FAMULUS

FAMULUS: Fostering diagnostic competence in medical and teacher education via adaptive online-case-simulations

Motivation

Diagnostic reasoning is a key competence in many professions. Examples are diagnosing diseases and suitable therapies in medicine and diagnosing whether pupils with learning difficulties suffer from a disability in educational settings. A good university curriculum should thus not only educate students regarding factual knowledge but also support them in developing diagnostic skills.

The interdisciplinary FAMULUS project aims to study how online case simulations that provide automatic adaptive feedback can foster students' diagnostic skills. To generate automatic feedback, we will develop novel methods for identifying and evaluating diagnostic reasoning (e.g. hypothesis generation, evidence generation and evaluation, hypothesis acceptance or rejection) in student essays. The effect of such feedback on the development of diagnostic skills will then be evaluated in a study conducted with students from medicine and education.

Goals

The FAMULUS project aims to answer the following questions regarding diagnostic essays written by students in medicine and education:

  • 1. How do different formats of online case simulations (e.g. “whole case” versus “serial cue”) affect the diagnostic reasoning of students with different levels of background knowledge? [study conducted by project partners]
  • 2. Is it possible to automatically and reliably detect diagnostic reasoning in student essays?
  • 3. How can the quality and suitability of diagnostic reasoning in an essay be automatically evaluated to generate adaptive feedback?
  • 4. How useful is the automatic feedback for students compared to providing a model essay? [study conducted by project partners]
  • 5. Does diagnostic reasoning differ when performed individually as compared to cooperatively? [study conducted by project partners and usage of automatic analysis from 2.]
  • 6. Can the methods developed for the automatic analysis and evaluation of diagnostic reasoning also be applied to essays of students from other fields of study?

Team

Partners

This project is established in cooperation with:

Institute for Medical Education (Ludwig-Maximilian University Munich)

Chair of Education and Educational Psychology (Ludwig-Maximilian University Munich)

Funding

The project is funded by the German Federal Ministry of Education and Research (BMBF) as part of the program “Digital Higher Education” (Digitale Hochschullehre).

Publications

Schulz, Claudia ; Meyer, Christian M. ; Gurevych, Iryna (2019):
Challenges in the Automatic Analysis of Students’ Diagnostic Reasoning.
In: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), [Online-Edition: https://fileserver.ukp.informatik.tu-darmstadt.de/UKP_Webpag...],
[Konferenzveröffentlichung]

Schulz, Claudia ; Meyer, Christian M. ; Sailer, Michael ; Kiesewetter, Jan ; Bauer, Elisabeth ; Fischer, Frank ; Fischer, Martin R. ; Gurevych, Iryna (2018):
Challenges in the Automatic Analysis of Students' Diagnostic Reasoning.
In: ArXiv e-prints, ISSN 1811.10550,
[Online-Edition: https://arxiv.org/abs/1811.10550],
[Article]

Schulz, Claudia ; Sailer, Michael ; Kiesewetter, Jan ; Bauer, Elisabeth ; Fischer, Frank ; Fischer, Martin R. ; Gurevych, Iryna (2018):
Automatic Recommendations for Data Coding: a use case from medical and teacher education.
In: Proceedings of the 14th eScience IEEE International Conference, Amsterdam, Netherlands, 29.10.2018--01.11.2018, DOI: 10.1109/eScience.2018.00100,
[Online-Edition: https://fileserver.ukp.informatik.tu-darmstadt.de/UKP_Webpag...],
[Konferenzveröffentlichung]

Schulz, Claudia ; Kiesewetter, Jan ; Sailer, Michael ; Bauer, Elisabeth ; Fischer, Martin R. ; Fischer, Frank ; Gurevych, Iryna (2018):
The Theory of Scientific Reasoning and Argumentation in Practice.
In: Bridging the Gap between Formal Argumentation and Actual Human Reasoning, Bochum, 4.-5. Oktober 2018, [Online-Edition: https://fileserver.ukp.informatik.tu-darmstadt.de/UKP_Webpag...],
[Konferenzveröffentlichung]

Schulz, Claudia ; Sailer, Michael ; Kiesewetter, Jan ; Meyer, Christian M. ; Gurevych, Iryna ; Fischer, Martin R. ; Fischer, Frank (2018):
Automatische Analyse von Diagnosekompetenzen in Fallsimulationen.
In: 6te Jahrestagung der Gesellschaft für Empirische Bildungsforschung (GEBF 2018), Basel, Switzerland, [Online-Edition: https://download.hrz.tu-darmstadt.de/media/FB20/Dekanat/Publ...],
[Konferenzveröffentlichung]

Schulz, Claudia ; Sailer, Michael ; Kiesewetter, Jan ; Meyer, Christian M. ; Gurevych, Iryna ; Fischer, Frank ; Fischer, Martin R. (2017):
Fallsimulationen und automatisches adaptives Feedback mittels Künstlicher Intelligenz in digitalen Lernumgebungen.
In: e-teaching.org Themenspecial „Was macht Lernen mit digitalen Medien erfolgreich?“, S. 1-14, [Online-Edition: https://www.e-teaching.org/etresources/pdf/erfahrungsbericht...],
[Article]

Sailer, Michael ; Kiesewetter, Jan ; Meyer, Christian M. ; Fischer, Martin R. ; Gurevych, Iryna ; Fischer, Frank (2017):
Förderung von Diagnosekompetenzen durch simulationsbasiertes Lernen im Lehramtsstudium.
In: Educational Research and Governance. Abstractband zur Tagung der Sektion „Empirische Bildungsforschung“ (AEPF), Tübingen, Germany, [Online-Edition: https://aepf2017.de//data/abstracts.pdf],
[Konferenzveröffentlichung]

go to TU-biblio search on ULB website