The Use of Game-Based Learning to Enhance Student Engagement in the Acupuncture Programme: South African Students’ Opinions
Journal for the Education of Gifted Young Scientists(2023)
University of Johannesburg
Abstract
Student engagement plays an important role in promoting student success at higher education institutions. It is of profound significance to improve student engagement through the utilisation of effective pedagogical approaches, such as game-based learning. However, there is a lack of study in the South African context focusing on game-based learning at higher education institutions. This study aimed to explore students’ views and experiences on game-based learning at an identified university in South Africa. The constructivism learning theory was anchored in this study as a theoretical lens. In this study, the authors adopted a qualitative single case study design within an interpretivist paradigm. A purposive sampling technique was followed to recruit participants from a public university in South Africa since it is the only university that provides acupuncture programmes in this country. Six participants were recruited for this study. The authors utilised thematic analysis to analyse the data. The findings of this study revealed that participants shared positive views and attitudes toward game-based learning. They believed that game-based learning significantly motivated them in the learning process. Furthermore, game-based learning also reduced their stress in learning compared to the learning in normal classrooms. They reported that game-based learning not only improved their engagement in learning but also enhanced their knowledge and skills. This study also highlighted that game-based learning should be well-planned to avoid demotivating students. It can be concluded that game-based learning is an effective approach to improve student engagement. Further studies should be conducted with diverse research approaches at different higher education institutions.
MoreTranslated text
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined