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Expertise-dependent mental representation in chess: evaluation and comparisons based on structural dimensional
Thomas Küchelmann1,2, Konstantinos Velentzas1,2, Christian Schütz3
1Department of Neurocognition and Action-Biomechanics, Faculty of Sport Sciences, Bielefeld University, Bielefeld, Germany.
Introduction:
Research findings underline that human behavior and decisive action significantly depend on knowledge accessibility in long-term memory (LTM). For this purpose, various methods have been conducted and applied to help researchers gain insights into LTM functioning. These methods are based on traditional low-cost instruments (e.g., think-aloud protocols, memory protocols, questionnaires, a. o.) as well as modern high-cost technologies.
Method:
Furthermore, an emerging method that evolves traditional research techniques in a digitalized environment is Structural Dimensional Analysis-Motoric. This analysis is based on participants' preferences regarding the closeness of given task-related concepts (TRCs) during a sorting process. From this perspective, chess is a highly cognitive domain involving an immense amount of specific knowledge-a reason it became a prominent field in cognitive research. The present study aims to examine how strategy-related patterns (meaningful and interconnected standardized chess motifs) are incorporated into the LTM of chess players, depending on their expertise (novices, intermediates, and high-level players).
Results:
The analysis shows a significant similarity between experts and intermediate chess players but no significant results for the comparisons between experts and intermediates to novices.
Discussion:
Researchers should make efforts to expand mental representation research in chess, for example, by manipulating a variety of strategy-related patterns (e.g., critical openings, middle games, and endgame situations) and/or enhancing the difficulty of the TRCs. The results can be applied to the further development of augmented feedback (e.g., assistive training systems) and virtual players (platforms).
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