Active versus Passive Strategy in Online Creativity Training: How to Best Promote Creativity of Students with Different Cognitive Styles?. (June 2022)

• Record Type: Journal Article
• Authors: Gu, Xiaojing; Tan, Yafei; Wu, Xiaofei; Cai, Zhouqu; Lai, Qing; Cheng, Min; Zhao, Qingbai
• Is Part Of: Thinking skills and creativity. Volume 44(2022)
• Publication Date: 2022-06
• Subjects: Online training -- Creativity -- Active learning -- Passive learning -- Cognitive style; Thought and thinking -- Periodicals; Critical thinking -- Study and teaching -- Periodicals; Creative thinking -- Study and teaching -- Periodicals; Thinking -- Periodicals; Creativeness -- Periodicals; Teaching -- Periodicals; Pensée -- Étude et enseignement -- Périodiques; Créativité (Éducation) -- Étude et enseignement -- Périodiques; 370.15205
• DOI: 10.1016/j.tsc.2022.101021
• Languages: English
• ISSNs: 1871-1871

Abstract

Highlights: Interaction effects between cognitive style and online training strategy were examined; Individuals with different cognitive styles (FDs rely on external references while FIs rely on external references in the processing of information) prefer different training strategies; FDs significantly improved on creative performance in the active online training; FIs didn't differ in creative performance between active or passive online training Abstract: While online education has become a new trend for knowledge acquisition and skill development, empirical studies on the effectiveness of online creativity training are scarce and the findings are inconclusive. In the current study, we investigated whether individual differences in cognitive style (i.e., FD-field dependence, FI-field independence) influence learners' performance in online creativity training. The literature suggests that when processing information, FD learners tend to prefer inductive learning and rely on external references while the FI learners are more likely to prefer deductive learning and rely on internal reference. A three-day online training was developed and delivered to participants via either the active or the passive training strategy. This study was a pre-posttest between-subjects design, and three creativity tasks (AUT-alternative uses task, visual imagination task, and the design problem) were used to measure participants' creative performance. The MANOVA results showed a significant interaction effects that FD participants greatly improved on performance of the AUT and the design problem after exposing to the active training compared to the passive training, whereas the FI participants did not show improvement. Besides, the FD participants reported positive training experiences (preference and motivation) on the active training strategy while the FI participants didn't seem to differ in their experiences of different training strategies. The current findings implicate that instructor and teachers should be aware of the individual differences while designing creativity training materials/courses in digital as well as real-life contexts.