Proceedings of the 9th International Conference on Language, Innovation, Culture & Education 2018

Contextualised MALL Quantitative Evaluation Tool for L2 Chinese

Orit Ezra, Anat Cohen

Tel Aviv University, Israel


Contextualised Mobile Assisted Language Learning (MALL) has been known for its potential in language learning pedagogies rooted in social constructivism theories. However a consistent approach to constituents of contextualised MALL in addition to an operative and quantitative tool to evaluate it is seemingly missing in reported case studies. The purpose of the present research is to present an index for analysing, designing and evaluating contextualised MALL drawing upon integration of existing literature of context definitions. Accordingly, real world and real life contexts variables were analysed in both Taiwan – where learners’ L2 (Chinese) is the spoken language and in Israel – where learners’ L1 (Hebrew) is the spoken language. Empirical data collected using a fully structured interview from 53 Chinese L2 students in Taiwan and Israel encompassing 296 types of MALL activities performed by students, was used to develop the contextualised MALL index for measuring real world and real life context learning. This measuring index was established in a combined top-down and bottom-up process, using context pre-defined literature augmented with students stories. Real world was measured by amount of activity content relation to the place, typical or non-typical objects of the place and typical situations at the place. Real life was measured by the degree of other tools assisting in another core activity which purpose was not learning. The paper presents the developed index, with preliminary examples illustrating their application. The index and the clarified demarcations between real world and real life contextualised MALL may be used by researchers and practitioners in the challenging task of analysis, design and evaluation of contextualised MALL activities.


MALL, mobile-assisted language learning, Chinese learning, mobile learning, language learning

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