One-Topic-Doesn't-Fit-All: Transcreating Reading Comprehension Test for Personalized Learning

This paper develops a transcreation pipeline using GPT-4o to generate personalized English reading comprehension tests aligned with individual EFL students' interests, and conducts a controlled experiment with Korean EFL learners showing improved comprehension and motivation retention with personalized materials compared to non-personalized content.

Personalized learning has gained attention in English as a Foreign Language (EFL) education, where engagement and motivation play crucial roles in reading comprehension. We propose a novel approach to generating personalized English reading comprehension tests tailored to students'interests. We develop a structured content transcreation pipeline using OpenAI's gpt-4o, where we start with the RACE-C dataset, and generate new passages and multiple-choice reading comprehension questions that are li

Study Type

Source

Framework Categories

Tool Types

Tags