Intelligent Student Support in the FLIP Learning System based on Student Initial Misconceptions and Student Modelling

Sokratis Karkalas, Sergio Gutiérrez Santos

2014

Abstract

The ’FLIP Learning’ (Flexible, Intelligent and Personalised Learning) is an Exploratory Learning Environment (ELE) for teaching elementary programming to beginners using JavaScript. This paper presents a sub-system in FLIP that can be used to generate individualised real-time support to students depending on their initial misconceptions. The sub-system is intended to be used primarily in the early stages of student engagement in order to help them overcome the constraints of their Zone of Proximal Development (ZPD) with minimal assistance from teachers. Since this is an ongoing project we also report on issues related to potential changes or enhancements that will enable a more optimised use under real classroom conditions.

References

  1. Bennedsen, J. and Caspersen, M. E. (2007). Failure rates in introductory programming. ACM SIGCSE Bulletin, 39(2):32-36.
  2. Brown, J. S. and Burton, R. R. (1978). Diagnostic models for procedural bugs in basic mathematical skills*. Cognitive science, 2(2):155-192.
  3. Bruner, J. S. (1966). Toward a theory of instruction, volume 59. Harvard University Press.
  4. Brusilovsky, P. and Peylo, C. (2003). Adaptive and intelligent web-based educational systems. International Journal of Artificial Intelligence in Education, 13(2):159-172.
  5. Brusilovsky, P., Schwarz, E., and Weber, G. (1996). Elmart: An intelligent tutoring system on world wide web. In Intelligent tutoring systems, pages 261-269. Springer.
  6. Goldman, K., Gross, P., Heeren, C., Herman, G., Kaczmarczyk, L., Loui, M. C., and Zilles, C. (2008). Identifying important and difficult concepts in introductory computing courses using a delphi process. ACM SIGCSE Bulletin, 40(1):256-260.
  7. Holland, J., Mitrovic, A., and Martin, B. (2009). J-latte: a constraint-based tutor for java.
  8. Huitt, W. (2003). Constructivism. Educational psychology interactive.
  9. Johnson, W. L. and Soloway, E. (1985). Proust: Knowledge-based program understanding. Software Engineering, IEEE Transactions on, (3):267-275.
  10. Kaczmarczyk, L. C., Petrick, E. R., East, J. P., and Herman, G. L. (2010). Identifying student misconceptions of programming. In Proceedings of the 41st ACM technical symposium on Computer science education, pages 107-111. ACM.
  11. Kolb, D. A. et al. (1984). Experiential learning: Experience as the source of learning and development, volume 1. Prentice-Hall Englewood Cliffs, NJ.
  12. Konak, A., Clark, T. K., and Nasereddin, M. (2014). Using kolb's experiential learning cycle to improve student learning in virtual computer laboratories. Computers & Education, 72:11-22.
  13. Mitrovic, A. (2003). An intelligent sql tutor on the web. International Journal of Artificial Intelligence in Education, 13(2):173-197.
  14. Peylo, C., Teiken, W., Rollinger, C.-R., and Gust, H. (2000). An ontology as domain model in a web-based educational system for prolog. In FLAIRS Conference, pages 55-59.
  15. Reiser, B. J., Anderson, J. R., and Farrell, R. G. (1985). Dynamic student modelling in an intelligent tutor for lisp programming. In IJCAI, pages 8-14.
  16. Robins, A., Rountree, J., and Rountree, N. (2003). Learning and teaching programming: A review and discussion. Computer Science Education, 13(2):137-172.
  17. Savery, J. R. (2006). Overview of problem-based learning: Definitions and distinctions. Interdisciplinary Journal of Problem-based Learning, 1(1):3.
  18. Strauss, A. and Corbin, J. (1994). Grounded theory methodology. Handbook of qualitative research, pages 273- 285.
  19. Sykes, E. R. and Franek, F. (2003). A prototype for an intelligent tutoring system for students learning to program in java (tm). In Proceedings of the IASTED International Conference on Computers and Advanced Technology in Education, June 30-July 2, 2003, Rhodes, Greece, pages 78-83.
  20. Vygotski?i, L. S., Cole, M., and John-Steiner, V. (1978). Mind in society.
  21. 22. AS-1: Understanding the difference between assignment and equality operation.
  22. 23. SCO-1: Understanding the implications of not declaring a variable.
  23. 24. SCO-2: Understanding the difference between a global and a local variable.
  24. 25. SCO-3: Understanding that a (homonymous) local variable masks a global one.
  25. 26. SCO-4: Understanding the difference between block scope and function scope.
  26. 27. PVR-1: Understanding the difference between variables which hold data and variables which hold memory references.
  27. 28. IT2-1: Understanding that loop variables can be used in expressions that occur in the body of a loop.
  28. 29. IT3-1: Understanding the implications of having an empty body in a loop structure.
  29. 30. IT4-1: Understanding the semantics behind different loop structures.
  30. 31. IT5-1: Understanding that loop variables can help in loop termination.
  31. 32. REC-1: Understanding the implications of not using a base case in a recursive function.
  32. 33. REC-2: Understanding the implications of not using the return values from recursive calls within a function.
  33. 34. AR1-1: Understanding off-by-one errors when using arrays in loop structures.
  34. 35. AR2-1: Understanding the difference between a reference to an array and an element of an array.
  35. 36. AR3-1: Understanding the declaration of an array and correctly manipulating arrays.
Download


Paper Citation


in Harvard Style

Karkalas S. and Gutiérrez Santos S. (2014). Intelligent Student Support in the FLIP Learning System based on Student Initial Misconceptions and Student Modelling . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014) ISBN 978-989-758-049-9, pages 353-360. DOI: 10.5220/0005127603530360


in Bibtex Style

@conference{keod14,
author={Sokratis Karkalas and Sergio Gutiérrez Santos},
title={Intelligent Student Support in the FLIP Learning System based on Student Initial Misconceptions and Student Modelling},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014)},
year={2014},
pages={353-360},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005127603530360},
isbn={978-989-758-049-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014)
TI - Intelligent Student Support in the FLIP Learning System based on Student Initial Misconceptions and Student Modelling
SN - 978-989-758-049-9
AU - Karkalas S.
AU - Gutiérrez Santos S.
PY - 2014
SP - 353
EP - 360
DO - 10.5220/0005127603530360