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This chapter argues that there are many, just many many variables which contribute to academic performance as measured in degree outcome, and, as such, simple bivariate analysis is inappropriate. We use structural equation modelling, and explore the contribution of academic behavioural confidence, to make the point that it does contribute to academic performance, but to a lesser extent than self-efficacy theory argues. We suggest that this is because degree outcome is made up of many efficacy variables, which we argue are better captured overall in academic behavioural confidence.

The “Colleague Review of Teaching” programme (CRT) aimed to enhance reviewees’ confidence to teach. The paper aims to discuss this issue.

Case studies using mixed-method, interview and questionnaire, repeated measures intervention were employed whereby academics in an Australian university science faculty volunteered to participate in a multi-faceted teaching review programme. Underpinned by confidence and self-determination theory, the CRT included peer coach training, reviewee choice, and a strengths-based approach to peer reviewing and coaching colleagues.

The reviewees declared an enhanced confidence to teach, teaching skills and unit design knowledge in an environment that was supportive of psychological needs. The peer coaches reported the CRT to be a positive experience that should continue. The strengths-based approach to peer observation of teaching and peer coaching facilitated department collegiality and was positively received by all participants who completed the programme.

The indifferent response to the CRT protocol completion reconfirms that peer review is a complex science and needs careful negotiation.

Review, peer coach and mentor training, review practice, choice protocols and the multi-faceted approach (pre-observation meeting, observations, written report and post-observation meeting) were positively received.

This paper provides rich insight into the experiences of a teaching review process.

This study aims to investigate the relationship between the personal traits and computational thinking skills of second graders within the context of robotics activities.

Through literature review, a research model and hypotheses were tested with 122 second graders after robotic activities.

The hypothesized model showed that learning preference, intrinsic motivation and self-efficacy were the main predictors of coding achievement and computational thinking skills, while no direct relationship was found between learning preference, intrinsic or extrinsic motivation. The final path analysis revealed that intrinsic and extrinsic motivation predict self-efficacy, self-efficacy predicts coding achievement and coding achievement predicts computational thinking skills. Another important finding was the strong impact of self-efficacy on coding achievement, as well as computational thinking skills. Results are interpreted with reference to implications for potential methods of improving computational thinking skills when using robotics in the lower grades in elementary schools.

This study not only examined these relationships but also proposed, tested and built a research model containing a wide range of personal traits based on path analysis and multiple regression analysis, which, to the best of the researchers’ knowledge, has not been investigated in the current literature.

As reflected in the final research model, self-efficacy played an important role in impacting second grader’s coding achievement and computational thinking skills.

Few studies have investigated the various relationships in the context of robotics instruction in elementary schools as in this study. Given the increasing popularity of robotics education in elementary schools, the re-examination and identification of the pivotal role of self-efficacy in predicting second graders’ learning of coding and computational thinking skills have important implications for the implementation of robotics education.