Towards seamless vocabulary learning: how we can entwine in-class and outside-of-class learning

  • Authors:

  • Noriko Uosaki;Hiroaki Ogata;Taro Sugimoto;Mengmeng Li;Bin Hou

  • Affiliations:

  • Department of Information Science and Intelligent Systems, Faculty of Engineering, The University of Tokushima, 2-1 Minamijosanjima-cho, Tokushima 770-8506, Japan.;Department of Information Science and Intelligent Systems, Faculty of Engineering, The University of Tokushima, 2-1 Minamijosanjima-cho, Tokushima 770-8506, Japan.;Department of Information Science and Intelligent Systems, Faculty of Engineering, The University of Tokushima, 2-1 Minamijosanjima-cho, Tokushima 770-8506, Japan.;Department of Information Science and Intelligent Systems, Faculty of Engineering, The University of Tokushima, 2-1 Minamijosanjima-cho, Tokushima 770-8506, Japan.;Department of Information Science and Intelligent Systems, Faculty of Engineering, The University of Tokushima, 2-1 Minamijosanjima-cho, Tokushima 770-8506, Japan

  • Venue:
  • International Journal of Mobile Learning and Organisation
  • Year:
  • 2012

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Abstract

This paper proposes Seamless Mobile-Assisted Language Learning Support System (SMALL system), which aims to entwine in-class learning with out-of-class learning. Learners upload what they have learned out-of-class to the SMALL system and then it supports linking out-of-class vocabulary learning with in-class one. It also links students' self-learning with that of others. This linking function is significant because we need to encounter as many different contexts as possible to build up vocabulary. It also supports retaining vocabulary in long-term memory by giving quizzes. The evaluation of this system showed that the experimental group uploaded less words, but learned more words than the control group and that the entwining function showed statistically significant effectiveness when excluding two exceptional cases. The subjects predominantly used mobile devices during out-of-class learning, which supports what is generally believed that mobile devices are more fitting tools for vocabulary learning than PCs.