Insights into undergraduate pathways using course load analytics-Reference-Cited by-同舟云学术

Insights into undergraduate pathways using course load analytics

Published:2023-03-13 Issue: Volume: Page:
ISSN:
Container-title:LAK23: 13th International Learning Analytics and Knowledge Conference
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Author:

Borchers Conrad¹^ORCID,Pardos Zachary A.²^ORCID

Affiliation:

1. Carnegie Mellon University, United States

2. University of California, Berkeley, United States

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3576050.3576081

Reference51 articles.

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3. Dropouts and turnover: The synthesis and test of a causal model of student attrition

4. Shahab Boumi and Adan Vela . 2019. Application of Hidden Markov Models to Quantify the Impact of Enrollment Patterns on Student Performance . International Educational Data Mining Society ( 2019 ). Shahab Boumi and Adan Vela. 2019. Application of Hidden Markov Models to Quantify the Impact of Enrollment Patterns on Student Performance. International Educational Data Mining Society (2019).

5. Shahab Boumi and Adan Ernesto Vela . 2021 . Quantifying the Impact of Students’ Semester Course Load on Their Academic Performance. In 2021 ASEE Virtual Annual Conference Content Access. Shahab Boumi and Adan Ernesto Vela. 2021. Quantifying the Impact of Students’ Semester Course Load on Their Academic Performance. In 2021 ASEE Virtual Annual Conference Content Access.

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