Innovation in Language Learning

The increasing necessity for students to read in English as L2 underscores the importance of proficient L2 reading skills. Learning to read in L2 is complex as learners must grasp literacy in an unfamiliar language [4]. Thus, there is an urgent need to support L2 reading from early school years. However, teachers face challenges in providing interactive and adaptive learning experiences for large numbers of students with limited time.  Digital environments such as intelligent CALL (ICALL) enable new ways of learning and teaching, enhancing outcomes, motivation, and teaching quality by offering automatic feedback, intelligent tutoring, and personalized support to students [1].

In this presentation, we introduce the Annotated Reading Enhancement System (ARES), a pedagogically oriented web-based ICALL system designed to enhance L2 reading experiences, developed using an action research design [2]. Based on text comprehension and SLA theories, ARES autonomously identifies over 650 grammar constructs listed on the English Grammar Profile (EGP) in input texts, providing learners with detailed explanations and practical examples. It also includes on-demand vocabulary lookup with information on form, meaning, and use. To support practical teaching, ARES implements large language models (LLMs) to automatically generate tailored reading comprehension questions and evaluate students’ responses, involving teachers to ensure effective learning. We discuss the development of ARES and its application in pedagogy, including research plans to leverage behavioral data (logs) to both advance SLA research and refine educational tools.