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Open academic analytics initiative: initial research findings

Published: 08 April 2013 Publication History

Abstract

This paper describes the results on research work performed by the Open Academic Analytics Initiative, an on-going research project aimed at developing an early detection system of college students at academic risk, using data mining models trained using student personal and demographic data, as well as course management data. We report initial findings on the predictive performance of those models, their portability across pilot programs in different institutions and the results of interventions applied on those pilots.

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Campbell, J. P. (2007). Utilizing Student Data within the Course Management System to Determine Undergraduate Student Academic Success: An Exploratory Study (Doctoral dissertation, Purdue University, 2007). (UMI No. 3287222).
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KDD Cup 2010. This Year's Challenge. Available: http://www.sigkdd.org/kddcup
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Lauría E., Baron J., Devireddy M., Sundararaju V., Jayaprakash S. (2012), "Mining academic data to improve college student retention: An open source perspective", Proceedings of LAK 2012, Vancouver, BC, Canada, April 29 -- May 2, 2012
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Laurie, P. D., & Timothy, E. (2005). Using data mining as a strategy for assessing asynchronous discussion forums. Comput. Educ., 45(1), 141--160.
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Morris, L. V., Wu, S., & Finnegan, C. (2005). Predicting retention in online general education courses. The American Journal of Distance Education, 19(1), 23--36.
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Cited By

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  • (2023)ADHE: A Tool to Characterize Higher Education Dropout PhenomenonRevista Facultad de Ingeniería Universidad de Antioquia10.17533/udea.redin.20230519Online publication date: 2-May-2023
  • (2022)Charting Design Needs and Strategic Approaches for Academic Analytics Systems through Co-DesignLAK22: 12th International Learning Analytics and Knowledge Conference10.1145/3506860.3506939(381-391)Online publication date: 21-Mar-2022
  • (2022)Studying Cohort Influence on Student Performance Prediction in Multi-cohort University CoursesEducating for a New Future: Making Sense of Technology-Enhanced Learning Adoption10.1007/978-3-031-16290-9_59(623-630)Online publication date: 5-Sep-2022
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cover image ACM Conferences
LAK '13: Proceedings of the Third International Conference on Learning Analytics and Knowledge
April 2013
300 pages
ISBN:9781450317856
DOI:10.1145/2460296
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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Publication History

Published: 08 April 2013

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Author Tags

  1. course management systems
  2. data mining
  3. intervention
  4. learning analytics
  5. open source
  6. portability

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LAK '13 Paper Acceptance Rate 16 of 58 submissions, 28%;
Overall Acceptance Rate 236 of 782 submissions, 30%

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Cited By

View all
  • (2023)ADHE: A Tool to Characterize Higher Education Dropout PhenomenonRevista Facultad de Ingeniería Universidad de Antioquia10.17533/udea.redin.20230519Online publication date: 2-May-2023
  • (2022)Charting Design Needs and Strategic Approaches for Academic Analytics Systems through Co-DesignLAK22: 12th International Learning Analytics and Knowledge Conference10.1145/3506860.3506939(381-391)Online publication date: 21-Mar-2022
  • (2022)Studying Cohort Influence on Student Performance Prediction in Multi-cohort University CoursesEducating for a New Future: Making Sense of Technology-Enhanced Learning Adoption10.1007/978-3-031-16290-9_59(623-630)Online publication date: 5-Sep-2022
  • (2021)Students matter the most in learning analytics: The effects of internal and instructional conditions in predicting academic successComputers & Education10.1016/j.compedu.2021.104251(104251)Online publication date: Jun-2021
  • (2021)BacAnalytics: A Tool to Support Secondary School Examination in FranceIntelligent Systems in Industrial Applications10.1007/978-3-030-67148-8_4(47-58)Online publication date: 4-Feb-2021
  • (2020)Where is the Learning in Learning Analytics? A Systematic Literature Review on the Operationalization of Learning-Related Constructs in the Evaluation of Learning Analytics InterventionsIEEE Transactions on Learning Technologies10.1109/TLT.2020.299997013:3(631-645)Online publication date: 1-Jul-2020
  • (2020)The effect of providing learning analytics on student behaviour and performance in programming: a randomised controlled experimentHigher Education10.1007/s10734-020-00560-zOnline publication date: 10-Jun-2020
  • (2019)Predicting the Risk of Academic Dropout With Temporal Multi-Objective OptimizationIEEE Transactions on Learning Technologies10.1109/TLT.2019.291107012:2(225-236)Online publication date: 1-Apr-2019
  • (2018)Learning AnalyticsImpact of Learning Analytics on Curriculum Design and Student Performance10.4018/978-1-5225-5369-4.ch004(41-55)Online publication date: 2018
  • (2018)The efficacy of learning analytics interventions in higher education: A systematic reviewBritish Journal of Educational Technology10.1111/bjet.1272050:5(2594-2618)Online publication date: 14-Nov-2018
  • Show More Cited By

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