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M-CAFE: Managing MOOC Student Feedback with Collaborative Filtering

Authors:

Mo Zhou,

Ken GoldbergAuthors Info & Claims

L@S '15: Proceedings of the Second (2015) ACM Conference on Learning @ Scale

Pages 309 - 312

https://doi.org/10.1145/2724660.2728681

Published: 14 March 2015 Publication History

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Abstract

Ongoing student feedback on course content and assignments can be valuable for MOOC instructors in the absence of face-to-face-interaction. To collect ongoing feedback and scalably identify valuable suggestions, we built the MOOC Collaborative Assessment and Feedback Engine (M-CAFE). This mobile platform allows MOOC students to numerically assess the course, their own performance, and provide textual suggestions about how the course could be improved on a weekly basis. M-CAFE allows students to visualize how they compare with their peers and read and evaluate what others have suggested, providing peer-to-peer collaborative filtering. We evaluate M-CAFE based on data from two EdX MOOCs.

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[2]

Kristin, S.M., Hearst, M.A., and Fox, A. Monitoring MOOCs: which information sources do instructors value? Proceedings of the First ACM conference on Learning @ Scale Conference. (2014), 79--88.

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Marsh, H.W., and Roche, L.A. Making students' evaluations of teaching effectiveness effective: The critical issues of validity, bias, and utility. American Psychologist, 52(11). (1997), 1187--1197.

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Stark, P.B. and Richard F. An Evaluation of Course Evaluations. UC Berkeley Technical Report; Center for Teaching and Learning. (2014)

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Duncan ATang THuang YLuu JThakkar NJoyner DJoyner DKim MWang XXia M(2024)Forums, Feedback, and Two Kinds of AI: A Selective History of Learning @ ScaleProceedings of the Eleventh ACM Conference on Learning @ Scale10.1145/3657604.3664667(376-382)Online publication date: 9-Jul-2024
https://dl.acm.org/doi/10.1145/3657604.3664667
Sun XFu YZheng WHuang YLi Y(2022)Big Educational Data Analytics, Prediction and Recommendation: A SurveyJournal of Circuits, Systems and Computers10.1142/S021812662230007031:09Online publication date: 25-Feb-2022
https://doi.org/10.1142/S0218126622300070
Gold RHemberg EO'Reilly UJoyner DKizilcec RSinger S(2020)Analyzing K-12 Blended MOOC Learning BehaviorsProceedings of the Seventh ACM Conference on Learning @ Scale10.1145/3386527.3406743(345-348)Online publication date: 12-Aug-2020
https://dl.acm.org/doi/10.1145/3386527.3406743
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Index Terms

M-CAFE: Managing MOOC Student Feedback with Collaborative Filtering
1. Applied computing
  1. Education
    1. Distance learning
    2. E-learning
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Web-based interaction

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Published In

L@S '15: Proceedings of the Second (2015) ACM Conference on Learning @ Scale

March 2015

438 pages

ISBN:9781450334112

DOI:10.1145/2724660

General Chair:
Gregor Kiczales
University of British Columbia
,
Program Chairs:
Daniel M. Russell
Google
,
Beverly Woolf
University of Massachusets, Amherst

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 March 2015

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USAID Cooperative Agreement
UC-Berkeley AMPLab
Fujitsu

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L@S 2015

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ACM Ed Board

L@S 2015: Second (2015) ACM Conference on Learning @ Scale

March 14 - 18, 2015

BC, Vancouver, Canada

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L@S '15 Paper Acceptance Rate 23 of 90 submissions, 26%;

Overall Acceptance Rate 117 of 440 submissions, 27%

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Duncan ATang THuang YLuu JThakkar NJoyner DJoyner DKim MWang XXia M(2024)Forums, Feedback, and Two Kinds of AI: A Selective History of Learning @ ScaleProceedings of the Eleventh ACM Conference on Learning @ Scale10.1145/3657604.3664667(376-382)Online publication date: 9-Jul-2024
https://dl.acm.org/doi/10.1145/3657604.3664667
Sun XFu YZheng WHuang YLi Y(2022)Big Educational Data Analytics, Prediction and Recommendation: A SurveyJournal of Circuits, Systems and Computers10.1142/S021812662230007031:09Online publication date: 25-Feb-2022
https://doi.org/10.1142/S0218126622300070
Gold RHemberg EO'Reilly UJoyner DKizilcec RSinger S(2020)Analyzing K-12 Blended MOOC Learning BehaviorsProceedings of the Seventh ACM Conference on Learning @ Scale10.1145/3386527.3406743(345-348)Online publication date: 12-Aug-2020
https://dl.acm.org/doi/10.1145/3386527.3406743
Hou YZhou PXu JWu D(2018)Course recommendation of MOOC with big data support: A contextual online learning approachIEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)10.1109/INFCOMW.2018.8406936(106-111)Online publication date: Apr-2018
https://doi.org/10.1109/INFCOMW.2018.8406936
Nonnecke BMohanty SLee ALee JBeckman SMi JKrishnan SRoxas ROco NCrittenden CGoldberg K(2017)Malasakit 1.0: A participatory online platform for crowdsourcing disaster risk reduction strategies in the philippines2017 IEEE Global Humanitarian Technology Conference (GHTC)10.1109/GHTC.2017.8239265(1-6)Online publication date: Oct-2017
https://doi.org/10.1109/GHTC.2017.8239265
Krishnan SWang JFranklin MGoldberg KKraska TÖzcan FKoutrika GMadden S(2016)PrivateCleanProceedings of the 2016 International Conference on Management of Data10.1145/2882903.2915248(937-951)Online publication date: 26-Jun-2016
https://dl.acm.org/doi/10.1145/2882903.2915248
Zhou MCliff AKrishnan SNonnecke BCrittenden CUchino KGoldberg KSettle ASteinbach TBoisvert D(2015)M-CAFE 1.0Proceedings of the 16th Annual Conference on Information Technology Education10.1145/2808006.2808020(153-158)Online publication date: 29-Sep-2015
https://dl.acm.org/doi/10.1145/2808006.2808020
Nonnecke BKrishnan SPatel JZhou MByaruhanga LMasinde DMeneses Mdel Campo ACrittenden CGoldberg K(2015)DevCAFE 1.0: A participatory platform for assessing development initiatives in the field2015 IEEE Global Humanitarian Technology Conference (GHTC)10.1109/GHTC.2015.7344009(437-444)Online publication date: Oct-2015
https://doi.org/10.1109/GHTC.2015.7344009

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Recommendations

M-CAFE 1.0: Motivating and Prioritizing Ongoing Student Feedback During MOOCs and Large on-Campus Courses using Collaborative Filtering

M-CAFE 2.0: A Scalable Platform with Comparative Plots and Topic Tagging for Ongoing Course Feedback

Monitoring MOOCs: which information sources do instructors value?

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