Leveraging AI to enhance writing skills of senior TFL students in Kazakhstan: A case study using "Write & Improve"

This study investigates the effectiveness of feedback provided by teachers versus feedback generated by the Write & Improve platform in enhancing the writing skills of senior undergraduate students enrolled in a "two foreign language" program at a private university in Kazakhstan. The quasi-experimental design involved four teachers, each teaching one control and one experimental class, totaling eight groups of students. Pre- and post-tests were conducted over a period of five weeks, focusing on task achievement, coherence and cohesion, lexical resource, grammar and accuracy, and overall score. Data analysis included descriptive statistics, Mann-Whitney U tests for pre-test comparisons, and MANCOVA analyses for post-test comparisons. Results show no significant difference in the impact of Write & Improve feedback compared to traditional teacher feedback across multiple dimensions of the writing test, both within individual teachers' classes and when combined. Longitudinal analysis reveals fluctuating scores over time with no consistent improvement. Thus, the study concludes that the Write & Improve tool is equally effective as teacher feedback in improving students' writing skills. This implies that educational institutions can potentially integrate technology-based feedback systems like Write & Improve alongside traditional teaching methods to enhance student learning outcomes in writing proficiency.