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Revealing the Relations between Learning Behaviors and Examination Scores via a Prediction System

Published: 08 December 2018 Publication History

Abstract

In this paper, we present a regression model to predict students' midterm and final examinations by using student interaction history from course's online system. The regression result shows not only a low regression error but some clues for improving student learning behavior and modifying course policy. Ultimately, an instructor can focus on those students with low prediction score.

References

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Cheng Ye, John S. Kinnebrew, Gautam Biswas, Brent J. Evans, Douglas H. Fisher, Gayathri Narasimham, Katherine A. Brady. Behavior Prediction in MOOCs using Higher Granularity Temporal Information. Proceedings of the Second (2015) ACM Conference on Learning, Pages 335--338
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Catherine M. Hicks Scott, C. Ailie Fraser, Purvi Desai, Scott Klemmer Do Numberic Ratings Impact Peer Reviewers? Proceedings of the Second (2015) ACM Conference on Learning, Pages 359--362
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Christopher Chudzicki, David E. Pritchard, Zhongzhou Chen Learning Experiments Using AB Testing at Scale. Proceedings of the Second (2015) ACM Conference on Learning, Pages 405--408.
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Cho, K., and Schunn, C. D. Scaffolded writing and rewriting in the discipline: A web-based reciprocal peer review system. Comput. Educ. 48, 3 (Apr. 2007), 409--426.
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Cited By

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  • (2021)Revealing the Relation Between Students’ Reading Notes and Scores Examination with NLP FeaturesAdvances in Data Science and Information Engineering10.1007/978-3-030-71704-9_2(27-41)Online publication date: 30-Oct-2021

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CSAI '18: Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence
December 2018
641 pages
ISBN:9781450366069
DOI:10.1145/3297156
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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  • Shenzhen University: Shenzhen University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 December 2018

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  1. Prediction
  2. Regression

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  • (2021)Revealing the Relation Between Students’ Reading Notes and Scores Examination with NLP FeaturesAdvances in Data Science and Information Engineering10.1007/978-3-030-71704-9_2(27-41)Online publication date: 30-Oct-2021

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