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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)

Abstract

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.

Keywords

Course authoring Learning content recommendation 

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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

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