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Paper

Digital Games in Non-formal and Informal Learning Practices for Science Learning: a Case Study

Iro Voulgari and Georgios N. Yannakakis (2019) Proceedings of the 8th International Conference, GALA 2019, Athens, Greece, November 27–29, 2019 Download in PDF format

Abstract

This paper examines non-formal and informal learning practices for science learning. Through a case study and an exploratory, qualitative approach we identify aspects involved such as the content, the goals, the pedagogical approaches, the settings, the role of fun and playfulness, challenges, and the role of the practitioner. Data was collected through interviews and a survey. Despite the diversity in the format, settings, structure, and target group of the practices examined in this study, there seems to be a convergence in certain themes such as the objectives of the practices, the pedagogical approaches involved, and the importance of fun. These aspects are linked with the design and implementation of digital games in the context of informal and non-formal science learning. Further issues emerged from the analysis such as gender representation, resources required for efficient implementation of practices, and the role of the parents. Strength-ening the links between formal and informal or non-formal science learning practices could ben-efit not only formal education but access of students to and effectiveness of non-formal and in-formal practices as well.
Paper

Measuring Fun with Adolescents: Introducing the Spanish and Dutch Adaptation of the FunQ

Tisza, G., Gollerizo, A. & Markopoulos, P. (2019) CHI PLAY EA'19, October 22-25, 2019, Barcelona, Spain

Abstract

It is increasingly understood how fun is an essential aspect in interaction for children in or beyond game play, as well as supporting learning and other activities involving children, e.g., for participatory design. While it is often proclaimed that such activities are fun for children participants, empirical evidence is hard to come by as measuring fun is not straightforward. Currently available assessment tools suitable for adolescents are scarce. FunQ is a recently developed measurement tool specifically designed for adolescents for the assessment of the experienced fun. Here we discuss ongoing work for adapting FunQ - to Spanish and Dutch. We report on the process followed to adapt the questionnaire; the reliability measures based on the initial results (ωoverall-SP= 0.876 and ωpartial-SP= 0.859; ωoverall-NL= 0.819 and ωpartial-NL= 0.804); and discuss our findings in reflection of the current state of the adaptation procedure.
Paper

Exploring children’s learning experience in constructionism-based coding activities through design-based research

Sofia Papavlasopoulou, Michail Giannakos, Maria Letizia Jaccheri (2019) Computers in Human Behavior, Volume 99, 2019, Pages 415-427

Abstract

Over the last few years, the integration of coding activities for children in K-12 education has flourished. In addition, novel technological tools and programming environments have offered new opportunities and increased the need to design effective learning experiences. This paper presents a design-based research (DBR) approach conducted over two years, based on constructionism-based coding experiences for children, following the four stages of DBR. Three iterations (cycles) were designed and examined in total, with participants aged 8–17 years old, using mixed methods. Over the two years, we conducted workshops in which students used a block-based programming environment (i.e., Scratch) and collaboratively created a socially meaningful artifact (i.e., a game). The study identifies nine design principles that can help us to achieve higher engagement during the coding activity. Moreover, positive attitudes and high motivation were found to result in the better management of cognitive load. Our contribution lies in the theoretical grounding of the results in constructionism and the emerging design principles. In this way, we provide both theoretical and practical evidence of the value of constructionism-based coding activities.
Paper

Coding games and robots to enhance computational thinking: How collaboration and engagement moderate children’s attitudes? International Journal of Child-Computer Interaction.

Kshitij Sharma, Sofia Papavlasopoulou, and Michail Giannakos. (2019) Coding games and robots to enhance computational thinking: How collaboration and engagement moderate children’s attitudes? International Journal of Child-Computer Interaction.

Abstract

Collaboration and engagement while coding are vital elements for children, yet very little is known about how children’s engagement and collaboration impact their attitudes toward coding activities. The goal of the study is to investigate how collaboration and engagement moderate children’s attitudes about coding activities. To do so, we designed a study with 44 children (between 8 and 17 years old) who participated in a full-day coding activity. We measured their engagement and collaboration during the activity by recording their gaze, and their attitudes in relation to their learning, enjoyment, team-work and intention by post-activity survey instruments. Our analysis shows that there is a significant moderating effect of collaboration and engagement on children’s attitudes. In other words, highly engaging and collaborative coding activities significantly moderate children’s attitudes. Our findings highlight the importance of designing highly collaborative and engaging coding activities for children and quantifies how those two elements moderate children’s attitudes.
Paper

The role of age and gender on implementing informal and non-formal science learning activities for children

Gabriella Tisza, Sofia Papavlasopoulou, Dimitra Christidou, Iro Voulgari, Netta Iivari, Michail N. Giannakos, Marianne Kinnula, and Panos Markopoulos. (2019) The role of age and gender on implementing informal and non-formal science learning activities for children. In Proceedings of the FabLearn Europe 2019 Conference (FabLearn Europe '19). ACM, New York, NY, USA, Article 10, 9 pages Download in PDF format

Abstract

There is a growing number of informal and non-formal learning activities worldwide related to STEM (Science, Technology, Engineering, Mathematics) subject areas -- particularly, those related to coding and making. To understand the general aim and content of such activities, we conducted a survey addressing highly experienced instructional designers and instructors of informal and non-formal science learning activities in nine European countries (N=128). The goal of this paper is to investigate the relation between (1) the targeted age-group and (2) the gender of the participants in these activities, and (3) the gender of the activity leader experts and (I) the content and (II) the main goal of the activity. The results show that the gender and age of the participants and the gender of the activity leader experts are associated with regards to the underlined content and the goal of the activity. We introduce the revealed patterns that describe typical goals and content in association with the participant's gender and age along with patterns between the activity leader experts' gender and the content and the main goal of the activity. We discuss the study findings in detail, their implications and their value for the informal and non-formal learning communities.
Paper

Joint Emotional State of Children and Perceived Collaborative Experience in Coding Activities.

Kshitij Sharma, Sofia Papavlasopoulou, and Michail Giannakos (2019) In Proceedings of the 18th ACM International Conference on Interaction Design and Children (IDC '19). ACM, New York, NY, USA, 133-145.

Abstract

This paper employs facial features to recognize emotions during a coding activity with 50 children. Extracting group-level emotional states via facial features, allows us to understand how emotions of a group affect collaboration. To do so, we captured joint emotional state using videos and collaborative experience using questionnaires, from collaborative coding sessions. We define groups' emotional state using a method inspired from dynamic systems, utilizing a measure called cross-recurrence. We also define a collaborative emotional profile using the different measurements from facial features of children. The results show that the emotional cross recurrence (coming from the videos) is positively related with the collaborative experience (coming from the surveys). We also show that the groups with better experience than the others showcase more positive and a consistent set of emotions during the coding activity. The results inform the design of an emotion-aware collaborative support system.
Paper

Activistas Científicos, una propuesta didáctica para trabajar los objetivos de desarrollo sostenible.

Gollerizo Fernández, A., y Luengo Pierrard, M. (2019) In Pérez-Aldeguer, S., & Akombo, D. (Eds.), Research, technology and best practices in Education. (pp. 112-122). Eindhoven, NL: Adaya Press Download in PDF format

Abstract

Explica la propuesta enmarcada en el proyecto europeo Horizonte 2020 COMnPLAY SCIENCE, del que Design for Change España es miembro.
Paper

Empowered to Make a Change: Guidelines for Empowering the Young Generation in and through Digital Technology Design

Marianne Kinnula and Netta Iivari (2019) In Proceedings of the FabLearn Europe 2019 Conference (FabLearn Europe '19). ACM, New York, NY, USA, Article 16, 8 pages. Download in PDF format

Abstract

This paper scrutinizes how children can be empowered to make a change through acquiring skills in digital technology design. We propose a framework that integrates theoretical understanding from literature on nexus analysis, values, and value as well as empowerment and genuine participation of children, and a related tool for educators and researchers advocating empowerment and inclusion. They should benefit from this tool when planning, analyzing, and evaluating their projects. We argue that the tool is useful beyond studies with children and can be used as a practical tool when planning and implementing digital technology design projects with any group of people and as a theoretical tool when studying such endeavors, especially when working with vulnerable or underserved participants.
Paper

Thinkpetizers: Small Mental Bites of Creative Thinking

Dimitris Grammenos (2019) In Proceedings of the FabLearn Europe 2019 Conference (FabLearn Europe '19). ACM, New York, NY, USA, Article 20, 3 pages Download in PDF format

Abstract

A fast-paced hands-on workshop introducing the concept and practice of Thinkpetizers. The workshop presents the underlying philosophy and a ‘recipe’ for successfully creating Thinkpetizers, along with how they used as building blocks for creating multi-hour workshops, sessions and events. The Thinkpetizers support the step that precedes (digital and analogue) fabrication, i.e., coming up with creative and innovative ideas. They can also be used for refreshing one’s mind and creative powers throughout the whole creation process. Furthermore, they can be used in a classroom setting as a means for triggering (creative) thinking and setting the mood for conducting any type of activity, but also as an engaging way for approaching any learning subject. The workshop is targeted to anyone interested in supporting creative thinking in a formal/non-formal/ informal learning environment. Participants will experience a design philosophy, as well as, a series of practical activities and will have a lot of FUN!.
Paper

Procedural Content Generation through Quality-Diversity

Daniele Gravina, Ahmed Khalifa, Antonios Liapis, Julian Togelius, Georgios N. Yannakakis (2019) Proceedings of the IEEE Conference on Games, 2019 Download in PDF format

Abstract

Quality-diversity (QD) algorithms search for a set of good solutions which cover a space as defined by behavior metrics. This simultaneous focus on quality and diversity with explicit metrics sets QD algorithms apart from standard single- and multi-objective evolutionary algorithms, as well as from diversity preservation approaches such as niching. These properties open up new avenues for artificial intelligence in games, in particular for procedural content generation. Creating multiple systematically varying solutions allows new approaches to creative human-AI interaction as well as adaptivity. In the last few years, a handful of applications of QD to procedural content generation and game playing have been proposed; we discuss these and propose challenges for future work.
Paper

Fusing Level and Ruleset Features for Multimodal Learning of Gameplay Outcomes

Antonios Liapis, Daniel Karavolos, Konstantinos Makantasis, Konstantinos Sfikas, Georgios N. Yannakakis (2019) Proceedings of the IEEE Conference on Games, 2019 Download in PDF format

Abstract

There is growing evidence suggesting that subjective values such as emotions are intrinsically relative and that an ordinal approach is beneficial to their annotation and analysis. Ordinal data processing yields more reliable, valid and general predictive models, and preference learning algorithms have shown a strong advantage in deriving computational models from such data. To enable the extensive use of ordinal data processing and preference learning, this paper introduces the Python Preference Learning Toolbox. The toolbox is open source, features popular preference learning algorithms and methods, and is designed to be accessible to a wide audience of researchers and practitioners. The toolbox is evaluated with regards to both the accuracy of its predictive models across two affective datasets and its usability via a user study. Our key findings suggest that the implemented algorithms yield accurate models of affect while its graphical user interface is suitable for both novice and experienced users.
Paper

From Pixels to Affect: A Study on Games and Player Experience

Elizabeth Camilleri, Georgios N. Yannakakis, David Melhart, Antonios Liapis (2019) Proceedings of the International Conference on Affective Computing and Intelligent Interaction, 2019 Download in PDF format

Abstract

There is growing evidence suggesting that subjective values such as emotions are intrinsically relative and that an ordinal approach is beneficial to their annotation and analysis. Ordinal data processing yields more reliable, valid and general predictive models, and preference learning algorithms have shown a strong advantage in deriving computational models from such data. To enable the extensive use of ordinal data processing and preference learning, this paper introduces the Python Preference Learning Toolbox. The toolbox is open source, features popular preference learning algorithms and methods, and is designed to be accessible to a wide audience of researchers and practitioners. The toolbox is evaluated with regards to both the accuracy of its predictive models across two affective datasets and its usability via a user study. Our key findings suggest that the implemented algorithms yield accurate models of affect while its graphical user interface is suitable for both novice and experienced users.
Paper

PAGAN: Video Affect Annotation Made Easy

David Melhart, Antonios Liapis, Georgios N. Yannakakis (2019) In Proceedings of the International Conference on Affective Computing and Intelligent Interaction, 2019 Download in PDF format

Abstract

How could we gather affect annotations in a rapid, unobtrusive, and accessible fashion? How could we still make sure that these annotations are reliable enough for data-hungry affect modelling methods? This paper addresses these questions by introducing PAGAN, an accessible, general-purpose, online platform for crowdsourcing affect labels in videos. The design of PAGAN overcomes the accessibility limitations of existing annotation tools, which often require advanced technical skills or even the on-site involvement of the researcher. Such limitations often yield affective corpora that are restricted in size, scope and use, as the applicability of modern data-demanding machine learning methods is rather limited. The description of PAGAN is accompanied by an exploratory study which compares the reliability of three continuous annotation tools currently supported by the platform. Our key results reveal higher inter-rater agreement when annotation traces are processed in a relative manner and collected via unbounded labelling.
Paper

A Multi-Faceted Surrogate Model for Search-based Procedural Content Generation

Daniel Karavolos, Antonios Liapis, Georgios N. Yannakakis (2019) IEEE Transactions on Games, 1–1 Download in PDF format

Abstract

This paper proposes a framework for the procedural generation of level and ruleset components of games via a surrogate model that assesses their quality and complementarity. The surrogate model combines level and ruleset elements as input and gameplay outcomes as output, thus constructing a mapping between three different facets of games. Using this model as a surrogate for expensive gameplay simulations, a search-based generator can adapt content towards a target gameplay outcome. Using a shooter game as the target domain, this paper explores how parameters of the players’ character classes can be mapped to both the level’s representation and the gameplay outcomes of balance and match duration. The surrogate model is built on a deep learning architecture, trained on a large corpus of randomly generated sets of levels, classes and simulations from gameplaying agents. Results show that a search-based generative approach can adapt character classes, levels, or both towards designerspecified targets. The model can thus act as a design assistant or be integrated in a mixed-initiative tool. Most importantly, the combination of three game facets into the model allows it to identify the synergies between levels, rules and gameplay and orchestrate the generation of the former two towards desired outcomes.