The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
AIGC Technology in Mobile English Learning: An Empirical Study on Learning Outcomes
Open accessAbstract
This study evaluates the impact of Artificial Intelligence Generated Content (AIGC) on mobile English learning outcomes through a randomized controlled trial involving 240 sixth-grade students from a city primary school. The experimental group engaged with AIGC-generated English story videos, followed by targeted reading comprehension and vocabulary exercises, while the control group watched the same content without additional tasks. The intervention was conducted twice weekly for 10 minutes over 8 weeks.The results indicate a significant improvement in the experimental group's academic performance. Specifically, the proportion of students scoring below 60 was reduced to 2.1% from the control group's 4.6%. The majority of students in both groups scored within the 60-84 range, with the experimental group showing a higher prevalence of high achievers, 22.5% scoring 85 or above compared to 14.2% in the control group. Questionnaire data reveal that 65% of students enjoyed watching English story videos, and 62.5% found them helpful for understanding. Over half remembered a significant amount of new vocabulary, and 53.33% expressed a desire to continue learning English through video.These findings underscore the potential of AIGC to enhance educational outcomes in mobile English learning, providing empirical evidence that could inform teaching strategies and support the integration of AIGC in educational technology.
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Studies used AI interventions to address common barriers such as limited teacher feedback, low student motivation for revision, or insufficient opportunities for creative expression.
“These studies used AI interventions to address common barriers such as limited teacher feedback, low student motivation for revision, or insufficient opportunities for creative expression [81-87].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [81]
The Abstract and §2.2 describe an AI-enhanced English-learning intervention, and §5 reports that students generally liked the videos and wanted to keep learning through them. The paper does not identify limited teacher feedback, low motivation for revision, or insufficient opportunities for creative expression as barriers the intervention addressed. (LLM, conf=0.83)
Experimental — accuracy not yet measuredEvidence spans STEM and the humanities, including gains in understanding physics and programming, as well as improved reading and poetry interpretation.
“Evidence spans STEM and the humanities, including gains in understanding physics [91,101,104,147] and programming [95,148,150], as well as improved reading and poetry interpretation [72,75,81,116].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [81]
Section 4.1 reports higher reading-comprehension scores in the experimental group, and Section 4.1.2 says the findings hint at improved reading comprehension, pending more rigorous analysis. The paper does not report poetry interpretation. The physics and programming claims have separate citations in the citing sentence and are not attributed to this source. (LLM, conf=0.86)
Experimental — accuracy not yet measuredNumerous studies report higher enthusiasm, participation, curiosity, and satisfaction after AI use, alongside a general preference for AI tools as efficient and convenient.
“Numerous studies report higher enthusiasm, participation, curiosity, and satisfaction after AI use [6,70,74,81,87,91,92,101,104,106,113,114,116,119,131,141,142], alongside a general preference for AI tools as efficient and convenient [99,111,124,127,135,140].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [81]
The Questionnaire Data section reports that 65% of surveyed sixth-grade students liked the English story videos, and Educational significance says students using interactive modules showed higher engagement. The paper does not establish increased curiosity or satisfaction after AI use, and both study groups watched AIGC videos, so it cannot attribute those changes specifically to AI. The efficient-and-convenient preference is attached to other citations in the citing sentence, not this source. (LLM, conf=0.85)
Experimental — accuracy not yet measured
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Cites
Chinese postgraduate EFL learners’ self-directed use of mobile English learning resources
Zhang, D., & Pérez-Paredes, P. (2019) · Computer Assisted Language Learning · doi:10.1080/09588221.2019.1662455 · Cited by 141
Frontiers in Education Conference
(2008) · IEEE Transactions on Education · doi:10.1109/te.2008.917748 · Cited by 78
Wang, X., Hong, Y., & He, X. (2024) · IET Blockchain · doi:10.1049/blc2.12076 · Cited by 38
Linda, V., Xie, Y., & Han, M. (2018) · 2022 IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie.2018.8658568 · Cited by 8
Interactive Learning Modules With Visual Feedback Improve Resident Learning in Colposcopy
Nelson, E. L., & Knudtson, J. F. (2020) · Journal of Lower Genital Tract Disease · doi:10.1097/lgt.0000000000000515 · Cited by 7
Flagged first, then by citations
Research works printed but not linked: 4
- Ziyan W, Luyao S, Emily K, Shumeng Z, Mingming F, Exploring the Impact of Artificial Intelligence-Generated Content (AIGC) Tools on Social Dynamics in UX Collaboration.[J], Conference on Designing Interactive Systems, 2024: 1594-1606.
- Shutian Zhao. Design of Mobile English learning system based on Android platform[J], Electronic Test, 2020: 84-85,103.
- Pin-Hsiang H, Matthew H, Anthony O, Boaz S, A meta-analysis for comparing effective teaching in clinical education.[J], Medical teacher, 2019, 41.0(10.0): 1129.0-1142.0.
- Е.В. Яковлева, А.Р. Шайдуллина. Organizational and methodological support for students’ foreign language personalized learning pathway modeling in the context of digital challenges[J], Казанский педагогический журнал, 2021.
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Lin, X., & Tan, H. (2025) · Systems · doi:10.3390/systems13100840 · Cited by 22
Metadata
- Authors
- Ding, L.
- Affiliations
- Hunan Sports Vocational College (CN)
- Corresponding author
- Ding, Linfang
- ORCID
- Ding, Linfang
- Venue
- Proceedings of the 2024 Asia Pacific Conference on Computing Technologies, Communications and Networking
- Publisher
- ACM
- Published
- 2024-07-26
- Pages
- 92-98
- OpenAlex
- W4402346992
- Cited by
- 7
- References
- 5
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 1
- FWCI
- 2.66
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Asia Pacific Conference on Computing Technologies, Communications and Networking (CTCNet) (publishedVersion)
- Topics
- Social Sciences › Education › English Language Learning and Teaching
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Social Sciences › Education › Artificial Intelligence in Education
- Keywords
- AI-generated content, English as a foreign language, elementary school students, learning outcomes, vocabulary acquisition, reading comprehension, educational technology, student engagement
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