The influence of Artificial Intelligence (AI), and specifically Large Language Models (LLM), on education is continuously increasing. These models are frequently used by students, giving rise to the question whether current forms of assessment are still a valid way to evaluate student performance and comprehension. The theoretical framework developed in this paper is grounded in Constructive Alignment (CA) theory and Bloom's taxonomy for defining learning objectives. We argue that AI influences learning objectives of different Bloom levels in a different way, and assessment has to be adopted accordingly. Furthermore, in line with Bloom's vision, formative and summative assessment should be aligned on whether the use of AI is permitted or not. Although lecturers tend to agree that education and assessment need to be adapted to the presence of AI, a strong bias exists on the extent to which lecturers want to allow for AI in assessment. This bias is caused by a lecturer's familiarity with AI and specifically whether they use it themselves. To avoid this bias, we propose structured guidelines on a university or faculty level, to foster alignment among the staff. Besides that, we argue that teaching staff should be trained on the capabilities and limitations of AI tools. In this way, they are better able to adapt their assessment methods.

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Creating reasonable AI for sidekicks in games has proven to be a difficult challenge synthetizing player modelling and cooperative planning, both being problems hard by themselves. In this paper, we experiment with designing around these problems: we propose a cooperative puzzle-platformer game that was designed to look similarly to the mainstream of the genre, but to allow for an easy implementation of a quality sidekick AI, letting us test player reactions to the AI. The game was designed so that it is easy for the AI to find optimal solutions while the problem is relatively hard for a human player. We gathered survey responses from players who played the game online (N=28). While the AI sidekick was reported as likeable and helpful, players still reported greater enjoyment of the game when they were allowed to control the sidekick themselves. These findings indicate that the AI itself is not the only obstacle to truly enjoyable gameplay with an AI sidekick.