Abstract:
I observed that my first-year BSc Artificial Intelligence and Data Science (n=85) students following
the Web Technology module were not motivated to self-learn and explore beyond what was
taught in lectures. As they were also less interested in self-reading the recommended textbooks
or supplementary reading, I deployed a questionnaire that showed the majority as interested in
self-learning (90%) but only 56% being slightly enthusiastic about reading. As reading is integral
for self-learning, this research discusses transforming these students into active self-learners
through introducing a stepwise reading procedure with group work opportunities to voice their
thoughts, learning and findings. Lecture times were used to give students (formed into small
groups of eight) a concept to learn using the SQ4R reading procedure. At the end of each group
session of fifteen minutes, each group was given the opportunity to present their work to the
class. To give ‘deliberate practice’ of this procedure to the students, this learning activity was
repeated four times as classroom tasks based on readings from recommended textbooks. Think-
Pair-Share intervals were introduced between practice tasks to clarify doubts with the lecturer’s
input. The student perceptions of the implemented activities were evaluated through an online
questionnaire that had a 68% response rate. Results showed that 62% of students did not refer
to the textbooks before the activity while 90% of students stated the activity encouraged them
to refer recommended textbooks. Of the students, 91% mentioned that the activity helped them
to explore supplementary materials and they were willing to engage in similar activities in future.
Encouragement, interaction, inspiration, and motivation were major keywords identified
through thematic analysis of general comments received. It is evident that learning in groups
with peer voice input in reading activities has a positive influence on Artificial Intelligence and
Data Science students in the classroom.
