Design and evaluation of FEBS Education and Training Academy module – Integrating generative artificial intelligence into life‐science education
- 1Department of Pharmaceutical Analysis, Faculty of Pharmacy and Biochemistry University of Zagreb Croatia
- 2Faculty of Medicine İzmir University of Economics Türkiye
Abstract
Generative artificial intelligence (AI) is now embedded in higher education. Yet educators often adopt it more slowly and cautiously than students, and generic guidance rarely translates into changes in teaching or assessment practice. We designed a short, hands‐on, pedagogy‐first workshop in which life‐science educators work with their own course materials, intended to increase confidence in pedagogically informed AI use and prompt concrete changes to course design, teaching and assessment. However, this is an exploratory feasibility and specification report; therefore, the evaluation was not designed to test that intention. Here we describe the design of a transferable three‐session FEBS Education and Training Academy module, organised around the PICRAT (Passive‐Interactive‐Creative/Replace‐Amplify‐Transform) framework, a four‐element prompt structure and studio‐style application to participants' own teaching artefacts, and evaluate it using matched pre/post surveys, anonymous after‐session feedback and an online follow‐up meeting. Thirty‐four educators from 14 countries attended; 21 completed the pre‐workshop and 13 the post‐workshop survey (12 matched). Among the 12 respondents who completed both surveys, the proportion reporting high confidence rose by the same margin, 4 of 12, in each of the five practical domains. Ten of 13 follow‐up respondents reported implementing at least one idea and while views of AI as beneficial were already positive and changed little, agreement that AI poses significant risks to academic integrity fell. These participant‐reported, uncontrolled findings should be read as evidence of feasibility and perceived usefulness rather than causal impact.
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BibTeX
@article{mlinaric2026design,
title = {{Design and evaluation of FEBS Education and Training Academy module – Integrating generative artificial intelligence into life‐science education}},
author = {Zvonimir Mlinarić and Ali Burak Özkaya},
journal = {FEBS Open Bio},
year = {2026},
month = oct,
doi = {10.1002/2211-5463.70359},
url = {https://doi.org/10.1002/2211-5463.70359},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Design and evaluation of FEBS Education and Training Academy module – Integrating generative artificial intelligence into life‐science education
AU - Zvonimir Mlinarić
AU - Ali Burak Özkaya
PY - 2026
DA - 2026/10/26
JO - FEBS Open Bio
DO - 10.1002/2211-5463.70359
UR - https://doi.org/10.1002/2211-5463.70359
AB - Generative artificial intelligence (AI) is now embedded in higher education. Yet educators often adopt it more slowly and cautiously than students, and generic guidance rarely translates into changes in teaching or assessment practice. We designed a short, hands‐on, pedagogy‐first workshop in which life‐science educators work with their own course materials, intended to increase confidence in pedagogically informed AI use and prompt concrete changes to course design, teaching and assessment. However, this is an exploratory feasibility and specification report; therefore, the evaluation was not designed to test that intention. Here we describe the design of a transferable three‐session FEBS Education and Training Academy module, organised around the PICRAT (Passive‐Interactive‐Creative/Replace‐Amplify‐Transform) framework, a four‐element prompt structure and studio‐style application to participants' own teaching artefacts, and evaluate it using matched pre/post surveys, anonymous after‐session feedback and an online follow‐up meeting. Thirty‐four educators from 14 countries attended; 21 completed the pre‐workshop and 13 the post‐workshop survey (12 matched). Among the 12 respondents who completed both surveys, the proportion reporting high confidence rose by the same margin, 4 of 12, in each of the five practical domains. Ten of 13 follow‐up respondents reported implementing at least one idea and while views of AI as beneficial were already positive and changed little, agreement that AI poses significant risks to academic integrity fell. These participant‐reported, uncontrolled findings should be read as evidence of feasibility and perceived usefulness rather than causal impact.
SN - 2211-5463
ER -