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Volume 1, Issue 1

Perception of Vocational Educators on the Use of Artificial Intelligence for Personalized Learning in Technical Courses

Adebesin Lucky Isikilu , Salaudeen, F.M.,Taiwo, A.B & Lafiaji-Okuneye, B.B

Abstract

Introduction: The study examined vocational educators’ awareness,
perception, and readiness toward adopting artificial intelligence (AI) for
personalized learning in technical courses across tertiary institutions in Lagos
State. Guided by four research questions and two hypotheses, the study aimed
to explore the depth of educators’ familiarity with AI, its perceived usefulness,
their preparedness for integration, and the challenges impeding its adoption.
Methodology: The study adopted a descriptive survey research design. The
population consisted of vocational educators in three Lagos-based institutions:
FCET Akoka, YABATEC, and FSTC Yaba. A sample of 106 respondents was
selected using purposive sampling. A structured questionnaire, validated by
educational technology experts, served as the main instrument for data
collection. The instrument’s reliability was established with a Cronbach alpha
coefficient of 0.86. Data were analyzed using descriptive statistics (mean and
standard deviation) for research questions and inferential statistics (Pearson
correlation and one-way ANOVA) for testing hypotheses at a 0.05 significance
level.
Results and Recommendations: Findings revealed that while awareness of AI
was moderate, educators generally recognized its usefulness for personalized
instruction. A significant positive correlation was found between awareness
and readiness to adopt AI. Moreover, educators from Polytechnics perceived
AI more positively than their counterparts in Colleges of Education and
Technical Colleges. It was concluded that awareness and perception play
crucial roles in adoption, but infrastructural and policy limitations hinder
progress. The study recommends targeted training, improved infrastructure,
AI policy development, inter-institutional collaboration, and curriculum
enhancement to support AI integration in vocational education.

Keywords

Teachers' attributes, work place features, determinants, students, students' academic performance.

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