Dissertation
The Social Learning Theory
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The Social Learning TheorySchunk & DiBenedetto, (2020), Social Learning Theory postulates that learning occurs through observing and modelling the behaviour of others, as well as through reinforcement and cognitive processes. This theory emphasises the significance of social context in influencing the behaviour and learning of individuals. In the context of bridging the digital skills gap with disruptive technologies in engineering education, the Social Learning Theory can help explain how students and instructors adopt new technologies through observation and modelling of others. By understanding the social dynamics that influence the adoption and use of disruptive technologies within the context of engineering education, we can design more effective interventions to promote their adoption and use. Additionally, the Social Learning Theory can inform our understanding of other underlying theories, such as the Theory of the Diffusion of Innovations and Technological Determinism. The Social Learning Theory provides a framework for understanding how these social factors influence individual behaviour and learning. This study seeks to develop a comprehensive understanding of the factors that influence the adoption and effective use of disruptive technologies in engineering education, as well as their implications for addressing the industry's digital skills divide, by integrating these theories. Utilising the Social Learning Theory, previous research has examined the adoption and effective use of technologies in educational settings. Pan et al.,(2020); Tokarieva et al., (2019), for instance, utilised the theory to investigate the factors influencing the adoption of mobile learning among Chinese college students. Social influence, self-efficacy, and perceived utility were identified as significant predictors of mobile learning adoption. Similarly, Pan et al., (2020) applied the theory to examine the factors influencing college students' adoption of online learning in Taiwan. Their findings suggested that perceived ease of use, self- efficacy, and social influence were significant predictors of online learning adoption. Download 2.1 Mb. Share with your friends:
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