Redefining Reading Assessment through the Use of AI-Harnessed App “Readlee”

Abstract

Reading is paramount in English language acquisition, especially in the Pakistani ESL context because it is a source of linguistic input. So far, reading assessment has been undergoing diversifying scenarios, but still, there is a need to explore and experiment with new things like AI-based apps to come up with applicable solutions to the issue. Thus, the current study integrated an AIharnessed application, "Readlee” to assess college students reading fluency through an automated feedback system. 40 college-level ESL students participated in the study. They were made to read English text aloud through the AI-Based application “Readlee” which recorded their loud reading and produced results on the basis of Word Count per Minute (WCPM). The results were then analyzed quantitatively and presented in tabular forms. Furthermore, the performances of the students were compared with one another for which graphs were used. The effectiveness of the Readlee App to teach and assess reading fluency was qualitatively analyzed on the basis of the features of the app which were tested in this study. The results showed that the Readlee App is effective in teaching and assessing reading fluency at the college level. Moreover, the results showed that students had different reading paces though the minimum WCPM was 38 and the maximum was 153. Thus, the study recommended the use of the Readlee App to teach and assess reading fluency at college level.