Enhancing Toxicology Achievement by the VARK and the GRSLSS-mixed Models in Team-Based Learning.

Front Public Health

Occupational Health and Safety, School of Public Health, Walailak University, Nakhon Si Thammarat, Thailand.

Published: April 2022

Toxicology is needed to implement in the occupational health and safety (OHS) curriculum. Teaching toxicology is very challenging as its multidisciplinary science. Keeping students engaged in learning is a difficult issue when introducing solely theoretical framework. To enhance student performance, educators need to be aware of different learning styles and teach students accordingly. This study aimed to examine preferred learning styles and to further investigate the impact of learning style on team allocation and the effectiveness of team-based learning (TBL) in toxicology. A cross-sectional study of OHS students was performed. The visual, aural, reading/writing, and kinesthetic (VARK) learning style questionnaire and the Grasha-Reichmann Student Learning Styles Scale (GRSLSS), which identifies independent, dependent, collaborative, participant, competitive, and avoidant learning styles, were used with 101 study participants. After classification, participants studied three aspects of toxicology in three respective situations: (i) individual learning, (ii) TBL with students of the same VARK learning style, and (iii) TBL with students of varying VARK learning styles. Afterward, participants wrote a test on each of the aspects. The dominant VARK and GRSLSS learning styles were reading/writing (33.33%) and collaborative (50.00%), respectively. The participants achieved the highest test scores (88.31%) when they studied in a team with the various VARK styles, followed by studying in a team with the same VARK style (83.43%). Individual learning produced the lowest average score (69.79%). The results of this study suggest that creating a successful heterogeneity team based on the preferred learning styles is an effective teaching method in toxicology. It might be useful to toxicology educators and research studies from a wide range of disciplines to enhance student performance.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8804276PMC
http://dx.doi.org/10.3389/fpubh.2021.732550DOI Listing

Publication Analysis

Top Keywords

learning styles
28
learning
15
learning style
12
vark learning
12
team-based learning
8
enhance student
8
student performance
8
styles
8
preferred learning
8
learning tbl
8

Similar Publications

Using data from the 2014 China Family Panel Studies (CFPS), this study finds that when mothers hold dominant positions in their children's educational decisions, they are more likely to adopt a "tiger mom" approach. This dynamic explains why maternal dominance in educational decisions significantly enhances adolescents' cognitive abilities while hindering their non-cognitive skills. We propose time investment, material investment, and parenting styles as channel variables that offer a more comprehensive explanation.

View Article and Find Full Text PDF

Style mixup enhanced disentanglement learning for unsupervised domain adaptation in medical image segmentation.

Med Image Anal

December 2024

Department of Electrical Engineering, Yale University, New Haven, CT, USA; Department of Biomedical Engineering, Yale University, New Haven, CT, USA. Electronic address:

Unsupervised domain adaptation (UDA) has shown impressive performance by improving the generalizability of the model to tackle the domain shift problem for cross-modality medical segmentation. However, most of the existing UDA approaches depend on high-quality image translation with diversity constraints to explicitly augment the potential data diversity, which is hard to ensure semantic consistency and capture domain-invariant representation. In this paper, free of image translation and diversity constraints, we propose a novel Style Mixup Enhanced Disentanglement Learning (SMEDL) for UDA medical image segmentation to further improve domain generalization and enhance domain-invariant learning ability.

View Article and Find Full Text PDF

Introduction: Patient-centered communication is an essential skill in nursing, particularly in the care of older adult patients. However, generation Z nursing students, who primarily communicate through digital platforms, face unique challenges in adapting to traditional face-to-face communication with older adults. As a result, there is a need for teaching methods that align with this generation's learning style to enhance their communication skills.

View Article and Find Full Text PDF

Background: Machine learning models can reduce the burden on doctors by converting medical records into International Classification of Diseases (ICD) codes in real time, thereby enhancing the efficiency of diagnosis and treatment. However, it faces challenges such as small datasets, diverse writing styles, unstructured records, and the need for semimanual preprocessing. Existing approaches, such as naive Bayes, Word2Vec, and convolutional neural networks, have limitations in handling missing values and understanding the context of medical texts, leading to a high error rate.

View Article and Find Full Text PDF

Organic matter and biomarkers: Why are samples required?

Proc Natl Acad Sci U S A

January 2025

Center for Marine Environmental Sciences, University of Bremen, 28359 Bremen, Germany.

The search for evidence of past prebiotic or biotic activity on Mars will be enhanced by the return of samples to Earth laboratories. While impressive analytical feats have been accomplished by in situ missions on the red planet, accessing the capabilities of Earth's global laboratories will present a step change in data acquisition. Highly diagnostic markers of past life are biomarkers, organic molecules whose architecture can be attributed to once living organisms.

View Article and Find Full Text PDF

Want 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!