Title: Investigating the impact of a mobile learner-generated-content tool on pupils' after-school English vocabulary behavioural learning patterns, learning performance and motivation: a case study

Authors: Yanjie Song; Hiroaki Ogata; Yin Yang; Kousuke Mouri

Addresses: Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong ' Academic Centre for Computing and Media Studies, Kyoto University, Japan ' Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong ' Faculty of Information Sciences, Hiroshima City University, Japan

Abstract: This paper reports on a case study of investigating the effect of a mobile learner-generated content (m-LGC) tool on pupils' after-class English as a second language (ESL) vocabulary behavioural learning patterns, learning performance and motivation. Participants were 34 students in grade 4 from two classes in a primary school in Hong Kong. Data collection included students' learning logs on the m-LGC tool, pre-and post-vocabulary tests and pre-and post-questionnaires. Both qualitative and quantitative data analysis methods were adopted. An active group (AG) and a passive group (PG) were categorised based on visualisation and the number of student created learning logs. The results show that: 1) student behavioural learning patterns varied across AG and PG; 2) students in the AG made significant improvement in their learning performance, but those in the PG did not; 3) student learning motivation in the AG was improved, but that in the PG dropped significantly.

Keywords: vocabulary learning; mobile learner-generated-content tool; m-LGC; behavioural learning patterns; visualisation tool; motivation.

DOI: 10.1504/IJMLO.2023.131855

International Journal of Mobile Learning and Organisation, 2023 Vol.17 No.3, pp.406 - 425

Received: 07 Sep 2021
Accepted: 29 Nov 2021
Published online: 04 Jul 2023 *

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