Gestalt perception: A game designed to explore players’ gameplay self-efficacy and anxiety reflected in their learning effects

Abstract

Gestalt perception relates to inferring a holistic scene from separate elements. Using this theory, an application game named Gestalt Puzzle was designed for students to play by recognizing a few parts of an image to reason the whole image of a particular object. Cognitive style can be divided into field independence (FI) and field dependence (FD) depending on individuals’ ability to identify minor components of a whole image. To understand the gameplay learning effect, this study explored how players’ field-independent cognitive style (FI-CS) interacted with their gameplay performance as the two types of cognitive styles were mediated by their self-efficacy and gameplay anxiety in a competition setting. Data from 112 sixth-grade students were collected for confirmatory factor analysis with structural equation modeling. First, participants completed a trial to familiarize themselves with the functions and mechanism of the game; second, all of the participants were divided into teams to compete against each other for 15 minutes by identifying Chinese paintings; they then completed a questionnaire. The results of this study indicated that FI-CS was positively related to gameplay self-efficacy, but negatively related to gameplay anxiety; perceived utility value could be positively predicted by gameplay self-efficacy, but negatively predicted by gameplay anxiety; and perceived value was positively related to game performance. Moreover, FI-CS was positively related to perceived value mediated by gameplay self-efficacy and gameplay anxiety. The implication of this study is that the Gestalt perception game may engage FI-CS learners with higher levels of gameplay self-efficacy, perceived value, and performance, but a lower level of gameplay anxiety. The present study findings imply that teachers can use Gestalt perception games to promote students’ learning of Taiwanese culture.

Keywords:

• Elementary education
• human-computer interface
• improving classroom teaching
• interactive learning environments
• teaching/learning strategies

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was financially supported by the “Institute for Research Excellence in Learning Sciences” of National Taiwan Normal University (NTNU) from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan and also the Ministry of Science and Technology in Taiwan under grant number MOST 104-2511-S-003-003 and MOST 105-2511-S-003-002.

Notes on contributors

Jon-Chao Hong

Jon-Chao Hong is a Professor in the Department of Industrial Education at National Taiwan Normal University and also a member of the Institute for Research Excellence in Learning Science.

Ming-Yueh Hwang

Ming-Yueh Hwang is a Professor in the Department of Adult and Continuing Education at National Taiwan Normal University.

Hui-Ting Hsu

Hui-Ting Hsu graduated from Department of Industrial Education in National Taiwan Normal University for master degree.

Kai-Hsin Tai

Kai-Hsin Tai is a Postdoctoral fellow of National Taiwan Normal University and also a member of the Institute for Research Excellence in Learning Science.