AUTOMATED FEEDBACK AND TEACHER FEEDBACK: WRITING ACHIEVEMENT IN LEARNING ENGLISH AS A FOREIGN LANGUAGE AT A DISTANCE
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Information and communication technologies have been transforming the way we teach and learn. Either for facilitating teaching practices or for making learning more interesting and joyful for the learners, artificial intelligence-based applications are utilized in recent years. In this connection, this study intends to examine if automated feedback and teacher feedback contribute to academic writing achievement and whether they differ in their effect on achievement in learning English as a foreign language in an open and distant learning context. The participants of the study were open education faculty students in a higher education institution in Turkey. In this quasi-experimental quantitative study repeated measures design was adopted. the participants were given writing tasks each week in a nine-week writing activity and they received feedback from their English language teachers for the first three tasks, and they received feedback from the software for the last three tasks. All participants wrote an English text as a diagnostic test at the beginning of the process. At the end of the teacher and software feedback phases, they took post-tests. All grades were statistically analyzed in order to find any effect of regular feedback either from a language teacher or from an online software on academic writing achievement. Results revealed significant differences between the diagnostic test and two achievement tests. Participants tended to improve their academic writing skills by taking regular feedback, and it was observed that the writing scores increased slightly more when receiving feedback from teachers compared to automated feedback software.
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Computer-mediated feedback has evolved as a potential solution to the problem of providing feedback in large writing classrooms.
“Computermediated feedback has evolved as a potential solution to this problem in writing classrooms (Taskiran & Goksel, 2022;Yamashita, 2021)”
From Impact of ChatGPT on ESL students’ academic writing skills: a mixed methods intervention study (2024) · cites this paper as Taskiran & Goksel, 2022
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AI‐Driven Feedback versus Human Touch
Mahmood, R. Q. (2026) · doi:10.1002/9781394486151.ch6
- Authors
- TASKIRAN, A., & GOKSEL, N.
- Venue
- Turkish Online Journal of Distance Education
- Published
- 2022-03-30
- Volume
- 23
- Issue
- 2
- Pages
- 120-139
- ISSN
- 1302-6488 (ISSN-L)
- OpenAlex
- W4226023014
- Semantic Scholar
- cbec914257aafa6fee1dc34dfc5cfccc7adbd031
- Cited by
- 61
- References
- 10
- Citations by year
- 2026: 11 · 2025: 28 · 2024: 14 · 2023: 8
- FWCI
- 47.04
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Turkish Online Journal of Distance Education (publishedVersion)
- DergiPark (Istanbul University) (submittedVersion)
- Topics
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
- Social Sciences › Education › Student Assessment and Feedback
- Keywords
- automated feedback, teacher feedback, English as a foreign language, distance education, open and distance learning, AI-assisted language learning, writing software, university students
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