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Updated: Dec 12, 2025

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
Published on: December 9, 2022
Quantitative and qualitative evaluation of a learning model based on workstation activities
Judit Sánchez1, Cristina Andreu-Vázquez1, Marta Lesmes1
1Universidad Europea de Madrid, Madrid, Spain.
Background:
Moving towards a horizontal and vertical integrated curriculum, Work-Station Learning Activities (WSLA) were designed and implemented as a new learning instrument. Here, we aim to evaluate whether and how this specific learning model affects academic performance. To better understand how it is received by medical students, a mixed methods research study was conducted.
Methods:
In the quantitative strand, two cohorts of first year students were compared: academic year 2015-2016 n = 320 with no exposure to WSLA, and academic year 2016-2017 n = 336 with WSLA. Learning objectives at different levels of Bloom's taxonomy were identified and performance evaluated from multiple-choice questions. In the qualitative strand, a total of six students were purposely selected considering academic performance and motivation, and submitted to semistructured interviews.
Results:
Performance at both cohorts for learning objectives at lower levels of Bloom's taxonomy was similar (38.8 vs. 39.0%; p = 0.955). In contrast, students in the WSLA group outperformed significantly those not exposed for learning objectives involving upper levels (68.5 vs. 54.2%; p <0.001). A multivariate analysis confirmed that the probability of mastering the second (more complex) objective is 1.64 times higher in students with WSLA methodology (OR 95% CI, 1.15-2.34; p = 0.007) than with traditional methodology. In the interviews, students perceived the clinical scenario of WSLA as a motivator and recognized this methodology as a more constructive framework for understanding of complicated concepts.
Conclusions:
In summary, our mixed methods research supports WSLA as a strategy that promotes deep learning and has a positive impact on academic performance for learning objectives involving higher order thinking skills in medical curricula.
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