A pilot study on the evaluation of cognitive abilities’ cluster through game-based intelligent technique

Numerous scientific studies measured cognitive abilities through administered tests. Most of these traditional tests are inappropriate for several reasons, such as cost-ineffectiveness, tiresomeness, and invasiveness. The need is to build cost-effective, exciting, and plausibly engaging techniques that could noninvasively measure cognitive abilities. This paper presents LAS , an intelligent technique that utilizes non-invasively collected game analytics to automatically evaluate the cluster of three cognitive abilities (i.e. , Visual L ong-term Memory ( VLTM ), A nalytical Capability ( AC ), and Visual S hort-term Memory in Change Detection Paradigm ( VSTMiCDP )). The experimental group-based cross-generational cognitive evaluation in the game-based scenario established the potential of the proposed technique is twofold: 1) It successfully categorizes cluster of three targeted cognitive abilities within the 5-point evaluation sphere (i.e., 0–1 = very bad, 1–2 = bad, 2–3 = fair, 3–4 = good, 4–5 = excellent), and 2) It highly correlates with the results of a control group that are measured with three traditional cognitive tests.