Mobile Learning in Higher Education: A Classification Framework for Learning Applications

Bachelor Thesis (2021)
Author(s)

E.M.D. Toledo (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

M.M. Specht – Mentor (TU Delft - Web Information Systems)

E.B.K. Tan – Mentor (TU Delft - Web Information Systems)

M.A. Migut – Graduation committee member (TU Delft - Computer Science & Engineering-Teaching Team)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2021 Denise Toledo
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Denise Toledo
Graduation Date
01-07-2021
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

The focus in over two decades of mobile learning (m-learning) research has meanly been on PK-12 education. M-learning is seen as an important new development in PK-12 and higher education (HE). Yet, the ease of app identification is lacking. This paper aimed to classify different m-learning applications to ensure that they are more easily accessible to teachers. Such a framework has been proposed earlier. However, the technological approach misses, and the apps are mainly for PK-12 pupils. Thus, the current paper aimed to create a framework for (learning) apps for higher education, including their pedagogical and technological approaches. Overall, eleven different app types were identified and categorized into four main categories: practice, organization, social, and creation. Then the apps were further classified using their pedagogical design and instructional approach. The applications can be identified as skill-, content- or function-based applications with overlap in the different categories. Finally, the mobile platform and the features used were analyzed and included in the framework here it was found that most of the apps were hybrid applications which allow for a diverse set of features for the apps. Web based applications are the least prominent and provide the least amount of features.

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