Considering the usefulness of monitoring students’ response to available task-level feedback in confidence-based assessment, in this paper, we introduce a novel approach to classify students problem-solving activities into various engagement and disengagement behaviors and study their occurrences during complete learning sessions. Then by clustering these sessions, we obtained four distinct groups which varied both in terms of students’ (dis)engagement behaviors and their quantitative performance scores in confidence-based assessment. Moreover, a qualitative analysis shows that high and low-performance students (determined based on their final scores in the course) relate differently to the obtained clusters. Based on these findings we highlight that our approach of investigating students’ engagement by observing traces of performed problem-solving activities is promising and opens new avenues of research. Also, our approach is more generic as it does not contain human-expert defined time limits which are usually determined by analyzing students’ data who participated in the experimental study.
Discovering Students’ Engagement Behaviors in Confidence-based Assessment / R. Maqsood, P. Ceravolo, S. Ventura - In: 2019 IEEE Global Engineering Education Conference (EDUCON)[s.l] : IEEE, 2019. - ISBN 9781538695067. - pp. 841-846 (( Intervento presentato al 10. convegno IEEE Global Engineering Education Conference (EDUCON) tenutosi a Dubai nel 2019.
Discovering Students’ Engagement Behaviors in Confidence-based Assessment
R. Maqsood
;P. Ceravolo;
2019
Abstract
Considering the usefulness of monitoring students’ response to available task-level feedback in confidence-based assessment, in this paper, we introduce a novel approach to classify students problem-solving activities into various engagement and disengagement behaviors and study their occurrences during complete learning sessions. Then by clustering these sessions, we obtained four distinct groups which varied both in terms of students’ (dis)engagement behaviors and their quantitative performance scores in confidence-based assessment. Moreover, a qualitative analysis shows that high and low-performance students (determined based on their final scores in the course) relate differently to the obtained clusters. Based on these findings we highlight that our approach of investigating students’ engagement by observing traces of performed problem-solving activities is promising and opens new avenues of research. Also, our approach is more generic as it does not contain human-expert defined time limits which are usually determined by analyzing students’ data who participated in the experimental study.File | Dimensione | Formato | |
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