Focus

This presentation explores the transformative process of decolonising the law curriculum through the standpoint of Indigenous and non-Indigenous co-authors.

Background/context

Embedding Indigenous Knowings and perspectives in university curriculum is an ongoing and iterative project to improve opportunities and outcomes for Indigenous peoples, educate all students, and develop staff cultural capability. Decolonising curriculum calls for critical listening and engagement with Indigenous and decolonial scholarship (Galloway, 2018; Russ-Smith 2019) and a critically reflexive standpoint adopted by educators to undo the colony within curriculum.

Description

The presenters will examine the decolonising process through a law literature review project, emphasising the transformative impact of Indigenous and decolonial scholarship upon the presenters. The significance of process and standpoint will be highlighted, showcasing the embodied and vital work involved in decolonising curriculum.

Method

This presentation reports on the findings of a literature review conducted as part of a broader project involving interviews with Indigenous Australian legal scholars. A decolonial relationally responsive analysis process (Yunkaporta & Shillingsworth, 2020) was applied to interpret the key themes identified by the literature review.

Evidence

Critically reflective standpoint analyses by two authors will be shared to highlight the wider transformative and relationally responsive process of decolonising curriculum where Indigenous Knowledges are centred. These analyses are informed by key themes identified through the literature review and reflected in the interviews.

Contribution

The presenters offer fellow educators an insight into the process of decolonising curriculum through honest and vulnerable reflections of educators, and how this can be embodied to decolonise teaching and learning practice across the academy.

Engagement

Critically reflective discussion prompts will be utilised to invite the audience into the process of relationally responsive standpoint. Attendees will be encouraged to bravely deconstruct their colonial pedagogical practices and understand their role in decolonising the academy and embedding Indigenous Knowledges into curriculum.

Focus
The showcase will focus on presenting research outcomes.

Background/context
Women are underrepresented in STEM (science, technology, engineering, and mathematics) degrees in higher education (HE), despite outperforming at other levels of education (Kriesi & Imdorf, 2019). Previous research explains this in terms of stereotype threat and gender dominance (Koch et al., 2022; Hill et al., 2010). Inconsistent findings of a male advantage (Matz et al., 2017) highlight the need for a more detailed examination of student behavior.

Description
Our study addresses the research gap on gender differences in performance and participation by examining variations in gender differences in student performance and participation at the module level from two perspectives: 1) between STEM and non-STEM programs, and 2) between female- and male-dominated programs.

Method
We use administrative datasets from three undergraduate programs at a large German university. The total of 5,853 cases consists of the 2016-2021 program cohorts in mechanical engineering (male-dominated STEM), political science (male-dominated non-STEM), and sociology (female-dominated non-STEM).

Evidence
Women tend to outperform men in terms of grades, regardless of whether the program is in a STEM or gender-dominated field. The same is true for module exam participation rates in non-STEM programs, while in male-dominated STEM fields they may be outperformed by men, who on the other hand have to retake exams more often than women in these fields.

Contribution
Our findings suggest that when studying gender differences in higher education, it is important to look at detailed behaviors rather than focusing only on overall student success. The study also highlights the importance of comparing not only STEM and non-STEM fields, but also gender dominance, as we see nuanced cross-level effects.

Engagement
We plan to engage the audience by asking a thought-provoking question: "Do our assumptions about gender differences affect the way we design and assess educational programs?”

This presentation provides actionable insight into how the teacher role is vital in group problem-based learning (PBL) for undergraduate health science students, highlighting how to scaffold students’ decision making while supporting individual and peer learning.
Delivering expert guidance and promoting self-directed learning during PBL continues to be questioned in higher education. Additionally, translating traditional face-to-face (F2F) PBL strategies into the digital environment has generated discussion about teacher resources.
To discern ‘what works’ in practice, a Design-based Research (DBR) methodological framework (Bakker. 2018; Cochrane, et al, 2023; Reeves & Lin, 2020) was applied over a span of 15 months. The research used qualitative reflexive thematic analysis (Braun & Clarke, 2022) and bounded rationality theory (Herbert, 1972), to test, refine, and retest an online decision wheel tool to use during PBL independently, in groups, and when guided by a teacher.
Participants included 34 students, 26 teachers, and 5 learning designers from twenty undergraduate health science and nursing subjects across all learning modes. Data were generated from 44 semi-structured interviews and 20 focus groups.
The theme of Central guide informed one of the six final design principles, DP1: Be the Guide in the Hive. Key developments included teachers and peer mentors engaging in explicit instruction alongside self-directed learning opportunities, and the provision of quality alternatives for group debate in early undergraduate years to enhance skills and confidence in decision making for PBL.
Outputs from this DBR doctorate project have both situated and broader implications for teacher training and resource allocation for PBL in undergraduate years and across a variety of learning environment modes.
The audience is invited to learn about this research before joining a discussion guided by conversation prompts to consider the central guide theme in broad group learning contexts.

Focus: Ethical reflection on emerging practice and prospective guidelines for use of chatbots in higher education.

Background/context: The introduction of Generative AI "Chatbot tutors into higher education is contentious: some laud its potential to render learning more accessible; others take Chatbots as a threat to the core mission of higher learning (Williams 2024). Chatbot tutoring systems have as yet received no sustained attention at the level of philosophical ethics.

Description: We present arguments that (a) recognition of effort is a condition of meaningful experiences of work (Gheaus and Herzog 2016), and, by extension, of learning (Fleming 2014); and (b) that Chatbot tutors are not capable of providing this form of recognition. This does not rule out the use of Chatbot tutors; rather, it provides us with appropriate (c) guidelines for their integration.

Method: Conceptual analysis drawing on philosophical literature as well as emerging empirical research on the use of Chatbots in higher education.

Evidence: The argument will be supported by (a) philosophical literature on the importance of recognition in learning experiences (e.g., Gheaus and Herzog 2016, Fleming 2014); (b) empirical studies on the effects of Chatbots on student engagement and learning outcomes (e.g., Gill et al. 2024, Gupta and Chen 2022); and (c) rational argumentation drawing out the implications of (a) and (b) for the ethical implementation of Chatbots.

Contribution: The argument of this paper suggests that the introduction of Chatbots into higher education settings must be carefully scaffolded by human-to-human interactions. or risk exacerbating student disengagement.

Engagement: the audience will be engaged through the use of two "thought experiments," drawing out attendees' intuitions on Chatbot tutors. The first experiment is designed to demonstrate the centrality of human recognition for the experience of teaching and learning, the second to demonstrate the absurdity of taking AI systems to recognize effort.