STUDENTS’ USE OF REFLECTIVE THINKING SKILL WHILE ENGAGING WITH AI-GENERATED DATA AND ITS ASSOCIATION WITH GENDER AMONG UNIVERSITY STUDENTS IN ANAMBRA STATE.

Abstract

This study focused on understanding the relationship between gender and reflective thinking skills
among university students in Anambra state while engaging with AI-generated data. Four research
questions and three hypotheses guided the study. Ex-post facto research design was used for the study
and students’ assignment scores was used as the data for the study. The study was carried out in
Nnamdi Azikiwe University Awka, Anambra State, Nigeria. Multi-stage sampling procedures was
used for the study. The population comprised nine departments in the department of Education.
Purposive sampling technique was used to select 3rd year students of department of Adult Education,
which has 105 students. For the scoring of the assignment, a rubric titled Rubric for Reflective
thinking scores (RRTS) was developed by the authors with the help of ChatGPT-AI. With the scores
from the RRTS, the students were categorized into levels as either exemplary reflective thinker,
competent reflective thinker, developing reflective thinker, Emerging reflective thinker. The mean and
standard deviation were used for the descriptive statistics while t-test and Pearson Product Moment
Co-relational analysis were used for the inferential statistics. The findings revealed that gender did not
significantly correlate with students’ reflective thinking skills while engaging with AI-generated data.
The study concluded that both genders have equal capacity for reflective thinking engagement with
AI-generated data, and reflective thinking subcomponents are interconnected process while answering
the assignment questions.