An in-depth framework for analyzing the outcomes of computer science instruction in an adaptive educational environment

Maxot Rakhmetov (), Zhanargul Kabylkhamit (), Nurgul Shazhdekeyeva (), Galiya Zhusupkalieva () and Bayan Kuanbayeva ()

International Journal of Innovative Research and Scientific Studies, 2025, vol. 8, issue 4, 2394-2404

Abstract: This article presents a comprehensive methodology for evaluating the effectiveness of the educational process in computer science within an adaptive learning environment. Adaptive learning is an approach in which the content, pace, and form of educational material presentation are adjusted to each student's characteristics, such as their level of knowledge, learning style, interests, and the pace of mastering the material. Unlike traditional methods, where all students receive the same amount and structure of knowledge, the adaptive system offers flexibility and individualization of learning. The developed methodology includes designing, implementing, and evaluating the effectiveness of an interactive digital platform that enables students to diagnose their initial educational level, identify their strengths and weaknesses, and automatically select educational materials and practical assignments aligned with their learning trajectory. An experimental study was conducted at Atyrau University named after Khalel Dosmukhamedov (Atyrau, Kazakhstan) involving 118 students studying in the field of Computer Science. The article describes the stages of integrating adaptive technologies into the educational process and presents comparative learning outcomes for students using the adaptive platform versus those studying with traditional methodologies. The results indicate that the use of an adaptive learning environment facilitates deeper assimilation of educational material, increases motivation, and improves students' academic results in computer science. The presented methodology can be utilized by educators and educational institutions to enhance teaching quality through modern digital and analytical tools.

Keywords: Adaptive learning; Computer science; Education; Efficiency; Individual needs. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijirss.com/index.php/ijirss/article/view/8401/1892 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aac:ijirss:v:8:y:2025:i:4:p:2394-2404:id:8401

Access Statistics for this article

International Journal of Innovative Research and Scientific Studies is currently edited by Natalie Jean

More articles in International Journal of Innovative Research and Scientific Studies from Innovative Research Publishing
Bibliographic data for series maintained by Natalie Jean ().