Learning Content Recommender System for Instructors of Programming Courses

  • Hung ChauEmail author
  • Jordan Barria-Pineda
  • Peter Brusilovsky
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10948)


In this paper, we present a course-adaptive recommender system that assists instructors of programming courses in selecting the most relevant learning materials. The recommender system deduces the envisioned structure of a specific course using program examples prepared by the course instructor and recommends learning content items adapting to instructor’s intentions. We also present a study that assessed the quality of recommendations using datasets collected from different courses.


Course authoring Learning content recommendation 


  1. 1.
    Moffatt, D. V., Moffatt, P. B.: Eighteen pascal texts: an objective comparison. SIGCSE Bull. 14, 2, 2–10 (1982)Google Scholar
  2. 2.
    Wang, S., He, F., Andersen, E.: A unified framework for knowledge assessment and progression analysis and design. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, pp. 937–948. ACM, New York (2017)Google Scholar
  3. 3.
    Hsiao, I.H., Sosnovsky, S., Brusilovsky, P.: Guiding students to the right questions: adaptive navigation support in an e-learning system for Java programming. J. Comput. Assist. Learn. 26(4), 270–283 (2010)CrossRefGoogle Scholar
  4. 4.
    Brusilovsky, P., Yudelson, M.V.: From WebEx to NavEx: interactive access to annotated program examples. Proc IEEE 96, 6, 990–999 (2008)Google Scholar
  5. 5.
    Murray, T.: Authoring intelligent tutoring systems: an analysis of the state of the art. Int. J. AIED 1, 10 , 98–129 (1999)Google Scholar
  6. 6.
    Murray, T.: An overview of intelligent tutoring system authoring tools: updated analysis of the state of the art. In: Murray, T., Blessing, S.B., Ainsworth, S. (eds.) Authoring Tools for Advanced Technology Learning Environments: Toward Cost-Effective Adaptive, Interactive and Intelligent Educational So ware, pp. 491–544. Springer, Dordrecht (2003). Scholar
  7. 7.
    Sottilare, R.A.: Challenges to enhancing authoring tools and methods for intelligent tutoring systems. In: Sottilare, R.A., Graesser, A.C., Hu, X., Brawner, K. (eds.) Design Recommendations for Intelligent Tutoring Systems, pp. 3–7. U.S. Army Research Laboratory, Orlando, FL (2015)Google Scholar
  8. 8.
    Cristea, A., Aroyo, L.: Adaptive authoring of adaptive educational hypermedia. In: De Bra, P., Brusilovsky, P., Conejo, R. (eds.) AH 2002. LNCS, vol. 2347, pp. 122–132. Springer, Heidelberg (2002). Scholar
  9. 9.
    Brusilovsky, P., Sosnovsky, S., Yudelson, M., Chavan, G.: Interactive authoring support for adaptive educational systems. In: Proceedings of the 2005 Conference on AIED: Supporting Learning Through Intelligent and Socially Informed Technology, pp. 96–103. IOS Press, Amsterdam, The Netherlands (2005)Google Scholar
  10. 10.
    Brusilovsky, P., Eklund, J., Schwarz, E: Web-based education for all: a tool for developing adaptive courseware. In: Ashman, H., Thistewaite, P. (eds.) Proceedings of Seventh International World Wide Web Conference, Brisbane, Australia, 14–18 April 1998, pp. 291–300 (1998)Google Scholar
  11. 11.
    Hosseini, R., Brusilovsky, P.: JavaParser: a fine-grain concept indexing tool for java problems. In: The First Workshop on AI-supported Education for Computer Science, pp. 60–63. Springer, Heidelberg (2013)Google Scholar
  12. 12.
    Medio, C.D., Gasparetti, F., Limongelli, C., Sciarrone, F., Temperini, M.: Course-driven teacher modeling for learning objects recommendation in the Moodle LMS. In: Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization (UMAP 2017), pp. 141–145. ACM, New York (2017)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Hung Chau
    • 1
    Email author
  • Jordan Barria-Pineda
    • 1
  • Peter Brusilovsky
    • 1
  1. 1.School of Computing and InformationUniversity of PittsburghPittsburghUSA

Personalised recommendations