Teachers' Development of Competence in Managing Generative AI Technology: Findings from a Qualitative Interview Series

This research full paper strives to shed light on educators' ways of dealing with the rapid advances in generative AI tools, which have opened up new challenges and opportunities for learners and educators alike. Both are confronted with the opportunity of supporting themselves in the completion of a wide range of tasks in this new reality. The study presented here aims to identify different strategies teachers use to develop their competences in responding to students' AI usage and in utilizing this new technology for their own professional tasks. Strategies are identified through a series of semi-structured qualitative interviews with a diverse group of nineteen teachers from two vocational and three general education secondary schools in urban and rural areas of Austria. The participants are mainly teaching technical and language subjects and range from technical experts teaching IT to general education teachers who are faced with the need to quickly adapt to learners with different levels of digital and AI competences. The findings of a qualitative content analysis of the gathered data are contextualized with previous work on educators' digital competence development and comparisons are drawn. It was found that a major contribution to the educators' skills in handling generative AI technology was made through self-regulated learning facilitated by various resources ranging from academic literature to social media and experimentation, as was the case with general digital skills. Nevertheless, the desire to be formally supported in further developing AI competence through training was voiced with requirements for this training being that the content is up-to-date, contains practical examples, and is delivered by experts. In addition, open, inclusive forms of seminars were suggested. These findings aim to inform curriculum designers, teacher educators, professional development trainers and administrators. Furthermore, struggling educators will find a starting point for self-organized work on their AI competences and pointers to potentially useful resources both for their teaching and their own learning in the field.

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Published
2024-10-13
DOI
https://doi.org/10.1109/fie61694.2024.10893585
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.41
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article

Teachers' Development of Competence in Managing Generative AI Technology: Findings from a Qualitative Interview Series

Renate Motschnig, Michael Jemetz
1 citations
Online Learning and Analytics
0.41
article

Teachers' Development of Competence in Managing Generative AI Technology: Findings from a Qualitative Interview Series

Renate Motschnig, Michael Jemetz
article en
1 citations

Abstract

This research full paper strives to shed light on educators' ways of dealing with the rapid advances in generative AI tools, which have opened up new challenges and opportunities for learners and educators alike. Both are confronted with the opportunity of supporting themselves in the completion of a wide range of tasks in this new reality. The study presented here aims to identify different strategies teachers use to develop their competences in responding to students' AI usage and in utilizing this new technology for their own professional tasks. Strategies are identified through a series of semi-structured qualitative interviews with a diverse group of nineteen teachers from two vocational and three general education secondary schools in urban and rural areas of Austria. The participants are mainly teaching technical and language subjects and range from technical experts teaching IT to general education teachers who are faced with the need to quickly adapt to learners with different levels of digital and AI competences. The findings of a qualitative content analysis of the gathered data are contextualized with previous work on educators' digital competence development and comparisons are drawn. It was found that a major contribution to the educators' skills in handling generative AI technology was made through self-regulated learning facilitated by various resources ranging from academic literature to social media and experimentation, as was the case with general digital skills. Nevertheless, the desire to be formally supported in further developing AI competence through training was voiced with requirements for this training being that the content is up-to-date, contains practical examples, and is delivered by experts. In addition, open, inclusive forms of seminars were suggested. These findings aim to inform curriculum designers, teacher educators, professional development trainers and administrators. Furthermore, struggling educators will find a starting point for self-organized work on their AI competences and pointers to potentially useful resources both for their teaching and their own learning in the field.

University of Vienna (AT)
Quality Education
Openalex Percentile: Top 23%
Online Learning and Analytics
0.41
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Teachers' Development of Competence in Managing Generative AI Technology: Findings from a Qualitative Interview Series — Renate Motschnig, Michael Jemetz · (2024) | TGRS Research Map | TGRS