Modeling Student Persistence in a Learning-By-Teaching Environment
Persistence is a non-cognitive attribute referring to one's disposition to attain a specific goal despite challenges and difficulties. Persistence is of particular interest and importance because of its relationship to students' academic achievement and other individual and societal outcom...
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Archīum Ateneo
2018
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ph-ateneo-arc.quality-education-10072022-03-08T03:09:37Z Modeling Student Persistence in a Learning-By-Teaching Environment Dumdumaya, Cristina E Persistence is a non-cognitive attribute referring to one's disposition to attain a specific goal despite challenges and difficulties. Persistence is of particular interest and importance because of its relationship to students' academic achievement and other individual and societal outcomes. Despite claims that persistence is a highly valuable skill, quantitative studies on persistence in technology enhanced learning environments are limited. This study will attempt to build a quantitative model of persistence utilizing machine learning and related methodologies using features distilled from students' domain knowledge assessments and system logs from their use of an Intelligent Tutoring System. The results of the study could potentially provide additional insights on learners' persistence, the factors that influence student persistence, and what interventions to employ to induce learners to persist in tasks. 2018-07-01T07:00:00Z text https://archium.ateneo.edu/quality-education/1 https://dl.acm.org/doi/10.1145/3209219.3213596 Goal 4: Quality Education Archīum Ateneo Education |
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Persistence is a non-cognitive attribute referring to one's disposition to attain a specific goal despite challenges and difficulties. Persistence is of particular interest and importance because of its relationship to students' academic achievement and other individual and societal outcomes. Despite claims that persistence is a highly valuable skill, quantitative studies on persistence in technology enhanced learning environments are limited. This study will attempt to build a quantitative model of persistence utilizing machine learning and related methodologies using features distilled from students' domain knowledge assessments and system logs from their use of an Intelligent Tutoring System. The results of the study could potentially provide additional insights on learners' persistence, the factors that influence student persistence, and what interventions to employ to induce learners to persist in tasks. |
format |
text |
author |
Dumdumaya, Cristina E |
author_facet |
Dumdumaya, Cristina E |
author_sort |
Dumdumaya, Cristina E |
title |
Modeling Student Persistence in a Learning-By-Teaching Environment |
title_short |
Modeling Student Persistence in a Learning-By-Teaching Environment |
title_full |
Modeling Student Persistence in a Learning-By-Teaching Environment |
title_fullStr |
Modeling Student Persistence in a Learning-By-Teaching Environment |
title_full_unstemmed |
Modeling Student Persistence in a Learning-By-Teaching Environment |
title_sort |
modeling student persistence in a learning-by-teaching environment |
publisher |
Archīum Ateneo |
publishDate |
2018 |
url |
https://archium.ateneo.edu/quality-education/1 https://dl.acm.org/doi/10.1145/3209219.3213596 |
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1728621367634427904 |