Programme

ProposedWebinar

From Presentation to Participation: Designing Better Training

Effective training requires more than polished presentations. This session explores how trainers and facilitators can create interactive learning experiences through purposeful activities, discussion, collaboration, and opportunities for participants to apply what they learn.

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ProposedWebinar

What Makes Professional Training Actually Work?

Delivering information does not automatically produce learning or improved performance. This session explores the factors that make professional training effective, including relevant objectives, participant engagement, practical application, feedback, and follow-through.

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ProposedWebinar

Helping Educators Move From AI Anxiety to AI Readiness

AI adoption can create uncertainty, resistance, and professional concerns among educators. This session explores how faculty development initiatives can build confidence, address concerns, encourage experimentation, and support responsible AI integration into teaching.

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ProposedWebinar

What Faculty Actually Need From AI Training

Many AI training initiatives focus on tools rather than educators' actual needs. This session explores how institutions can design relevant, practical, and sustainable faculty development programs that address teaching challenges, confidence gaps, and real classroom applications.

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ProposedWebinar

Preparing Faculty for AI-Enabled Education

As AI becomes increasingly embedded in education, faculty need more than general awareness of emerging technologies. This session explores the competencies, institutional support, and professional learning opportunities educators need to adapt confidently and responsibly.

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ProposedWebinar

Designing Learning Activities for Authentic Participation

Meaningful learning depends on what students actively do, not only on the work they submit. This session explores how educators can design activities that encourage inquiry, discussion, application, reflection, and genuine participation throughout the learning process.

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ProposedWebinar

Designing for Thinking, Not Just Answers

Learning is more than producing correct responses. This session explores how educators can design activities and learning experiences that develop reasoning, problem-solving, reflection, and deeper understanding, even when AI-generated answers are readily available.

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ProposedWebinar

Making Student Reasoning Visible in AI-Enabled Learning

When polished answers can be generated instantly, educators need learning activities that make students’ reasoning visible. This session explores process documentation, explanation, dialogue, iteration, and reflection as ways to help students demonstrate how their understanding develops.

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ProposedWebinar

Preparing Students to Question AI, Not Just Use It

Effective AI literacy requires more than generating answers. This session explores how students can evaluate AI-generated information, recognize limitations and potential errors, and develop habits of questioning and verification.

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ProposedWebinar

AI Is Available. But When Should Students Use It?

Having access to AI does not mean it is appropriate for every academic task. This session explores how students can decide when AI use supports learning, when it creates risks, and how to make responsible choices.

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ProposedWebinar

Using AI Without Losing Your Own Thinking

AI can support learning, but excessive reliance may weaken independent thinking. This session explores how students can use AI as a learning aid while maintaining critical reasoning, personal judgment, and authentic academic contribution.

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ProposedWebinar

What Should Students Actually Know About AI?

Students increasingly use AI tools, but knowing how to operate them is not the same as understanding their capabilities and limitations. This session explores the essential AI knowledge students need to become informed, responsible, and critical users.

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ProposedWebinar

What Do Students Actually Understand About Academic Integrity?

Students may know academic integrity policies without understanding how they apply in practice, particularly when using AI. This session explores gaps in student understanding and how educators can communicate expectations more clearly.

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ProposedWebinar

From Catching Misconduct to Building Integrity

Detecting misconduct matters, but preventing it requires more than identifying violations. This session explores education-centered approaches, clearer expectations, supportive learning environments, and meaningful student engagement.

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ProposedWebinar

Teaching Academic Integrity Beyond Detection

Academic integrity is often addressed through plagiarism checks, AI detection, and misconduct procedures. This session explores how educators can go beyond these measures to teach responsible academic practices, develop student understanding, and encourage ethical decision-making.

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ProposedWebinar

Does More Technology Actually Mean Better Learning?

Educational institutions continue to adopt new technologies, but greater technology use does not automatically lead to better learning. This session explores how educators can evaluate the educational value of digital tools and prioritize learning outcomes over technology adoption.

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ProposedWebinar

Designing Learning for an AI-Enabled Classroom

AI-powered tools are becoming part of everyday learning environments, creating new opportunities and challenges for educators. This session explores how learning experiences can be designed to incorporate AI thoughtfully while supporting learner engagement, critical thinking, and meaningful educational outcomes.

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ProposedWebinar

The Classroom After Generative AI

Generative AI is changing how students access information, complete assignments, and engage with learning. This session explores what the future university classroom could look like and how educators can create learning experiences that remain relevant, engaging, and meaningful.

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ProposedWebinar

Should Students Be Allowed to Use AI?

Universities and educators are navigating difficult questions about when and how students should use generative AI. This session explores responsible AI use in academic settings, the importance of clear expectations, and how educators can balance innovation with learning objectives and academic integrity.

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ProposedWebinar

Teaching When Students Have AI

Students increasingly have access to AI tools that can explain concepts, generate content, and support academic tasks. This session explores how university educators can adapt their teaching approaches while preserving critical thinking, meaningful participation, and authentic student learning.

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ProposedWebinar

Beyond the Essay: Rethinking Academic Assessment

Traditional essays remain valuable, but they are not the only way to evaluate academic learning. This session explores alternative assessment approaches that can encourage critical thinking, reflection, problem-solving, and authentic demonstrations of student knowledge.

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ProposedWebinar

What Should We Assess When Writing Can Be Automated?

As AI-generated writing becomes increasingly accessible, the relationship between written assignments and demonstrated learning is changing. This session explores which skills and learning outcomes educators should prioritize when writing alone may no longer provide sufficient evidence of understanding.

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ProposedWebinar

Designing Assessment When AI Can Produce the Answer

When AI can generate convincing responses to traditional assessment tasks, educators need to reconsider how they evaluate student learning. This session explores assessment approaches that emphasize thinking processes, evidence of understanding, and meaningful application.

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ProposedWebinar

The Assignment Has Changed

Generative AI can now complete many traditional academic assignments, raising questions about what these tasks actually measure. This session explores how educators can rethink assignments to better evaluate learning, reasoning, and authentic student contribution.

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