Learning in MOOCS: An exploratory analysis of participation patterns and their relation to demographic variables and other influential factors

Haniya, Samaa

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https://hdl.handle.net/2142/104811 Copy

Description

Title

Learning in MOOCS: An exploratory analysis of participation patterns and their relation to demographic variables and other influential factors

Author(s)

Haniya, Samaa

Issue Date

2019-04-14

Director of Research (if dissertation) or Advisor (if thesis)

Paquette, Luc

Doctoral Committee Chair(s)

Cope, William

Committee Member(s)

• McCarthy, Cameron
• Hood, Denice

Department of Study

Educ Policy, Orgzn & Leadrshp

Discipline

Educ Policy, Orgzn & Leadrshp

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

MOOCs, Participation Patterns.

Abstract

One of the recent innovations taking place in higher education is the phenomenon of Massive Open Online Courses, known as MOOCs. MOOCs have grown rapidly over the last several years and have become a popular topic in media and academic research. Much has been said about MOOCs in terms of their impact and reach with a wide range of opinions between supporters and opponents (Daniel, 2012; Liyanagunawardena, Adams, & Williams, 2013; Yuan & Powell, 2013; Chen 2014; Hvam, 2015;). However, there is a lack of research capturing the dynamic of learning and the different ways learners participate in this new massive e-learning ecology. Influenced by theories of constructivism and differentiated learning approaches, this study aimed to explore the different patterns of participation among MOOC learners in the Coursera platform and identify the different demographic variables and influential factors that could relate to these patterns. Data was obtained from the data logs and survey results recorded by the Coursera platform of the session-based “Subsistence Marketplaces” MOOC. This was the first MOOC to be offered by the College of Business at the University of Illinois Urbana-Champaign in Spring of 2014. The study utilized a mixed method approach in the data analysis (Creswell 2014; Greene 2007) combining Educational Data Mining, statistical analysis and content analysis. Findings of this research revealed five different patterns of participation in MOOCs as follows: advanced, balanced, early, limited and delayed. Data analysis have also revealed that there is a relationship between the different patterns of participation and employment status, education level, and age groups, but not gender. Moreover, the content analysis of the open-ended survey questions explored multiple reasons that motivate and limit learners’ level of participation in MOOCs. The findings of this research are significant in helping to improve future iterations of MOOCs to be more flexible and transparent to the varied levels of participation that learners may need.

Graduation Semester

2019-05

Type of Resource

text

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http://hdl.handle.net/2142/104811

Copyright and License Information

Copyright 2019 Samaa Haniya

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