AI Driven Tutoring vs. Human Teachers Examining the on Student Teacher Relationship
DOI:
https://doi.org/10.47067/ramss.v8i1.466Keywords:
AI-driven tutoring, human teachers, student learning outcomes, teacher-student relationship, education technology, quantitative research, statistical analysis, AI in higher education, adaptive learningAbstract
This study analyses the impact of AI-based tutoring as compared with human teachers by looking at aspects like learning results, teacher-learner relations, and AI as an adjunct resource for teaching. The research methodology employed here is a quantitative type, wherein the data for this research were collected by means of a self-report questionnaire distributed over 290 university teachers of Punjab. Statistical analyses carried out included correlation (r = 0.678, p < 0.01), regression (R² = 0.462, ? = 0.589, p < 0.01), and post hoc analysis (MD = 0.524, p = 0.003), and all of them affirmed that AI tutoring significantly enhances the academic performance but fails to approximate the emotional and social support delivered by human teachers. Public university lecturers rated AI higher than their counterparts in private institutions, a mean of 4.21 with a standard deviation of 0.79 against 3.69 and 0.85, respectively. There is therefore institutional differences in the uptake of AI. From the findings of the research, AI-based tutoring is, however a suitable solution for learning; it ought instead to complement rather than supplement human teaching. Future research should focus on enhancing AI’s emotional intelligence and optimizing AI-human collaboration in education.
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