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Team‐based learning and training transfer: a case study of training for the implementation of enterprise resources planning software
Author(s) -
Hart Sharon L.,
Steinheider Brigitte,
Hoffmeister Vivian E.
Publication year - 2019
Publication title -
international journal of training and development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.558
H-Index - 26
eISSN - 1468-2419
pISSN - 1360-3736
DOI - 10.1111/ijtd.12150
Subject(s) - knowledge management , knowledge transfer , computer science , context (archaeology) , transfer of training , transfer of learning , enterprise resource planning , process management , artificial intelligence , business , paleontology , biology
While traditional models of training such as behavioral modeling (BMT) have been found to enhance training transfer, research suggests that more active learning strategies such as error management (EMT) and team‐based learning (TBL) may be more effective. This paper analyzes BMT, EMT and TBL strategies to train employees on new enterprise resources planning (ERP) software and discusses which training leads to successful procedural and declarative knowledge transfer, knowledge retention and application, and tangible business outcomes. TBL was predicted to be the most effective training type, as it models several components needed to use ERP software in the actual job setting. Overall and procedural knowledge as well as knowledge application scores improved most for TBL participants, while declarative knowledge improved the most in the EMT condition. During training, all conditions showed significant improvement in knowledge application; however, the TBL condition showed the highest knowledge application gains. This paper discusses the elements of TBL that support its use as an effective strategy to increase knowledge transfer in an organizational context.