Early Identification of Student Struggles at the Topic Level Using Context-Agnostic Features-Reference-Cited by-同舟云学术

Early Identification of Student Struggles at the Topic Level Using Context-Agnostic Features

Published:2022-02-22 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 53rd ACM Technical Symposium on Computer Science Education
language:
Short-container-title:

Author:

Arakawa Kai¹,Hao Qiang¹,Deneke Wesley¹,Cowan Indie¹,Wolfman Steven²,Peterson Abigayle¹

Affiliation:

1. Western Washington University, Bellingham, WA, USA

2. The University of British Columbia, Vancouver, BC, Canada

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3478431.3499298

Reference44 articles.

1. Towards understanding online question & answer interactions and their effects on student performance in large-scale stem classes;David H;International Journal of Educational Technology in Higher Education,2020

2. Predicting computer science students' online help-seeking tendencies;Hao Qiang;Knowledge Management & E-Learning: An International Journal,2017

3. Exploring the Value of Different Data Sources for Predicting Student Performance in Multiple CS Courses

4. Behaviors of Higher and Lower Performing Students in CS1

5. Sally Fincher , Anthony Robins , Bob Baker , Ilona Box , Quintin Cutts , Michael de Raadt , Patricia Haden , John Hamer , Margaret Hamilton , Raymond Lister , Predictors of success in a first programming course . In Proceedings of the 8th Australasian Computing Education Conference (ACE 2006 ), volume 52 , pages 189 -- 196 . Australian Computer Society Inc. , 2006 . Sally Fincher, Anthony Robins, Bob Baker, Ilona Box, Quintin Cutts, Michael de Raadt, Patricia Haden, John Hamer, Margaret Hamilton, Raymond Lister, et al. Predictors of success in a first programming course. In Proceedings of the 8th Australasian Computing Education Conference (ACE 2006), volume 52, pages 189--196. Australian Computer Society Inc., 2006.

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. OPTES: A Tool for Behavior-based Student Programming Progress Estimation;2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC);2023-06

2. G is for Generalisation;Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1;2023-03-02

3. Relation Between Student Characteristics, Git Usage and Success in Programming Courses;Lecture Notes in Computer Science;2023

4. Retention Factors in STEM Education Identified Using Learning Analytics: A Systematic Review;Education Sciences;2022-11-03