Titelangaben
Chrostowski, Mariusz
; Najda, Andrzej Jacek:
From Verse to Vision : Exploring AI-Generated Religious Imagery in Bible Teaching.
In: Religions / Molecular Diversity Preservation International (MDPI). 16 (2025) 8: 1051.
- 15 S.
ISSN 2077-1444
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Link zum Volltext (externe URL): https://www.mdpi.com/2077-1444/16/8/1051 |
Kurzfassung/Abstract
This article critically analyses the use of generative Artificial Intelligence (GenAI)—specifically, the DALL·E system within the ChatGPT-4o environment—for creating visualisations of biblical scenes for teaching purposes. As part of a case study examining the Baptism of Jesus in the Jordan (Mt 3:13–17; cf. Mark 1:9–11; Luke 3:21–22; John 1:31, 34) and the Last Supper (Mt 26:17–30; cf. Mark 14:12–16; Luke 22:7–13), four AI-generated images are analysed. Two were created using general, non-specific prompts, while the other two were based on more precise queries containing references to Catholic symbolism and the images’ intended educational use. A comparison of these variants reveals a lack of theological depth and symbolic oversimplification in AI-generated images, as well as a tendency to reproduce Western cultural stereotypes. Despite their aesthetic appeal and quick availability, these images do not reflect the complexity of the biblical or spiritual contexts of the scenes depicted. This study aims to evaluate the theological, symbolic, and pedagogical value of AI-generated images and to provide practical recommendations for their responsible use in Bible didactics. In conclusion, the authors argue that GenAI can support biblical teaching when used consciously, critically, and reflectively.
Weitere Angaben
| Publikationsform: | Artikel |
|---|---|
| Schlagwörter: | biblical teaching; generative Artificial Intelligence; DALL·E; ChatGPT; religious education |
| Sprache des Eintrags: | Englisch |
| Institutionen der Universität: | Theologische Fakultät > Praktische Theologie > Lehrstuhl für Didaktik der Religionslehre, Katechetik und Religionspädagogik |
| DOI / URN / ID: | 10.3390/rel16081051 |
| Open Access: Freie Zugänglichkeit des Volltexts?: | Ja |
| Peer-Review-Journal: | Ja |
| Verlag: | MDPI |
| Die Zeitschrift ist nachgewiesen in: | |
| Titel an der KU entstanden: | Ja |
| KU.edoc-ID: | 35523 |
Letzte Änderung: 14. Aug 2025 09:24
URL zu dieser Anzeige: https://edoc.ku.de/id/eprint/35523/
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Creative Commons: Namensnennung (CC BY 4.0)