Replay-peak attention chart: A performance measure for improving online video lecture design

Nitza Geri, Orna Kopolovich, Amir Winer

نتاج البحث: نشر في مجلةمقالةمراجعة النظراء

ملخص

The ability to replay selected video segments is a major advantage of online video lectures. Replay is a learning instance that reflects active engagement. This paper develops the ‘replay-peak attention chart’ as a new performance measure of learner’s attention, based on the control chart concept, which is used for Statistical Process Control (SPC) in operations management. This study follows the design science research paradigm and employs a mixed methods methodology,
combining quantitative learning analytics with qualitative analysis of notable segment replay instances by viewers of online video lectures. An analysis of a successful Massive Open Online Course (MOOC), titled “Negotiation Management” provides a proof-of-concept for the replay-peak attention chart, as a visual heuristic tool for identifying notable learning instances. The MOOC includes Educational Entertainment (edutainment) in the form of negotiation simulations
which are presented as sitcoms and are meant to increase learner engagement. From an attention economy perspective, the replay-peak attention chart may help instructors and designers to focus their limited attention resources on segments of online video lecture sessions that may require pedagogical interventions. This paper critically discusses the replay-peak attention chart conceptualization and its initial proof-of-concept. It suggests future research directions for substantiating the replay-peak attention chart and investigating the effect of edutainment on online learning. The replay-peak attention chart is a dynamic descriptive performance measure, which has a promising potential to improve the design of effective online video lectures as an e-learning resource.
اللغة الأصليةإنجليزيّة أمريكيّة
الصفحات (من إلى)1-15
عدد الصفحات15
دوريةOnline Journal of Applied Knowledge Management
مستوى الصوت8
رقم الإصدار1
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - 2020

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