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SANTIAGO CITY, PHILIPPINES — Artificial intelligence-assisted instruction is strongly associated with better academic performance and more positive attitudes toward learning among high school students, according to a study by Lily Anne O. Climente and Celso C. Dumalig of Northeastern College, Inc. Graduate School in Santiago City, Philippines. Published in 2026, the study provides data-based evidence on how AI-supported learning relates not only to students’ academic outcomes but also to motivation, engagement, self-confidence, and learning satisfaction.
Artificial intelligence is rapidly changing the way technology is used in education. Intelligent tutoring systems, adaptive learning platforms, AI chatbots, automated assessment tools, and personalized feedback systems allow learning support to become more responsive to individual student needs. These technologies can help students receive information, feedback, and learning assistance more quickly while also supporting teachers in managing instructional activities.
The impact of AI in education, however, extends beyond academic scores. Students’ attitudes toward learning can also influence how effectively they participate in educational activities. Motivation, classroom engagement, confidence in their own abilities, and satisfaction with the learning experience are important indicators of how students respond to new learning technologies. Climente and Dumalig examined these factors together with academic performance among senior high school students.
The study involved 100 senior high school students exposed to AI-assisted instructional tools. The researchers used a validated questionnaire to examine students’ perceptions of AI-assisted instruction and their attitudes toward learning. Academic performance information was also obtained from approved academic records or assessment measures. The researchers then analyzed the data to determine the relationships between AI-assisted instruction, academic performance, motivation, engagement, self-efficacy, and learning satisfaction.
Students reported a very positive perception of AI-assisted instruction. The overall mean score reached 4.31 on the study’s rating scale, classified as “strongly agree.” Personalized learning support received the highest rating at 4.42, followed by AI-driven feedback mechanisms at 4.38. The results indicate that students particularly valued AI’s ability to provide learning assistance tailored to their needs.
Student motivation also received a highly positive assessment, with an overall mean of 4.33. The statement that AI-assisted instruction makes learning more enjoyable and engaging received the highest score at 4.41. Students also reported that AI increased their interest in learning activities, helped them complete academic tasks efficiently, encouraged classroom participation, and inspired them to improve their academic performance.
Engagement produced an overall mean of 4.36. Students gave the highest rating, 4.44, to the statement that AI-based learning tools helped them become more engaged in their studies. AI also received a 4.40 rating for making classroom activities more interactive and collaborative. These findings suggest that AI is perceived not simply as a tool for delivering information, but also as a technology that can encourage students to participate more actively in learning.
Students also reported stronger confidence in their learning abilities. Self-efficacy recorded an overall mean of 4.36. The highest-rated statement, at 4.42, indicated that AI-assisted instruction encouraged students to believe they could perform well academically. Students also reported greater confidence in completing academic tasks and understanding difficult lessons. Independent problem-solving received the lowest score in this category at 4.28, although it remained within the study’s strongly positive range.
Learning satisfaction recorded the highest overall mean among the attitudinal measures, reaching 4.40. Students gave a 4.46 rating to the statement that AI-based learning tools improve the overall quality of their learning experience. Convenience and accessibility also received a high rating of 4.41. The findings indicate that students generally viewed AI-supported learning as more supportive, accessible, effective, and satisfying.
Academic performance was also rated very highly, with an overall mean of 4.32. Task completion efficiency received the highest score at 4.41, followed by classroom-based academic outcomes at 4.35, knowledge retention at 4.30, standardized assessment scores at 4.28, and critical thinking performance at 4.24. While all indicators remained in the very high category, critical thinking received a slightly lower rating than the other academic performance measures.
The statistical analysis found a very strong positive relationship between AI-assisted instruction and academic performance, with a correlation coefficient of 0.82. The relationship between AI-assisted instruction and learning satisfaction was even stronger at 0.86, while self-efficacy reached 0.84. Engagement recorded a correlation of 0.81, and motivation reached 0.79. The study reported all of these relationships as statistically significant.
Multiple regression analysis further showed that AI-assisted instruction was a significant predictor across all measured outcomes. Learning satisfaction had the strongest beta coefficient at 0.88, followed by self-efficacy at 0.85, engagement at 0.83, academic performance at 0.81, and motivation at 0.76. The regression model produced an R² value of 0.79, indicating that the model accounted for approximately 79 percent of the variance in the outcomes examined in the study.
For schools, the findings provide evidence supporting a more structured approach to AI integration in education. AI can be used to support personalized, interactive, and responsive learning experiences. At the same time, the researchers emphasize that successful implementation requires adequate infrastructure, teacher training, institutional policies, and responsible use. Data privacy, algorithmic bias, unequal access to technology, limited infrastructure, and gaps in digital skills remain important challenges that schools need to address.
The findings from Lily Anne O. Climente and Celso C. Dumalig suggest that the role of AI in education goes beyond improving academic outcomes. AI-assisted instruction is also associated with how students experience learning, including their motivation, engagement, confidence, and satisfaction. However, the findings should be interpreted within the study’s context because the research involved 100 students in a Philippine educational setting. The authors recommend future research involving larger samples, different educational contexts, and longer-term analysis to further examine the effects of AI-assisted instruction.
Author Profiles
Lily Anne O. Climente — Northeastern College, Inc. Graduate School, Santiago City, Philippines.
Celso C. Dumalig — Northeastern College, Inc. Graduate School, Santiago City, Philippines.
Research Source
Climente, Lily Anne O., & Dumalig, Celso C. (2026). The Influence of Artificial Intelligence-Assisted Instruction on Students’ Academic Performance and Attitudinal Dispositions. International Journal of Scientific Multidisciplinary Research (IJSMR), Volume 4, No. 8, pp. 2055–2072.
DOI: https://doi.org/10.55927/ijsmr.v4i8.119
Journal: https://journalijsmr.my.id/index.php/ijsmr
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