Towards Flow Theory on the Design of a Tutoring System for Improving Affective Quality

Csikszentmihalyi’s flow theory states that the components that lead to an optimal state of intrinsic motivation and personal experience may further lead to optimal learning. However, little evidence suggests that a tutoring system (TS) aimed at providing flow preconditions impacts student learning when the contents are the same. Therefore, this study tests this hypothesis by modifying a TS used in an international English language institute (IELI) to provide flow preconditions of students and maintain a balance between the skill level of students and the difficulty level of learning tasks. Fifty-five students in the IELI were separated into two groups to use the modified TS and the original TS. Analysis results indicate an improved engagement and affective quality, as well as reduced frustration levels of the students who used the proposed TS.

Authors and Affiliations

1. Institute of Computer Science and Engineering, National Chiao Tung University, Taiwan (R.O.C.)

   Po-Ming Lee

2. Institute of Biomedical Engineering, National Chiao Tung University, Taiwan (R.O.C.)

   Sin-Yu Jheng & Tzu-Chien Hsiao

3. Department of Computer Science, National Chiao Tung University, Taiwan (R.O.C.)

   Po-Ming Lee & Tzu-Chien Hsiao

4. Biomedical Electronics Translational Research Center and Biomimetic Systems Research Center, National Chiao Tung University, Taiwan (R.O.C.)

   Tzu-Chien Hsiao

Editors and Affiliations

1. Computer Science Department, University Politehnica of Bucharest, Splaiul Independentei 313, 060042, Bucharest, Romania

   Stefan Trausan-Matu

2. North Carolina State University, 890 Oval Dr., Campus Box 8206, 27695-8206, Raleigh, NC, USA

   Kristy Elizabeth Boyer

3. Department of Information and Computer Sciences, University of Hawaii, 1680 East-West Road, POST 317, 96822, Honolulu, HI, USA

   Martha Crosby

4. Neoanalysis Ltd., Marni 56, 10437, Athens, Greece

   Kitty Panourgia

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