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

Faizan Ahmad; Zeeshan Ahmed; Momina Shaheen; Sara Muneeb; Rubata Riasat

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

Faizan Ahmad, Zeeshan Ahmed, Momina Shaheen, Sara Muneeb, Rubata Riasat

Faculty of Business and Law

Research output: Contribution to journal › Article › peer-review

Abstract

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 Long-term Memory (VLTM), Analytical Capability (AC), and Visual Short-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.

Original language	English
Journal	Multimedia Tools and Applications
Publication status	Published - 10 Apr 2023

Access to Document

https://link.springer.com/article/10.1007/s11042-023-15100-x

Cite this

@article{c32910942faa4e83871dd17f146fc55c,

title = "A pilot study on the evaluation of cognitive abilities{\textquoteright} cluster through game-based intelligent technique",

abstract = "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 Long-term Memory (VLTM), Analytical Capability (AC), and Visual Short-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.",

author = "Faizan Ahmad and Zeeshan Ahmed and Momina Shaheen and Sara Muneeb and Rubata Riasat",

year = "2023",

month = apr,

day = "10",

language = "English",

journal = "Multimedia Tools and Applications",

issn = "1380-7501",

publisher = "Springer Netherlands",

}

TY - JOUR

T1 - A pilot study on the evaluation of cognitive abilities’ cluster through game-based intelligent technique

AU - Ahmad, Faizan

AU - Ahmed, Zeeshan

AU - Shaheen, Momina

AU - Muneeb, Sara

AU - Riasat, Rubata

PY - 2023/4/10

Y1 - 2023/4/10

N2 - 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 Long-term Memory (VLTM), Analytical Capability (AC), and Visual Short-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.

AB - 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 Long-term Memory (VLTM), Analytical Capability (AC), and Visual Short-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.

M3 - Article

SN - 1380-7501

JO - Multimedia Tools and Applications

JF - Multimedia Tools and Applications

ER -