2026· Journal of Educational Review· Vol 17, pp. 67-81· 0 citations
TL;DR
An in-depth systematic review was deplored to investigate the relationship between AI-powered learning tools, student engagement, and academic performance, focusing on the moderating roles of perceived ease of use (PEOU), frequency of AI tool use, instructor training and support (IT&S), and student digital literacy levels.
Abstract
The increasing rate of embracing artificial intelligence (AI) in higher institutions of learning globally has generated significant debate concerning its impact on student engagement and academic performance. While AI-powered tools promise personalized learning and greater efficiency, their effectiveness is highly dependent upon several moderating factors. An in-depth systematic review was deplored to investigate the relationship between AI-powered learning tools, student engagement, and academic performance, focusing on the moderating roles of perceived ease of use (PEOU), frequency of AI tool use, instructor training and support (IT&S), and student digital literacy levels. The detailed review synthesized existing literature to address vital research questions, exploring how these moderating factors influence the technology's effectiveness. The findings confirmed PEOU as the most significant predictor of positive student attitudes, while a higher frequency of AI tool use consistently correlates with better engagement and academic outcomes. Crucially,IT&S serves as the indispensable bridge, enabling instructors transition to studentcentred models and effectively manage AI's ethical and logistical demands. However, the in-depth review suggests that digital literacy plays a complex, but an indirect role: though it is necessary for technical competence, it does not automatically ensure greater academic engagement, suggesting a persistent need for motivationalapproaches. These findings highlight the need for balanced AI incorporation that prioritize both academic success and student well-being. This review contributes key insights for policymakers and developers seeking to enhance AI-powered learning environments
The rapid integration of Artificial Intelligence (AI)-powered assistant tools into higher education
has generated significant scholarly interest, particularly regarding their influence on student
engagement and the development of critical thinking skills. This study investigated the influence
of AI-powered assistant tools on students' engagement and critical thinking in curriculum
learning within the Faculty of Education, University of Port Harcourt, Nigeria. The study
adopted a descriptive survey research design; the study targeted a population of 1,406 students
from the 2022 and 2023 academic sets. A sample of 343 respondents was selected through
purposive, simple random, and proportional stratified random sampling techniques. Data were
collected using a structured questionnaire titled (IAATSECQ) with eight items each. Also, an AI
assisted quiz was administered via Google Forms. The reliability of the instrument using
Cronbach’s alpha was 0.751. Descriptive statistics (mean and standard deviation) were used to
answer research questions, while independent samples t-tests were employed to test the
hypotheses at a 0.05 significance level. Findings revealed that AI-powered tools significantly
enhanced students' engagement. Gender was found to significantly influence engagement (z =
2.985, p = 0.003), with female students demonstrating higher engagement levels. Age
significantly influenced critical thinking (z = 5.365, p = 0.000), with younger students (18–25
years) recording higher critical thinking scores than older students (26–35 years). The study
concludes that AI-powered assistant tools are effective instruments for enhancing academic
engagement and critical thinking in Nigerian higher education, and recommends the
institutionalization of AI literacy programmes and differentiated AI integration strategies that
are responsive to students' gender and age characteristics.
Faith Chinenye Okoye, Harriet Akudo Agbarakwe· International Journal of Edu...· 0 citations
This study aims to examine the effect of AI-powered tools on academic performance, conducted among students at the Faculty of Education at Ajilat city and explores the potential benefits and challenges of AI technology in education.
A. Saad· AlQalam journal of medical a...· 0 citations
Abstract
Artificial intelligence (AI) has moved from a peripheral support tool to a structural feature of online education, reshaping how content is sequenced, how learners are guided, and how platforms attract and retain enrollment. This paper presents a structured literature review and conceptual analysis of how AI-powered personalized learning systems influence two closely related but distinct outcomes in online education: student engagement and course enrollment decisions. Drawing on peer-reviewed research spanning adaptive learning systems, intelligent tutoring systems, recommender systems, and learning analytics, the paper synthesizes evidence on the mechanisms through which personalization affects behavioral, cognitive, and emotional engagement, and traces the downstream relationship between engagement, perceived value, and enrollment or re-enrollment behavior. A conceptual framework is proposed that links AI personalization features to engagement dimensions and enrollment-related outcomes through mediating constructs such as perceived usefulness, self-efficacy, and course fit. The paper also outlines a proposed mixed-methods research design that future empirical studies could use to test the framework, discusses ethical and equity considerations including data privacy and the digital divide, and identifies gaps in the current literature. The review indicates that while AI personalization is consistently associated with higher engagement and more favorable enrollment intentions in the studies examined, effects are moderated by digital literacy, platform design quality, and institutional context, and the evidence base remains fragmented across disciplines and geographic regions. The paper concludes with implications for online education providers, platform designers, and policymakers, and recommends directions for future longitudinal and cross-institutional research.
Keywords: Artificial intelligence; personalized learning; adaptive learning systems; student engagement; course enrollment; online education; recommender systems; learning analytics
V. C. V, J. K.· International Scientific Jou...· 0 citations
The skill-based dimensions of AI literacy were positively associated with AI dependency, whereas AI self-efficacy and academic self-efficacy were both negatively associated, suggesting a unified compensatory self-efficacy mechanism.
