Student ability to succeed in collaborative problem solving (CPS) is increasingly important. However, identifying aspects of CPS that individuals can act on to improve it remains a challenge. This study explores listening behaviour as a lever for effective CPS, given that listening is at once cognitive and social, and that individuals can enact it. Despite its importance in communication, listening is rarely systematically examined in CPS. To address this gap, we propose a framework for identifying listening behaviours in the text of student exchanges, and apply it to analyse patterns of listening behaviours of 34 K-12 students aged 11-14, working in nine groups on CPS activities. By combining content analysis, k-means cluster analysis, and correlation-based coupling network analysis, we identify ten distinct patterns of listening behaviours and their coupling over time, across groups with different success outcomes. We found that listening patterns varied by performance, under the assumption of moderate temporal dependence among interaction segments. Higher performing groups engaged in more counterarguments and constructive listening. Groups with lower CPS successes exhibited two ineffective patterns: questioning with instrumental listening, and counterarguments and questioning without encouraging listening. These findings pose questions about the relationship between listening and learning processes and have implications for multimodal research in learning analytics.

In response to the evolving demands of the contemporary workplace, higher education (HE) institutions are increasingly emphasising the development of transversal skills and graduate attributes (GAs). The development of GAs, such as effective communication, collaboration, and lifelong learning, are non-linear and follow distinct trajectories for individual learners. The ability to trace and measure the progression of GA remains a significant challenge. While previous studies have focused on empirical methods for measuring GAs in individual courses, a notable gap exists in understanding their longitudinal development within HE programs. To address this research gap, our study focuses on measuring and tracing the development of GAs in an Initial Teacher Education (ITE) undergraduate program at a large public university in Australia. By combining learning analytics (LA) with psychometric models, we analysed students’ assessment grades to measure learners’ GA development in each year of the ITE program. The resulting measurements enabled the identification of distinct profiles of GA attainment, as demonstrated by learners and their distinct pathways. The overall approach allows for a comprehensive representation of a learner's progress throughout the program of study. As such, the developed approach sets the grounds for more personalised learning support, program evaluation, and improvement of students’ GA attainment.

Industry supervisors play a pivotal role in ongoing learner support and guidance within a work-integrated learning context. Effective provisional feedback from industry supervisors in work-integrated learning environments is essential for increasing a team’s metacognitive awareness and ability to evaluate their performance. However, research that examines the usefulness and type of feedback from industry supervisors for teams remains limited. In this study, we investigate the quality of provisional feedback by comparing the teams’ helpfulness rating of the feedback from two types of industry supervisors (i.e., clients and mentors), based on the feedback type (task, process, regulatory and self-level oriented) using learning analytics. The results show that teams rated the perceived helpfulness scores of clients and mentors as very useful, with mentors providing slightly more helpful feedback. We also found that mentors provide more co-occurrences of feedback classifications than clients. The overall results show that teams perceive mentor feedback as more helpful than clients and that the mentor targets feedback that is more beneficial to the teams learning than the clients. Our findings can aid in developing guidelines that aim to validate and improve existing or new feedback quality frameworks by leveraging backward evaluation data.

Students enrol into STEM programs with varying degrees of confidence with citing and referencing texts in their written work. Students often have an inclination to choose numbers over written language throughout schooling which means less opportunity to practice referencing and citation. This is compounded by large numbers of students for whom English is an additional language or who articulate from different cultural ways-of-doing. The Search, Evaluate, Integrate, Reference and Act Ethically (SEIRA) modules were developed to provide discipline-relevance to a confounding task. Data Analysis looking at the student engagement with the SEIRA site and subsequent student success provides an indication of the value of this approach to developing academic literacy across the STEM disciplines.