THE MEDIATING ROLE OF CRITICAL AND ALGORITHMIC THINKING INDICATORS IN DETERMINING STUDENTS' PROGRAMMING APTITUDE (A CASE STUDY OF THE MindMetricAI PLATFORM)
Year: 2026
Type: article
Abstract: In today's era of rapid development of information technology and digitalization processes, changes in education and the proliferation of automated educational systems are radically transforming real-time diagnostic and effective development methods for future IT professionals' programming aptitude. Using the MindMetricAI intelligent diagnostic platform as a case study, this research investigates the relationship between higher education students' academic performance in programming and their cognitive aptitude indicators by examining the mediating role of critical and algorithmic thinking. The introduction of intelligent diagnostic systems and flexible assessment platforms has expanded the flexibility of identifying students' cognitive profiles and individual capabilities. However, concerns regarding the effectiveness of traditional methods for assessing programming aptitude persist. Multi-factor cognitive indicators, which include the ability to use software tools, analyze logical structures, and critically evaluate algorithmic solutions, are of vital importance in this regard.This study examines how students' programming aptitude indicators affect their academic performance and analyzes the mediating role of critical and algorithmic thinking in this process. The study hypothesizes that critical and algorithmic thinking skills mediate the relationship between programming aptitude and academic achievement. To gather primary data, questionnaires based on MindMetricAI platform indicators were administered to 356 undergraduate students in their 1st and 2nd years at Nukus State Technical University, Bukhara State Technical University, and Navoi State University. The analysis results demonstrated that critical and algorithmic thinking indicators play a significant mediating role in determining students' programming aptitude and academic performance levels, while possessing high accuracy in identifying cognitive profiles.
Source: HSR (London)
Author: Tleubaeva Gulnur
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7225682796
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