Technology-enhanced learning: Using learning analytics to unveil students’ use of multiple devices in blended learning

Author: 
Date created: 
2019-11-26
Identifier: 
etd20636
Keywords: 
Multi-device use
Mobile Learning
Learning Analytics
Learner Models
Blended Learning
Seamless Learning
Trace Analysis
Temporal Analysis
Abstract: 

In recent times, there has been a substantial interest in capitalizing on the abundance and the ubiquity of mobile and personal technologies for their educational use. Even though use of emerging technologies in education is associated with emerging educational practices, their role in educational setting is still largely under-researched. This doctoral research aims to bridge this gap in knowledge by understanding the learning habits and behaviours of students using different devices (such as desktops, tablets, mobile) for learning. Our first goal is to explore how mobile devices are used when regulating learning via learning management systems (LMS) in the context of blended learning. To do so, we examine the extent to which various technological modalities (including mobile devices, tablets, desktops) are either used sequentially and/or simultaneously to influence the overall academic performance and study habits at various learning activities. Next, with the intent of understanding associations between temporal patterns and modality preferences, our second goal is to assess how learning takes place during different times of the day and on weekdays/weekends. Further, given the substantial differences between utility of each modality for a learning activity, the fourth goal is to demonstrate how considering the modality for learning actions can lead to improvement in predictive power of learning models generated from student engagement data. Our fifth and final goal is to investigate whether preferences for a modality evolve over time and, if so, analyze the role it plays in consistency of work habits and student persistence in learning. Each of these goals has been previously published or submitted for review to a peer-reviewed journal/conference. The full texts of these studies are included in this cumulative format dissertation. In each of these studies, the log data for analyzing the aforementioned research questions was collected from undergraduate students at our university from courses that followed a blended delivery format, utilizing the university's learning management system (LMS), Canvas, to support learning activities and students' overall schoolwork. The overall aim of this thesis is to extend current theoretical understanding of the way students move between technological modalities, physical and temporal contexts and learning activities.

Document type: 
Thesis
Rights: 
This thesis may be printed or downloaded for non-commercial research and scholarly purposes. Copyright remains with the author.
File(s): 
Senior supervisor: 
Marek Hatala
Department: 
Communication, Art & Technology: School of Interactive Arts and Technology
Thesis type: 
(Thesis) Ph.D.
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