Bridging the digital divide in bio-manufacturing

Construction and validation of an OBE-AI-BT integrated teaching framework using a modified Delphi method

Datos Bibliográficos

ID22168564
AutoresXiangui Wang (National Research Institute of Brewing), Maoyu Zhao (National Research Institute of Brewing), Yihao Tang (National Research Institute of Brewing), Huawei Chen (0000-0002-6083-5080, National Research Institute of Brewing), Huajie Xu (National Research Institute of Brewing), Ju Guo (0000-0001-5254-792X, National Research Institute of Brewing)
Año2026
Volumen11
Fecha de publicación2026-06-04
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Education (JOURNAL)
Identificadores de la revistaISSN: 2504-284X • E-ISSN: 2504-284X
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/feduc.2026.1814782
OpenAlexW7163673885
IdiomaEN
Referencias citadas43

Driven by Industry 4.0, fermentation engineering is rapidly evolving from traditional empirical experimentation toward data-driven intelligent bio-manufacturing. This transition has created an urgent need for engineers who are fluent in both biological sciences and artificial intelligence (AI), yet many undergraduate programs remain compartmentalized, leaving graduates without the computational literacy required for modern research and development. To address this skills gap, we developed a Triadic Integration Framework that combines outcomes-based education (OBE), artificial intelligence (AI), and biotechnology (BT) within a unified teaching model. The framework was validated using a modified Delphi method involving 20 experts from academia and industry. Results from the first round revealed a clear tension between the recognized need for reform and the practical constraints of implementation, particularly with respect to excessive mathematical complexity (mean = 1.60) and inadequate hardware infrastructure (mean = 1.55). Accordingly, the framework was refined by shifting the pedagogical emphasis from algorithm development to tool-oriented application and by adopting cloud-based computing solutions to reduce hardware dependence. In the second validation round, the revised framework achieved high expert consensus (mean > 4.65) and strong stability (CV <=0.10). These findings support the value of a scaffolded curriculum and a Dual-Tutor mentorship model for aligning bioengineering education with the future bioeconomy

Cloud computing · Curriculum · Delphi · Delphi method · Mentorship · Bioeconomy and Sustainability Development · Biomedical and Engineering Education · Genetics, Bioinformatics, and Biomedical Research

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