Abstract
Considering the importance of individualised learning, artificial intelligence tools can effectively create an environment where students can learn by using them both in lessons and on their own, and enable students to learn a foreign language more effectively and permanently. The aim of this study is to examine the thinking worlds and thought patterns of prospective German teachers about the role of artificial intelligence in language teaching and learning and their views on the concept of artificial intelligence. The starting point of this study is the question of which metaphors prospective teachers use when talking about the concept of artificial intelligence. The questions of the study are as follows: 1. with which metaphors do pre-service German teachers express artificial intelligence? 2. How do pre-service German teachers define their metaphors related to the concept of artificial intelligence? 3. Under which conceptual categories are these metaphors categorised in terms of common characteristics? The participants of the study consisted of 1st, 2nd, 3rd and 4th year prospective teachers studying at the Department of German Language Teaching, Faculty of Education, Faculty of Foreign Languages Education, Trakya University. The data were collected by qualitative data analysis method. Firstly, Student Information Form was given to the students and what is metaphor was explained by giving examples of metaphor. Then, the students filled out an opinion form consisting of semi-structured questions. This form consists of two parts, in which short demographic information about the students is asked and the open-ended question ‘artificial intelligence is like ...., because...’ is asked. Metaphor analysis technique was used to analyse the data. The data obtained were interpreted by categorising the metaphors used by the prospective German teachers.
Primary Language | English |
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Subjects | Specialist Studies in Education (Other) |
Journal Section | Research Articles |
Authors | |
Early Pub Date | September 24, 2024 |
Publication Date | September 24, 2024 |
Submission Date | August 2, 2024 |
Acceptance Date | September 22, 2024 |
Published in Issue | Year 2024 |
ISSN: 2667-5870