Real-World Problem Solving as a Means of Promoting IS Expertise

By:
Dr. Weiqi Li,
Ming Li
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The fundamental goal of this study was to investigate the effects of an experience-based learning environment on information systems (IS) students' learning process, knowledge acquisition and knowledge structure. The learning environment was structured in a way consistent with the problem solving approaches used by IS experts. To assess the knowledge structure of the learners, this study designed three research instruments that included a declarative-knowledge test, a problem-solving task, and a similarity-judgment task. The analysis results suggested that the learning outcome from this experience-based learning environment was very positive. The environment that imposed an expert-like organization both on information gathering and on problem solving activities resulted in improved problem-solving skills. The learners mastered the necessary declarative knowledge, as well as developed domain-specific basic skill and strategies.


Keywords: Learning Environment, Knowledge Structure Assessment, Experience-Based Learning, Learning Technology
Stream: Curriculum and Pedagogy
Presentation Type: Virtual Presentation in English
Paper: Real-World Problem Solving as a Means of Promoting IS Expertise


Dr. Weiqi Li

Assistant Professor, School of Management, University of Michigan-Flint
USA

Weiqi Li received the B.S. degree in mechanical engineering in 1982 from Nanjing University of Aeronautics and Astronautics, China; the B.A. degree in international trade in 1986 from University of International Business and Economics, China; the M.B.A., M.S. in computer science, and Ph.D. in management information systems from University of Mississippi in 1994, 1996, and 1998, respectively. He served as assistant professor in the School of Business at Michigan Technological University from 1999 to 2001. In 2001 he joined the faculty of the School of Management of the University of Michigan - Flint, where he currently is assistant professor of Management Information Systems. His research interests include machine learning, heuristics for the combinatorial optimization problems, and e-learning.


Ming Li

Affiliation not supplied


Ref: L05P0133