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Pakizar Shamoi

Work place: Kazakh-British Technical University, School of Information Technology and Engineering, Almaty, 050000, Kazakhstan

E-mail: p.shamoi@kbtu.kz

Website: https://orcid.org/0000-0001-9682-0203

Research Interests:

Biography

Pakizar Shamoi received the B.S. and M.S. degrees in information systems from the Kazakh-British Technical University, Almaty, Kazakhstan, in 2011 and 2013, and the Ph.D. degree in engineering from Mie University, Tsu, Japan, in 2019. She has 13 years of experience in teaching technical subjects to university students. In her academic journey, she has held various teaching and research positions at Kazakh-British Technical University, where she has been serving as a professor in the School of Information Technology and Engineering since August 2020. She is the author of 1 book and more than 33 scientific publications. Awards for the best paper at conferences were received six times. Her research interests include artificial intelligence and machine learning in general, focusing on fuzzy sets and logic, soft computing, representing and processing colors in computer systems, natural language processing, computational aesthetics, and human-friendly computing and systems. She took part in the organization and worked in the org. committee of several international conferences IFSA-SCIS 2017, Otsu, Japan; SCIS-ISIS 2022, Mie, Japan; EUSPN 2023, Almaty, Kazakhstan. She served as a reviewer at several international conferences, including IEEE: SIST 2023/2024, SMC 2022, SCIS-ISIS 2022, SMC 2020, ICIEV-IVPR 2019, ICIEV-IVPR 2018. Dr. Shamoi is an IEEE member and member of the presidium of the Council of Young Scientists of the Academy of Sciences of Kazakhstan.

Author Articles
Fuzzy Intelligent System for Student Software Project Evaluation

By Anna Ogorodova Pakizar Shamoi Aron Karatayev

DOI: https://doi.org/10.5815/ijmecs.2025.04.02, Pub. Date: 8 Aug. 2025

Developing software projects allows students to put knowledge into practice and gain teamwork skills. However, assessing student performance in project-oriented courses poses significant challenges, particularly as class sizes increase. This paper introduces a fuzzy intelligent system designed to evaluate academic software projects using an object-oriented programming and design course as an example. Our methodology involved conducting a survey of student project teams (n=31) and faculty (n=3) to identify key evaluation parameters and their applicable ranges. The critical criteria—clean code, use of inheritance, and functionality—were represented as fuzzy variables with corresponding fuzzy sets. We collaborated with three experts, including one professor and two course instructors, to define a set of fuzzy rules for a fuzzy inference system. This system processes the input criteria to produce a quantifiable measure of project success. Our fuzzy intelligent system demonstrated promising results in automating project evaluation, standardizing assessments, and reducing subjective bias in manual grading. The key findings show that the system effectively manages the increasing instructor workload, provides consistent and transparent evaluations, and offers timely and accurate feedback to students.

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