Chapter 10
References
27 min read
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#Figures
- Figure 2.1 Image of the VU Education Padlet with AI tools for Education
- Figure 3.1 TPACK model according Mishra and Koehler (2006).
- Figure 3.2 Picture of UvA TLC e-learning depicting the tension in the Constructive Alignment concept induced with the emergence of generative AI (TLC University of Amsterdam, 2025).
- Figure 3.3 Depiction of Bloom's taxonomy is seen as more appropriate by Dylan Wiliam.
- Figure 3.4 Comparison of the Bloom’s taxonomy in an age of AI according to Michelle Kassorla (2025).
- Figure 3.5 The spiral representation of UnBloom ™ learning, developed by Tina Austin.
- Figure 3.6 UnBlooms™ Levels of Critical Engagement with AI by Tina Austin is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).
- Figure 4.1 The Academic Fraud Triangle (Becker et al., 2006).
- Figuur 4.1 SBE’s depiction of the negative cycle of generative AI, also known as the “AI dependency trap.”
- Figure 4.2 Screenshot of an AI Tutorbot on Cogniti, engaging students in learning trough presenting closed and open questions. The questions are included in the prompt itself so they will always be the same.
- Figure 4.3 Screenshot of an AI Tutorbot on Cogniti, engaging students in learning trough presenting and discussing common misconceptions. The questions are generated on the fly.
- Figure 4.4 Screenshots of AI-driven Avatars for the SBE case Foundations of Strategic Management.
- Figure 4.5 Image from the YouTube video in which David Nicol explains the Inner Feedback approach, source https://www.youtube.com/watch?v=bPqIu2k24JE
- Figure 6.1 An AI generated image of A Blueprint for Critical Thinking. If you want to practice with this kind of framework for Critical Thinking, go to this Chatbot on VU Amsterdam’s Cogniti to converse about a topic that interests you or let the bot generate a topic for you.
- Figure 6.2 Image of an AI generated picture of ‘humanitarian aid in Afrika’
- Figure 6.3 Images of an AI generated picture by Elon Musk showing himself in bikini’s.
- Figure 7.1 Figure showing the VU Vision for future-proof assessment.
- Figure 7.2 Liu’s slightly adapted perspective on lane 1 and lane 2 assessments in a curriculum (program) and course level (unit).
- Figure 7.3 Western Sydney University AI Approach to Assessment (Assure and Inspire).
- Figure 7.4 Example simple Excel sheet to keep a record of student attainment and progress
- Figure 7.5 The writing pie: A conceptualization of human and AI writing skills.
- Figure 9.1 Scatterplot of manual scores and LLM scores on a test of 12 open ended questions.
- Figure 9.2 Scatterplot of manual scores and LLM scores on two typical questions.
- Figure 9.3 Scatterplot of a relatively high correlated manual and LLM scores.
#Tables
- Table 2.1 AI Assessment Scale (AIAS), v2.1, Copyright Learning Innovation Practice Ltd. Based on the original AIAS.
- Table 3.1 Requirements for teachers regarding impact of generative AI for their knowledge and skill.
- Table 4.1 An example of a circular reasoning to preserve validity of assessment.
- Table 4.2 Seven Practical tips to share with students when explaining your active learning pedagogy.
- Table 4.3 Five practical tips on how to integrate a tutor bot productively in a course.
- Table 7.1 Liu’s menu of options to use generative AI that a students and teachers could use and see the fit with the task and learning goals at hand.(Liu, 2025)
- Table 7.2 Suggested assessment types in lane 1 and lane 2 according to Liu (2025).
- Table 7.3 Tips for conducting sound assessment using interviews, oral assessment or group presentations.
- Table 7.4 Rubric used in the AUC Capstone projects to assess Academic Competence.
- Table 7.5 Examples from the student text and suggestions by ChatGPT 3.5