A research framework of pair learning in robotics education
by Liying Xia; Baichang Zhong
International Journal of Smart Technology and Learning (IJSMARTTL), Vol. 1, No. 4, 2019

Abstract: Currently, traditional cooperative learning faces some problems in robotics education (RE), e.g., free-rider issue, conflicts of interest, fixed roles, and negative groupthink effects. In view of this, we propose the methodology of pair learning (PL), in which students cooperate in pairs to construct, build and program a robot under scripted but switchable roles. A research framework was designed to further explore the mechanism and effectiveness of PL in RE. The framework covered four research perspectives of PL, including role assignment and role switching strategy, grouping strategy, the integration strategy of PL and coopetition, and the effectiveness of PL. On this basis, five groups of true experiments or quasi-experiments were designed. In addition, five data collection methods were introduced to evaluate students' performances from the perspectives of artefacts, attitude towards RE, immersion/attention, compatibility of groups, and cognitive load. It is hoped that this paper will enrich the teaching model of RE and provide new guidance for promoting the healthy development of RE.

Online publication date: Thu, 09-Apr-2020

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