21st Academic Practice and Technology Conference (APT23)

Implications and Ethical Dimensions of using Artificial Intelligence in Higher Education teaching, learning and assessment

The twenty-first Academic Practice and Technology (APT23) conference, co-hosted by King’s College London, University College London, the London School of Economics & Political Science and Imperial College London will take place on Friday 30 June 2023 at the KCL Strand campus, and it will be preceded by streamed events and presentations.

Following the success of the 2022 conference, this annual conference, co-hosted by KCL, UCL, LSE and Imperial College London, will run ‘in person’ mode but with online elements. The design of this year’s conference will maximise the benefits of face-to-face methods using high engagement and participation activities such as workshops, round tables and open space dialogue to discuss and reflect on ideas and further develop our APT community. We will invite attendees to engage with asynchronous resources and use them as a starting point for real-time activities at the live in-person event.


This year we focus on 4 main sub-themes: Implications of AI for assessment design and academic integrity, The ethical dimension of AI (data management and more), How to support students and staff to develop new skills, Learning with and through AI.

The sub-themes invite participants to critically reflect and explore ways in which they are developing their practice using AI. Through a range of discussion and interactive formats, the event will showcase and celebrate examples of academic practice that can inspire academic and professional services staff.


AT2023 seeks research papers/work in progress, case studies, field reports, workshops that interpret the conference theme of ‘Implication of the use of Artificial Intelligence in teaching, learning and assessment’, aligned to one or more of the following sub-themes:

      1. Implications of AI for assessment design, delivery and academic integrity  – Assessment design, authentic and alternative assessment, academic integrity and identity verification, issues of surveillance and sousveillance.
      2. The ethical dimension of AI – Frameworks for setting teacher expectations; identifying and preventing bias; what counts as useful knowledge; exploring the power relationship of stakeholders including teachers, students institution, PRSBs, employers; implications for teaching approaches; regulations and policies for data management.
      3. How to support students and staff to develop new skills – Interdisciplinary approaches, employability, sustainable and scalable support, CPD and recognition of new skills, sharing good practice and networking, building and sustaining communities.
      4. Learning with and through AI – Innovative and alternative practice, training and education staff and students, accessibility, managing communication and building expectations, sustainable teaching practices and environments, mechanisms of inclusion and exclusions, online engagement etc.
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