Identifying Students' Persistence Profiles in Problem Solving Task

This study explores task persistence in the context of Learning by Teaching. Using features extracted from students' interaction logs, a centroid based clustering algorithm derived two well-separated groups describing two types of students, Cluster 1 which is characterized by the more persisten...

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Main Authors:	Dumdumaya, Cristina E, Banawan, Michelle P, Rodrigo, Ma. Mercedes T
Format:	text
Published:	Archīum Ateneo 2018
Subjects:	Applied computing Education Computer-managed instruction Computer Sciences
Online Access:	https://archium.ateneo.edu/discs-faculty-pubs/42 https://dl.acm.org/doi/10.1145/3213586.3225237
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Institution:	Ateneo De Manila University

id	ph-ateneo-arc.discs-faculty-pubs-1041
record_format	eprints
spelling	ph-ateneo-arc.discs-faculty-pubs-10412020-04-02T05:37:22Z Identifying Students' Persistence Profiles in Problem Solving Task Dumdumaya, Cristina E Banawan, Michelle P Rodrigo, Ma. Mercedes T This study explores task persistence in the context of Learning by Teaching. Using features extracted from students' interaction logs, a centroid based clustering algorithm derived two well-separated groups describing two types of students, Cluster 1 which is characterized by the more persistent students and Cluster 0 which is characterized by the less persistent students. The more persistent students demonstrated effective help-seeking behavior, and greater level of task engagement and resourcefulness compared to the less persistent students. 2018-07-01T07:00:00Z text https://archium.ateneo.edu/discs-faculty-pubs/42 https://dl.acm.org/doi/10.1145/3213586.3225237 Department of Information Systems & Computer Science Faculty Publications Archīum Ateneo Applied computing Education Computer-managed instruction Computer Sciences
institution	Ateneo De Manila University
building	Ateneo De Manila University Library
continent	Asia
country	Philippines Philippines
content_provider	Ateneo De Manila University Library
collection	archium.Ateneo Institutional Repository
topic	Applied computing Education Computer-managed instruction Computer Sciences
spellingShingle	Applied computing Education Computer-managed instruction Computer Sciences Dumdumaya, Cristina E Banawan, Michelle P Rodrigo, Ma. Mercedes T Identifying Students' Persistence Profiles in Problem Solving Task
description	This study explores task persistence in the context of Learning by Teaching. Using features extracted from students' interaction logs, a centroid based clustering algorithm derived two well-separated groups describing two types of students, Cluster 1 which is characterized by the more persistent students and Cluster 0 which is characterized by the less persistent students. The more persistent students demonstrated effective help-seeking behavior, and greater level of task engagement and resourcefulness compared to the less persistent students.
format	text
author	Dumdumaya, Cristina E Banawan, Michelle P Rodrigo, Ma. Mercedes T
author_facet	Dumdumaya, Cristina E Banawan, Michelle P Rodrigo, Ma. Mercedes T
author_sort	Dumdumaya, Cristina E
title	Identifying Students' Persistence Profiles in Problem Solving Task
title_short	Identifying Students' Persistence Profiles in Problem Solving Task
title_full	Identifying Students' Persistence Profiles in Problem Solving Task
title_fullStr	Identifying Students' Persistence Profiles in Problem Solving Task
title_full_unstemmed	Identifying Students' Persistence Profiles in Problem Solving Task
title_sort	identifying students' persistence profiles in problem solving task
publisher	Archīum Ateneo
publishDate	2018
url	https://archium.ateneo.edu/discs-faculty-pubs/42 https://dl.acm.org/doi/10.1145/3213586.3225237
_version_	1728621353213362176

Identifying Students' Persistence Profiles in Problem Solving Task

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