The validity and utility of activity logs as a measure of student engagement. Motz, B., Quick, J., Schroeder, N., Zook, J., & Gunkel, M. In Proceedings of the 9th International Conference on Learning Analytics & Knowledge, pages 300-309, 3, 2019. Association for Computing Machinery.
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Paper Website doi abstract bibtex Learning management system (LMS) web logs provide granular, near-real-time records of student behavior as learners interact with online course materials in digital learning environments. However, it remains unclear whether LMS activity indeed reflects behavioral properties of student engagement, and it also remains unclear how to deal with variability in LMS usage across a diversity of courses. In this study, we evaluate whether instructors' subjective ratings of their students' engagement are related to features of LMS activity for 9,021 students enrolled in 473 for-credit courses. We find that estimators derived from LMS web logs are closely related to instructor ratings of engagement, however, we also observe that there is not a single generic relationship between activity and engagement, and what constitutes the behavioral components of “engagement” will be contingent on course structure. However, for many of these courses, modeled engagement scores are comparable to instructors' ratings in their sensitivity for predicting academic performance. As long as they are tuned to the differences between courses, activity indices from LMS web logs can provide a valid and useful proxy measure of student engagement.
@inproceedings{
title = {The validity and utility of activity logs as a measure of student engagement},
type = {inproceedings},
year = {2019},
keywords = {LMS,Student engagement,Trace data,Web logs},
pages = {300-309},
websites = {http://dl.acm.org/citation.cfm?doid=3303772.3303789},
month = {3},
publisher = {Association for Computing Machinery},
day = {4},
city = {New York, New York, USA},
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created = {2020-04-22T21:44:57.118Z},
accessed = {2020-04-21},
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last_modified = {2020-05-11T14:43:33.708Z},
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citation_key = {Motz2019},
private_publication = {false},
abstract = {Learning management system (LMS) web logs provide granular, near-real-time records of student behavior as learners interact with online course materials in digital learning environments. However, it remains unclear whether LMS activity indeed reflects behavioral properties of student engagement, and it also remains unclear how to deal with variability in LMS usage across a diversity of courses. In this study, we evaluate whether instructors' subjective ratings of their students' engagement are related to features of LMS activity for 9,021 students enrolled in 473 for-credit courses. We find that estimators derived from LMS web logs are closely related to instructor ratings of engagement, however, we also observe that there is not a single generic relationship between activity and engagement, and what constitutes the behavioral components of “engagement” will be contingent on course structure. However, for many of these courses, modeled engagement scores are comparable to instructors' ratings in their sensitivity for predicting academic performance. As long as they are tuned to the differences between courses, activity indices from LMS web logs can provide a valid and useful proxy measure of student engagement.},
bibtype = {inproceedings},
author = {Motz, Benjamin and Quick, Joshua and Schroeder, Noah and Zook, Jordon and Gunkel, Matthew},
doi = {10.1145/3303772.3303789},
booktitle = {Proceedings of the 9th International Conference on Learning Analytics & Knowledge}
}Downloads: 0
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