Motivation and achievement in EFL: the power of instructional approach
Maintaining learning motivation and achieving academic success in English language learning remains a challenge for many university students, particularly those with lower proficiency. Conventional teacher-centered classrooms are often characterized by passive learners with limited personalized supp...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-06-01
|
| Series: | Frontiers in Education |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/feduc.2025.1614388/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849422495998803968 |
|---|---|
| author | Jingdan Liu Jingdan Liu Hazrul Abdul Hamid Xujie Bao Xujie Bao |
| author_facet | Jingdan Liu Jingdan Liu Hazrul Abdul Hamid Xujie Bao Xujie Bao |
| author_sort | Jingdan Liu |
| collection | DOAJ |
| description | Maintaining learning motivation and achieving academic success in English language learning remains a challenge for many university students, particularly those with lower proficiency. Conventional teacher-centered classrooms are often characterized by passive learners with limited personalized support. In contrast, blended and artificial intelligence (AI)-assisted learning have emerged as promising alternatives to address motivational and performance challenges in English as a foreign language (EFL) contexts. However, empirical comparisons of these instructional approaches remain limited. Grounded in Self-Determination Theory (SDT) and cognitive constructivism, this study examined the comparative effects of conventional, blended, and AI-blended instructional approaches on Chinese university students’ goal orientation, self-efficacy, instructional support, and English academic achievement. The AI-blended approach integrated tools such as automated writing evaluation (AWE), automated speech recognition (ASR), and the chatbot DouBao to support pre-class learning. A 1.5-year longitudinal within-subject design was employed with 43 first-year EFL students at a Chinese university. Participants experienced all three instructional approaches sequentially, with data collected via motivational questionnaires and achievement tests. Repeated measures analyses, including ANOVA and Friedman tests, were conducted. Results indicated that both blended and AI-blended instruction significantly improved students’ motivation and academic performance relative to conventional instruction. The AI-blended approach produced the most substantial gains in self-efficacy, instructional support, and key language skills such as listening comprehension, translation, and writing. These findings inform ongoing discussions on the integration of AI in EFL pedagogy and provide practical implications for instructional design, teacher preparation, and education policy innovation. The study’s limitations, including the small sample size, limited demographic diversity, and constraints of a within-subject design, should be addressed in future research. |
| format | Article |
| id | doaj-art-79eb543e66814672b099a0ddc8ddd47a |
| institution | Kabale University |
| issn | 2504-284X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Education |
| spelling | doaj-art-79eb543e66814672b099a0ddc8ddd47a2025-08-20T03:31:02ZengFrontiers Media S.A.Frontiers in Education2504-284X2025-06-011010.3389/feduc.2025.16143881614388Motivation and achievement in EFL: the power of instructional approachJingdan Liu0Jingdan Liu1Hazrul Abdul Hamid2Xujie Bao3Xujie Bao4School of Distance Education, Universiti Sains Malaysia, Gelugor, Penang, MalaysiaSchool of General Education, Hunan University of Information Technology, Changsha, Hunan, ChinaSchool of Distance Education, Universiti Sains Malaysia, Gelugor, Penang, MalaysiaSchool of General Education, Hunan University of Information Technology, Changsha, Hunan, ChinaSchool of Graduate Studies, Lingnan University, Tuen Mun, Hong Kong SAR, ChinaMaintaining learning motivation and achieving academic success in English language learning remains a challenge for many university students, particularly those with lower proficiency. Conventional teacher-centered classrooms are often characterized by passive learners with limited personalized support. In contrast, blended and artificial intelligence (AI)-assisted learning have emerged as promising alternatives to address motivational and performance challenges in English as a foreign language (EFL) contexts. However, empirical comparisons of these instructional approaches remain limited. Grounded in Self-Determination Theory (SDT) and cognitive constructivism, this study examined the comparative effects of conventional, blended, and AI-blended instructional approaches on Chinese university students’ goal orientation, self-efficacy, instructional support, and English academic achievement. The AI-blended approach integrated tools such as automated writing evaluation (AWE), automated speech recognition (ASR), and the chatbot DouBao to support pre-class learning. A 1.5-year longitudinal within-subject design was employed with 43 first-year EFL students at a Chinese university. Participants experienced all three instructional approaches sequentially, with data collected via motivational questionnaires and achievement tests. Repeated measures analyses, including ANOVA and Friedman tests, were conducted. Results indicated that both blended and AI-blended instruction significantly improved students’ motivation and academic performance relative to conventional instruction. The AI-blended approach produced the most substantial gains in self-efficacy, instructional support, and key language skills such as listening comprehension, translation, and writing. These findings inform ongoing discussions on the integration of AI in EFL pedagogy and provide practical implications for instructional design, teacher preparation, and education policy innovation. The study’s limitations, including the small sample size, limited demographic diversity, and constraints of a within-subject design, should be addressed in future research.https://www.frontiersin.org/articles/10.3389/feduc.2025.1614388/fullAIinstructional approachmotivationachievementblendedEFL |
| spellingShingle | Jingdan Liu Jingdan Liu Hazrul Abdul Hamid Xujie Bao Xujie Bao Motivation and achievement in EFL: the power of instructional approach Frontiers in Education AI instructional approach motivation achievement blended EFL |
| title | Motivation and achievement in EFL: the power of instructional approach |
| title_full | Motivation and achievement in EFL: the power of instructional approach |
| title_fullStr | Motivation and achievement in EFL: the power of instructional approach |
| title_full_unstemmed | Motivation and achievement in EFL: the power of instructional approach |
| title_short | Motivation and achievement in EFL: the power of instructional approach |
| title_sort | motivation and achievement in efl the power of instructional approach |
| topic | AI instructional approach motivation achievement blended EFL |
| url | https://www.frontiersin.org/articles/10.3389/feduc.2025.1614388/full |
| work_keys_str_mv | AT jingdanliu motivationandachievementineflthepowerofinstructionalapproach AT jingdanliu motivationandachievementineflthepowerofinstructionalapproach AT hazrulabdulhamid motivationandachievementineflthepowerofinstructionalapproach AT xujiebao motivationandachievementineflthepowerofinstructionalapproach AT xujiebao motivationandachievementineflthepowerofinstructionalapproach |