As part of CSEdX 2025, a series of exclusive 1-hour workshops will be available for Charles Sturt University staff.
These sessions, scheduled in two concurrent time slots 9:45 AM to 10:45AM and 2:00 PM to 3:00 PM on Tuesday 11 November, offer a unique opportunity to dive deeper into key topics explored during the conference.
What to expect:
These are concurrent sessions so people should only register for one per time slot. Please register for your preferred workshop in each time allocation below.
Please note: each session has a limited number of spaces. Early registration is recommended to secure your spot. A minimum number of registrations will need to be achieved for each workshop to go ahead, and registrants will be advised of any changes need to be made to workshop offerings.
Choose one workshop from this time slot
Presenters: Rebecca Fabry¹, Lorraine Rose¹, Kelly Shaw², Lachlan Kalache²
Overview: Generative AI is reshaping how students search, screen, and synthesise literature, yet many do not understand tool limits, data sources, or responsible use. This hands-on workshop equips educators to integrate research-oriented AI tools into literature-review assessments without compromising academic integrity. The processes and learning covered are tool-agnostic, discipline-portable, and aligned to information, digital, and critical AI literacies.
Presenter: Dr Genaro Oliveira
Overview: This workshop examines how the deliberate use of generative AI in group assessment tasks fosters critical thinking, creative practice, and ethical engagement. Drawing on a first-year teacher education subject, participants will examine a case study where students create a children's book using AI tools, combined with process-folios and self/peer assessment. The workshop demonstrates how AI can be positioned as a tool for inquiry and creativity rather than a shortcut, while exploring strategies for prompt engineering and transparent documentation.
Presenters: Andrea Francis, Jacki Sherwood, Sangeetha Kirsnan, Trudie Fenwick
Overview: Generative AI is reshaping higher education, with particular impact on first-year students who are building foundational skills in learning, communication, and integrity. This workshop supports academics to design learning experiences that embed GenAI thoughtfully and ethically. Using three guiding principles: clarity & transparency, human agency, and accountability & ownership, participants will explore strategies to help students navigate GenAI in ways that foster confidence, integrity, and belonging.
Choose one workshop from this time slot
Presenters: Ryun Fell and Matt Olson
Overview: Artificial intelligence is reshaping the way academics and professional staff design and develop learning activities. This workshop explores how AI can support the creation of reusable templates for tools such as H5P, as well as simple bespoke activities designed for targeted student experiences. The session focuses on efficiency, pedagogical integrity, and sustainability while participants engage critically with AI practices in learning activity design.
Presenters: Nicole Mitchell and Liz Stephens
Overview: This workshop is designed to remind participants of Charles Sturt's existing assessment design principles and how AI can be used to evaluate assessment tasks against these principles. Following a brief overview of the assessment design principles, scaffolded activities will guide participants through using AI to evaluate existing assessment tasks, recommend improvements, and consider contextual factors while developing relevant and well-articulated prompts.
Presenters: Peir Woon, Arnela Ceric, Ana Torres Ahumada
Overview: This workshop explores the scalability of AI-enhanced assessment design across disciplines, using a practical case study from Accounting as a foundation. The session demonstrates how a single AI-supported assessment framework can be adapted, amended, and improved across diverse subject areas. The workshop addresses the growing need for scalable, supervised, and authentic assessment models in the age of generative AI, providing a cross-disciplinary lens on AI adoption.