TY - CHAP
T1 - Learning effectiveness of virtual entrepreneurship programs
T2 - 82nd Annual Meeting of the Academy of Management
AU - Jin, Fuhe
AU - Shimaoka, Mikiko
AU - Kito, Tomomi
AU - Sayama, Hiroki
AU - Chao, Chun-Han
AU - Tsai, Chou-Yu
N1 - "Academy of Management Proceedings (Proceedings) is an online publication that includes abstracts of all papers and symposia presented at the AOM Annual Meeting. It also includes 6-page abridged versions of the Best Papers accepted for inclusion in the program (approximately 10%). Papers published in the Proceedings are abridged so that the full length paper may be submitted for future journal publication."
PY - 2022
Y1 - 2022
N2 - With the expansion in entrepreneurship, the number of entrepreneurship education programs worldwide has increased significantly. Meanwhile, the advancement of computer information technology and the COVID-19 pandemic have contributed/forced immensely to the implications of virtual tools in entrepreneurship education programs. This rise forces entrepreneurship educators to overcome challenges associated with technology-mediated communications that limit social participation and interactions that substantially constitute students' learning and cognitive development. To address the needs of evaluating the effectiveness of virtual entrepreneurship education, we measured students' learning and growth in a Zoom-based entrepreneurship education program. With a longitudinal design, we applied machine- learning algorithms with network analysis and growth modeling to analyze the program's effectiveness in student learning. The results from network analysis indicated that high-performing teams displayed more equally distributed communication structures, while those of low- performing teams were more centralized. Growth modeling successfully captured students' enhanced entrepreneurial intentions at the end of the program; such growth patterns were distinctive between students with different personal characteristics (i.e., perspective-taking and imaginative capability). In sum, the proposed multilevel analytical framework and the current study's findings can be used to offer the best practices for entrepreneurship education programs and applicable methodologies for educators utilizing virtual learning systems.
AB - With the expansion in entrepreneurship, the number of entrepreneurship education programs worldwide has increased significantly. Meanwhile, the advancement of computer information technology and the COVID-19 pandemic have contributed/forced immensely to the implications of virtual tools in entrepreneurship education programs. This rise forces entrepreneurship educators to overcome challenges associated with technology-mediated communications that limit social participation and interactions that substantially constitute students' learning and cognitive development. To address the needs of evaluating the effectiveness of virtual entrepreneurship education, we measured students' learning and growth in a Zoom-based entrepreneurship education program. With a longitudinal design, we applied machine- learning algorithms with network analysis and growth modeling to analyze the program's effectiveness in student learning. The results from network analysis indicated that high-performing teams displayed more equally distributed communication structures, while those of low- performing teams were more centralized. Growth modeling successfully captured students' enhanced entrepreneurial intentions at the end of the program; such growth patterns were distinctive between students with different personal characteristics (i.e., perspective-taking and imaginative capability). In sum, the proposed multilevel analytical framework and the current study's findings can be used to offer the best practices for entrepreneurship education programs and applicable methodologies for educators utilizing virtual learning systems.
M3 - Conference abstract in proceedings
T3 - Academy of Management Proceedings
BT - Academy of Management Proceedings
PB - Academy of Management
Y2 - 5 August 2022 through 9 August 2022
ER -