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Towards a Taxonomy of Artificial Intelligence in Teaching Writing in a Foreign Language

Title: Towards a Taxonomy of Artificial Intelligence in Teaching Writing in a Foreign Language
Language: English
Authors: Jesús García Laborda (ORCID 0000-0003-0125-4611); Teresa Magal Royo (ORCID 0000-0002-7640-6264); Slavka Madarova (ORCID 0000-0003-3771-3576)
Source: South African Journal of Education. 2024 44(4).
Availability: Education Association of South Africa. University of Pretoria, Centre for the Study of Resilience, Level 3, Groenkloof Student Centre, Department of Educational Psychology, Faculty of Education, George Storrar Road and Lleyds Street, Pretoria 0001, South Africa. Web site: http://www.sajournalofeducation.co.za/index.php/saje/index
Peer Reviewed: Y
Page Count: 8
Publication Date: 2024
Document Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Descriptors: Taxonomy; Artificial Intelligence; Writing Instruction; Second Language Learning; Computer Assisted Instruction; Teaching Methods; Web Sites; Higher Education; Writing Processes
ISSN: 0256-0100; 2076-3433
Abstract: The use of artificial intelligence in foreign language teaching, and particularly in teaching writing, is still under investigation for its potential positive impact and potential benefits. So far, the focus was on controversial uses, due to the challenges for the teachers. However, when used just for learning purposes, it can be a facilitating tool for the students. The key now is to understand its effects, challenges, and opportunities, to establish a framework for its use, and to make teachers aware of its potential. To this end, in this article we take a functional and utilitarian approach by identifying the characteristics and capacities of currently available sites. A description of the different sites is given along with their advantages and disadvantages. Since only a few fundamental works have been published on the subject, we propose a taxonomy with examples, evaluate its benefits and drawbacks and suggests potential applications for teaching and research.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1459753
Database: ERIC