Delving into Participants’ Profiles and Use of Social Tools in MOOCs

Alario-Hoyos, Carlos; Pérez‐Sanagustín, Mar; Kloos, Carlos Delgado; G, Hugo A. Parada; Muñoz-Organero, Mario

doi:10.1109/tlt.2014.2311807

Cited by 91 publications

(87 citation statements)

References 8 publications

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“…The study of the academic engagement of students in Massive Open Online Courses (MOOCs) has already been tackled from different perspectives in the literature [1,2,6,7,14,17,18]. With this aim, various engagement indicators that describe different observable behaviors of MOOC students were employed.…”

Section: Introductionmentioning

confidence: 99%

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Predicting the decrease of engagement indicators in a MOOC

Bote‐Lorenzo

Gómez‐Sánchez

2017

Proceedings of the Seventh International Learning Analytics &Amp; Knowledge Conference

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Predicting the decrease of students' engagement in typical MOOC tasks such as watching lecture videos or submitting assignments is key to trigger timely interventions in order to try to avoid the disengagement before it takes place. This paper proposes an approach to build the necessary predictive models using students' data that becomes available during a course. The approach was employed in an experimental study to predict the decrease of three different engagement indicators in a MOOC. The results suggest its feasibility with values of area under the curve for different predictors ranging from 0.718 to 0.914.

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Section: Introductionmentioning

confidence: 99%

“…Another important finding is that the values of engagement indicators of many MOOC students decay over time often leading to dropping out [1,6,7,14,17,18]. As a consequence, the educational impact that the MOOC has in these disengaging learners is reduced, even if they do not eventually drop out.…”

Section: Introductionmentioning

confidence: 99%

Predicting the decrease of engagement indicators in a MOOC

Bote‐Lorenzo

Gómez‐Sánchez

2017

Proceedings of the Seventh International Learning Analytics &Amp; Knowledge Conference

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“…However, since the appearance of the first MOOC in 2008 (Connectivism and Connective Knowledge -CCK08), many authors have explored the benefits of using active pedagogies in this type of courses claiming that these pedagogies have a positive influence in various facets such as students' engagement [10]. The analysis of collaboration among students shows that social participation has a positive influence into student performance [1]. Some studies have focused on the students' preferences [11] finding that learners demand more opportunities for discussing in groups.…”

Section: Introductionmentioning

confidence: 99%

Automatic Group Formation in a MOOC Based on Students’ Activity Criteria

Sanz-Martínez

Martínez‐Monés

Bote‐Lorenzo

et al. 2017

Data Driven Approaches in Digital Education

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Abstract. Although there is significant evidence regarding benefits of small group collaboration in small-scale contexts, several challenges have been detected about the use of collaborative learning in MOOCs. Group formation, which is a crucial activity in order to achieve effective collaboration, is scarcely covered in MOOC platforms, which do not allow the formation of teams using criteria defined by the instructors. This paper presents an exploratory study conducted in a seven-week MOOC, comparing our group formation proposal, based on students' activity criteria, to a baseline grouping function provided by the platform. We analyse the impact of each grouping approach over group performance, group activity, and student satisfaction. The results show initial evidence about the advantages of using the criteria-based group formation approach regarding student satisfaction and group interactions.

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“…Twitter has been used to connect peers and share information, such as resources or comments on their personal and real-time status (Lin, Hoffman, & Borengasser, 2013). Facebook was found to have a greater impact than Twitter (Alario-Hoyos, Pérez-Sanagustín, Delgado Kloos, & Munoz-Organero, 2014;Salmon, Ross, Pechenkina, & Chase, 2015), and also more useful according to MOOC learners (Liu et al, 2016). MOOC learners also reported that the social networking tools had a positive impact on the social aspects of their learning process (Brownell & Swaner, 2010;Dodge & Kendall, 2004;Kassens-Noor, 2012) but they preferred to use the social medium to which they were already accustomed (Veletsianos & Navarrete, 2012).…”

Section: Tools For Interactionmentioning

confidence: 99%

Decision, Implementation, and Confirmation: Experiences of Instructors behind Tourism and Hospitality MOOCs

Lin

Cantoni

2018

IRRODL

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As the popularity of Massive Open Online Courses (MOOCs) continues to grow, studies are emerging to investigate various topics in this area. Most have focused on the learners' perspective, leaving a gap in the literature about MOOC instructors. The current research-conducted in the field of tourism and hospitality-explored early experiences of MOOC instructors as they progressed through three stages of the innovation-decision process: decision, implementation, and confirmation. The tourism and hospitality field was chosen because its related industries contribute significantly to global employment, and training is one of their critical success factors. MOOCs possess a good potential to benefit tourism and hospitality education, yet tourism and hospitality MOOCs are under-researched. Semi-structured interviews were conducted with six instructors who offered tourism and hospitalityMOOCs between 2008 and 2015. Findings revealed that: (1) the instructors' decisions to offer MOOCs were mostly influenced by their institutes' interests in MOOCs; (2) when the instructors implemented MOOCs, a pattern of action emerged, which included six phases and one cross-phase elementprepare, design, develop, launch, deliver, and evaluate-and across phases-support and train; (3) most instructors chose to avoid risk in their adoption and implementation of the MOOCs, staying away from innovative teaching or learning activities such as peer-review assessments and collaborative activities; and (4) half of the instructors intended to repeat the experience of teaching in the MOOCs format in the future.

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Delving into Participants’ Profiles and Use of Social Tools in MOOCs

Cited by 91 publications

References 8 publications

Predicting the decrease of engagement indicators in a MOOC

Predicting the decrease of engagement indicators in a MOOC

Automatic Group Formation in a MOOC Based on Students’ Activity Criteria

Decision, Implementation, and Confirmation: Experiences of Instructors behind Tourism and Hospitality MOOCs

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