research-article

Content Wizard: Concept-Based Recommender System for Instructors of Programming Courses

Authors:

Hung Chau,

Jordan Barria-Pineda,

Peter BrusilovskyAuthors Info & Claims

UMAP '17: Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization

Pages 135 - 140

https://doi.org/10.1145/3099023.3099039

Published: 09 July 2017 Publication History

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Abstract

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 reflect 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 off-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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Fan HChen GWang XPeng Z(2024)LessonPlanner: Assisting Novice Teachers to Prepare Pedagogy-Driven Lesson Plans with Large Language ModelsProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676390(1-20)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676390
Wu ZLiang QZhan Z(2023)Course Recommendation Based on Enhancement of Meta-Path Embedding in Heterogeneous GraphApplied Sciences10.3390/app1304240413:4(2404)Online publication date: 13-Feb-2023
https://doi.org/10.3390/app13042404
Alcantara RBarracas JManao JYamongan JTubola O(2022)HELPNAYAN: An Adaptive Learning System Utilizing Bayesian Network and Felder-Silverman Learning Style Model to Improve Grade 10 Students’ Learning in Physics2022 6th International Conference on Information Technology (InCIT)10.1109/InCIT56086.2022.10067542(216-221)Online publication date: 10-Nov-2022
https://doi.org/10.1109/InCIT56086.2022.10067542
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Index Terms

Content Wizard: Concept-Based Recommender System for Instructors of Programming Courses
1. Human-centered computing
  1. Interaction design
    1. Interaction design process and methods
      1. User centered design

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Published In

UMAP '17: Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization

July 2017

456 pages

ISBN:9781450350679

DOI:10.1145/3099023

Editors:
Marko Tkalcic
Free University of Bolzano
,
Dhaval Thakker
University of Leeds
,
Panagiotis Germanakos
SAP SE & University of Cyprus
,
Kalina Yacef
University of Sydney
,
Cecile Paris
CSIRO ICT Centre
,
Olga Santos
Spanish National University for Distance Education
,
General Chairs:
Maria Bielikova
Slovak University of Technology in Bratislava, Slovakia
,
Eelco Herder
L3S Research Center, Germany and Radboud Universiteit Nijmegen, The Netherlands
,
Program Chairs:
Michel Desmarais
Polytechnique University, Montreal, Canada
,
Federica Cena
University of Torino, Italy

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 July 2017

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UMAP '17: 25th Conference on User Modeling, Adaptation and Personalization

July 9 - 12, 2017

Bratislava, Slovakia

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Overall Acceptance Rate 162 of 633 submissions, 26%

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Fan HChen GWang XPeng Z(2024)LessonPlanner: Assisting Novice Teachers to Prepare Pedagogy-Driven Lesson Plans with Large Language ModelsProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676390(1-20)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676390
Wu ZLiang QZhan Z(2023)Course Recommendation Based on Enhancement of Meta-Path Embedding in Heterogeneous GraphApplied Sciences10.3390/app1304240413:4(2404)Online publication date: 13-Feb-2023
https://doi.org/10.3390/app13042404
Alcantara RBarracas JManao JYamongan JTubola O(2022)HELPNAYAN: An Adaptive Learning System Utilizing Bayesian Network and Felder-Silverman Learning Style Model to Improve Grade 10 Students’ Learning in Physics2022 6th International Conference on Information Technology (InCIT)10.1109/InCIT56086.2022.10067542(216-221)Online publication date: 10-Nov-2022
https://doi.org/10.1109/InCIT56086.2022.10067542
Wu ZTang YLiang Q(2021)A Course Recommendation System Oriented to Multiple Condition Constraints2021 IEEE International Conference on Educational Technology (ICET)10.1109/ICET52293.2021.9563184(11-15)Online publication date: 18-Jun-2021
https://doi.org/10.1109/ICET52293.2021.9563184
Pereira FJunior HRodriguez LToda AOliveira ECristea AOliveira DCarvalho LFonseca SAlamri AIsotani S(2021)A Recommender System Based on Effort: Towards Minimising Negative Affects and Maximising Achievement in CS1 LearningIntelligent Tutoring Systems10.1007/978-3-030-80421-3_51(466-480)Online publication date: 9-Jul-2021
https://doi.org/10.1007/978-3-030-80421-3_51
Asha KRajkumar R(2020)A Comprehensive Survey on Web Recommendations Systems with Special Focus on Filtering Techniques and Usage of Machine LearningComputational Vision and Bio-Inspired Computing10.1007/978-3-030-37218-7_106(1009-1022)Online publication date: 7-Jan-2020
https://doi.org/10.1007/978-3-030-37218-7_106
Lin JLi YLian J(2019)A novel recommendation system via L0-regularized convex optimizationNeural Computing and Applications10.1007/s00521-019-04213-wOnline publication date: 20-Apr-2019
https://doi.org/10.1007/s00521-019-04213-w
Brusilovsky PMalmi LHosseini RGuerra JSirkiä TPollari-Malmi K(2018)An integrated practice system for learning programming in Python: design and evaluationResearch and Practice in Technology Enhanced Learning10.1186/s41039-018-0085-913:1Online publication date: 4-Dec-2018
https://doi.org/10.1186/s41039-018-0085-9

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Efficient Authoring of SCORM Courseware Adapted to User Learning Style: The Case of ProPer SAT

Course-Adaptive Content Recommender for Course Authoring

Authoring Personalised Interactive Content

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