Tobias Raupach
Biographic Data
| ID | 7093438 |
|---|---|
| NAME | Tobias Raupach |
| GIVEN NAMES | Tobias |
| FAMILY NAME | Raupach |
| SIGNATURE | RAUPACH T |
| AFFILIATIONS | University Hospital Bonn |
| ORCID | 0000-0003-2555-8097 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 10 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
A randomised cross-over trial assessing the impact of AI-generated individual feedback on written online assignments for medical students
Purpose Self-testing has been proven to significantly improve not only simple learning outcomes, but also higher-order skills such as clinical reasoning in medical students. Previous studies have shown that self-testing was especially beneficial when it was presented with feedback, which leaves the question whether an immediate and personalized feedback further encourages this effect. Therefore, we hypothesised that individual feedback has a grea…
Algorithm aversion revisited
Scientific publications on AI education frequently express concerns that students at all educational levels, lacking sufficient AI literacy, may become passive learners due to the use of generative language models and blindly trust AI outputs. Concurrently, recent research has increasingly identified an ‘algorithm aversion’ tendency, leading individuals to regard information generated by AI with scepticism. Both uncritical trust and unfounded ave…
Impact of providing a customized guideline on virtual medical history taking in two serious games for medical education
The results suggest that history taking benefits from self-directed learning in a long menu format relying on cued recall but not in a free-entry chatbot relying on free recall. Since serious games are partially artificial learning environments for training history taking, future studies should examine the extent to which students can transfer their learning in and out of serious games
Large Language Models in Medical Education
AI Course Design Planning Framework
The use of artificial intelligence (AI) is becoming increasingly important in various domains, making education about AI a necessity. The interdisciplinary nature of AI and the relevance of AI in various fields require that university instructors and course developers integrate AI topics into the classroom and create so-called domain-specific AI courses. In this paper, we introduce the “AI Course Design Planning Framework” as a course planning fr…
Answer to the commentary about compliance to assumptions and choice of the model in item response theory
"Answer to the commentary about compliance to assumptions and choice of the model in item response theory." Medical Teacher, ahead-of-print(ahead-of-print), p. 1
Artificial intelligence literacy in higher and adult education
Since artificial intelligence (AI) is finding its way into more and more areas of everyday life, improving the AI skills of non-experts is important and will become even more relevant in the future. While it is necessary that children learn about the possibilities of AI at an early age, adults in higher education and beyond should also have at least a basic understanding of AI (i.e., AI literacy) to be able to interact effectively with the techno…
Using item response theory to appraise key feature examinations for clinical reasoning
BACKGROUND: Validation of examinations is usually based on classical test theory. In this study, we analysed a key feature examination according to item response theory and compared the results with those of a classical test theory approach. METHODS: Over the course of five years, 805 fourth-year undergraduate students took a key feature examination on general medicine consisting of 30 items. Analyses were run according to a classical test theory…
A prediction-based method to estimate student learning outcome
BACKGROUND: Low response rates threaten the reliability and validity of student evaluations of teaching. Previous research has shown that asking students to predict how satisfied their fellow students were with a course produces reliable results at lower response rates. The aim of this study was to investigate whether this prediction-based method can also be used to evaluate student learning outcome. METHODS: Before and after a cardiorespiratory …
Study protocol of the German Study on Tobacco Use (Debra)
This study has been registered at the German Clinical Trials Register ( DRKS00011322 ) on 25th November 2016
No prominent works on this page.
Study protocol of the German Study on Tobacco Use (Debra)
This study has been registered at the German Clinical Trials Register ( DRKS00011322 ) on 25th November 2016
A prediction-based method to estimate student learning outcome
BACKGROUND: Low response rates threaten the reliability and validity of student evaluations of teaching. Previous research has shown that asking students to predict how satisfied their fellow students were with a course produces reliable results at lower response rates. The aim of this study was to investigate whether this prediction-based method can also be used to evaluate student learning outcome. METHODS: Before and after a cardiorespiratory …
Artificial intelligence literacy in higher and adult education
Since artificial intelligence (AI) is finding its way into more and more areas of everyday life, improving the AI skills of non-experts is important and will become even more relevant in the future. While it is necessary that children learn about the possibilities of AI at an early age, adults in higher education and beyond should also have at least a basic understanding of AI (i.e., AI literacy) to be able to interact effectively with the techno…
Using item response theory to appraise key feature examinations for clinical reasoning
BACKGROUND: Validation of examinations is usually based on classical test theory. In this study, we analysed a key feature examination according to item response theory and compared the results with those of a classical test theory approach. METHODS: Over the course of five years, 805 fourth-year undergraduate students took a key feature examination on general medicine consisting of 30 items. Analyses were run according to a classical test theory…
AI Course Design Planning Framework
The use of artificial intelligence (AI) is becoming increasingly important in various domains, making education about AI a necessity. The interdisciplinary nature of AI and the relevance of AI in various fields require that university instructors and course developers integrate AI topics into the classroom and create so-called domain-specific AI courses. In this paper, we introduce the “AI Course Design Planning Framework” as a course planning fr…
Answer to the commentary about compliance to assumptions and choice of the model in item response theory
"Answer to the commentary about compliance to assumptions and choice of the model in item response theory." Medical Teacher, ahead-of-print(ahead-of-print), p. 1
Large Language Models in Medical Education
A randomised cross-over trial assessing the impact of AI-generated individual feedback on written online assignments for medical students
Purpose Self-testing has been proven to significantly improve not only simple learning outcomes, but also higher-order skills such as clinical reasoning in medical students. Previous studies have shown that self-testing was especially beneficial when it was presented with feedback, which leaves the question whether an immediate and personalized feedback further encourages this effect. Therefore, we hypothesised that individual feedback has a grea…
Algorithm aversion revisited
Scientific publications on AI education frequently express concerns that students at all educational levels, lacking sufficient AI literacy, may become passive learners due to the use of generative language models and blindly trust AI outputs. Concurrently, recent research has increasingly identified an ‘algorithm aversion’ tendency, leading individuals to regard information generated by AI with scepticism. Both uncritical trust and unfounded ave…
Impact of providing a customized guideline on virtual medical history taking in two serious games for medical education
The results suggest that history taking benefits from self-directed learning in a long menu format relying on cued recall but not in a free-entry chatbot relying on free recall. Since serious games are partially artificial learning environments for training history taking, future studies should examine the extent to which students can transfer their learning in and out of serious games
Medicine (6 works) · Psychology (6 works) · Artificial Intelligence in Healthcare and Education (5 works) · Computer Science (5 works) · Innovations in Medical Education (5 works) · Medical education (4 works) · Clinical Reasoning and Diagnostic Skills (3 works) · Artificial Intelligence (2 works) · Artificial Intelligence (2 works) · Ethics and Social Impacts of AI (2 works)