Background: Blended learning is a blend of online and in-person instruction. This study was conducted to see its effect to learn Shalyatantra topic.
Methodology: Final-year students (58) were equally in two groups. The topic was taught using a conventional technique in group A and a blended learning way in group B. Pre-test and post-test were conducted before and after the study, respectively. Students' and teachers' perceptions on Likert scale were also taken. Statistical analysis was done.
Observation And Results: The mean post-test score of group B, i.e. blended learning group (18.37 ± 0.97), was more as compared to group A, i.e. conventional learning group (16.31 ± 1.53). Individually both groups were statistically significant.
Conclusion: It can be concluded that blended learning helped in developing critical thinking, communication skill in students, and enhance the retention of course content.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11805112 | PMC |
| http://dx.doi.org/10.4103/jpbs.jpbs_911_24 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Rapid Authentication of Plant-Based Milk Alternatives by Coupling Portable Raman Spectroscopy with Machine Learning.
J AOAC Int
March 2025
Department of Chemistry, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, K1S 5B6 Canada.
Background: Plant-based milk alternatives (PBMA) are increasingly popular due to rising lactose intolerance and environmental concerns over traditional dairy products. However, limited efforts have been made to develop rapid authentication methods to verify their biological origin.
Objective: In this study, we developed a rapid, on-site analytical method for the authentication and identification of PBMA made by six different plant species utilizing a portable Raman spectrometer coupled with machine learning.
Novel, multimodal, simulation practice with evolving case scenario for teaching familial communications in undergraduate medical training.
Med Teach
March 2025
Centre for Healthcare Simulation, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
There is a growing recognition of the importance of familial involvement in patient care. In Asian societies, communications with patients' families for routine medical updates and shared decision-making are considered part-and-parcel of clinical practice. Yet, training in familial communications has remained, by and far, a neglected aspect of conventional communications skills training in the medical curriculum, despite distinctive nuances in the communications approach.
View Article and Find Full Text PDFProtocol: Effectiveness of Sexual and Reproductive Health Blended Learning Approaches for Capacity Strengthening of Health Professionals in Low- and Middle-Income Countries: A Systematic Review.
Campbell Syst Rev
March 2025
Liverpool School of Tropical Medicine, International Public Health Liverpool UK.
This is the protocol for a Campbell systematic review. The objectives are as follows. The primary objective of this systematic review is to evaluate and synthesise both published and unpublished literature on the effectiveness of sexual and reproductive health blended learning approaches for capacity strengthening of healthcare practitioners in LMICs.
View Article and Find Full Text PDFMachine learning based estimation of density of binary blends of cyclohexanes in normal alkanes.
Sci Rep
March 2025
Department of Petroleum and Geo-energy Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
Given the application of cycloalkanes in surrogate blends for aviation fuels, their determination of critical characteristics pertinent to fuel transportation and combustion becomes imperative. In this study, we aim to construct intelligent models based on machine learning methods of random forest (RF), adaptive boosting, decision tree (DT), ensemble learning, K-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP) artificial neural network and convolutional neural network (CNN) to predict the density of binary blends of ethylcyclohexane or methylcyclohexane with n-hexadecane/n-dodecane/n-tetradecane in terms of operational conditions (pressure and temperature) and cycloalkane mole fractions in n-alkanes, utilizing laboratory data extracted from existing scholarly publications. The reliability of the data used is affirmed using an outlier detection algorithm, and the relevancy factor concept is utilized to find the relative effects of the input parameters on the output parameter.
View Article and Find Full Text PDFBWM analysis of online and offline learning effectiveness in Bangladesh.
Sci Rep
March 2025
Deaprtment of Mechatronics and Industrial Engineering, Chittagong University of Engineering and Technology, Chattogram, 4349, Bangladesh.
The shift to online learning during the COVID-19 pandemic presented significant challenges and opportunities, particularly in developing nations like Bangladesh, where digital infrastructure is limited. This study compares the effectiveness of online and offline learning for Bangladeshi engineering students using the Best Worst Method (BWM), a robust decision-making tool that simplifies the analysis by focusing on the best and worst criteria, ensuring consistency and accuracy. Eight key factors, including cost, flexibility, learning effectiveness, and technological challenges, were evaluated to identify the distinct strengths and limitations of each learning modality.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!