Enhancing students’ subject-verb agreement skill by using CiCi artificial intelligence-based app: Embedded mixed-methods study

Abstract

In recent years, AI-based language learning apps have found their way into English as a Second Language (ESL) classrooms. This case study employing embedded mixed-method design investigates the effectiveness of the CiCi app for enhancing the subject-verb agreement skills of ESL learners from the Philippines. Through random sampling, 40 Grade 7 students, 20 in each group, participated in this study. The students in the experimental group underwent a 4-week intervention program, spending 100 minutes per week, integrating the CiCi App as a supplemental learning tool, while the students in the control group underwent the traditional instruction method of teaching subject-verb agreement, also with the same number of minutes. Aside from the pretest and posttest data of both groups, one-on-one interviews with the students from the experimental group and their teacher were also conducted to analyze their perceptions of the app. Results show that the app significantly improved students’ subject-verb agreement skills in the experimental group, with no significant improvement observed in the control group. The interview data revealed four themes: Offering Free Charge and User-Friendly Features, Making English Learning Fun, Providing Various SV Agreement Exercises, and Encouraging Collaborative Learning. Drawing on the findings, AI-powered educational resources, like CiCi, enable teachers to customize English classroom activities. The study contributes to understanding the role of technology in language learning and provides insights for educators seeking innovative teaching strategies.