Honoursmodule: AIducation - The Future of Education?

Course manual 2024/2025

Course content

Over the last couple of decades, the digitalization of our society has led to remarkable changes in the way we operate within the university. Now, with the large-scale introduction of generative AI, the educational landscape is bound to change even more drastically. In fact, it already has changed significantly and this process is continuing ever more rapidly. Up until now, the university has prohibited students to use generative AI. The question is whether this position is tenable in the long run, or whether it is destined to get used in our academic education – not only by students but also by the teachers. This question is the central point of departure in this course.

We will explore what the future of education may hold, by developing various scenarios for forthcoming education in which the use of generative AI either is permitted and integrated or remains formally forbidden but may nevertheless be used anyway. We will investigate the implications of the different scenarios, particularly what will happen to student's learning paths when GAI is allowed or is not allowed to be used in the learning process. To what changes will it lead in our theories of learning when most if not all answers to our knowledge questions can simply be generated by consulting the bot? How will the introduction of generative AI affect our vision on education? Do we need to move from pedagogy to pedAIgogy? What kind of assessment is required to make any kind of meaningful learning still possible? By addressing these questions together, we aim to inspire a well-wrought transformation from education to AIducation.

Study materials

Literature

• Both the compulsory literature and additional materials can be found on Canvas.

  Per week it is indicated what you need to read for the topic at hand.

  And for relevant topics that you might want to address in your future scenarios and the course that you will design, numerous suggestions for additional literature are shared.

Software

• Software – ChatGPT4 version that will be provided by the UvA (as this course is part of an pilot where the use of generative AI is experimented with).

Objectives

• Develop scenarios on how the future of academic education should preferably look like or should definitely not look like in an era where AI has fundamentally changed the educational environment.
• Identify how Generative AI can or could be used to work on learning objectives of various levels of complexity.
• Analyse how the use of Generative AI – either permitted or on the sly – may help students to realize a selected set of learning objectives.
• Analyse what the use of Generative AI means for how students learn about the chosen topic.
• Design a form of assessment to reliably test the learning outcomes with regard to the set objectives, assuming that the learners either may or may not make use of Generative AI to produce the answers to the assignment(s).
• Evaluate how the introduction of Generative AI in our society (though not necessarily our education) affects the existing general theories of how learning takes place.
• Indicate what kind of attitude teachers and learners need to employ to enhance fruitful learning trajectories in an AI-enhanced environment.

Teaching methods

• Lecture
• Seminar
• Presentation/symposium
• Self-study
• Working independently on e.g. a project or thesis
• Supervision/feedback meeting

The class meetings will consist of a combination of (guest) lectures, student driven Q&As and tutorials.     As they play a crucial role in achieving the course objectives and are essential for your overall progress, they are compulsory. The quality of the meeting largely depends on the attendance and active participation of every student, and thus you are expected to come to them well-prepared.

Learning activities

Attendance

Additional requirements for this course:

The class meetings are a combination of lectures and work group, as exercises are integral part of the meetings. These exercises consist of elements of the Assignments that you need to make during the course.

You need to attend minimally 80% of the meetings. If you don’t meet this requirement, you will be excluded from the course.

Assessment

Assessment Table of AIducation

  * Note: lack of sufficient individual contribution can also diminish the grade to < 5.5! See the explanation of Assignment 4 about the Group Process and the file Determining the final individual grade.

** No submittal before Friday 17 January 2025 23.59 means you can’t successfully complete the course and need to do it again next year.

An average grade of 5,5 or higher is required to pass the course.

Note that at IIS/FNWI final grades are rounded to whole or half digits (8.2 becomes 8.0). Final grades between 5 and 6 will not be awarded (5.5 becomes 6).

You are registered for this course via GLASS This means that you are automatically registered for exams and possible resits that are part of this course.

Assessment diagram

Assessment Matrix – Constructive Alignment between Objectives & Assessment

Inspection of assessed work

Up to 20 working days after the announcement of the result students have the right of inspection of their work (all forms of assessment). You can request a copy of your work by e-mailing the teacher/course coordinator. If you want to discuss your final grade, you can make an appointment by sending an email to j.c.tromp@uva.nl

After the above mentioned 20 working days have expired the entire exam package must be handed over to the IIS Service Desk after which the work will be archived.

Assignments

See separate file Overall Assignment AIducation in the folder with Course Information, and the descriptions in the separate Assignments in the dedicated folder.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Additional information

Policy regarding Generative AI

As AIducation – The Future of Education? is part of the FNWI pilot in which we are experimenting with Generative AI (GAI), you are permitted to use GAI during this course.

Learning to work with GAI is an emerging skill, and we think it is important to explore in what ways it can be used in a fruitful way at the university. But also, to learn more about its downsides and dangers so that we can hopefully develop a sensible GAI policy in the near future.

Some of the limitations of GAI that are already well-known (cf. Bloem, 2023):

• If you provide minimum effort prompts, you will get low quality results. You will need to make an effort and refine your prompts in order to get good outcomes.
• GAI is not completely trustworthy. If it gives you any number, code or fact, you can’t just assume it’s right. You will be held responsible for the answers you hand in, including for any omissions or errors generated by GAI. So you either need to be sure about the answer yourself or check it with (an)other source(s).
• If you make use of GAI, you need to acknowledge it. For instance by including a paragraph of any assignment in which you explain what you used GAI for and what prompts you used to generate the answers / results. Failure to do so is in violation of academic rules concerning authorship and academic integrity. In this course, such compulsory reflection paragraph is explicitly included in the summative assignments.
• Be cautious in using GAI. Don’t use it if it isn’t appropriate for the case or circumstance. And make sure not to over-use it so that you become too reliant on AI to think, write, code, analyse, reflect et cetera and never get to learn those necessarily basic academic skills yourself.

Teaching and Examination Regulations

The IIS elective and honours courses are covered by the Examination Board and the OER of the Bachelor Beta-Gamma. Teaching and Examination Regulations (OER) are published annually and lay down all the rules and guidelines regarding assessment and examination which the IIS pursues. The OER can be found via https://student.uva.nl/en/topics/teaching-and-examination-regulations-and-other-regulations. Students and contractors who follow courses at the IIS can draw appeal to the Board of Appeals Board (COBEX).

Social safety and Evaluation Committee

The Evaluation Committee for Honours Education ensures the quality of electives and is committed to providing a safe learning environment. The committee, consisting of students and teachers, meets at least four times a year to provide requested and unsolicited advice on all educational matters related to IIS Honours Education. It utilizes course evaluations and actively seeks contact with students enrolled in IIS Honours Education.

The Evaluation Committee is very interested in comments, suggestions, recommendations, and other insights regarding the content, implementation, and offerings of IIS Honours Education. Students can contact them at evaluatiecommissie-honours-iis@uva.nl.

If you experience undesirable behavior or unsafe situations, you can contact the study advisor of your educational program, one of UvA's confidential advisors, the Evaluation Committee, or the coordinators of the IIS Honours Program (via honours-iis@uva.nl). More information and contact details of confidential advisors can be found here.

Last year's student feedback

In order to provide students some insight how we use the feedback of student feedback to enhance the quality of education, we decided to include the table below in all course guides.

Not applicable; this is the first time the course runs.

Contact information

Coordinator

• dr. Coyan Tromp

Email address: j.c.tromp@uva.nl