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Content wizard: Concept-based recommender system for instructors of programming courses

Chau, H and Barria-Pineda, J and Brusilovsky, P (2017) Content wizard: Concept-based recommender system for instructors of programming courses. In: UNSPECIFIED.

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Abstract

© 2017 ACM. Authoring an adaptive educational system is a complex process that involves allocating a large range of educational content within a fixed sequence of units. In this paper, we describe Content Wizard, a concept-based recommender system for recommending learning materials that meet the instructor's pedagogical goals during the creation of an online programming course. Here, the instructors are asked to provide a set of code examples that jointly re.ect the learning goals that are associated with each course unit. The Wizard is built on top of our course-authoring tool, and it helps to decrease the time instructors spend on the task and to maintain the coherence of the sequential structure of the course. It also provides instructors with additional information to identify content that might be not appropriate for the unit they are creating. We conducted an o.- line study with data collected from an introductory Java course previously taught at the University of Pittsburgh in order to evaluate both the practicality and effectiveness of the system. We found that the proposed recommendation's performance is relatively close to the teacher's expectation in creating a computer-based adaptive course.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Chau, H
Barria-Pineda, J
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 9 July 2017
Date Type: Publication
Journal or Publication Title: UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization
Page Range: 135 - 140
Event Type: Conference
DOI or Unique Handle: 10.1145/3099023.3099039
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: No
ISBN: 9781450350679
Date Deposited: 09 Aug 2017 15:12
Last Modified: 01 Nov 2017 12:57
URI: http://d-scholarship.pitt.edu/id/eprint/32816

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