Focus: Presentation of research outcomes and recommendations for evidence-based practice.
Background: Many technologically-enhanced learning strategies (TELS) were retained in online and hybrid learning following COVID-19 restrictions. However, the literature is limited in providing insight into the impacts of TELS on student intrinsic motivation (IM), engagement, and academic performance.
Description: Underpinned by theories of self-determination¹ (SDT) and self-efficacy², a cross-institutional, quantitative and qualitative mixed method approach was used to investigate the impact of TELS on students IM, engagement, and academic performance.
Methods: Students and staff were recruited across a range of biomedical and healthcare degrees at two Australian institutions in semester 2, 2023. Students’ questionnaires were undertaken, and semi-structured interviews were conducted with both students and educators. Modified Intrinsic Motivation Inventory³ (IMI) and University Academic Self Efficacy Scale⁴ (UASES) were used to measure SDT constructs and academic performance.
Evidence: Quantitative and qualitative data were statistically and thematically analysed; respectively. Results of the questionnaire (n=130) and interviews (n=36) revealed positive relationship between TELS and both SDT IM aspects and perceived academic performance. Various TELS were found to impact aspects of IM in different ways, which translated to enhanced academic performance by varying degrees. Additionally, students who prefer hybrid learning were more likely to report positive attitudes towards TELS compared to those who prefer traditional in-person delivery.
Contribution: This research uncovered the mechanisms of success behind common TELS and arrived at evidence-based recommendations for the sustained use of these technologies. Recommendations highlight the ways in which TELS can be used to promote the engagement, motivation, and performance of students, how to better facilitate their learning and drive successful outcomes in higher education setting.
Engagement: Interactive visual presentation with online poll questions to gather initial expectations then challenge in line with study results and highlight misconceptions around students and educators perceptions.

Focus:
Presentation of research outcomes.

Background/context:

With increasing numbers of students progressing directly from undergraduate to postgraduate study, particularly international students, many coursework Masters students have limited professional experience or career networks in Australia. This restricts their ability to gain meaningful employment.

Research on effective mentoring highlights its benefits for student success and retention (Young et al., 2019), increasing students’ perceptions of self-efficacy and helping students feel emotionally supported and valued (Mousavi et al., 2018). However, despite the growing body of research evaluating the effectiveness of mentoring, there is limited understanding of why postgraduate students engage (or not) in these activities (Tymons, 2013).

Description:
While research in academic settings highlights how mentoring “should“ work, many theoretical models operate on assumptions about available time, expertise, and institutional support (Hall & Liva, 2022). Limited research examines postgraduate students’ perceptions of the benefits and challenges around mentoring, the type of mentor sought, and when mentoring would best suit them across their student journey. This study explores these critical themes in mentoring over their student journey.

Method:
This study employed an exploratory qualitative research methodology, using purposive sampling techniques through Recollective (https://recollective.com/), an asynchronous data collection platform.
Reflexive thematic analysis of the data collected allowed us to uncover several critical themes that shape mentoring engagement.

Evidence:
The study provides insights into postgraduate students’ motivation and expectations of mentors and mentoring activities. The results are currently being applied to engage various stakeholders, including students, staff, industry and alumni, in developing a university-wide career mentoring strategy.

Contribution:
The expected outcome is to enhance design and engagement through a more connected, inclusive, and relevant mentoring experience (focusing on academic, peer, and industry/alumni mentors) and student pathways.

Engagement:
Conversation Goal: Explore how different types of mentors connect with students and each other in curriculum and extracurricular activities.

Focus. The process of crowdsourcing a rubric to assess doctoral learning quality and outcomes associated with its use will be discussed. Background/context. Many faculty members have individualized expectations of doctoral learning and offer students feedback accordingly, which can impact dissertation quality (Lehan et al., 2016). A dichotomous pass/fail disposition offers limited information on the extent to which expectations were met and ways to improve (Ragupathi & Lee, 2020). Few rubrics, including those developed specifically for the dissertation, are applicable beyond the program(s) or institution where they were designed (Okahana et al., 2020). Description. Efforts were undertaken at one institution to assess the quality of doctoral learning as demonstrated in the dissertation. The result was a crowdsourced rubric that was applied by internal and external raters to dissertations from multiple institutions and programs. Method. A systematic approach to crowdsourcing as well as norming and applying a rubric to assess the quality of doctoral learning was used. Mixed methods and a concurrent parallel design were employed to analyze the ratings and feedback. Evidence. Raters’ scores and feedback, including areas of strength and opportunities for learning, were relatively consistent. Most reported that each component of the rubric was extremely or somewhat clear and that the rubric was useful, understandable, and relevant. Findings informed improvements in doctoral teaching and learning at the institution, resulting in improved learning outcome scores. Contribution. This work contributes by detailing a process to crowdsource a rubric that can be adapted for use across institutions and programs to improve doctoral teaching and learning. Engagement. Participants will be prompted to share their institution's practices relating to assessing doctoral learning through storytelling and live polls, asked about opportunities for improving those practices, and given the opportunity to review and reflect upon the applicability of the crowdsourced rubric at their institution and beyond.