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Aufsatz (Zeitschrift) zugänglich unter
URN: urn:nbn:de:0111-pedocs-357787
DOI: 10.25656/01:35778; 10.1186/s12909-025-06756-0
URN: urn:nbn:de:0111-pedocs-357787
DOI: 10.25656/01:35778; 10.1186/s12909-025-06756-0
| Titel |
Teaching opportunities for anamnesis interviews through AI based teaching role plays. A survey with online learning students from health study programs |
|---|---|
| Autoren |
Rädel-Ablass, Katharina   ;
Schliz, Klaus ;
Schlick, Cornelia ;
Meindl, Benjamin;
Pahr-Hosbach, Sandra ;
Schwendemann, Hanna ;
Rupp, Stephanie ;
Roddewig, Marion ;
Miersch, Claudia |
| Originalveröffentlichung | BMC medical education 25 (2025), Art. 259  |
| Dokument | Volltext (1.711 KB) |
| Lizenz des Dokumentes |
|
| Schlagwörter (Deutsch) | Künstliche Intelligenz; Student; Anamnese; Gesprächsverhalten; Hochschuldidaktik; Gesundheitsberuf; Selbstgesteuertes Lernen; Digitales System; Training |
| Teildisziplin | Empirische Bildungsforschung Hochschulforschung und Hochschuldidaktik |
| Dokumentart | Aufsatz (Zeitschrift) |
| ISSN | 1472-6920; 14726920 |
| Sprache | Englisch |
| Erscheinungsjahr | 2025 |
| Begutachtungsstatus | Peer-Review |
| Abstract (Englisch): | Background: This study presents a novel approach to educational role-playing through an AI-based bot, leveraging GPT-4 to simulate anamnesis interviews in various learning scenarios. Developed collaboratively by an interdisciplinary team of university lecturers and AI experts, the bot provides a platform for students of different health study programs to engage in complex patient-health professional conversations, offering an alternative to traditional role plays with actors or real patients. Methods: This study utilized a GPT-4 based digital teaching assistant, implemented through a proprietary chatbot design platform, to train anamnesis interviews in virtual settings with students from different online health care study programs. Students’ satisfaction, virtual patient’s accuracy, its realism, and quality were evaluated with a quantitative survey. Results: The evaluation of the bot focused on student feedback, highlighting a preference for the AI-driven method due to its immersive and interactive nature. Preliminary results show that students consistently rate the language ability of the AI model positively. More than 80% of students rated the professional and content-related precision of the virtual patient as good to excellent. Even as a text-based chatbot, the vast majority of students see a fairly close to very close relationship to a real anamnesis interview. The results further indicate that students even prefer this training approach to traditional in-person role-plays. Conclusions: The study underscores the bot’s potential as a versatile tool for enriching learning experiences across multiple health disciplines, signaling a meaningful shift in educational practices towards the integration of AI technologies. (DIPF/Orig.) |
| Statistik |  Anzahl der Zugriffe auf dieses Dokument
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| Prüfsummen | Prüfsummenvergleich als Unversehrtheitsnachweis |
| Eintrag erfolgte am | 10.07.2026 |
| Quellenangabe | Rädel-Ablass, Katharina; Schliz, Klaus; Schlick, Cornelia; Meindl, Benjamin; Pahr-Hosbach, Sandra; Schwendemann, Hanna; Rupp, Stephanie; Roddewig, Marion; Miersch, Claudia: Teaching opportunities for anamnesis interviews through AI based teaching role plays. A survey with online learning students from health study programs - In: BMC medical education 25 (2025), Art. 259 - URN: urn:nbn:de:0111-pedocs-357787 - DOI: 10.25656/01:35778; 10.1186/s12909-025-06756-0 |
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