Notes taken from presentation from Dr. Simon McCallum, Victorial University Wellington on 'Adapting to AI'.
The presentation is part of a fortnightly series organised through ATAIN which is a SIG of Flexible Learning Association of NZ (FLANZ).
Simon began with an introduction. He has been teaching game development since 2004 but has also taught AI since 1991. Noted that Gen Ai is everywhere and we use it unintentionally, unconsciously, but also using it consciously and strategically. Productivity benefits depends on training of the AI. Ai agents work together to automate generic tasks.
Across industries, adoption is mixed, some fast, some very slow. The risks include programmers with AI automating other industries and the use of 'software / automation on demand'.
Revised the two lane approach to assessments. Students are using AI - At UVW 66% admit using it.
Covered the following:
AI literacy - Core / domain specific - compulsory for all students and staff, understand if and when to use AI and avoid the risk of thoughtless AI use.
Assessments need to move to testing understanding and learning rather then outputs. Test meta cognition, use oral assessments.
All non-invigilated (lane 2) work should be considered as group work, using group work assessment techniques - assess process, influence, delta, learning journey.
Assessments can embrace AI assistance. AI selects questions, create bespoke questions, suggest oral assessment questions. Human markers determine the grade. Provided details of the process from his context. Use AI to generate questions from student submission for them to complete, to check understanding they have presented in their essay!
Increase the quantity of group/team work so students can create human connections and increase their experiences with working with others. Invrease the amount of work that is groupwork but not the groupmark.
Proposed that NZ universities fund a NZ based server to assure AI sovereignty. A more equitable approach as all students will have access to high quality models instead of having to pay for the upgraded models.
Also the creation of a position to report to Te Hiwa (leadership group to organise and manage AI across the entire university - teaching, learning, research and professional.
Summarised agentic AI. Moves AI from being a chatbot to actually being able to 'do things'. AI will sort out a plan, and work through it to meet the prompt objective. Swarm coding can be activated, to check the outputs from each agent. Therefore, AI is not a search engine. It is better to have the AI question us to work out what we want done! 'help me do ----'
Summarised project on how AI is used in NZ secondary schools. Mixed across schools on strategy, current use, professional / student use and community involvement. Schools welcome clearer policies and guidelines. Challenges are similar to Universities, assessments, professional development, etc.
Shifted to a summary of the extrinsic and intrinsic purposes of learning. If the motivation is just to pass the exam, then AI is an impediment. However, if there is a less constricted 'assessment' e.g. develop a game, AI accelerated capability and leads to extended learning.
Therefore important to engage learnings to focus on intrinsic motivation, self-reflection and etc. and to hold them to account for what they want to learn. Teacher as NPC . Encouraged learner negotiated assessments and rubrics, giving them agency. For example, have learners establish the range of marks assigned to various aspects of an assessment. This encourages meta cognition for students to structure their learning, their strengths/ weaknesses etc.
How do we measure metacognition - confidence is good when it is accurate, under / over-confidence is a problem and AI makes this worse. Important to operationalise and elicit accurate statements from learners.
Invitation to use the group's Discord to continue the conversation and share ideas.
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