Journal of Engineering Education Transformations
DOI: 10.16920/jeet/2024/v37is2/24137
Year: 2024, Volume: 37, Issue: Special Issue 2, Pages: 893-900
Original Article
Radhakrishnan Nithya1, Karthikeyan Sathasivam2, Muthiah Ramanathan3
1,2Department of Pharmaceutics, PSG College of Pharmacy, Coimbatore-641004
3Department of Pharmacology, PSG College of Pharmacy, Coimbatore-641004
*Corresponding Author
Email: nithyar7340@psgpharma.ac.in
skarthik.kerala@gmail.com
muthiah.in@gmail.com
This study delves deeply into the complex interplay between distinct learner categories and their impact on performance trends and graduation outcomes within the pharmaceutical sciences domain. A cohort of 60 Bachelor of Pharmacy students was analyzed across different learner categories—slow, average, advanced, and non-performers. Methodologically, students' learning capacities were assessed, and tailored support measures were implemented. Graduation outcomes were measured based on industry placements, competitive exam success, and higher studies pursuit. Statistical analysis, including Chi-Square tests, revealed intriguing patterns. Notably, each learner category exhibited varying degrees of achievement on specific graduation outcomes. Our findings challenge the traditional assumptions, and results showcases those average learners significantly contributed across various graduation outcomes, emphasizing their adaptability and resilience. Both slow and advanced learners made comparable contributions, highlighting factors beyond initial learning abilities impacting success. Conversely, non-performers faced challenges hindering their academic and career prospects. Performance trends indicated challenges in pharmaceutical chemistry for slow and average learners, while advanced learners excelled in specific subjects. Average learners dominated in industry placements but displayed weaker performance in competitive exams. The equality in graduation outcomes among advanced and slow learners underscores differing performance metrics. This study's implications emphasize reconsideration of support mechanisms, spotlighting the potential of average learners and the necessity to address challenges faced by non-performers. Future research should explore additional factors influencing graduation outcomes.
Keywords—learner categories; learning trends; graduation outcomes; pharmaceutical sciences
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