Uncovering student learning profiles with a video annotation tool: reflective learning with and without instructional norms

Mirriahi, Negin; Liaqat, Daniyal; Dawson, Shane; Gašević, Dragan

doi:10.1007/s11423-016-9449-2

Cited by 38 publications

(33 citation statements)

References 42 publications

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“…In order to identify learners' engagement patterns with videos and the video annotation tool, the following set of features indicative of students' engagement (Mirriahi et al, 2016) were computed for each user and each program module:…”

Section: Clusteringmentioning

confidence: 99%

“…The analysis of this behavioural data can provide insight into how learners engage with videos as part of their course learning activities (Brooks, Epp, Logan, & Greer, 2011;Giannakos, Chorianopoulos, & Chrisochoides, 2014. These forms of video analytics, can be extended beyond the clickstream data, such as video play, pause, forward, and rewind events, to include other associated learning activities (e.g., video annotations or invideo quizzes) (Mirriahi, Liaqat, Gašević, & Dawson, 2016). The analysis of this data can assist in developing models for early identification of learners who are not engaged or undertaking less optimal learning pathways or study behaviour.…”

Section: Introductionmentioning

confidence: 99%

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Identifying engagement patterns with video annotation activities: A case study in professional development

Mirriahi

Jovanović

Dawson

et al. 2018

AJET

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The rapid growth of blended and online learning models in higher education has resulted in a parallel increase in the use of audio-visual resources among students and teachers. Despite the heavy adoption of video resources, there have been few studies investigating their effect on learning processes and even less so in the context of academic development. This paper uses learning analytic techniques to examine how academic teaching staff engage with a set of prescribed videos and video annotations in a professional development course. The data was collected from two offerings of the course at a large research-intensive university in Australia. The data was used to identify patterns of activity and transition states as users engaged with the course videos and video annotations. Latent class analysis and hidden Markov models were used to characterise the evolution of engagement throughout the course. The results provide a detailed description of the evolution of learner engagement that can be readily translated into action aimed at increasing the quality of the learning experience.

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Section: Clusteringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identifying engagement patterns with video annotation activities: A case study in professional development

Mirriahi

Jovanović

Dawson

et al. 2018

AJET

Self Cite

View full text Add to dashboard Cite

show abstract

“…on video learning systems [8], [9], [10]. Mirriahi et al aimed to uncover students' learning profiles from the behavior logs of their video annotation tool [8], and they classified user profiles into four clusters. This study, however, was not concerned with specific video analysis.…”

Section: B Learning Analysis Of User Behaviormentioning

confidence: 99%

Response Collector: A Video Learning System for Flipped Classrooms

Okumoto

Yoshida

Umemura

et al. 2018

2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA)

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The flipped classroom has become famous as an effective educational method that flips the purpose of classroom study and homework. In this paper, we propose a video learning system for flipped classrooms, called Response Collector, which enables students to record their responses to preparation videos. Our system provides response visualization for teachers and students to understand what they have acquired and questioned. We performed a practical user study of our system in a flipped classroom setup. The results show that students preferred to use the proposed method as the inputting method, rather than naive methods. Moreover, sharing responses among students was helpful for resolving individual students' questions, and students were satisfied with the use of our system.

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“…The mentioned rapid growth in educational video content published online, it gave way for video annotation software to help students create and share their reflections about the content [62]. In the literature, there are hints of an existing relationship between note-taking (i.e., annotating) and active learning engagement [62,79,45]. To 1 the development side of the online note-taking activity, the technology that allows utilizing it for learning is already there and is progressing [62].…”

Section: Introductionmentioning

confidence: 99%

“…In the literature, there are hints of an existing relationship between note-taking (i.e., annotating) and active learning engagement [62,79,45]. To 1 the development side of the online note-taking activity, the technology that allows utilizing it for learning is already there and is progressing [62]. As part of a study by Bargeron et al.…”

Section: Introductionmentioning

confidence: 99%

NotesKB: Web-Based Semantic Annotation Tool for Online Multimedia Learning Content

Alamoudi¹

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Uncovering student learning profiles with a video annotation tool: reflective learning with and without instructional norms

Cited by 38 publications

References 42 publications

Identifying engagement patterns with video annotation activities: A case study in professional development

Identifying engagement patterns with video annotation activities: A case study in professional development

Response Collector: A Video Learning System for Flipped Classrooms

NotesKB: Web-Based Semantic Annotation Tool for Online Multimedia Learning Content

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