In this article we compare the benefits for game design and development relative to the use of three Game User Research (GUR) methodologies (user interviews, game metrics, and psychophysiology) to assist in shaping levels for a 2-D platformer game. We illustrate how these methodologies help level designers make more informed decisions in an otherwise qualitative design process. GUR data sources were combined in pairs to evaluate their usefulness in small-scale commercial game development scenarios, as commonly used in the casual game industry. Based on the improvements suggested by each data source, three levels of a Super Mario clone were modified and the success of these changes was measured. Based on the results we conclude that user interviews provide the clearest indications for improvement among the considered methodologies while metrics and biometrics add different types of information that cannot be obtained otherwise. These findings can be applied to the development of 2-D games; we discuss how other types of games may differ from this. Finally, we investigate differences in the use of GUR methodologies in a follow-up study for a commercial game with children as players.
LINK
In this paper we compare the effects of using three game user research methodologies to assist in shaping levels for a 2-D platformer game, and illustrate how the use of such methodologies can help level designers to make more informed decisions in an otherwise qualitative oriented design process. Game user interviews, game metrics and psychophysiology (biometrics) were combined in pairs to gauge usefulness in small-scale commercial game development scenarios such as the casual game industry. Based on the recommendations made by the methods, three sample levels of a Super Mario clone were improved and the opinions of a second sample of users indicated the success of these changes. We conclude that user interviews provide the clearest indications for improvement among the considered methodologies while metrics and biometrics add different types of information that cannot be obtained otherwise.
DOCUMENT
Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiat- ing event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a standardized way to map and organize toxicological mechanistic information. As such, AOPs inform on key events underlying toxicity, thus supporting the development of New Approach Methodologies (NAMs), which aim to reduce the use of animal testing for toxicology purposes. However, the establishment of a novel AOP relies on the gathering of multiple streams of evidence and infor- mation, from available literature to knowledge databases. Often, this information is in the form of free text, also called unstructured text, which is not immediately digestible by a computer. This information is thus both tedious and increasingly time-consuming to process manually with the growing volume of data available. The advance- ment of machine learning provides alternative solutions to this challenge. To extract and organize information from relevant sources, it seems valuable to employ deep learning Natural Language Processing techniques. We review here some of the recent progress in the NLP field, and show how these techniques have already demonstrated value in the biomedical and toxicology areas. We also propose an approach to efficiently and reliably extract and combine relevant toxicological information from text. This data can be used to map underlying mechanisms that lead to toxicological effects and start building quantitative models, in particular AOPs, ultimately allowing animal-free human-based hazard and risk assessment.
DOCUMENT
Implementation of reliable methodologies allowing Reduction, Refinement, and Replacement (3Rs) of animal testing is a process that takes several decades and is still not complete. Reliable methods are essential for regulatory hazard assessment of chemicals where differences in test protocol can influence the test outcomes and thus affect the confidence in the predictive value of the organisms used as an alternative for mammals. Although test guidelines are common for mammalian studies, they are scarce for non-vertebrate organisms that would allow for the 3Rs of animal testing. Here, we present a set of 30 reporting criteria as the basis for such a guideline for Developmental and Reproductive Toxicology (DART) testing in the nematode Caenorhabditis elegans. Small organisms like C. elegans are upcoming in new approach methodologies for hazard assessment; thus, reliable and robust test protocols are urgently needed. A literature assessment of the fulfilment of the reporting criteria demonstrates that although studies describe methodological details, essential information such as compound purity and lot/batch number or type of container is often not reported. The formulated set of reporting criteria for C. elegans testing can be used by (i) researchers to describe essential experimental details (ii) data scientists that aggregate information to assess data quality and include data in aggregated databases (iii) regulators to assess study data for inclusion in regulatory hazard assessment of chemicals.
DOCUMENT
Abstract: Combined lifestyle interventions (CLI) are focused on guiding clients with weight-related health risks into a healthy lifestyle. CLIs are most often delivered through face-to-face sessions with limited use of eHealth technologies. To integrate eHealth into existing CLIs, it is important to identify how behavior change techniques are being used by health professionals in the online and offline treatment of overweight clients. Therefore, we conducted online semi-structured interviews with providers of online and offline lifestyle interventions. Data were analyzed using an inductive thematic approach. Thirty-eight professionals with (n = 23) and without (n = 15) eHealth experience were interviewed. Professionals indicate that goal setting and action planning, providing feedback and monitoring, facilitating social support, and shaping knowledge are of high value to improve physical activity and eating behaviors. These findings suggest that it may be beneficial to use monitoring devices combined with video consultations to provide just-in-time feedback based on the client’s actual performance. In addition, it can be useful to incorporate specific social support functions allowing CLI clients to interact with each other. Lastly, our results indicate that online modules can be used to enhance knowledge about health consequences of unhealthy behavior in clients with weight-related health risks.
DOCUMENT
Both because of the shortcomings of existing risk assessment methodologies, as well as newly available tools to predict hazard and risk with machine learning approaches, there has been an emerging emphasis on probabilistic risk assessment. Increasingly sophisticated AI models can be applied to a plethora of exposure and hazard data to obtain not only predictions for particular endpoints but also to estimate the uncertainty of the risk assessment outcome. This provides the basis for a shift from deterministic to more probabilistic approaches but comes at the cost of an increased complexity of the process as it requires more resources and human expertise. There are still challenges to overcome before a probabilistic paradigm is fully embraced by regulators. Based on an earlier white paper (Maertens et al., 2022), a workshop discussed the prospects, challenges and path forward for implementing such AI-based probabilistic hazard assessment. Moving forward, we will see the transition from categorized into probabilistic and dose-dependent hazard outcomes, the application of internal thresholds of toxicological concern for data-poor substances, the acknowledgement of user-friendly open-source software, a rise in the expertise of toxicologists required to understand and interpret artificial intelligence models, and the honest communication of uncertainty in risk assessment to the public.
DOCUMENT
A case study and method development research of online simulation gaming to enhance youth care knowlegde exchange. Youth care professionals affirm that the application used has enough relevance as an additional tool for knowledge construction about complex cases. They state that the usability of the application is suitable, however some remarks are given to adapt the virtual environment to the special needs of youth care knowledge exchange. The method of online simulation gaming appears to be useful to improve network competences and to explore the hidden professional capacities of the participant as to the construction of situational cognition, discourse participation and the accountability of intervention choices.
DOCUMENT
The COVID-19 pandemic has revealed the importance for university teachers to have adequate pedagogical and technological competences to cope with the various possible educational scenarios (face-to-face, online, hybrid, etc.), making use of appropriate active learning methodologies and supporting technologies to foster a more effective learning environment. In this context, the InnovaT project has been an important initiative to support the development of pedagogical and technological competences of university teachers in Latin America through several trainings aiming to promote teacher innovation. These trainings combined synchronous online training through webinars and workshops with asynchronous online training through the MOOC “Innovative Teaching in Higher Education.” This MOOC was released twice. The first run took place right during the lockdown of 2020, when Latin American teachers needed urgent training to move to emergency remote teaching overnight. The second run took place in 2022 with the return to face-to-face teaching and the implementation of hybrid educational models. This article shares the results of the design of the MOOC considering the constraints derived from the lockdowns applied in each country, the lessons learned from the delivery of such a MOOC to Latin American university teachers, and the results of the two runs of the MOOC.
DOCUMENT
Cities are becoming increasingly vulnerable for climate change and there is an urgent needto become more resilient. This research involves the development of the City climate scanRotterdam (September 2017) methodology to measure, map, scan and assess differentparameters that together give insight in the vulnerability of urban areas and neighborhoods.The research at recent City climate scan / Sketch your city in April 2018 used storytelling andsketching1 as main method to connect stakeholders, motivate action, evoke recognition in ajointly formulated goal, such as taking climate action. The city climate scan also involved thedevelopment of a set of measurement tools that can be applied in different urbanneighborhoods in a low-cost low-tech approach with teams of stakeholders andpractitioners. The city climate scan method was tested in different cities around the globe(Rotterdam, Manila and Cebu) in groups of young professionals and stakeholders in rapidurban appraisals.
DOCUMENT
Probation and after-care service is of great social importance and you want to do a proper job. ‘Doing a proper job’ tends to revolve around effective interventions or instruments. Which is important, but doing a proper and effective job involves more than that. We distinguish three forms of effectiveness: -Effective methods: what works? For example, working according to the principles of Risk, Needs and Responsivity6. Or structured behavioural training according to the cognitive-behavioural model. Or working according to the Good Lives Model7. Or the network approach. Methods are referred to as ‘effective’ if there is scientific evidence that they increase the chances of achieving the probation objectives. The risk of recidivism decreases if you work according to these methods. Proper coordination of the working method with specific clients is always part of an effective methodology. -Effective professionals: who works? Methodologies do not lead a life of their own, they only become effective in the hands of professionals8. Effective professionals are rooted in professional values, work with theoretically consistent methods, stand behind their working methods, are able to interact with different types of people (also with people who find this difficult) and systematically provide specific feedback on their actions and results. The importance of effective and open client feedback is important in this. Furthermore, an effective professional attempts to connect his own experiential knowledge to scientific knowledge to the best of his ability. A professional who meets these characteristics is in a better position than other professionals to ‘ensure the effectiveness’ of the method. -Effective interactions: the working alliance (how does it work?) Methodologies and professionals gain meaning in proper interaction with clients and other stakeholders (for example, social network and volunteers). A proper quality of the working alliance increases the chance of successful completion of a probation programme. The risk of problems within the process is reduced and the risk of dropout (no-show or a negative report) decreases.
DOCUMENT
