Resource type
Thesis type
(Thesis) M.Sc.
Date created
2023-09-06
Authors/Contributors
Author: Aghaei, Kimia
Abstract
The utilization of Learning Analytics Dashboards (LADs) within the educational domain has been growing. Following the Weiners Attribution Theory, we designed LADs to understand how grades, time spent on the spent, and ability impact students' emotions and motivation who had different achievement goal orientations. We assessed this effect among students with mastery, performance-approach, and performance-avoidance goal orientations. To get an in-depth understating of students' attribution of achievement, we conducted a mixed-method study to collect multi-channel data through think-aloud interviews, surveys, and eye tracking. To delve deeper into time and ability effects, we split participants into two groups. Group one saw ability and grade, while group two saw time and grade on dashboards. Later, all participants viewed a dashboard with grades, time, and ability. Our results indicate that the time spent on the assignment plays a more effective role for students to attribute their performance to effort, compared to ability. Additionally, in order to maximize the positive effects of dashboards on motivation, considering achievement goal orientations of students is important. In the 'Time Group', students with high-mastery were the most motivated by the dashboard in which their peers were significantly better, while students with low-mastery and middle-performance avoidance were more motivated by seeing their peers performing similarly or lower than them. Among students with high mastery and low performance-avoidance, adding the 'Time' element to the dashboard increased their motivation. Students with high performance-avoidance were motivated to put in more effort when they saw peers with higher grades and lower abilities. However, participants with low mastery in the 'Ability Group' displayed high levels of demotivation.
Document
Extent
84 pages.
Identifier
etd22727
Copyright statement
Copyright is held by the author(s).
Supervisor or Senior Supervisor
Thesis advisor: Hatala, Marek
Language
English
Member of collection
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