Assessment using artificial intelligence in higher education: innovations and ethical challenges in the Ibero-American and Kazakh contexts—a mini-review

Scientific research on the assessment of educational outcomes using artificial intelligence technologies in higher education is still fragmented, especially in the context of Ibero-American countries and the transforming educational systems, which include Kazakhstan. Despite the active introduction of digital platforms, analytical tools, and automated assessment systems, comprehensive research revealing innovative approaches, methodological foundations, and ethical aspects of AI-based assessment remains limited. In this regard, this mini-review is aimed at filling the identified research gap by analyzing key theoretical works and modern empirical studies that determine the prospects for further development of this field. The methodological basis of the review is a conceptual model that considers assessment using artificial intelligence as a multi-level system that includes automated analysis of educational data, personalized feedback, predictive evaluation mechanisms, and algorithmic support for pedagogical decisions. Within the framework of this model, assessment is interpreted not as an isolated control tool, but as an integrated component of the educational environment that influences individual learning trajectories, academic success and student engagement. It should be noted that this mini-review is one of the first studies in which this conceptual framework is applied to a comparative analysis of assessment practices using artificial intelligence in the Ibero-American and Kazakh contexts of higher education. The review included 12 peer-reviewed scientific publications published since 2020, which addressed the issues of automated assessment, learning analytics, adaptive feedback systems and ethical aspects of the introduction of artificial intelligence in the university environment of these regions. The paper analyzes the main innovations in the field of AI-based assessment, including the use of behavioral and cognitive analytics, automated formative assessment, forecasting academic risks and personalized assessment support for students. Special attention is paid to contextual factors such as the level of digital readiness of students, the institutional features of universities, as well as differences in assessment practices between public and private educational organizations. Along with technological innovations, the mini-review examines the key ethical challenges associated with the use of artificial intelligence in assessing educational achievements. Such challenges include algorithmic bias, limited transparency of assessment decisions, issues of protecting students’ personal data, and the risks of increasing educational inequality. The analysis shows that the manifestation of these ethical issues varies in Ibero-American countries and Kazakhstan, reflecting differences in educational policies, the level of digital infrastructure, and socio-economic conditions. Based on research using a variety of methodological approaches, including quantitative, qualitative, and mixed designs, this mini-review demonstrates the multiplicity of interpretations and practices of applying artificial intelligence in higher education assessment. At the same time, the need to expand interdisciplinary research aimed at analyzing poorly studied categories of students and alternative educational trajectories in the digital environment is emphasized. In conclusion, the educational and ethical implications of further implementation of AI-based assessment in higher education are considered. Given the increasing role of automated assessment systems and the desire of universities to improve the objectivity and fairness of assessment, the development of methodologically sound and ethically responsible models for the use of artificial intelligence is of particular relevance. At the same time, taking into account the regional characteristics of educational systems makes the comparative analysis of the Ibero-American and Kazakh experience an important area of modern research in the field of digital education.

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Publication Details

Journal
Frontiers in Education
Published
2026-03-03
DOI
https://doi.org/10.3389/feduc.2026.1798126
Primary Topic
Artificial Intelligence in Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Assessment using artificial intelligence in higher education: innovations and ethical challenges in the Ibero-American and Kazakh contexts—a mini-review

Maxot Rakhmetov, Bakytgul Jugembayeva, Zhandos Zulpykhar, Raushan Zhilmagambetova et al.
Frontiers in Education
Artificial Intelligence in Education
article

Assessment using artificial intelligence in higher education: innovations and ethical challenges in the Ibero-American and Kazakh contexts—a mini-review

Maxot Rakhmetov, Bakytgul Jugembayeva, Zhandos Zulpykhar, Raushan Zhilmagambetova, Dameli Kapanova
article en

Abstract

Scientific research on the assessment of educational outcomes using artificial intelligence technologies in higher education is still fragmented, especially in the context of Ibero-American countries and the transforming educational systems, which include Kazakhstan. Despite the active introduction of digital platforms, analytical tools, and automated assessment systems, comprehensive research revealing innovative approaches, methodological foundations, and ethical aspects of AI-based assessment remains limited. In this regard, this mini-review is aimed at filling the identified research gap by analyzing key theoretical works and modern empirical studies that determine the prospects for further development of this field. The methodological basis of the review is a conceptual model that considers assessment using artificial intelligence as a multi-level system that includes automated analysis of educational data, personalized feedback, predictive evaluation mechanisms, and algorithmic support for pedagogical decisions. Within the framework of this model, assessment is interpreted not as an isolated control tool, but as an integrated component of the educational environment that influences individual learning trajectories, academic success and student engagement. It should be noted that this mini-review is one of the first studies in which this conceptual framework is applied to a comparative analysis of assessment practices using artificial intelligence in the Ibero-American and Kazakh contexts of higher education. The review included 12 peer-reviewed scientific publications published since 2020, which addressed the issues of automated assessment, learning analytics, adaptive feedback systems and ethical aspects of the introduction of artificial intelligence in the university environment of these regions. The paper analyzes the main innovations in the field of AI-based assessment, including the use of behavioral and cognitive analytics, automated formative assessment, forecasting academic risks and personalized assessment support for students. Special attention is paid to contextual factors such as the level of digital readiness of students, the institutional features of universities, as well as differences in assessment practices between public and private educational organizations. Along with technological innovations, the mini-review examines the key ethical challenges associated with the use of artificial intelligence in assessing educational achievements. Such challenges include algorithmic bias, limited transparency of assessment decisions, issues of protecting students’ personal data, and the risks of increasing educational inequality. The analysis shows that the manifestation of these ethical issues varies in Ibero-American countries and Kazakhstan, reflecting differences in educational policies, the level of digital infrastructure, and socio-economic conditions. Based on research using a variety of methodological approaches, including quantitative, qualitative, and mixed designs, this mini-review demonstrates the multiplicity of interpretations and practices of applying artificial intelligence in higher education assessment. At the same time, the need to expand interdisciplinary research aimed at analyzing poorly studied categories of students and alternative educational trajectories in the digital environment is emphasized. In conclusion, the educational and ethical implications of further implementation of AI-based assessment in higher education are considered. Given the increasing role of automated assessment systems and the desire of universities to improve the objectivity and fairness of assessment, the development of methodologically sound and ethically responsible models for the use of artificial intelligence is of particular relevance. At the same time, taking into account the regional characteristics of educational systems makes the comparative analysis of the Ibero-American and Kazakh experience an important area of modern research in the field of digital education.

Frontiers in EducationVol. 11
L. N. Gumilyov Eurasian National University (KZ), Humanitarian Institute (RU), Khalel Dosmukhamedov Atyrau University (KZ)
Openalex Percentile: Top 55%
Artificial Intelligence in Education
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