A Review of Self-Regulated Learning and Self-Efficacy: The Key to Tertiary Transition in Science, Technology, Engineering and Mathematics (STEM)

Abstract

The ability to distinguish between effective and ineffective study strategies based on feedback is of utmost importance for secondary school leavers transitioning to tertiary education (Brinkworth et al., 2009; Salisbury & Karasmanis, 2011). Often accompanying this learning environment transition is academic difficulty and an increased possibility of failure, and it is therefore essential for undergraduate students, in particular those studying the disciplines of Science, Technology, Engineering and Maths (STEM), to establish a solid repertoire of learning strategies early in their academic career. Self-regulation is a key component of learning that can be fostered to encourage a successful transition from secondary school to university (Vosniadou, 2020). Self-regulated learning refers to learning that is fostered by one’s metacognition, strategy adaptability, and motivation. Of these constructs, metacognition is fundamental, as having self-awareness allows one to identify the requirement for corrective action in the learning process, allowing learners to monitor their behaviour and reflect on the success of their learning strategies, where the motivation to do this should lead to strategy adaptation. In addition, students must make accurate self-efficacious judgements about their learning in order to evaluate the effectiveness of their learning strategies or to decide when they have sufficiently completed a learning task. Therefore, in order to develop a means of improving students’ transition from secondary school to university, one must first appreciate the impacts of self-regulated learning and self-efficacy on academic performance. This review aims to focus on self-regulated learning and self-efficacy, of which self-regulated learning is a construct of metacognition, motivation and strategy adaptability. This review will also evaluate self-regulated learning with an emphasis on Zimmerman’s model, the calibration of self-efficacy, and how students might break the cycle of poor learning with a focus on STEM.

Understanding the role of peer pressure on engineering students' learning behavior: A TPB perspective

“…(3) Peer pressure was found to positively influence engineering students' learning intention through the perceived behavioral control dimension (p < 0.001). This result is consistent with the findings of scholars such as Blackmore et al (87) and Sarosa (88), indicating that engineering students' perceived ability is positively related to learning intention, i.e., the stronger the perception of stress, the stronger the willingness to learn. After analysis of the survey results, it was identified that most engineering students show high motivation to learn engineering skills and expertise with certainty, and when they felt peer pressure, students would mobilize positive learning emotions and believe that they could complete their tasks better and faster.…”

The Effect of Dysphagia Education Through Video on the Level of Knowledge and Screening of Dysphagia and Self-Efficacy of Nurses

“…The value of self-efficacy in this study had no significant effect for either the control group or the video group. This can happen because one of the roles in self-efficacy is academic motivation and selfregulation in learning that is influenced by culture, gender, external incentives, individual status in the environment (Bandura, 1986and Zimmerman, 2000in (Blackmore et al, 2021. In line with the results of (Thompson, 2019) on self-efficacy of nurse knowledge in stroke disease explained that education about stroke to hospital nurses should be given to all nurses so that learning can provide positive efficacy results, so it is important for managers in hospitals to create educational programs in order to help improve nurse knowledge and promotion of self-efficacy about knowledge of stroke care.…”

Measuring Career Adaptability in a Sample of Italian University Students: Psychometric Properties and Relations with the Age, Gender, and STEM/No STEM Courses

“…By having available data on the presence of a low proactive personality and low levels of boundaryless mindset, it would be possible to build guidance interventions capable of preventing critical issues and increasing the probability of success. Previous studies suggest that there are several psychosocial areas on which it could be possible to intervene to improve personal adaptability: for example self-efficacy (Blackmore et al 2021;Dillahunt and Hsiao 2021;Guan et al 2013), self-esteem (Amarnani et al 2018;Cai et al 2015); team work skills (de Guzman and Choi 2013; Ebenehi et al 2016;Fawehinmi and Yahya 2018), learning goal orientation and, past and future temporal focus (Tolentino et al 2014;Zacher 2015), resilience (Buyukgoze-Kavas 2016) problem solving and decision making (Kozlowski et al 2001;Coetzee et al 2015). These interventions could be carried out both at the individual level with targeted counseling sessions, both at the group level with training moments, and at the organizational level through the implementation of professional orientation policies.…”