 2011.Search in Google Scholar

49. S. Schubert and A. Schwill. Didaktik der Informatik. Spektrum, 2012.10.1007/978-3-8274-2653-6Search in Google Scholar

50. C. Schulte. Uncovering structure behind function: the experiment as teaching method in computer science education. In WiPSCE’12 Proceedings of the 7th Workshop in Primary and Secondary Computing Education, pages 40–47, Wiley, 2012.10.1145/2481449.2481460Search in Google Scholar

51. M. Seiffert and B. Koerber. Neue Methoden braucht der Unterricht. LOG IN, 138:3, 2003.Search in Google Scholar

52. R. E. Slavin, Educational psychology: Theory and practice. Pearson Education, 2014.Search in Google Scholar

53. A. J. Spurgin. Human reliability assessment theory and practice. Boca Raton: CRC Press, 2009.10.1201/9781420068528Search in Google Scholar

54. R. Tennyson, F. Schott, N. Seel, and S. Dijkstra. Instructional design: International perspective: Theory, research, and models (volume 1). Lawrence Erlbaum Associates, 1997.Search in Google Scholar

55. The Center for Teaching and Learning. 150 teaching methods. http://teaching.uncc.edu/learning-resources/articles-books/best-practice/instructional-methods/150-teaching-methods. Accessed: 2017-08-01.Search in Google Scholar

56. N. Thota and R. Whitfield. Holistic approach to learning and teaching introductory object-oriented programming. Comp. Sci. Educ., 20(2):103–127, 2010.10.1080/08993408.2010.486260Search in Google Scholar

57. F. E. Weinert. Ansprüche an das Lernen in der heutigen Zeit. In MSW – Ministerium für Schule und Weiterbildung des Landes Nordrhein-Westfalen (Ed.), Fächerübergreifendes Arbeiten – Bilanz und Perspektiven. Ritterbach, 1997.Search in Google Scholar

58. J. Wiechmann Direkte Instruktion. In J. Wiechmann, editor, Zwölf Unterrichtsmethoden, pages 35–39, Beltz, 2011.Search in Google Scholar

59. A. Woolfolk. Educational psychology. Pearson, 2015.Search in Google Scholar

60. A. Zendler and D. Klaudt. Booklet I: Instructional methods to computer science education. epubli, 2015.Search in Google Scholar

61. A. Zendler and D. Klaudt. Instructional methods to computer science education as investigated by computer science teachers. Journal of Computer Science, 11(8):915–927, 2015.10.3844/jcssp.2015.915.927Search in Google Scholar

62. A. Zendler. Computer science education teaching methods—an overview of the literature. International Journal of Research Studies in Computing, 4(2):3–11, 2015.10.5861/ijrsc.2015.1242Search in Google Scholar

63. A. Zendler, C. Seitz, and D. Klaudt. Instructional methods in the context of significant learning theories. In A. Zendler, editor, Elements of empirical computer science education, 2018.Search in Google Scholar

Received: 2017-8-9
Revised: 2018-1-18
Accepted: 2018-2-5
Published Online: 2018-3-22
Published in Print: 2018-4-25

© 2018 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 19.4.2024 from https://www.degruyter.com/document/doi/10.1515/itit-2017-0015/html
Scroll to top button