Coarse-grained detection of student frustration in an introductory programming course
We attempt to automatically detect student frustration, at a coarse-grained level, using measures distilled from student behavior within a learning environment for introductory programming. We find that each student's average level of frustration across five lab exercises can be detected based...
Saved in:
Main Authors: | , |
---|---|
Format: | text |
Published: |
Archīum Ateneo
2009
|
Subjects: | |
Online Access: | https://archium.ateneo.edu/discs-faculty-pubs/95 https://dl.acm.org/doi/abs/10.1145/1584322.1584332 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Ateneo De Manila University |
id |
ph-ateneo-arc.discs-faculty-pubs-1094 |
---|---|
record_format |
eprints |
spelling |
ph-ateneo-arc.discs-faculty-pubs-10942020-06-23T08:15:03Z Coarse-grained detection of student frustration in an introductory programming course Rodrigo, Ma. Mercedes T Baker, Ryan S We attempt to automatically detect student frustration, at a coarse-grained level, using measures distilled from student behavior within a learning environment for introductory programming. We find that each student's average level of frustration across five lab exercises can be detected based on the number of pairs of consecutive compilations with the same edit location, the number of pairs of consecutive compilations with the same error, the average time between compilations and the total number of errors. Attempts to detect frustration at a finer grain-size, identifying individual students' fluctuations in frustration between labs, were less successful. These results indicate that it is possible to detect frustration at a coarse-grained level, solely from coarse-grained data about students' behavior within a learning environment. 2009-01-01T08:00:00Z text https://archium.ateneo.edu/discs-faculty-pubs/95 https://dl.acm.org/doi/abs/10.1145/1584322.1584332 Department of Information Systems & Computer Science Faculty Publications Archīum Ateneo Computer Sciences |
institution |
Ateneo De Manila University |
building |
Ateneo De Manila University Library |
country |
Philippines |
collection |
archium.Ateneo Institutional Repository |
topic |
Computer Sciences |
spellingShingle |
Computer Sciences Rodrigo, Ma. Mercedes T Baker, Ryan S Coarse-grained detection of student frustration in an introductory programming course |
description |
We attempt to automatically detect student frustration, at a coarse-grained level, using measures distilled from student behavior within a learning environment for introductory programming. We find that each student's average level of frustration across five lab exercises can be detected based on the number of pairs of consecutive compilations with the same edit location, the number of pairs of consecutive compilations with the same error, the average time between compilations and the total number of errors. Attempts to detect frustration at a finer grain-size, identifying individual students' fluctuations in frustration between labs, were less successful. These results indicate that it is possible to detect frustration at a coarse-grained level, solely from coarse-grained data about students' behavior within a learning environment. |
format |
text |
author |
Rodrigo, Ma. Mercedes T Baker, Ryan S |
author_facet |
Rodrigo, Ma. Mercedes T Baker, Ryan S |
author_sort |
Rodrigo, Ma. Mercedes T |
title |
Coarse-grained detection of student frustration in an introductory programming course |
title_short |
Coarse-grained detection of student frustration in an introductory programming course |
title_full |
Coarse-grained detection of student frustration in an introductory programming course |
title_fullStr |
Coarse-grained detection of student frustration in an introductory programming course |
title_full_unstemmed |
Coarse-grained detection of student frustration in an introductory programming course |
title_sort |
coarse-grained detection of student frustration in an introductory programming course |
publisher |
Archīum Ateneo |
publishDate |
2009 |
url |
https://archium.ateneo.edu/discs-faculty-pubs/95 https://dl.acm.org/doi/abs/10.1145/1584322.1584332 |
_version_ |
1681506668842582016 |