Land Use Mix (LUM) is a central concept in urban development theory, advocating the integration of distinct primary functions such as residential, commercial, and public spaces within urban environments, contributing to increased street vitality, reduced car dependency, and support for alternative transport. However, LUM remains difficult to define and quantify. Existing frameworks decompose it into scale, dimension, and texture, where the vertical dimension refers to stacking functions within buildings (e.g., retail below residential). While horizontal LUM has been quantified, vertical LUM remains largely unmeasured. Procedural urban generation pipelines focus on urban form rather than functional composition; although density measures such as Floor Space Index (FSI) and Ground Space Index (GSI) are used, LUM is rarely incorporated as a controllable parameter. This paper introduces the Vertical Mix Index (VMI), a novel metric to quantify vertical LUM and integrate it into procedural urban generation. Results show that increasing VMI produces greater vertical functional mixing, though its effectiveness depends on alignment between density distribution, functional allocation, and generative constraints. ... Read more

Human behaviour is strongly shaped by social context. Understanding how individuals influence one another requires experimental settings in which multiple participants can interact naturally while researchers retain control over environmental conditions and data collection. Extended reality (XR) provides immersive, controllable, and reproducible environments that are well suited for investigating human behaviour while maintaining a high sense of presence. However, existing research platforms primarily support single-user studies and offer limited integration of synchronized multi-user interaction, experimental control, and multimodal data acquisition. This paper presents an integrated multi-user XR framework designed to support research on socially-mediated behaviour. The framework enables participants to interact within a shared virtual environment while maintaining real-time synchronization, configurable experimental conditions, and synchronized acquisition of behavioural and physiological data. To demonstrate and evaluate the framework, we designed and developed DIVE: a collaborative fear-of-heights case study in which participants experience configurable elevated environments while interacting toward a shared objective. It includes dedicated researcher tools for experiment configuration, monitoring, safety management, and post-hoc reconstruction of recorded sessions. DIVE was evaluated from the participant's perspective with eighteen participants using the Networked Minds Social Presence Inventory, achieving positive perceived social presence across the measured dimensions. Two researchers evaluated usability using the System Usability Scale, resulting in a score of 80 and indicating good usability. Overall, these findings demonstrate that DIVE supports controlled multi-user XR experiments through shared immersive experiences, perceived social interaction, and multimodal data capture. ... Read more

Wave Function Collapse (WFC) is an algorithm for procedural content generation of tile-based images and game worlds out of adjacency constraints. It has gained traction over the past few years due to its ease of use and simplicity. However, slow runtime remains a major bottleneck of WFC, making it inconvenient to use for the generation of larger outputs. Having faster runtime would both allow for larger worlds to be generated in a reasonable amount of time, as well as make it practical for real-time use. Game developers would also be able to iterate more easily by having to wait less while designing. Using parallelisation would be an effective speedup method, but is nontrivial due to the sequential nature of the algorithm. The constraint propagation step of WFC, which is the most time-consuming step, is difficult to parallelise due to it being sequential in nature. Our solution to this is Binary Space Partitioned Wave Function Collapse (bspWFC), which generates the output image by following the structure of a BSP tree. Each time the tree splits the image in half, the border between the regions is generated, then the two regions can be generated separately in parallel. This process continues recursively up to a desired depth. As more and more branches of the tree are explored, more CPU threads can be utilised, until eventually they are all used at the same time. The individual tree nodes can also be rerun individually in the case of a conflict, improving the algorithm’s success rate. We implemented this algorithm in C++ and benchmarked it to evaluate its performance, measuring runtime, success rate and visual quality. A variety of tilesets were used to test the algorithm’s behaviour under different constraints, yielding significant improvements. For most tilesets, doubling the number of used threads resulted in about a ×1.7 runtime improvement. It also improved their success rate at large output sizes. Many tilesets that would normally have a successful generation less than 10% of the time were improved to over 90%. Due to the modified generation method, the output images could show noticeable artefacts, but this is only the case for a small number of tilesets. The biggest strength of our approach is that it allows parallelisation while remaining compatible with tilesets that would often propagate their constraints very far. ... Read more

This qualitative study explores how Bachelor's computer science students at TU Delft experience curriculum coherence across horizontal (concurrent) and vertical (sequential) dimensions. Based on semi-structured interviews analyzed using Reflexive Thematic Analysis, the results reveal how students view the trade-offs between academic depth and breadth, how well-timed repetition mitigates cognitive load, and how independence between parallel courses combats exhaustion. These insights highlight that curriculum designers should explicitly articulate connections between courses and carefully incorporate repetition to optimize student engagement. ... Read more

Generative AI (GenAI) tools such as ChatGPT have become widely used by computer science students for code generation, debugging, and concept clarification. While these tools can improve efficiency in programming tasks, concerns remain about their potential impact on the independent problem-solving skills that computer science education seeks to cultivate. This study investigates how the use of GenAI during programming tasks shapes the way Computer Science students engage with independent problem-solving. Drawing on semi-structured interviews with seven Computer Science students at TU Delft, Through reflexive thematic analysis, the study identifies two themes. First, students framed their reliance on GenAI as a deliberate, self-governed choice rather than a loss of ability: they kept the interpretive work of understanding and planning, and the judgment of whether a solution was correct, for themselves, while delegating execution and The filling of knowledge gaps, and maintained that they could still work unaided if they chose to. Second, students reported a weakening willingness to persist through difficulty without help, both an immediate lowered threshold to begin effortful tasks and a gradual decline of motivation over time. Mapped onto Pólya's four stages of problem-solving, engagement is retained at the early and evaluative stages but surrendered in the middle, Persistence governs whether students return to a problem after a failed attempt. These findings suggest that GenAI reshapes independent problem-solving less by removing ability than by lowering the effort required to avoid it, and contribute to ongoing discussions about the responsible integration of AI tools in computer science education. ... Read more

This qualitative study explores how final-year Computer Science students perceive and manage conflicts during collaborative software projects. While these projects simulate professional teamwork, they frequently introduce interpersonal and organizational challenges. Using semi-structured interviews and Reflexive Thematic Analysis, this research investigates the subjective experiences and resolution strategies of students navigating team conflicts. The findings reveal three primary themes regarding conflict perception and resolution outcomes. First, teams generally manage minor task-oriented disagreements constructively through clear communication, resulting in incidental friction with no lasting impact. Second, prolonged behavioral conflicts, such as teammate absenteeism, can be resolved positively when managed constructively; these experiences often lead to personal growth, leadership, and communication skills. Third, escalating relationship conflicts, characterized by disruptive behavior and ineffective escalation processes, lead to significant negative consequences, including academic delays and emotional strain. The study concludes that while students demonstrate resilience and leverage routine teamwork obstacles to develop essential professional competencies, they struggle to navigate severe interpersonal conflicts without adequate external mediation. To optimize collaborative learning, software engineering curricula could integrate dedicated conflict management workshops, and universities must ensure accessible, transparent institutional support structures for complex interpersonal dynamics. ... Read more

Interdisciplinarity is important for Computer Science education because it prepares students to solve real-world problems and collaborate with different disciplines. Despite its benefits, computer science students struggle with interdisciplinary learning. Without understanding the students’ motivations and struggles, it is difficult to design interdisciplinary courses that are beneficial and accessible. This research aims to understand how these students experience interdisciplinary courses, in terms of benefits and challenges. Seven computer science students were interviewed, and their transcripts were analysed using reflexive thematic analysis. Within interdisciplinary learning, the students experienced broadened perspectives and the communication of their ideas across disciplines. By understanding these experiences, faculty can better understand how to design courses centred around interdisciplinarity. ... Read more

Assessments are a crucial, high-stakes part of the learning process, and students consolidate much of their learning during the considerable effort they make preparing for them. Computer science curricula typically include both theory-heavy and programming-heavy assessments. This study investigates which learning strategies final-year computer science students adopt when preparing for theory-heavy assessments compared to programming-heavy assessments. Using semi-structured interviews with three final-year Computer Science and Engineering students at TU Delft, transcripts were analysed through an inductive open-coding pass followed by deductive coding using an established framework of cognitive and metacognitive learning strategies. Results show that rehearsal and elaboration strategies—reviewing lecture slides, note-taking, and creating cheat sheets—were predominantly associated with preparation for theory-heavy assessments, while metacognitive self-regulation, through consulting assignment specifications, was predominantly associated with preparation for programming-heavy assessments. Critical thinking was the one strategy reported across both assessment types, expressed through the use of practice exams. These findings suggest that practice exams function as a strategy supporting critical thinking regardless of assessment type. The relevance and diversity of practice exam material may therefore be an important, underexplored lever for supporting effective learning in computer science education. ... Read more

With Virtual Reality, we can create and explore an infinite number of environments. These environments can have multiple applications, such as in education, training, or entertainment. However, we need a way to move through these environments. The most natural way is to walk, but we are limited by our physical space. A solution would be hyperbolic space. In this thesis, we explore navigational performance in hyperbolic space and its relation to the properties of hyperbolic geometry. By using the existing application Holonomy VR, we can use hyperbolic space and virtual reality to create an infinite world in a confined physical space. We let participants navigate in this virtual experience to study if they can navigate and learn about its properties. To achieve this, the performance of Holonomy VR is improved and new features are added that allow for a textured top view of the hyperbolic plane in the form of a 2D experience. Also, a new mode is added that requires users to find multiple landmarks in the environment. The beacon cue is developed to let users see targets outside of their current reach. A user study is conducted in collaboration with Leiden University to test the navigational performance and the understanding of the hyperbolic properties. The results show that some people can adapt to navigating in a confined hyperbolic space and that the 2D experience results in the fastest training time. However, it is found that training by exploring the environment and learning about the landmarks before the evaluation does not improve the navigational performance. This contradicts the findings about navigation in a Euclidean scene. It is also found that some hyperbolic properties can be learned and that the 2D experience made it easier to learn about the diverging paths property. Participants who grasped the concept found the experience fun and interesting, and some even indicated that they wanted to learn more about hyperbolic space. Overall, this study shows that people can navigate a confined hyperbolic environment and that they can learn about its properties. ... Read more

In musical (jazz) improvisation, musicians that are just starting out can often feel uncomfortable when being put on the spot by their fellow players. However, when a musician is on their own when practising or leisurely playing, this prevents them from listening to fellow musicians. When a musician wants to experience some notion of co-play when they are on their own, computers and musical generative techniques may be a source of help. We study the extent to which music improvisation algorithms can facilitate such interactions by proposing an experimental framework to evaluate and compare these different algorithms. We achieve this by developing MILES ('Mixed-Initiative musicaL interactivE System'), a generic music improvisation system that allows a musician to improvise with various musical improvisation models and facilitates comparative evaluation of these models. MILES makes use of the 'trading fours' paradigm, where two or more musicians exchange four measures of solo material. We conduct experiments with novice and advanced musicians in expert-pupil and peer-to-peer settings that compare differing algorithms, as well as different variations of similar algorithms. These comparisons are based on self-assessed opinions and third-party grading and ordering of recordings, based on improvisational reciprocity and enjoyment. Symbolic music recording analysis further quantifies the interactivity between the musician and the algorithms. With this experimental setup, we are able to track familiarity and enjoyment of using music improvisation algorithms, and compare different iterations of similar music improvisation algorithms. ... Read more

Gesture-based sonification games offer a promising medium for motor-skill rehabilitation by transforming therapeutic movements into interactive musical experiences. However, creating custom levels for such games remains inaccessible to therapists and researchers, who often lack the musical or technical expertise required to shape musical material into meaningful motor tasks. This thesis investigates how non-technical and non-musician users can be supported in generating music, authoring interaction structures, and validating playable levels for gesture-based sonification games.

To address this challenge, this work introduces an end-to-end authoring pipeline that combines symbolic music generation with an intuitive level-editing system. A hierarchical diffusion model is adapted to produce structured, multi-track musical material through high-level controls such as key, tempo, and song form. A web-based authoring interface then allows users to refine this material, simplify dense passages through a trigger--support note mechanism, and map notes to spatially and temporally aligned gesture targets. A target-configuration module provides synchronized previews and export functions that integrate directly with the PIZZICATO runtime, enabling real-time testing and performance logging.

A qualitative expert evaluation with nine therapists and researchers examined the usability, flexibility, and therapeutic potential of the system. Participants found the workflow accessible and intuitive, valued the direct manipulation of musical and spatial elements, and highlighted the potential of the tool to streamline content creation for motor-rehabilitation studies. The evaluation also surfaced conceptual limitations, including the need for broader musical genres beyond pop-derived structures, and the opportunity to incorporate clinically informed automation such as predefined motor-exercise patterns.

This thesis contributes (i) a novel, integrated workflow for non-technical authoring of gesture-based sonification levels, (ii) interface techniques that translate symbolic musical structure into spatial--temporal interaction tasks, and (iii) empirical insights into the needs of therapists and psychologists designing movement-based therapeutic content. ... Read more

Procedural Content Generation methods enable the creation of varied content algorithmically. Wave Function Collapse (WFC) is one such method. It is a tile-based local constraint solver commonly applied to world and map generation for grid-based content; it is able to create varied output from the same set of rules. While WFC is versatile, content generated with it is i) limited to one grid, ii) based on uniform tiles and iii) must use the same tile set and constraints throughout the grid. Due to these limitations, large classes of content are excluded, such as structured objects. Structured objects consist of an assembly of multiple components, each possibly based on a different tile set. We therefore propose Expressive Wave Function Collapse (XWFC), a major extension of WFC that enables solving and combining multiple grids with different Non-Uniform Tile (NUT) sets. Additionally, we can guarantee NUT shape and size preservation even under WFC’s Overlapping Model. With these generalizations, new domains are within reach for structured objects based on NUT sets, such as Tetris or LEGO. ... Read more

AI-generated music is a huge research field with many different approaches and models being the result of it. One such model is the ProceduraLiszt model, which utilizes the Wave Function Collapse algorithm, an algorithm similar to constraint programming, to generate its music. This research builds upon that model. It does so by trying to reverse engineer a given piece of music into a set of satisfied constraints that the model is compatible with. We present an approach that allows for the inference of constraints of a given music file that adheres to the MIDI format called MidiAnalyser. We run our model on a set of music files and analyze the inferred constraints. The constraints include aspects like key and note range. ... Read more

Procedurally generating a coherent and emotionally resonant piece of music can be very challenging. The Wave Function Collapse (WFC) algorithm is very effective when it comes to generating randomized patterns and maps that resemble an input sample. A version of this algorithm using a hierarchy of sections, chords and melody was used to create a model capable of generating music. In this paper, we extend the capabilities of this model to improve its utility and help composers more effectively utilize this music generation method to create engaging pieces. Our model offers improvements over previous methods by allowing composers to retain desirable elements of the music output while regenerating others, thus streamlining the iterative nature of music composition. We consider and compare different music visualization techniques and explore various user interface (UI) interaction methods to facilitate the effective selection of elements from the output. We designed and implemented this model with the conclusion that it significantly enhances the user experience and allows for creating a much more sound and complete piece of music compared to the original. ... Read more

Wave Function Collapse (WFC) can be described as a family of algorithms, meant for content generation through constraint solving. One variant is Hierarchical WFC, where a hierarchical structure is given to the tileset used in WFC. This variant has seen use in a mixed-initiative procedural music generation model, where pieces of music simulating a single instrument playing chords and a melody are generated. In this paper, we explore how this model can be adapted to generate (coherent) pieces of music simulating several instruments playing in parallel. To achieve this, three model properties had to be defined: a new canvas structure, a set of constraints that instruments impose on each other, and the manner in which cells of all canvasses are collapsed. A hierarchical structure has been defined of a single section canvas, of which every cell has an inheriting chord canvas, of which every cell has an inheriting melody canvas for each instrument. The section cells impose constraints on inheriting chord and melody cells, and the chord cells impose constraints on inheriting melody cells. Besides this, melody cells impose constraints on cells belonging to other melody canvases (i.e. other instruments). With this canvas structure and these sets of constraints, the cells could be collapsed, such that coherent pieces of music simulating several instruments playing in parallel were generated. ... Read more

Music, a profound expression of the human experience, is built upon intricate patterns that humans have spent centuries trying to understand and recreate. Consequentially, Hierarchical Wave Function Collapse was proposed as a novel model for procedural music generation, which organizes musical constraints within a three-level hierarchy. However, music with melody but no rhythm, is like a text with all characters but no spacing. This research aims to create rhythm procedurally by exploring existing representations and combining the most effective elements to propose a simple but comprehensive rhythmic model. Though not all-powerful, the proposed model accommodates varied measures and motifs. By implementing it, the research evaluates its efficiency and limitations, identifying the types of music it cannot generate. This study aims to contribute a tool for mixed-initiative music creation, expanding procedural music generation with a nuanced approach to rhythm. ... Read more

Procedural Content Generation (PCG) is a method to automatically generate content with little to no human assistance required. It emerges as a promising tool to generate educational content tailored to individual learning needs, a fundamental aspect of effective teaching.
This review aims to provide an overview of existing research on the educational applications of PCG across disciplines. The key objectives of this paper include identifying the range of domains that have profited from the educational use of PCG, the challenges faced by specific disciplines as well as discerning the similarities and differences in their approaches. By addressing these objectives, this literature review seeks to identify areas for further research and provide insight into understanding the obstacles preventing the adoption of PCG in certain educational domains. By carefully surveying a sample of research conducted on the educational use of PCG in a broad range of disciplines, we found that computer science and mathematics have extensively leveraged PCG to enhance learning experiences, while natural sciences and social sciences could benefit from further research. To the best of our knowledge, fields like geography, physics and biology as well as arts, business and economics remain largely unexplored. Furthermore, challenges such as adjusting content difficulty, generating coherent exercises, and educational accuracy issues have been identified as significant barriers in various fields. ... Read more

Procedural Content Generation (PCG) is a powerful content generation technique that can be used to automatically generate content (an example would be exercises for a quiz or a game). As it stands, PCG is able to create content with zero human interaction which makes it a technique worth exploring for educational purposes. In the context of PCG, this research focuses on how PCG is used to orchestrate the simultaneous generation of content of various types and identify what could be done more, possibly towards educational use. The method chosen for this research is literature review. As such, this paper provides a summary of "orchestrative" PCG approaches found in recent literature and evaluates said approaches through the lens of "PCG for education". Findings are presented in an exhaustive manner with each piece of literature occupying a subsection. A discussion section that explores how these approaches could benefit education and/or what could be done to facilitate that is also present. ... Read more

This paper investigates the use of Adaptive Procedural Content Generation (APCG), a form of procedural content generation that is adjusted to a player model, to tailor educational content based on individual learner profiles, thereby improving engagement and consequent learning outcomes. Key research questions include how to measure the success of APCG, its impact on academic performance, and the comparative advantages over traditional PCG methods. Through a literature review, this study identifies current trends, methodologies, and challenges in the application of APCG in educational settings. A list of existing papers has been synthesized on the knowledge body that exists on APCG implementations. We present these findings together with their most relevant methods, domains, target demographics and conclusions to gain an in- sight in which research currently exists on it. The findings aim to provide insights for educators, game developers, and researchers on effective implementations of APCG, paving the way for more personalized and impactful educational technologies. ... Read more

Wave Function Collapse (WFC) is among the most well-known and beloved procedural content generation algorithms. WFC solvers can be understood as a specific type of constraint solver, and as such, backtracking is an integral part of exploring the space of possible solutions. Recent advancements were inspired by this algorithm to model procedural music generation, using a hierarchy of many canvases, each with its own semantic domain within music composition (sections, chords, melody). In the model, due to the structural dependencies between canvases, constraints that involve cells from different canvases make exhaustive backtracking a challenge. Existing backtracking methods only consider a single set of variables, but if a specific value on one canvas can affect the entire structure of another canvas, we need more elaborate ways to deal with conflicts.

This paper presents the basic principles that backtracking models for this hierarchy should abide by, and additional guidelines for evaluating them. Two approaches are proposed, and their runtime efficiencies are compared. Depth-first traversal of the canvas hierarchy results in significantly shorter runtimes than its breadth-first counterpart. ... Read more