| Abstract [eng] |
This master’s final degree project examines the impact of AI-generated and teacher-provided personalized feedback on the quality of argumentative essays written by 7th–8th grade students in Lithuanian language lessons. The relevance of the research is determined by the rapidly increasing application of generative artificial intelligence in education and the need to identify effective ways of personalizing feedback that would foster the development of students’ writing skills, self-regulation, and conscious learning (European Commission, 2022; Holmes, Bialik, & Fadel, 2022; UNESCO, 2023). Scientific literature emphasizes that personalized feedback is one of the most important factors influencing students’ learning progress (Hattie & Timperley, 2007; Shute, 2008; Wisniewski, Zierer, & Hattie, 2020). However, there is still a lack of empirical research analyzing the impact of AI-generated and teacher-provided feedback on the quality of students’ essays in general education schools (Henderson, 2025; Kaliisa et al., 2025; Shi & Aryadoust, 2024). The aim of the research was to investigate the impact of AI-generated and teacher-provided personalized feedback on the quality of students’ essays. The object of the research was the impact of AI-generated and teacher-provided personalized feedback on the quality of argumentative essays written by 7th–8th grade students during Lithuanian language lessons. The following objectives were set: 1. to analyze the concept of personalized feedback, its significance for improving the quality of students’ essays, and the possibilities of applying artificial intelligence in the educational process; 2. to substantiate the research methodology for investigating the impact of AI-generated and teacher-provided personalized feedback on the quality of students’ essays; 3. to determine the impact of AI-generated and teacher-provided personalized feedback on the quality of students’ essays and students’ experiences of using feedback. to analyze the concept of personalized feedback and its significance for the development of students’ writing skills; to discuss the possibilities of applying artificial intelligence in the educational process; and to empirically investigate the impact of AI-generated and teacher-provided feedback on changes in the quality of students’ essays. The study employed a mixed-methods intervention-based quasi-experimental crossover research design. The participants of the study were 7th–8th grade students who completed argumentative writing and rewriting tasks during Lithuanian language lessons. In the quantitative part of the study, changes in the quality of students’ argumentative essays before and after the application of feedback were analyzed by assessing the criteria of argumentation, text structure and coherence, higher-order thinking, and the use of feedback. In the qualitative part of the study, student interviews were analyzed in order to gain a deeper understanding of students’ experiences, their attitudes toward different types of feedback, and to interpret the quantitative research results within the context of students’ experiences. The research results revealed that both AI-generated and teacher-provided personalized feedback had a positive impact on the quality of students’ essays; however, different patterns of impact were identified. AI-generated feedback contributed more to improving text structure and coherence, whereas teacher-provided feedback had a stronger effect on the quality of argumentation, the expression of higher-order thinking, and deeper text revision. The findings suggest that the most effective approach in the educational process could be a blended model combining the possibilities of AI-generated and teacher-provided feedback. The study contributes to the still insufficiently explored field of applying generative artificial intelligence for personalized feedback in the context of general education and reveals the specific characteristics of different feedback sources in developing students’ writing skills. The results of the study may be applied in Lithuanian language teaching practice when developing personalized feedback models and integrating generative AI tools into the educational process. The thesis consists of an introduction, theoretical, methodological, and empirical research parts, conclusions, recommendations for teachers, a list of references and information sources, and appendices. |
