Quantitative analyses conducted on the self-reports of first year university students suggest that there is a relationship between the ways they emotionally experience their course and the approach they take to the learning of that course. Students who more strongly experience positive emotions, such as hope and pride, and more weakly experience negative emotions (such as anger, boredom, anxiety and shame), are likely to be adopting more of a deep approach to learning. In comparison, students who describe more of a surface approach to learning are more likely to report an experience of lower positive emotions and higher negative emotions. Both the experience of more positive emotions and the adoption of a deeper approach are associated with higher achievement scores. Lower achievement is associated with surface approaches to learning and negative emotional experiences. The value of these results lies in enhancing awareness of the elements that make up the learning experience for students, and of the need for consideration of the full range of emotional and approach to learning elements in designing new learning environments.

Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach is designed to provide meaningful pedagogical guidance, while the latter is designed to identify event patterns and relations that can be translated into actionable remediation. The benefits of both approaches have motivated this study to investigate if a combination of the self-report data and data arising from an observation of the engagement of students with online learning events offers a deeper understanding and explanation of why some students achieve relatively higher levels of academic performance. In this paper we explore how to combine data about self-regulated learning skills with observable measures of online activity in a blended learning course to increase predictive capabilities of student academic performance for the purposes of informing teaching and task design. A case study in a course with 145 students showed that the variation of the students’ final score for their course is better explained when factors from both approaches are considered. The results point to the potential of adopting a combined use of self-report and observed data to gain a more comprehensive understanding of successful university student learning

This article describes how phenomenography, as a qualitative research method, can be used to tackle key challenges in science education. It begins with an overview of the development of phenomenography. It then describes the philosophical underpinnings of phenomenographic inquiry, including ontological and epistemological roots, and its unique second-order perspective. From theoretical background to practicality, the paper uses rich examples to describe in detail the procedures of conducting a phenomenographic study, including sampling and data collection, analyzing phenomenographic data, and communicating key findings. The paper concludes by showing how the phenomenographic method can be used to develop students’ conceptual understanding of scientific concepts, to inform effective instructional design in science teaching, and to identify and improve evidence-based factors in student learning to enhance learning outcomes in science.

Good teaching strategies may not only engage students in learning but may also promote teachers’ self-concept about teaching. The present study empirically investigated the contributions of four popular teaching strategies, namely, feedback, scaffolding, active learning, and collaborating, to students’ engagement in learning and teachers’ self-concept in teaching. The study adopted a quantitative design, which surveyed 208 Australian primary school teachers by using a five-point Likert-scale questionnaire. The structure of the questionnaire was first explored by an exploratory factor analysis (EFA) and then through a confirmatory factor analysis (CFA) in order to provide an account for validity. The results of correlations showed that all the four teaching strategies were positively associated with both students’ engagement and teachers’ self-concept. The results of the structural equation modelling found that the strength of these relations varied. While feedback, scaffolding, and active learning strategies all positively contributed to teachers’ self-concept, collaborating neither significantly predicted students’ engagement nor teachers’ self-concept. Only scaffolding had a positive path to students’ engagement, implying that scaffolding may be the best strategy among the four teaching strategies to engage primary students. The study suggested to teachers that they need to consider the age of learners when implementing teaching strategies.

Four different indicators are used to assess the impact of a year‐long university teaching development programme in an Australian research‐led university. All four indicators show small positive outcomes. Teachers who complete the programme have higher rates of receipt of teaching awards and teaching development grants than their colleagues who do not participate in the programme. Students in the classes of teachers who complete the programme report, on average, higher satisfaction scores than students in the classes of the same teacher before she/he completed the programme. Students in the faculties where the programme is completed by a higher proportion of academic staff report greater change to levels of satisfaction in the quality of their degree over the seven‐year period of the study. The methodology adopted involves several new approaches to evaluation and confirms the need for the use of an evaluation framework and multi‐indicator strategy.