Promoting car mechatronics apprentices' diagnostic strategy with modeling examples: Development and evaluation of a simulation-based learning environment

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

Abstract

Crucial for training automotive mechatronics technicians (AMTs) is enabling them to diagnose car malfunctions. AMTs are particularly successful when they base their diagnostic process on a mental model of the affected automotive system. Still, only few AMT apprentices master such diagnoses after their apprenticeship. Therefore, we created a simulation-based learning environment with modeling examples to teach AMT apprentices a diagnostic strategy that builds on mental models. Following design-based research guidelines, we formatively evaluated our learning and testing materials by expert judgments and a small study during the development of the learning environment. Finally, an evaluation study showed that the learning environment promoted apprentices' knowledge about the diagnostic strategy. However, they could not transfer their knowledge to diagnostic problem-solving. Overall, the apprentices evaluated the learning environment positively, except it was considered too long and repetitive. Reasons for the outcomes as well as possible further developments of the learning environment are discussed.

Details

OriginalspracheEnglisch
FachzeitschriftStudies in Educational Evaluation
Jahrgang72
Ausgabenummer72
PublikationsstatusVeröffentlicht - März 2022
Peer-Review-StatusJa

Externe IDs

Scopus 85120174928
Mendeley 48836db0-ac30-33ab-857a-b1c432a69814
ORCID /0000-0002-3689-8428/work/142235930
ORCID /0000-0002-5182-577X/work/142249610

Schlagworte

Forschungsprofillinien der TU Dresden

DFG-Fachsystematik nach Fachkollegium

Fächergruppen, Lehr- und Forschungsbereiche, Fachgebiete nach Destatis

ASJC Scopus Sachgebiete

Schlagwörter

  • Diagnosis of car malfunctions, Mental models, Modeling examples, Simulation-based learning, Learning environment, Diagnosis of car malfunctions, Learning environment, Mental models, Modeling examples, Simulation-based learning

Bibliotheksschlagworte