Applying Generative Artificial Intelligence to Task-Based Language Teaching and Learning: A Systematic Review and Meta-Analysis
Saved in:
| Title: | Applying Generative Artificial Intelligence to Task-Based Language Teaching and Learning: A Systematic Review and Meta-Analysis |
|---|---|
| Language: | English |
| Authors: | Yan Li, Rustam Shadiev (ORCID |
| Source: | TechTrends: Linking Research and Practice to Improve Learning. 2026 70(1):150-163. |
| Availability: | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Peer Reviewed: | Y |
| Page Count: | 14 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research Information Analyses |
| Descriptors: | Artificial Intelligence, Technology Uses in Education, Task Analysis, Teaching Methods, Second Language Instruction, Second Language Learning, Meta Analysis, Digital Literacy, Planning, Teacher Education |
| DOI: | 10.1007/s11528-025-01140-7 |
| ISSN: | 8756-3894 1559-7075 |
| Abstract: | Generative artificial intelligence (GenAI) has received increasing attention from language researchers and educators due to its capability to influence student language performance. Very limited previous meta-analysis studies have examined instructional factors in their analysis, while it deserves great attention. Task-based language teaching (TBLT) is a widely applied language instructional approach. Hence, this systematic review and meta-analysis study adopts TBLT to investigate how these instructional factors (e.g., task-based variables, learner variables) impact student language learning in GenAI contexts. Using the PRISMA guidelines, we collected literature and included 25 empirical studies involving 2,431 participants. The study confirmed the positive influence of GenAI on language learning and identified three moderators--student AI literacy, task planning, and task assessors--that potentially moderate its effectiveness. This finding likely relates to the GenAI tools employed; specifically, ChatGPT--not primarily designed for language learning--was used most frequently. This general-purpose GenAI may require students to understand how AI works, how to plan their tasks, and the necessity of involving teachers as assessors. We suggest teachers should get more involved in language learning with GenAI, and more language learning-specific GenAI should be developed. These suggestions help institutions and teachers to plan their instructions in the AI era. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1505833 |
| Database: | ERIC |
| Abstract: | Generative artificial intelligence (GenAI) has received increasing attention from language researchers and educators due to its capability to influence student language performance. Very limited previous meta-analysis studies have examined instructional factors in their analysis, while it deserves great attention. Task-based language teaching (TBLT) is a widely applied language instructional approach. Hence, this systematic review and meta-analysis study adopts TBLT to investigate how these instructional factors (e.g., task-based variables, learner variables) impact student language learning in GenAI contexts. Using the PRISMA guidelines, we collected literature and included 25 empirical studies involving 2,431 participants. The study confirmed the positive influence of GenAI on language learning and identified three moderators--student AI literacy, task planning, and task assessors--that potentially moderate its effectiveness. This finding likely relates to the GenAI tools employed; specifically, ChatGPT--not primarily designed for language learning--was used most frequently. This general-purpose GenAI may require students to understand how AI works, how to plan their tasks, and the necessity of involving teachers as assessors. We suggest teachers should get more involved in language learning with GenAI, and more language learning-specific GenAI should be developed. These suggestions help institutions and teachers to plan their instructions in the AI era. |
|---|---|
| ISSN: | 8756-3894 1559-7075 |
| DOI: | 10.1007/s11528-025-01140-7 |
