Encouraging Teacher-Sourcing of Social Recommendations Through Participatory Gamification Design

INTELLIGENT TUTORING SYSTEMS (ITS 2021)(2021)

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摘要
Teachers and learners who search for learning materials in open educational resources (OER) repositories greatly benefit from feedback and reviews left by peers who have activated these resources in their class. Such feedback can also fuel social-based ranking algorithms and recommendation systems. However, while educational users appreciate the recommendations made by other teachers, they are not highly motivated to provide such feedback by themselves. This situation is common in many consumer applications that rely on users' opinions for personalisation. A possible solution that was successfully applied in several other domains to incentivise active participation is gamification. This paper describes for the first time the application of a comprehensive cutting-edge gamification taxonomy, in a user-centred participatory-design process of an OER system for Physics, PeTeL, used throughout Israel. Physics teachers were first involved in designing gamification features based on their preferences, helping shape the gamification mechanisms likely to enhance their motivation to provide reviews. The results informed directly the implementation of two gamification elements that were implemented in the learning environment, with a second experiment evaluating their actual effect on teachers' behaviour. After a long-term, real-life pilot of two months, teachers' response rate was measured and compared to the prior state. The results showed a statistically significant effect, with a 4X increase in the total amount of recommendations per month, even when taking into account the 'Covid-pandemic effect'.
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关键词
Gamification, Blended learning, Recommendation, Crowd-sourcing
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