MATERIALS AND METHODS: In this study, mapping of the physiology curriculum of three batches of BDS programme was conducted retrospectively. The components of the curriculum used for mapping were expected learning outcomes, curriculum content, learning opportunities, assessments and learning resources. The data were gathered by reviewing office records.
RESULTS: Descriptive analysis of the data revealed reasonable alignment between the curriculum content and questions asked in examinations for all three batches. It was found that all the expected learning outcomes were addressed in the curriculum and assessed in different assessments. Moreover, the study revealed that the physiology curriculum was contributing to majority of the programme outcomes. Nevertheless, the study could identify some gaps in the curriculum, as well.
CONCLUSION: This study revealed that majority of the components of the curriculum were linked and contributed to attaining the expected learning outcomes. It also showed that curriculum mapping was feasible and could be used as a tool to evaluate the curriculum.
Methods: . We assessed links through curriculum mapping, between assessments and expected learning outcomes of dental physiology curriculum of three batches of students (2012-14) at Melaka-Manipal Medical College (MMMC), Manipal. The questions asked under each assessment method were mapped to the respective expected learning outcomes, and students' scores in different assessments in physiology were gathered. Students' (n = 220) and teachers' (n=15) perspectives were collected through focus group discussion sessions and questionnaire surveys.
Results: . More than 75% of students were successful (≥50% scores) in majority of the assessments. There was moderate (r=0.4-0.6) to strong positive correlation (r=0.7-0.9) between majority of the assessments. However, students' scores in viva voce had a weak positive correlation with the practical examination score (r=0.230). The score in the assessments of problem-based learning had either weak (r=0.1-0.3) or no correlation with other assessment scores.
Conclusions: . Through curriculum mapping, we were able to establish links between assessments and expected learning outcomes. We observed that, in the assessment system followed at MMMC, all expected learning outcomes were not given equal weightage in the examinations. Moreover, there was no direct assessment of self-directed learning skills. Our study also showed that assessment has supported students in achieving the expected learning outcomes as evidenced by the qualitative and quantitative data.
Methods: . In the mentored student project (MSP) programme at Melaka Manipal Medical College, students undertake a short-term group research project under the guidance of their mentor. After data collection and analysis, students are required to write an abstract, present a poster and also write individual reflective summaries of their research experience. We evaluated the MSP programme using reflective summaries of a batch of undergraduate medical students. Data from 41 reflective summaries were analysed using the thematic analysis approach. The learning outcomes at the third and fourth levels of the Kirkpatrick evaluation model were determined from the summaries.
Results: . Students' reflective summaries indicated that they were satisfied with the MSP experience. In all the summaries, there was a mention of an improvement in teamwork skills through MSP. Improved relations with mentors were another relevant outcome. Improvement in communication skills and a positive change related to research attitude were also reported by students.
Conclusions: . Reflective summaries as a means to evaluate the MSP programme was found to be an easy, feasible and cost-effective method. The qualitative approach adopted for data analysis enabled the programme coordinators to assess the strengths and barriers of the programme.
OBJECTIVE: This scoping review explores the nursing educators' perception of the e-learning approaches used in nursing colleges.
DESIGN: A comprehensive review of five databases, Cochrane, Ebsco (Medline), PubMed, Science Direct, and Scopus, was conducted, adhering to the Joanna Brings Institute (JBI) standards full theme, utilizing preset eligibility criteria and adhering to the PRISMA Extension for Scoping review (PRISMA-ScR) recommendations.
METHODS: This scoping review examined studies published in English from January 1st, 2017-2022. Three reviewers evaluated the eligibility of the literature and retrieved data to address the research question from prior literature. A content analysis was done.
RESULTS: Thirteen articles with various hypotheses and models were reviewed. The review reveals that nursing educators are novices at using e-learning approaches in their classes due to their novelty in most nursing colleges. Nursing educators have a modest positive perception, with an optimistic perspective on e-learning effectiveness in theoretical course teaching, emphasizing that it is inappropriate in teaching clinical courses. The review demonstrates that e-learning faces numerous challenges that negatively impact educators' perceptions.
CONCLUSION: Institutional preparedness in terms of personnel through educator training, provision of necessary infrastructure, administrative support, and incentives are critical to improving the perception of the e-learning method and increasing its adoption in nursing colleges.
METHODS: An initial bibliometric analysis shows that the reviewed papers focused on Electromyogram(EMG), Electroencephalogram(EEG), Electrocardiogram(ECG), and Electrooculogram(EOG). These four categories were used to structure the subsequent content review.
RESULTS: During the content review, we understood that deep learning performs better for big and varied datasets than classic analysis and machine classification methods. Deep learning algorithms try to develop the model by using all the available input.
CONCLUSIONS: This review paper depicts the application of various deep learning algorithms used till recently, but in future it will be used for more healthcare areas to improve the quality of diagnosis.
METHOD: The paper explores a combination of variational mode decomposition (VMD), and Hilbert transform (HT) called VMD-HT to extract hidden information from EEG signals. Forty-one statistical parameters extracted from the absolute value of analytical mode functions (AMF) have been classified using the explainable boosted machine (EBM) model. The interpretability of the model is tested using statistical analysis and performance measurement. The importance of the features, channels and brain regions has been identified using the glass-box and black-box approach. The model's local and global explainability has been visualized using Local Interpretable Model-agnostic Explanations (LIME), SHapley Additive exPlanations (SHAP), Partial Dependence Plot (PDP), and Morris sensitivity. To the best of our knowledge, this is the first work that explores the explainability of the model prediction in ADHD detection, particularly for children.
RESULTS: Our results show that the explainable model has provided an accuracy of 99.81%, a sensitivity of 99.78%, 99.84% specificity, an F-1 measure of 99.83%, the precision of 99.87%, a false detection rate of 0.13%, and Mathew's correlation coefficient, negative predicted value, and critical success index of 99.61%, 99.73%, and 99.66%, respectively in detecting the ADHD automatically with ten-fold cross-validation. The model has provided an area under the curve of 100% while the detection rate of 99.87% and 99.73% has been obtained for ADHD and HC, respectively.
CONCLUSIONS: The model show that the interpretability and explainability of frontal region is highest compared to pre-frontal, central, parietal, occipital, and temporal regions. Our findings has provided important insight into the developed model which is highly reliable, robust, interpretable, and explainable for the clinicians to detect ADHD in children. Early and rapid ADHD diagnosis using robust explainable technologies may reduce the cost of treatment and lessen the number of patients undergoing lengthy diagnosis procedures.