Year: 2024
Type: article
Abstract: While students have plenty of opportunities to mingle with successful business leaders, often they form only a very general impression of them through meeting, interacting, and work-shadowing them. Notwithstanding the merits of these opportunities, any student’s subsequent application of leadership concepts based on their real-life encounters with these business people is inevitably mediated by their own background, up-bringing, education, and personal experience that may be subjective and biased. In a teaching project described in this paper, we enhance students’ learning experience to enable them to conduct syntheses and evaluations of the leadership styles, social responsibility, and ethical standards of business leaders by using the computer-assisted qualitative data analysis software (CAQDAS) called ATLAS.ti. Here, we ask students to conduct semi-structured interviews with leader executives to talk about social responsibility, business ethics, and leadership. Then, they transcribe the verbatim interview into text transcripts. Students were provided with an opportunity to synthesize knowledge by employing the CAQDAS, whose artificial intelligence and machine learning algorithms are based partly on principles of lexical semantics.
Authors: Andrew Chan, Shuk Ling Cheng
Institution: City University of Hong Kong
Language: English
Subfield: Management of Technology and Innovation
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
Funder: City University of Hong Kong
OpenAlex ID: W4400317864