The Design and Evaluation of Intelligent Computer-Assisted Language Learning Tools for Beginner Learners of Mandarin Chinese

Abstract

The present research aims to design and evaluate two Intelligent Computer-Assisted Language Learning (iCALL) prototypes to assist the teaching and learning of spoken Chinese in the Irish post-primary context.

The research adopts a three-phase mixed-method design. The first phase involves a needs analysis for both teachers and students to ascertain their needs and challenges in teaching and learning spoken Chinese, as well as their attitude towards iCALL implementation. The second phase develops two iCALL prototypes based on the findings of the needs analysis, and the third phase trials and evaluates both prototypes against the intended design.

The first phase of the research identified three main challenges in teaching spoken Chinese, which are: (i) the difficulty of Mandarin phonological acquisition, particularly regarding the tones, (ii) insufficient and inappropriate teaching and learning materials, and (iii) the lack of opportunities to practice and use the language outside of class hours.

In the evaluation of the two iCALL prototypes, the findings indicate that in the context of assisting teachers, the positive impacts are mainly reflected in five areas, including (i) technological experience, (ii) in-class teaching, (iii) student engagement, (iv) formative assessment, and (v) teacher training. In the context of assisting learners, the positive impacts are more evident in four areas: (i) Mandarin tone acquisition, (ii) learner autonomy, (iii) language confidence, and (iv) self-assessment.

In terms of its contribution to the field of Teaching Chinese as a Foreign Language (TCFL), the present research is the first to analyze and address the needs of beginner-level post-primary students learning spoken Chinese in Ireland. As a cross-discipline research project, it brings together educational pedagogy and technology and further implements the iCALL study in the context of TCFL.