Game-like Setting Research Articles

Gamified Cybersecurity Education Through the Lens of the Information Search Process: An Exploratory Study of Capture-the-Flag Competitions [Research-in-Progress

Aim/Purpose. Capture the Flag (CTF) challenges are a popular form of cybersecurity education where students solve hands-on tasks in a game-like setting. These exercises provide learning experiences with various specific technologies and subjects, as well as a broader understanding of cybersecurity topics. Competitions reinforce and teach problem-solving skills that are applicable in various technical and non-technical environments outside of the competitions. Background. The Information Search Process (ISP) is a framework developed to under-stand the process by which an individual goes about studying a topic, identifying emotional ties connected to each step an individual takes. As the individual goes through the problem-solving process, there is a clear flow from uncertainty to clarity; the individual’s feelings, thoughts, and actions are all interconnected. This study aims to investigate the learning of cybersecurity concepts within the framework of the ISP, specifically in the context of CTF competitions. Methodology. A comprehensive research methodology designed to incorporate quantitative and qualitative analyses to draw the parallels between the participants’ emotional experiences and the affective dimensions of learning will be implemented to measure the three primary goals. Contribution. This study contributes significantly to the broader landscape of cybersecurity education and cognitive-emotional experiences in problem-solving. Findings. The study has three primary goals. First, we seek to enhance our under-standing of the emotional and intellectual aspects involved in problem-solving, as demonstrated by the ISP approach. Second, we aim to gain in-sights into how the presentation of CTF challenges influences the learning experience of participants. Lastly, we strive to contribute to the improvement of cybersecurity education by identifying actionable steps for more effective teaching of technical skills and approaches. Recommendations for Practitioners. Competitions reinforce and teach problem-solving skills applicable in various technical and non-technical environments outside of the competitions. Recommendations for Researchers. The Information Search Process (ISP) framework may enhance our understanding of the emotional and intellectual aspects involved in problem-solving as we study the emotional ties connected to each step an individual takes as the individual goes through the problem-solving process. Impact on Society. Our pursuit of advancing our understanding of cybersecurity education will better equip future generations with the skills and knowledge needed to ad-dress the evolving challenges of the digital landscape. This will better pre-pare them for real-world challenges. Future Research. Future studies would include the development of a cybersecurity curriculum on vulnerability exploitation and defense. It would include practice exploiting practical web and binary vulnerabilities, reverse engineering, system hardening, security operations, and understanding how they can be chained together.

Children's Learning of Non-adjacent Dependencies Using a Web-Based Computer Game Setting.

Infants show impressive speech decoding abilities and detect acoustic regularities that highlight the syntactic relations of a language, often coded via non-adjacent dependencies (NADs, e.g., is singing). It has been claimed that infants learn NADs implicitly and associatively through passive listening and that there is a shift from effortless associative learning to a more controlled learning of NADs after the age of 2 years, potentially driven by the maturation of the prefrontal cortex. To investigate if older children are able to learn NADs, Lammertink et al. (2019) recently developed a word-monitoring serial reaction time (SRT) task and could show that 6–11-year-old children learned the NADs, as their reaction times (RTs) increased then they were presented with violated NADs. In the current study we adapted their experimental paradigm and tested NAD learning in a younger group of 52 children between the age of 4–8 years in a remote, web-based, game-like setting (whack-a-mole). Children were exposed to Italian phrases containing NADs and had to monitor the occurrence of a target syllable, which was the second element of the NAD. After exposure, children did a “Stem Completion” task in which they were presented with the first element of the NAD and had to choose the second element of the NAD to complete the stimuli. Our findings show that, despite large variability in the data, children aged 4–8 years are sensitive to NADs; they show the expected differences in r RTs in the SRT task and could transfer the NAD-rule in the Stem Completion task. We discuss these results with respect to the development of NAD dependency learning in childhood and the practical impact and limitations of collecting these data in a web-based setting.

An Adaptive Game-Based Learning Strategy for Children Road Safety Education and Practice in Virtual Space.

Virtual reality (VR) has been widely used as a tool to assist people by letting them learn and simulate situations that are too dangerous and risky to practice in real life, and one of these is road safety training for children. Traditional video- and presentation-based road safety training has average output results as it lacks physical practice and the involvement of children during training, without any practical testing examination to check the learned abilities of a child before their exposure to real-world environments. Therefore, in this paper, we propose a 3D realistic open-ended VR and Kinect sensor-based training setup using the Unity game engine, wherein children are educated and involved in road safety exercises. The proposed system applies the concepts of VR in a game-like setting to let the children learn about traffic rules and practice them in their homes without any risk of being exposed to the outside environment. Thus, with our interactive and immersive training environment, we aim to minimize road accidents involving children and contribute to the generic domain of healthcare. Furthermore, the proposed framework evaluates the overall performance of the students in a virtual environment (VE) to develop their road-awareness skills. To ensure safety, the proposed system has an extra examination layer for children’s abilities evaluation, whereby a child is considered fit for real-world practice in cases where they fulfil certain criteria by achieving set scores. To show the robustness and stability of the proposed system, we conduct four types of subjective activities by involving a group of ten students with average grades in their classes. The experimental results show the positive effect of the proposed system in improving the road crossing behavior of the children.

Cybersecurity knowledge and skills taught in capture the flag challenges

Capture the Flag challenges are a popular form of cybersecurity education, where students solve hands-on tasks in an informal, game-like setting. The tasks feature diverse assignments, such as exploiting websites, cracking passwords, and breaching unsecured networks. However, it is unclear how the skills practiced by these challenges match formal cybersecurity curricula defined by security experts. We explain the significance of Capture the Flag challenges in cybersecurity training and analyze their 15,963 textual solutions collected since 2012. Based on keywords in the solutions, we map them to well-established ACM/IEEE curricular guidelines to understand which skills the challenges teach. We study the distribution of cybersecurity topics, their variance in different challenge formats, and their development over the past years. The analysis showed the prominence of technical knowledge about cryptography and network security, but human aspects, such as social engineering and cybersecurity awareness, are neglected. We discuss the implications of these results and relate them to contemporary literature. Our results indicate that future Capture the Flag challenges should include non-technical aspects to address the current advanced cyber threats and attract a broader audience to cybersecurity.

Pronoun drop and prosocial behavior: experimental evidence from Japan

We join a growing body of literature suggesting that the languages people speak influence their decision-making. We tested whether dropping the first-person pronoun “I” affects pro-social behavior in a dictator game-like setting. To this end, we conducted an online randomized, incentivized experiment with a socially representative sample of 2000 Japanese respondents. We provide compelling causal evidence that pronoun dropping reduces pro-sociality. Given that our results provide little empirical support for previous research findings linking first-person pronoun use and lower pro-sociality, we prescribe caution in using languages as a proxy for culture in several cross-country empirical studies in economics.

The ambiguity dilemma in procurement projects

PurposeThe purpose of this paper is to use game theory and ambiguity theory to show how “economically rational” vendors will behave in a procurement process that runs over more than one period. In light of that behavior, we have proposed “economically rational” counter-strategies on the part of purchasers.Design/methodology/approachBased on a perception–expectation framework, a unique game-based approach is designed. The authors have proposed “economically rational” counter-strategies on the part of purchasers, which are premised on the theory of rational agency.FindingsAmbiguity in the procurement process is a bane for procuring principals and a boon for suppliers – for the former, it is an issue to be managed, and for the latter it provides an opportunity to extract “insurance rents” from the principals. The authors show that, under certain conditions, the contracting principal can be exploited by a rational, rent-extracting vendor. In particular, they show that there is an incentive for a vendor to delay the resolution of ambiguities in the contract until late in the procurement process, when the insurance rents are at a maximum.Originality/valueThis study contributes to the current literature by highlighting an existing problem in the procurement process and describing it using decision theory under ambiguity in a game-like setting. Specifically, the authors use game theory in a unique way to deal with imperfect information coupled with ambiguity.

Engaging Community and Spatial Humanities for Postindustrial Heritage: The Keweenaw Time Traveler

Engaging Community and Spatial Humanities for Postindustrial Heritage:The Keweenaw Time Traveler Sarah Fayen Scarlett (bio), Don Lafreniere (bio), Daniel J. Trepal (bio), John D. M. Arnold (bio), and Robert Pastel (bio) The Keweenaw Time Traveler www.keweenawhistory.com The Keweenaw Time Traveler is an interactive, online historical atlas that creates a comprehensive spatial representation of the social and built environments of one of the country's first and largest extractive landscapes. Launched to the public in the summer of 2017, it combines deep mapping with digital public humanities to create a mutually beneficial online tool for researchers and community stakeholders alike. On Michigan's southern shore of Lake Superior, the Keweenaw Peninsula has an abundant built heritage that includes abandoned mine shaft buildings, former company towns, and ethnic community halls. Such sites recall the region's copper mining industry, active between 1860 and 1950, and demonstrate to tourists and residents alike the need to address the social and environmental impacts of deindustrialization. Our interdisciplinary team of researchers at Michigan Technological University is building the Keweenaw Time Traveler to empower citizens, municipal officials, and tourists, as well as academic researchers, to gain and share knowledge about this region's changing built and social environments, and to help a postindustrial community leverage its own past toward a healthier, more prosperous future. The Keweenaw Time Traveler project combines approaches from the spatial humanities, public history, and American studies. It answers the call of scholars such as David Bodenhamer to leverage the power of geospatial technologies and information to investigate the contingent and discursive relationships between people through space and time that drive American studies scholarship today.1 The project builds on foundational work in digital spatial humanities and facilitates what Anne Kelly Knowles has called "inductive visualization," [End Page 619] which promotes the discovery and interpretation of new spatial relationships.2 These relationships, analyzed using GIS technologies and methods, can drive critical inquiry about immigration, technological change, ethnic and class identities, environmental degradation, and more.3 Moreover, the Keweenaw Time Traveler's community-engaged process of development promotes access, inclusivity, and empowerment for diverse heritage constituencies.4 Following Sheila Brennan's call for public humanities projects to foster grassroots collaboration, the Keweenaw Time Traveler's platform and in situ public programming encourage a reflexive discussion about the impacts of deindustrialization and about the opportunities that the rich heritage landscape offers visitors and residents alike.5 To integrate contemporary humanities research with community-engaged practice, this project uses the concept of deep mapping, which is defined by five core principles. The map must be flexible, inviting exploration; open to accepting new sources or data; user-centric, supporting different pathways or views; and immersive, evoking experiences. The final principle, path-traceable, or supporting spatial storytelling, will be the focus of later platform developments.6 To build a deep map, the foundation of the Keweenaw Time Traveler is hundreds of georeferenced and digitized historical maps whose individual buildings and landscape features are represented in a spatiotemporal geodata-base.7 The maps and data reveal details about the region's built environments including the location, size, construction material, ownership, occupants, and civic address of over 125,000 residential, commercial, civic, and industrial structures over seventy years. The back end of this deep map is a historical spatial data infrastructure that allows for the rapid geolocation and relational linking of historical records to facilitate longitudinal research.8 Researchers have just begun using the Keweenaw Time Traveler to investigate connections between the region's built environment and children's health, to explore the role of neighborhood development in changing social power, and to model how urban watersheds and the built environment change over time.9 Public participatory initiatives at the core of this deep map facilitate the co-production of knowledge and dialogue that are vital to our public humanities goals. Three "Citizen Historian" apps offer a game-like setting where users transcribe handwritten notations on maps, categorize buildings by use, and identify building materials by matching colors. These apps were developed using open design charrettes in the winter of 2017, and draw on research in crowd-sourced heritage projects and public participatory GIS practices.10 Users have...

A Comparison Between Two Methods for Teaching Forearm Defense in Volleyball and Determining the Transfer of Learning from an Instructional Setting to a Game-Like Setting

This study aims to make a comparison between two different methods (the Bottom-up method and the Top-down method) for teaching forearm defense in volleyball and determining the transfer of learning from an instructional setting to a game-like setting. The subjects of the study were (36) students at physical education faculty in the university of Jordan, with mean age of (20 ± 0.5) years, who were assigned in volleyball course (2) in the second semester 2015/2016. They were divided randomly into two groups: The Bottom-up method group (18) students, and the Top-down method group (18) students. Two different (4-weeks) programs were applied, three times per week for (50 minutes) by the same physical education teacher; the author of this study who is specialized in teaching volleyball, (12) lessons plans were prepared for each group in which the subjects learned the forearm defense skill and how to use this skill under game conditions. Two measurements were taken; both groups were measured at the beginning (pre-test) in order to establish that all students started at the same level of skill performance and under game-like conditions performance. After the completion of the teaching program, the final measurements were taken (post-test) to note the different impact between the two methods of teaching on the subject`s performance in forearm defense skill performance and game-like conditions. Statistical analysis by using the (SPSS) program was done, included T-test for mean at pre and post test for the two groups and T-test for mean at post test between the two groups. The results showed significant differences (p < 0.05) in post test between the two groups in favor of the Bottom-up method group in forearm defense skill performance in volleyball. Whereas, the results showed significant differences (p < 0.05) in post test between the two groups in favor of the Top-down method group in transfer performance to a game-like setting. The study concluded that it is important to use the combination of both methods; both methods have merit according to the stage of motor learning.

Beat the Machine

We present techniques for gathering data that expose errors of automatic predictive models. In certain common settings, traditional methods for evaluating predictive models tend to miss rare but important errors—most importantly, cases for which the model is confident of its prediction (but wrong). In this article, we present a system that, in a game-like setting, asks humans to identify cases that will cause the predictive model-based system to fail. Such techniques are valuable in discovering problematic cases that may not reveal themselves during the normal operation of the system and may include cases that are rare but catastrophic. We describe the design of the system, including design iterations that did not quite work. In particular, the system incentivizes humans to provide examples that are difficult for the model to handle by providing a reward proportional to the magnitude of the predictive model's error. The humans are asked to “Beat the Machine” and find cases where the automatic model (“the Machine”) is wrong. Experiments show that the humans using Beat the Machine identify more errors than do traditional techniques for discovering errors in predictive models, and, indeed, they identify many more errors where the machine is (wrongly) confident it is correct. Furthermore, those cases the humans identify seem to be not simply outliers, but coherent areas missed completely by the model. Beat the Machine identifies the “unknown unknowns.” Beat the Machine has been deployed at an industrial scale by several companies. The main impact has been that firms are changing their perspective on and practice of evaluating predictive models. “ There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don't know. But there are also unknown unknowns. There are things we don't know we don't know .” -- Donald Rumsfeld

Designing Perspectively Correct Multiplanar Displays

Displays remain flat and passive amidst the many changes in their fundamental technologies. One natural step ahead is to create displays that merge seamlessly in shape and appearance with one’s natural surroundings. In this paper, we present a system to design, render to, and build view-dependent multiplanar displays of arbitrary piecewise-planar shapes, built using polygonal facets. Our system provides high quality, interactive rendering of 3D environments to a head-tracked viewer on arbitrary multiplanar displays. We develop a novel rendering scheme that produces exact image and depth map at each facet, producing artifact-free images on and across facet boundaries. The system scales to a large number of display facets by rendering all facets in a single pass of rasterization. This is achieved using a parallel, perframe, view-dependent binning and prewarping of scene triangles. The display is driven using one or more target quilt images into which facet pixels are packed. Our method places no constraints on the scene or the display and allows for fully dynamic scenes to be rendered interactively at high resolutions. The steps of our system are implemented efficiently on commodity GPUs. We present a few prototype displays to establish the scalability of our system on different display shapes, form factors, and complexity: from a cube made out of LCD panels to spherical/cylindrical projected setups to arbitrary complex shapes in simulation. Performance of our system is demonstrated for both rendering quality and speed, for increasing scene and display facet sizes. A subjective user study is also presented to evaluate the user experience using a walk-around display compared to a flat panel for a game-like setting.