Game development businesses often choose Lua for separating scripted game logic from reusable engine code. Lua can easily be embedded, has simple interfaces, and offers a powerful and extensible scripting language. Using Lua, developers can create prototypes and scripts at early development stages. However, when larger quantities of engine code and script are available, developers encounter maintainability and quality problems. First, the available automated solutions for interoperability do not take domain-specific optimizations into account. Maintaining a coupling by hand between the Lua interpreter and the engine code, usually in C++, is labour intensive and error-prone. Second, assessing the quality of Lua scripts is hard due to a lack of tools that support static analysis. Lua scripts for dynamic analysis only report warnings and errors at run-time and are limited to code coverage. A common solution to the first problem is developing an Interface Definition Language (IDL) from which ”glue code”, interoperability code between interfaces, is generated automatically. We address quality problems by proposing a method to complement techniques for Lua analysis. We introduce Lua AiR (Lua Analysis in Rascal), a framework for static analysis of Lua script in its embedded context, using IDL models and Rascal.
DOCUMENT
The research goal of this dissertation is to make configurational HRM usable for science and practice by developing a simulation model and serious game. These tools offer HRM professionals the opportunity to design a multiyear HRM configuration that shapes employee behaviour, while enabling HRM research to get access to a level of detail that was not achieved earlier, contributing to the current state of the art knowledge on strategic HRM. To shape employee behavior in such a way that it contributes to overarching organizational goals, organizations often deploy a set of human resource management (HRM) practices. If the set of individual HRM-practices is designed correctly, they amplify each other in shaping the desired behavior. However, while there is wide agreement on the importance of combining HRM-practices in a configuration that reflects the organizational strategy, we notice a lack of consensus on which HRM-practices need to be combined given a specific strategic goal and organizational starting point. Furthermore, we did not find an agreement on how to design HRM configurations that shape the desired employee behavior within organizations in multiple years. As a result, HRM professionals that design HRM configurations are left empty handed. While the configurational approach has the potential to provide new insight on how HRM shapes employees’ behavior, applying the configurational mode of theorizing to HRM remains challenging. We explain this challenge by the level of theoretical and practical detail that is needed, by the application of the holistic principle when studying HRM configurations, and due to methodological issues. Traditional methods do not align to the dynamic assumptions and the large number of variables included in configurational HRM. In this dissertation we pose that the time is ripe to unlock the deserved value of configurational HRM for theory and practice. We do so by specifying the underlying assumptions and dynamic implications of the configurational mode of theorizing in HRM, and by defining and adding the needed level of detail. In the current research, configurational HRM is made applicable with the use of a simulation model and serious game. -172- Five sequential steps are taken to make configurational HRM applicable. Firstly, key principles of configurational HRM are identified. Secondly, to ground the simulation we look at the manifestation of ideal type HRM configurations in theory and practice. Thirdly, we collect the solidified practical knowledge of HRM professionals on the alignment of HRM-practices. Fourthly, an initial simulation model is created and tested. And finally, we solidified the simulation model for practice and research by implementing it in a serious game for HRM professionals. Taking these five steps, we have specified configurational HRM to an unprecedented level of detail that allows us to address its complexity empirically and theoretically. We claim that with the results of this research we have opened the scientific and empirical “black box” of configurational HRM. Furthermore, the simulation model and serious game provides HRM professionals with a tool to design firm specific HRM configurations in an interactive and fun way. While prior studies did already acknowledge the importance of alignment when designing HRM, the simulation model and serious game specify the general concept of alignment to a level at which HRM professionals and researchers can start selecting, designing, implementing and researching HRM configurations. The tools provide HRM professionals with a method to grasp, maneuver through the complexity of, and explore the implementation of multi-year firm specific HRM.
MULTIFILE
For over thirty years, there has been a discussion about the effectiveness of educational games in comparison to traditional learning materials. To help further this discussion, we aim to understand ‘how educational games work’ by formalising (and visualising) the educational and motivational aspects of such games. We present a model that focuses on the relationship between three different aspects: user properties, game mechanics, and learning objectives. In two example cases, we have demonstrated how the model can be used to analyse existing games and their game/instructional design, and suggest possible improvements in both motivational and educational aspects based on the model. As such, we introduce a novel approach to analysing educational games and, by inference, a novel design process for designing more effective educational games.
DOCUMENT
Electronic Sports (esports) is a form of digital entertainment, referred to as "an organised and competitive approach to playing computer games". Its popularity is growing rapidly as a result of an increased prevalence of online gaming, accessibility to technology and access to elite competition.Esports teams are always looking to improve their performance, but with fast-paced interaction, it can be difficult to establish where and how performance can be improved. While qualitative methods are commonly employed and effective, their widespread use provides little differentiation among competitors and struggles with pinpointing specific issues during fast interactions. This is where recent developments in both wearable sensor technology and machine learning can offer a solution. They enable a deep dive into player reactions and strategies, offering insights that surpass traditional qualitative coaching techniquesBy combining insights from gameplay data, team communication data, physiological measurements, and visual tracking, this project aims to develop comprehensive tools that coaches and players can use to gain insight into the performance of individual players and teams, thereby aiming to improve competitive outcomes. Societal IssueAt a societal level, the project aims to revolutionize esports coaching and performance analysis, providing teams with a multi-faceted view of their gameplay. The success of this project could lead to widespread adoption of similar technologies in other competitive fields. At a scientific level, the project could be the starting point for establishing and maintaining further collaboration within the Dutch esports research domain. It will enhance the contribution from Dutch universities to esports research and foster discussions on optimizing coaching and performance analytics. In addition, the study into capturing and analysing gameplay and player data can help deepen our understanding into the intricacies and complexities of teamwork and team performance in high-paced situations/environments. Collaborating partnersTilburg University, Breda Guardians.
A world where technology is ubiquitous and embedded in our daily lives is becoming increasingly likely. To prepare our students to live and work in such a future, we propose to turn Saxion’s Epy-Drost building into a living lab environment. This will entail setting up and drafting the proper infrastructure and agreements to collect people’s location and building data (e.g. temperature, humidity) in Epy-Drost, and making the data appropriately available to student and research projects within Saxion. With regards to this project’s effect on education, we envision the proposal of several derived student projects which will provide students the opportunity to work with huge amounts of data and state-of-the-art natural interaction interfaces. Through these projects, students will acquire skills and knowledge that are necessary in the current and future labor-market, as well as get experience in working with topics of great importance now and in the near future. This is not only aligned with the Creative Media and Game Technologies (CMGT) study program’s new vision and focus on interactive technology, but also with many other education programs within Saxion. In terms of research, the candidate Postdoc will study if and how the data, together with the building’s infrastructure, can be leveraged to promote healthy behavior through playful strategies. In other words, whether we can persuade people in the building to be more physically active and engage more in social interactions through data-based gamification and building actuation. This fits very well with the Ambient Intelligence (AmI) research group’s agenda in Augmented Interaction, and CMGT’s User Experience line. Overall, this project will help spark and solidify lasting collaboration links between AmI and CMGT, give body to AmI’s new Augmented Interaction line, and increase Saxion’s level of education through the dissemination of knowledge between researchers, teachers and students.
Stedelijke regio’s streven naar een duurzame mobiliteitstransitie. Deze ambitie staat echter op gespannen voet met het hoge autobezit- en autogebruik. De stormachtige introductie van lichte elektrische voertuigen, oftewel LEVs (denk aan e-scooters, e-steps, e-(cargo)bikes en micro-cars) leek een belangrijke ‘gamechanger’ te zijn. Deze LEVs zijn namelijk klein en efficiënt, zijn nagenoeg emissievrij, bieden mogelijkheden voor het verbeteren van het voor- en natransport van het openbaar vervoer (OV) en worden bovendien door hun gebruikers als prettig ervaren tijdens het reizen.Tot op heden maken LEVs deze beloften echter onvoldoende waar. Bij de introductie, thans met name in de vorm van deelsystemen, komen diverse uitdagingen aan het licht zoals: 1) verrommeling en overlast door verkeerd gepareerde LEVs, 2) ongewenste substitutie van loop-, fiets- en OV-verplaatsingen en beperkte impact op autogebruik en 3) en zorgen over de verkeersveiligheid en beleving, met name op de (al steeds drukker wordende) fietsinfrastructuur in Nederland. Deze problemen komen mede voort uit de snelle introductie waardoor gemeenten achter de feiten aanliepen en geen gericht beleid konden voeren. Langzaam komen we nu in een periode van stabilisatie en regulering maar een doorontwikkeling naar pro-actief LEV beleid is nodig om de potentie van LEVs voor de mobiliteitstransitie te ondersteunen. Het LEVERAGE-consortium, bestaande uit sterke partners uit de triple helix, gaat daarom aan de slag met deze vraagstukken. De centrale onderzoeksvraag is:Wat is de potentie van LEVs voor de mobiliteitstransitie naar bereikbare, duurzame, verkeersveilige, inclusieve en leefbare stedelijke regio’s en hoe kan deze optimaal worden benut door een betere integratie van LEVs in het mobiliteitssysteem en het mobiliteitsbeleid en door een effectieve governance van de samenwerking tussen publieke en private stakeholders?Om deze vraag te beantwoorden heeft het consortium een ambitieus en innovatieve onderzoeksopzet gedefinieerd waarbij veel nadruk wordt gelegd op de disseminatie en exploitatie van kennis in de beleidspraktijk.Collaborative partnersProvincie Noord-Brabant, Metropoolregio Arnhem-Nijmegen, Gemeente Eindhoven, Gemeente Breda, Gemeente Arnhem, Ministerie I&W, Rijkswaterstaat, Arriva, PON, Check, Citysteps, Cenex, TIER, We-all-Wheel, Fleet investment, Goudappel, Kennisinstellingen en netwerkorganisaties, HAN, TU/e, CROW, Connekt, POLIS, SWOV.
