Active learners’ characterization in MOOC forums and their generated knowledge

Cohen, Anat; Shimony, Udi; Nachmias, Rafi; Soffer, Tal

doi:10.1111/bjet.12670

Cited by 53 publications

(37 citation statements)

References 38 publications

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“…Learners who watched videos the same day each week (Loya, Gopal, Shukla, Jermann, & Tormey, 2015), scored higher on the first assignment (Skrypnyk et al, 2015) and completed assignments frequently (Tseng et al, 2016) were more likely to complete a MOOC. From a social engagement perspective, a higher level of interaction with the instructor (Hone & El Said, 2016) and active participation in forum discussion (Cohen, Shimony, Nachmias, & Soffer, 2019; Engle, Mankoff, & Carbrey, 2015) were also found to be predictors of completion.…”

Section: Literature Reviewmentioning

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: Literature Reviewmentioning

confidence: 99%

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

Deng

Benckendorff

Gannaway

2020

Computer Assisted Learning

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“…In the e-learning communities, learners work together to enhance their understanding of learning topics, build new shared insights and solve problems (Cohen, Shimony, Nachmias & Soffer, 2019b). In Coursera, a learning community can be formed and characterized by a culture of collaborative and social learning, which may help the learning process (Kissinger & Bennett, 2014).…”

Section: Related Work E-learning Communitiesmentioning

confidence: 99%

Leveraging personality information to improve community recommendation in e‐learning platforms

Sun¹,

Geng²,

Cheng³

et al. 2020

Brit J Educational Tech

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E‐learning platforms are becoming more and more important and they are gradually changing people’s learning ways. In the e‐learning platforms, users actively create and join their favorite communities to share their questions and ideas. With the increase of users of e‐learning platforms, the number of communities is increasing dramatically. In this context, it has become difficult for users to find learning communities that match their interests and preferences. Therefore, how to effectively recommend the learning community for users has become an urgent need. However, compared to learning item recommendation, there is relatively limited work on learning community recommendation, and the existing research on community recommendation often ignores the personality information. Personality is considered one of the primary factors that influence human behavior and social relationships, as it affects how people react and interact with others. Several studies have demonstrated that people with similar personality tend to have similar interests. Furthermore, homophily theory also states that social interactions between similar individuals occur at a higher rate than among dissimilar ones. Since interests and interactions are important driving forces for users to join the learning communities, personality has an important impact on users’ choices of communities. Therefore, this paper aims at shedding some light on the impact of personality information on the accuracy of community recommendations. Particularly, we propose three enhanced matrix factorization models based on the Big Five personality framework. To evaluate the effectiveness of our proposed models, we conducted extensive experiments on myPersonality datasets. The results prove that the personality information can improve the performance of the learning community recommendation model and alleviate the data sparsity problem.

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“…The use of open problems is a matter that is very much considered in learning. The use of open questions in the form of descriptions can provide a space for students to develop strategies and student communication skills (Li, Ren and Wang, 2018;Cohen et al, 2019;Wenting and Lijuan, 2019). Students must be required to have arguments that support problem solving and can communicate the thought process in solving problems.…”

Section: The Need For 4cs Skill In the Heutagogical Approachmentioning

confidence: 99%

Analysis of the Necessity for Heutagogical Approach Through 4Cs Skills as Innovation for Vocational Lectures in the Education 4.0

Putra¹,

Syafrudie²,

Yunos³

et al. 2019

Proceedings of the 1st Vocational Education International Conference (VEIC 2019)

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This study aims to: (1) analyze the level of need for the heutagogical approach through 4Cs on aspects of creativity; (2) analyze the level of needs of the heutagogical approach through 4Cs in the communication aspect; (3) analyze the level of needs of the heutagogical approach through 4Cs in aspects of critical thinking; and (4) analyze the level of need for the heutagogical approach through 4Cs in the collaboration aspect. This study uses a qualitative method. Data collection techniques with interviews, literature review, documentation, and observation. Informants included lecturers, students, and stakeholders at the State University of Malang and used a sampling technique namely purposive sample. Data analysis techniques used are data reduction, data interpretation, and triangulation. Conclusions from this study indicate that: (1) the level of need for aspects of creativity includes the ability to: develop ideas (83.6%), express creative ideas (81.2%), adapt to new environments (88.2%), and creative independence (88.4%); (2) the level of need for communication aspect includes the ability to convey information (79.8%), express ideas (82.2%), accept opinions (84.2%), master various communication techniques (78.1%); (3) the level of need for Critical Thinking aspects including the ability to: evaluate (90.1%), identify problems (89.2%), solve problems (92.2%), distinguish facts from assessment (82.8%); and (4) the level of need for the Collaboration aspect includes the ability to: cooperate (89.6%), full responsibility (84.2%), respect differences (82.2%), discuss (87.6%).

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Active learners’ characterization in MOOC forums and their generated knowledge

Cited by 53 publications

References 38 publications

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

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

Leveraging personality information to improve community recommendation in e‐learning platforms

Analysis of the Necessity for Heutagogical Approach Through 4Cs Skills as Innovation for Vocational Lectures in the Education 4.0

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