Enhancing pharmaceutical calculation proficiency: Exploring self-directed learning and self-reinforcement assessment strategies for student success.

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Tác giả: Tarek Kassem, Uyen Minh Le, Tuan Tho Tran

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: United States : Currents in pharmacy teaching & learning , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 713575

INTRODUCTION: Proficiency in pharmaceutical calculations is essential for pharmacy students, particularly for their role in patient care. This study is to explore the impact of self-directed learning (SDL) and self-reinforcement assessment (SRA), (SDL/SRA), strategies on student performance in pharmaceutical calculations at [COP name]. METHODS: The study was conducted from 2020 to 2022, which included first-year pharmacy students. The calculation curriculum comprised a pre-pharmacy refresher, a primer program, a comprehensive course, and an online SDL program. SDL/SRA methodologies were introduced in 2021 and 2022 to enhance student engagement and learning outcomes. Data was collected through course evaluations, anonymous surveys, and comparative performance analysis. RESULTS: The implementation of SDL/SRA in 2021 and 2022 led to a notable improvement in student grades, with an increase of 13-17 % compared to 2020. Additionally, the failure rates dropped significantly from 30 % in 2020 to 2 % and 12 % in 2021 and 2022, respectively. Student feedback reflected a higher level of engagement and satisfaction with the course structure and the resources provided. Additionally, the analysis also identified challenges, particularly in understanding complex calculations and applying formulas to real-world scenarios. CONCLUSION: SDL/SRA strategies have the potential to effectively enhance student performance and engagement in pharmaceutical calculations. However, the study's limitations, such as being conducted at a single COP, the absence of demographic data, variations in teaching formats between online and onsite, and reliance on student feedback rather than direct analytics, highlight the need for further research to validate these findings across diverse educational contexts.
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