What motivates enrolment in programming MOOCs?

Luik, Piret; Suviste, Reelika; Lepp, Marina; Palts, Tauno; Tõnisson, Eno; Säde, Merilin; Papli, Kaspar

doi:10.1111/bjet.12600

Cited by 32 publications

(22 citation statements)

References 39 publications

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“…Therefore, the authors measured and reported these five variables in the current study. Motivation was measured by combining and consolidating key motivation items from previous validated MOOC studies (Luik et al, 2017; Milligan & Littlejohn, 2017; Watted & Barak, 2018).…”

Section: Methodsmentioning

confidence: 99%

Linking learner factors, teaching context, and engagement patterns withMOOClearning outcomes

Deng

Benckendorff

Gannaway

2020

Computer Assisted Learning

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Prior studies of MOOC learners have focused almost exclusively on behavioural and social aspects of engagement. This paper extends the scope of previous studies by adopting a multi‐dimensional, person‐centred approach to investigate learner engagement in MOOCs. An analysis of 1,452 self‐administered survey responses uncovered three prototypical categories of MOOC learners based on patterns of behavioural, cognitive, emotional and social engagement: (a) “Individually Engaged” learners, (b) “Least Engaged” learners and (c) “Wholly Engaged” learners. The study revealed significant differences among the three cohorts of MOOC participants with respect to learner factors (gender, origin, motivation), teaching context (course level, course duration, form of the assessment) and learning outcomes (course completion, perceived quality of instruction). The results of this study suggest that adopting a multi‐dimensional, person‐centred approach can be useful for researchers and practitioners to classify MOOC learners into subpopulations, design effective educational interventions that best engage different types of learners, and provide support and scaffolding to individuals with idiosyncratic or problematic engagement patterns.

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Section: Methodsmentioning

confidence: 99%

Linking learner factors, teaching context, and engagement patterns withMOOClearning outcomes

Deng

Benckendorff

Gannaway

2020

Computer Assisted Learning

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“…SPSS version 25.0 was used for statistical data analysis. First, composite scores of individual items from the FIEM scale were calculated based on seven factors (Luik et al, 2019). The second step focused on building motivation clusters from composite score results of the FIEM scale.…”

Section: Discussionmentioning

confidence: 99%

“…Studying motivation in MOOCs, it is important to understand the value and worth of the MOOC for the participant (Macdonald & Ahern, 2015). A wide range of motivations for using MOOCs has been described (Kizilcec & Schneider, 2015;Luik et al, 2019;Milligan & Littlejohn, 2017;Zheng et al, 2015). It has been found that the learners who enroll in MOOCs tend to have different motivations than learners in traditional courses (Watted & Barak, 2018).…”

Section: Motivation In Moocsmentioning

confidence: 99%

“…Motivation was measured with a Factors Influencing Enrolment in MOOC (FIEM) scale based on expectancy-value theory (Eccles & Wigfield, 2002). According to the results from confirmatory factor analysis, the scale consisted of 28 items, divided by 7 factors describing internal, external, and altruistic motivation; suitability of online learning; and social influence (Luik et al, 2019). This scale was chosen because it was based on motivational theory and covered different areas of motivation.…”

Section: Sample and Data Collectionmentioning

confidence: 99%

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Are Highly Motivated Learners More Likely to Complete a Computer Programming MOOC?

Luik

Lepp

2021

IRRODL

Self Cite

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Computer programming MOOCs attract people who have different motivations. Previous studies have hypothesized that the motivation declared before starting the course can be an important predictor of distinctive dropout rates. The aim of this study was to outline the main motivation clusters of participants in a computer programming MOOC, and to compare how these clusters differed in terms of intention to complete and actual completion rate. The sample consisted of 1,181 respondents to the pre-course questionnaire in the Introduction to Programming MOOC. A validated motivation scale, based on expectancy-value theory and k-means cluster analysis, was used to form the groups. The four identified clusters were named as Opportunity motivated (27.7%), Over-motivated (28.6%), Success motivated (19.6%) and Interest motivated (24.0%). Comparison tests and chi-square test were used to describe the differences among the clusters. There were statistically significant differences among clusters in self-evaluated probability of completion. Also, significant differences emerged among three clusters in terms of percentages of respondents who completed the MOOC. Interestingly, the completion rate was the lowest in the Over-motivated cluster. A statistically significant higher ratio of completers to non-completers was found in the Opportunity motivated, Success motivated, and Interest motivated clusters. Our findings can be useful for MOOC instructors, as a better vision of participants’ motivational profiles at the beginning of the MOOC might help to inform the MOOC design to better support different needs, potentially resulting in lower dropout rates.

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“…in order to participate and complete the course. Moreover, they tend to have different motivations than audiences in traditional courses [35]. In the context of ILMx MOOCs, we made our email communication both informative and beneficial (e.g., providing useful websites; recommended readings and activating the new Dynamic Pacing-weekly content highlight feature on edX etc.)…”

Section: Learning By Doing: Moocs In Land Managementmentioning

confidence: 99%

Sustaining a Culture of Excellence: Massive Open Online Course (MOOC) on Land Management

Lee

Vries

2019

Sustainability

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Increasing globalization and the emergence of disruptive learning technologies have derived a pedagogical paradigm shift from the conventional on-campus higher education to the digital and online higher education. Massive open online courses (MOOCs), especially, are the most notable manifestation of educational transformation. We developed a MOOC entitled Introduction to Land Management (ILMx MOOC) for potential entrants to the land management domain, or for those who simply want to become aware of land-related challenges and brought together with thousands of participants worldwide with freely accessible course content and rooms for open discussion. Our experience with ILMx MOOC has accumulated new knowledge and insight across a broad range of questioning on how to design and develop alternative courseware and teach using digital learning technologies in land management. This paper examines an account of emerging patterns of demographics, geography, and course engagement throughout the ILMx MOOC. We found that the subject of land management in digital higher education affects gender gaps in enrolments. We also assume that the topic of land management has been globally recognized as an important nexus to guide professionals in international development studies and practices as well as sustainability research. However, new behavioral patterns of learners were also observed. They participated in the learning process very enthusiastically only during the first month of the course and this seems to be due to lack of motivation and interest to induce learners efficiently into the learning content. We believe that the culture of excellence in land management needs to be accompanied by engaged excellence and new forms of educational culture and work processes. This means that the high-quality and rigorous knowledge we produce and accumulate is coupled closely with new styles of educational development and delivery, new types of resources and hardware, and extensive engagement with countries, localities, people, and practices of those who handle land matters.

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What motivates enrolment in programming MOOCs?

Cited by 32 publications

References 39 publications

Linking learner factors, teaching context, and engagement patterns withMOOClearning outcomes

Linking learner factors, teaching context, and engagement patterns withMOOClearning outcomes

Are Highly Motivated Learners More Likely to Complete a Computer Programming MOOC?

Sustaining a Culture of Excellence: Massive Open Online Course (MOOC) on Land Management

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