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Beyond Time on Task: A Novel Analytical Framework for Assessing Student Workload and Its Relationship with Learning

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Beyond Time on Task: A Novel Analytical Framework for Assessing Student Workload and Its Relationship with Learning
Γλώσσα: English
Συγγραφείς: Paul V. Sargent (ORCID 0009-0003-6312-2136), Isabel Hilliger (ORCID 0000-0001-5270-7655), Jorge A. Baier (ORCID 0000-0002-6280-5619)
Πηγή: Journal of Learning Analytics. 2026 13(1):110-129.
Διαθεσιμότητα: Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: https://learning-analytics.info/index.php/JLA/index
Peer Reviewed: Y
Page Count: 21
Ημερομηνία έκδοσης: 2026
Τύπος εγγράφου: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Student Responsibility, Time on Task, Foreign Countries, Higher Education, College Students, Engineering Education, Student Attitudes, Learning Management Systems, Measurement Techniques, Self Evaluation (Individuals), Time Factors (Learning), Difficulty Level
Γεωγραφικοί όροι: Chile
ISSN: 1929-7750
Περίληψη: Student workload analysis has the potential to play a crucial role in providing both actionable insights to inform course design and curricular adjustments that promote student learning and well-being. While numerous studies have emphasized the need for analyzing workload beyond single-value metrics, such as credit hours, the interpretation and practical application of these metrics for educational interventions remains unclear. In this study, we explore the interplay between time-on-task measurements with student-perceived learning and difficulty. We move beyond average indicators of time-on-task by proposing and examining various metrics related to the dynamics of workload over time. Across 14 engineering courses taught at Pontificia Universidad Catolica de Chile, we analyze three different sources of data: (1) self-reported time-on-task and perceived difficulty obtained through a weekly timesheet survey, (2) interactions with the learning management system (LMS), and (3) perceived learning attainment obtained from the course evaluation survey. Our results show that LMS-based and self-reported time-on-task were highly correlated. Also, workload dynamics metrics, such as the presence of workload peaks, were highly correlated with perceived learning and perceived difficulty. As such, this study provides evidence in support of considering workload dynamics, rather than average measures of time-on-task, to predict variables related to student learning. The metrics proposed by this framework could be used to implement practical tools for educators and administrators willing to optimize course design and improve learning attainment.
Abstractor: As Provided
Entry Date: 2026
Αριθμός Καταχώρησης: EJ1516637
Βάση Δεδομένων: ERIC
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  Data: <searchLink fieldCode="AR" term="%22Paul+V%2E+Sargent%22">Paul V. Sargent</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0003-6312-2136">0009-0003-6312-2136</externalLink>)<br /><searchLink fieldCode="AR" term="%22Isabel+Hilliger%22">Isabel Hilliger</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5270-7655">0000-0001-5270-7655</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jorge+A%2E+Baier%22">Jorge A. Baier</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-6280-5619">0000-0002-6280-5619</externalLink>)
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  Data: Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: https://learning-analytics.info/index.php/JLA/index
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  Data: Student workload analysis has the potential to play a crucial role in providing both actionable insights to inform course design and curricular adjustments that promote student learning and well-being. While numerous studies have emphasized the need for analyzing workload beyond single-value metrics, such as credit hours, the interpretation and practical application of these metrics for educational interventions remains unclear. In this study, we explore the interplay between time-on-task measurements with student-perceived learning and difficulty. We move beyond average indicators of time-on-task by proposing and examining various metrics related to the dynamics of workload over time. Across 14 engineering courses taught at Pontificia Universidad Catolica de Chile, we analyze three different sources of data: (1) self-reported time-on-task and perceived difficulty obtained through a weekly timesheet survey, (2) interactions with the learning management system (LMS), and (3) perceived learning attainment obtained from the course evaluation survey. Our results show that LMS-based and self-reported time-on-task were highly correlated. Also, workload dynamics metrics, such as the presence of workload peaks, were highly correlated with perceived learning and perceived difficulty. As such, this study provides evidence in support of considering workload dynamics, rather than average measures of time-on-task, to predict variables related to student learning. The metrics proposed by this framework could be used to implement practical tools for educators and administrators willing to optimize course design and improve learning attainment.
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        PageCount: 21
        StartPage: 110
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      – SubjectFull: Student Responsibility
        Type: general
      – SubjectFull: Time on Task
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      – SubjectFull: Foreign Countries
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      – SubjectFull: Chile
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