8 research outputs found

    Empathy levels of American and Bahamian Special Education graduate students and students in other majors

    Get PDF
    This study investigated the empathy of Special Education graduate students in the USA and the Bahamas, and of Counseling and Organizational Learning students. About 180 students were administered the Interpersonal Reactivity Index to assess: fantasy, perspective taking, empathetic concern, and personal distress. Significant differences existed by major and country

    Educational Scaffolding for Students Stuck in a Virtual World

    Get PDF
    Virtual worlds provide students with educational opportunities to explore and have experiences that are difficult to provide in reality. However, ensuring that students stay motivated and on task is important if the learning goals are to be achieved. Building on the findings of previous studies involving agent-based virtual worlds, adaptive collaborative learning and intelligent agents, we have designed an empathic intelligent virtual agent that provides educational scaffolding to encourage and support the students to understand what they are learning with less frustration. We have identified models of โ€˜stuckโ€™ behaviour and corresponding empathic response patterns that we have incorporated into the behaviours of the intelligent virtual agents in the XXX Virtual World for science inquiry

    โ€œI can feel it too!โ€: Emergent empathic reactions between synthetic characters

    No full text

    How to Design More Empathetic Recommender Systems in Social Media

    Get PDF
    Social mediaโ€™s value proposition heavily relies on recommender systems suggesting products to buy, events to attend, or people to connect with. These systems currently prioritize user engagement and social media providersโ€™ profit generation over individual usersโ€™ well-being. However, making these systems more โ€œempatheticโ€ would benefit social media providers and content creators as users would use social media more often, longer, and increasingly recommend it to other users. By way of a design science research approach, including twelve interviews with system designers, social media experts, psychologists, and users, we develop user-centric design knowledge on making recommender systems in social media more โ€œempathetic.โ€ This design knowledge comprises a conceptual framework, four meta-requirements, and six design principles. It contributes to the research streams โ€œdigital responsibilityโ€ and โ€œIS for resilienceโ€ and provides practical guidance in developing socially responsible recommender systems as next-generation social media services

    The role of need for cognitive closure and emotions in shaping the human social interactions and driving the intergroup decision behaviour

    Get PDF
    In this thesis author investigates the role of need for closure (NCC) and emotions in shaping intergroup relations. The thesis consists of two separate parts that correspond with three studies. In the first part (Study1c with preliminary Studies 1 a and b) author assumes that level of NCC is associated with the acceptance or rejection of the offers from outgroup proposers who differ in perceived similarity to the ingroup. Specifically, the author expects that high NCC individuals will more frequently reject offers from the outgroups than low NCC individuals, and it will be especially true for dissimilar and Disgust/Anger/Fear-eliciting outgroups. The results confirmed hypotheses. In the second part (Study 2) author tests the role of NCC in bargaining behaviour in the ingroup-outgroup context using fMRI method expecting different neural activation among high and low NCC individuals while playing in Ultimatum Game. The author found cerebellar activation in conflicting situations (i.e., offer 4:6 by Outgroup proposers; offer 1:9 by Ingroup proposers, and offer 4:6 by Ingroup proposers) among high NCC (vs. low NCC) individuals. In part three (Study 3) author tests a group-effect on emotional contagion, hypothesized that being emotionally contaminated by a facial expression could interfere with a mere cognitive task in terms of accuracy and Reaction Times (RTs). The results didnโ€™t confirm it

    ์ž๋™์ฐจ ์‚ฌ์–‘ ๋ณ€๊ฒฝ์„ ์‹ค์‹œ๊ฐ„ ๋ฐ˜์˜ํ•˜๋Š” ๋ฐ์ดํ„ฐ ๊ธฐ๋ฐ˜ ๋””์ž์ธ ์ ‘๊ทผ ๋ฐฉ๋ฒ•

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์œตํ•ฉ๊ณผํ•™๋ถ€(์ง€๋Šฅํ˜•์œตํ•ฉ์‹œ์Šคํ…œ์ „๊ณต), 2020. 8. ๊ณฝ๋…ธ์ค€.The automotive industry is entering a new phase in response to changes in the external environment through the expansion of eco-friendly electric/hydrogen vehicles and the simplification of modules during the manufacturing process. However, in the existing automotive industry, conflicts between structured production guidelines and various stake-holders, who are aligned with periodic production plans, can be problematic. For example, if there is a sudden need to change either production parts or situation-specific designs, it is often difficult for designers to reflect those requirements within the preexisting guidelines. Automotive design includes comprehensive processes that represent the philosophy and ideology of a vehicle, and seeks to derive maximum value from the vehicle specifications. In this study, a system that displays information on parts/module components necessary for real-time design was proposed. Designers will be able to use this system in automotive design processes, based on data from various sources. By applying the system, three channels of information provision were established. These channels will aid in the replacement of specific component parts if an unexpected external problem occurs during the design process, and will help in understanding and using the components in advance. The first approach is to visualize real-time data aggregation in automobile factories using Google Analytics, and to reflect these in self-growing characters to be provided to designers. Through this, it is possible to check production and quality status data in real time without the use of complicated labor resources such as command centers. The second approach is to configure the data flow to be able to recognize and analyze the surrounding situation. This is done by applying the vehicles camera to the CCTV in the inventory and distribution center, as well as the direction inside the vehicle. Therefore, it is possible to identify and record the parts resources and real-time delivery status from the internal camera function without hesitation from existing stakeholders. The final approach is to supply real-time databases of vehicle parts at the site of an accident for on-site repair, using a public API and sensor-based IoT. This allows the designer to obtain information on the behavior of parts to be replaced after accidents involving light contact, so that it can be reflected in the design of the vehicle. The advantage of using these three information channels is that designers can accurately understand and reflect the modules and components that are brought in during the automotive design process. In order to easily compose the interface for the purpose of providing information, the information coming from the three channels is displayed in their respective, case-specific color in the CAD software that designers use in the automobile development process. Its eye tracking usability evaluation makes it easy for business designers to use as well. The improved evaluation process including usability test is also included in this study. The impact of the research is both dashboard application and CAD system as well as data systems from case studies are currently reflected to the design ecosystem of the motors group.์ž๋™์ฐจ ์‚ฐ์—…์€ ์นœํ™˜๊ฒฝ ์ „๊ธฐ/์ˆ˜์†Œ ์ž๋™์ฐจ์˜ ํ™•๋Œ€์™€ ์ œ์กฐ ๊ณต์ •์—์„œ์˜ ๋ชจ๋“ˆ ๋‹จ์ˆœํ™”๋ฅผ ํ†ตํ•ด์„œ ์™ธ๋ถ€ ํ™˜๊ฒฝ์˜ ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ์ƒˆ๋กœ์šด ๊ตญ๋ฉด์„ ๋งž์ดํ•˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ธฐ์กด์˜ ์ž๋™์ฐจ ์‚ฐ์—…์—์„œ ๊ตฌ์กฐํ™”๋œ ์ƒ์‚ฐ ๊ฐ€์ด๋“œ๋ผ์ธ๊ณผ ๊ธฐ๊ฐ„ ๋‹จ์œ„ ์ƒ์‚ฐ ๊ณ„ํš์— ๋งž์ถฐ์ง„ ์—ฌ๋Ÿฌ ์ดํ•ด๊ด€๊ณ„์ž๋“ค๊ณผ์˜ ๊ฐˆ๋“ฑ์€ ๋ณ€ํ™”์— ๋Œ€์‘ํ•˜๋Š” ๋ฐฉ์•ˆ์ด ๊ด€์„ฑ๊ณผ ๋ถ€๋”ชํžˆ๋Š” ๋ฌธ์ œ๋กœ ๋‚˜ํƒ€๋‚  ์ˆ˜ ์žˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ๊ฐ‘์ž‘์Šค๋Ÿฝ๊ฒŒ ์ƒ์‚ฐ์— ํ•„์š”ํ•œ ๋ถ€ํ’ˆ์„ ๋ณ€๊ฒฝํ•ด์•ผ ํ•˜๊ฑฐ๋‚˜ ํŠน์ • ์ƒํ™ฉ์— ์ ์šฉ๋˜๋Š” ๋””์ž์ธ์„ ๋ณ€๊ฒฝํ•  ๊ฒฝ์šฐ, ์ฃผ์–ด์ง„ ๊ฐ€์ด๋“œ๋ผ์ธ์— ๋”ฐ๋ผ ๋””์ž์ด๋„ˆ๊ฐ€ ์ง์ ‘ ์˜๊ฒฌ์„ ๋ฐ˜์˜ํ•˜๊ธฐ ์–ด๋ ค์šด ๊ฒฝ์šฐ๊ฐ€ ๋งŽ๋‹ค. ์ž๋™์ฐจ ๋””์ž์ธ์€ ์ฐจ์ข…์˜ ์ฒ ํ•™๊ณผ ์ด๋…์„ ๋‚˜ํƒ€๋‚ด๊ณ  ํ•ด๋‹น ์ฐจ๋Ÿ‰์ œ์›์œผ๋กœ ์ตœ๋Œ€์˜ ๊ฐ€์น˜๋ฅผ ๋Œ์–ด๋‚ด๊ณ ์ž ํ•˜๋Š” ์ข…ํ•ฉ์ ์ธ ๊ณผ์ •์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์—ฌ๋Ÿฌ ์›์ฒœ์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์ž๋™์ฐจ ๋””์ž์ธ ๊ณผ์ •์—์„œ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ๋””์ž์ธ์— ํ•„์š”ํ•œ ๋ถ€ํ’ˆ/๋ชจ๋“ˆ ๊ตฌ์„ฑ์š”์†Œ๋“ค์— ๋Œ€ํ•œ ์ •๋ณด๋ฅผ ์‹ค์‹œ๊ฐ„์œผ๋กœ ํ‘œ์‹œํ•ด์ฃผ๋Š” ์‹œ์Šคํ…œ์„ ๊ณ ์•ˆํ•˜์˜€๋‹ค. ์ด๋ฅผ ์ ์šฉํ•˜์—ฌ ์ž๋™์ฐจ ๋””์ž์ธ ๊ณผ์ •์—์„œ ์˜ˆ์ƒ ๋ชปํ•œ ์™ธ๋ถ€ ๋ฌธ์ œ๊ฐ€ ๋ฐœ์ƒํ–ˆ์„ ๋•Œ ์„ ํƒํ•  ๊ตฌ์„ฑ ๋ถ€ํ’ˆ์„ ๋Œ€์ฒดํ•˜๊ฑฐ๋‚˜ ์‚ฌ์ „์— ํ•ด๋‹น ๋ถ€ํ’ˆ์„ ์ดํ•ดํ•˜๊ณ  ๋””์ž์ธ์— ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ์„ธ ๊ฐ€์ง€ ์ •๋ณด ์ œ๊ณต ์ฑ„๋„์„ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ์ž๋™์ฐจ ๊ณต์žฅ ๋‚ด ์‹ค์‹œ๊ฐ„ ๋ฐ์ดํ„ฐ ์ง‘๊ณ„๋ฅผ Google Analytics๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์‹œ๊ฐํ™”ํ•˜๊ณ , ์ด๋ฅผ ๊ณต์žฅ ์ž์ฒด์˜ ์ž๊ฐ€ ์„ฑ์žฅ ์บ๋ฆญํ„ฐ์— ๋ฐ˜์˜ํ•˜์—ฌ ๋””์ž์ด๋„ˆ์—๊ฒŒ ์ œ๊ณตํ•˜๋Š” ๋ฐฉ์‹์ด๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์ข…ํ•ฉ์ƒํ™ฉ์‹ค ๋“ฑ์˜ ๋ณต์žกํ•œ ์ธ๋ ฅ ์ฒด๊ณ„ ์—†์ด๋„ ์ƒ์‚ฐ ๋ฐ ํ’ˆ์งˆ ํ˜„ํ™ฉ ๋ฐ์ดํ„ฐ๋ฅผ ์‹ค์‹œ๊ฐ„์œผ๋กœ ํ™•์ธ ๊ฐ€๋Šฅํ•˜๋„๋ก ํ•˜์˜€๋‹ค. ๋‘ ๋ฒˆ์งธ๋Š” ์ฐจ๋Ÿ‰์šฉ ์ฃผ์ฐจ๋ณด์กฐ ์„ผ์„œ ์นด๋ฉ”๋ผ๋ฅผ ์ฐจ๋Ÿ‰ ๋ถ€์ฐฉ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ธ๋ฒคํ† ๋ฆฌ์™€ ๋ฌผ๋ฅ˜์„ผํ„ฐ์˜ CCTV์—๋„ ์ ์šฉํ•˜์—ฌ ์ฃผ๋ณ€์ƒํ™ฉ์„ ์ธ์‹ํ•˜๊ณ  ๋ถ„์„ํ•  ์ˆ˜ ์žˆ๋„๋ก ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ์ฐจ๋Ÿ‰์˜ ์กฐ๋ฆฝ ์ƒ์‚ฐ ๋‹จ๊ณ„์—์„œ ๋ถ€ํ’ˆ ๋‹จ์œ„์˜ ์ด๋™, ์šด์†ก, ์ถœํ•˜๋ฅผ ๊ฑฐ์ณ ์™„์„ฑ์ฐจ์˜ ์ฃผํ–‰ ๋‹จ๊ณ„์— ์ด๋ฅด๊ธฐ๊นŒ์ง€ ๋ฐ์ดํ„ฐ ํ๋ฆ„์„ ํŒŒ์•…ํ•˜๋Š” ๊ฒƒ์ด ๋””์ž์ธ ๋ถ€๋ฌธ์— ํ•„์š”ํ•œ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ๋ฒ•์œผ๋กœ ํ™œ์šฉ๋˜์—ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๊ธฐ์กด ์ดํ•ด๊ด€๊ณ„์ž๋“ค์˜ ํฐ ๋ฐ˜๋ฐœ ์—†์ด ๋‚ด๋ถ€์˜ ์นด๋ฉ”๋ผ ๊ธฐ๋Šฅ์œผ๋กœ๋ถ€ํ„ฐ ๋ถ€ํ’ˆ ๋ฆฌ์†Œ์Šค์™€ ์šด์†ก ์ƒํƒœ๋ฅผ ์‹ค์‹œ๊ฐ„ ํŒŒ์•… ๋ฐ ๊ธฐ๋ก ๊ฐ€๋Šฅํ•˜๋„๋ก ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๊ณต๊ณต API์™€ ์„ผ์„œ ๊ธฐ๋ฐ˜์˜ ์‚ฌ๋ฌผ์ธํ„ฐ๋„ท์„ ํ™œ์šฉํ•ด์„œ ๋„๋กœ ์œ„ ์ฐจ๋Ÿ‰ ์‚ฌ๊ณ ๊ฐ€ ๋ฐœ์ƒํ•œ ์œ„์น˜์—์„œ์˜ ํ˜„์žฅ ์ˆ˜๋ฆฌ๋ฅผ ์œ„ํ•œ ์ฐจ๋Ÿ‰ ๋ถ€ํ’ˆ ์ฆ‰์‹œ ์ˆ˜๊ธ‰ ๋ฐ ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šคํ™” ๋ฐฉ๋ฒ•๋„ ๊ฐœ๋ฐœ ๋˜์—ˆ๋‹ค. ์ด๋Š” ๋””์ž์ด๋„ˆ๋กœ ํ•˜์—ฌ๊ธˆ ๊ฐ€๋ฒผ์šด ์ ‘์ด‰ ์‚ฌ๊ณ ์—์„œ์˜ ๋ถ€ํ’ˆ ๊ต์ฒด ํ–‰ํƒœ์— ๋Œ€ํ•œ ์ •๋ณด๋ฅผ ์–ป๊ฒŒ ํ•˜์—ฌ ์ฐจ๋Ÿ‰์˜ ๋””์ž์ธ์— ๋ฐ˜์˜ ๊ฐ€๋Šฅํ•˜๋„๋ก ํ•˜์˜€๋‹ค. ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ด ์„ธ ๊ฐ€์ง€ ์ •๋ณด ์ œ๊ณต ์ฑ„๋„์„ ํ™œ์šฉํ•  ๊ฒฝ์šฐ, ์ž๋™์ฐจ ๋””์ž์ธ ๊ณผ์ •์—์„œ ๋ถˆ๋Ÿฌ๋“ค์—ฌ์˜ค๋Š” ๋ถ€ํ’ˆ ๋ฐ ๋ชจ๋“ˆ์˜ ๊ตฌ์„ฑ ์š”์†Œ๋“ค์„ ๋””์ž์ด๋„ˆ๊ฐ€ ์ •ํ™•ํžˆ ์•Œ๊ณ  ๋ฐ˜์˜ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์žฅ์ ์ด ๋ถ€๊ฐ๋˜์—ˆ๋‹ค. ์ •๋ณด ์ œ๊ณต์˜ ์ธํ„ฐํŽ˜์ด์Šค๋ฅผ ์‰ฝ๊ฒŒ ๊ตฌ์„ฑํ•˜๊ธฐ ์œ„ํ•ด์„œ, ์‹ค์ œ๋กœ ๋””์ž์ด๋„ˆ๋“ค์ด ์ž๋™์ฐจ ๊ฐœ๋ฐœ ๊ณผ์ •์—์„œ ๋””์ž์ธ ํ”„๋กœ์„ธ์Šค ์ƒ์—์„œ ํ™œ์šฉํ•˜๋Š” CAD software์— ์„ธ ๊ฐ€์ง€ ์ฑ„๋„๋“ค๋กœ๋ถ€ํ„ฐ ๋“ค์–ด์˜ค๋Š” ์ •๋ณด๋ฅผ ์‚ฌ๋ก€๋ณ„ ์ปฌ๋Ÿฌ๋กœ ํ‘œ์‹œํ•˜๊ณ , ์ด๋ฅผ ์‹œ์„ ์ถ”์  ์‚ฌ์šฉ์„ฑ ํ‰๊ฐ€๋ฅผ ํ†ตํ•ด ํ˜„์—… ๋””์ž์ด๋„ˆ๋“ค์ด ์‚ฌ์šฉํ•˜๊ธฐ ์‰ฝ๊ฒŒ ๊ฐœ์„ ํ•œ ๊ณผ์ •๋„ ๋ณธ ์—ฐ๊ตฌ์— ํฌํ•จ์‹œ์ผœ ์„ค๋ช…ํ•˜์˜€๋‹ค.1 Introduction 1 1.1 Research Background 1 1.2 Objective and Scope 2 1.3 Environmental Changes 3 1.4 Research Method 3 1.4.1 Causal Inference with Graphical Model 3 1.4.2 Design Thinking Methodology with Co-Evolution 4 1.4.3 Required Resources 4 1.5 Research Flow 4 2 Data-driven Design 7 2.1 Big Data and Data Management 6 2.1.1 Artificial Intelligence and Data Economy 6 2.1.2 API (Application Programming Interface) 7 2.1.3 AI driven Data Management for Designer 7 2.2 Datatype from Automotive Industry 8 2.2.1 Data-driven Management in Automotive Industry 8 2.2.2 Automotive Parts Case Studies 8 2.2.3 Parameter for Generative Design 9 2.3 Examples of Data-driven Design 9 2.3.1 Responsive-reactive 9 2.3.2 Dynamic Document Design 9 2.3.3 Insignts from Data-driven Design 10 3 Benchmark of Data-driven Automotive Design 12 3.1 Method of Global Benchmarking 11 3.2 Automotive Design 11 3.2.1 HMI Design and UI/UX 11 3.2.2 Hardware Design 12 3.2.3 Software Design 12 3.2.4 Convergence Design Process Model 13 3.3 Component Design Management 14 4 Vehicle Specification Design in Mobility Industry 16 4.1 Definition of Vehicle Specification 16 4.2 Field Study 17 4.3 Hypothesis 18 5 Three Preliminary Practical Case Studies for Vehicle Specification to Datadriven 21 5.1 Production Level 31 5.1.1 Background and Input 31 5.1.2 Data Process from Inventory to Designer 41 5.1.3 Output to Designer 51 5.2 Delivery Level 61 5.2.1 Background and Input 61 5.2.2 Data Process from Inventory to Designer 71 5.2.3 Output to Designer 81 5.3 Consumer Level 91 5.3.1 Background and Input 91 5.3.2 Data Process from Inventory to Designer 101 5.3.3 Output to Designer 111 6 Two Applications for Vehicle Designer 86 6.1 Real-time Dashboard DB for Decision Making 123 6.1.1 Searchable Infographic as a Designer's Tool 123 6.1.2 Scope and Method 123 6.1.3 Implementation 123 6.1.4 Result 124 6.1.5 Evaluation 124 6.1.6 Summary 124 6.2 Application to CAD for vehicle designer 124 6.2.1 CAD as a Designer's Tool 124 6.2.2 Scope and Method 125 6.2.3 Implementation and the Display of the CAD Software 125 6.2.4 Result 125 6.2.5 Evaluation: Usability Test with Eyetracking 126 6.2.6 Summary 128 7 Conclusion 96 7.1 Summary of Case Studies and Application Release 129 7.2 Impact of the Research 130 7.3 Further Study 131Docto

    Quantitative Framework For Social Cultural Interactions

    Get PDF
    For an autonomous robot or software agent to participate in the social life of humans, it must have a way to perform a calculus of social behavior. Such a calculus must have explanatory power (it must provide a coherent theory for why the humans act the way they do), and predictive power (it must provide some plausible events from the predicted future actions of the humans). This dissertation describes a series of contributions that would allow agents observing or interacting with humans to perform a calculus of social behavior taking into account cultural conventions and socially acceptable behavior models. We discuss the formal components of the model: culture-sanctioned social metrics (CSSMs), concrete beliefs (CBs) and action impact functions. Through a detailed case study of a crooked seller who relies on the manipulation of public perception, we show that the model explains how the exploitation of social conventions allows the seller to finalize transactions, despite the fact that the clients know that they are being cheated. In a separate study, we show that how the crooked seller can find an optimal strategy with the use of reinforcement learning. We extend the CSSM model for modeling the propagation of public perception across multiple social interactions. We model the evolution of the public perception both over a single interaction and during a series of interactions over an extended period of time. An important aspect for modeling the public perception is its propagation - how the propagation is affected by the spatio-temporal context of the interaction and how does the short-term and long-term memory of humans affect the overall public perception. We validated the CSSM model through a user study in which participants cognizant with the modeled culture had to evaluate the impact on the social values. The scenarios used in the experiments modeled emotionally charged social situations in a cross-cultural setting and with the presence of a robot. The scenarios model conflicts of cross-cultural communication as well as ethical, social and financial choices. This study allowed us to study whether people sharing the same culture evaluate CSSMs at the same way (the inter-cultural uniformity conjecture). By presenting a wide range of possible metrics, the study also allowed us to determine whether any given metric can be considered a CSSM in a given culture or not

    Computer Game Innovation

    Get PDF
    Faculty of Technical Physics, Information Technology and Applied Mathematics. Institute of Information TechnologyWydziaล‚ Fizyki Technicznej, Informatyki i Matematyki Stosowanej. Instytut InformatykiThe "Computer Game Innovations" series is an international forum designed to enable the exchange of knowledge and expertise in the field of video game development. Comprising both academic research and industrial needs, the series aims at advancing innovative industry-academia collaboration. The monograph provides a unique set of articles presenting original research conducted in the leading academic centres which specialise in video games education. The goal of the publication is, among others, to enhance networking opportunities for industry and university representatives seeking to form R&D partnerships. This publication covers the key focus areas specified in the GAMEINN sectoral programme supported by the National Centre for Research and Development
    corecore