Search

There is an increasing interest and growing practice in Citizen Science (CS) that goes along with the usage of websites for communication as well as for capturing and processing data and materials. From an educational perspective, it is expected that by integrating information about CS in a formal educational setting, it will inspire teachers to create learning activities. This is an interesting case for using bots to automate the process of data extraction from online CS platforms to better understand its use in educational contexts. Although this information is publicly available, it has to follow GDPR rules. This paper aims to explain (1) how CS communicates and is promoted on websites, (2) how web scraping methods and anonymization techniques have been designed, developed and applied to collect information from online sources and (3) how these data could be used for educational purposes. After the analysis of 72 websites, some of the results obtained show that only 24.8% includes detailed information about the CS project and 48.61% includes information about educational purposes or materials. El interés y la práctica de la ciencia ciudadana (CC) ha aumentado en los últimos años. Esto ha derivado en el uso de páginas web como herramienta de comunicación, recolección o análisis datos o repositorio materiales y recursos. Desde una perspectiva educativa, se espera que al integrar información sobre proyectos de CC en un entorno educativo formal, se inspire a los maestros a crear actividades de aprendizaje. Este, es un caso interesante para usar bots que automaticen el proceso de extracción de datos de webs de CC que ayuden a comprender mejor su uso en contextos educativos. Aunque esta información está disponible públicamente, se deben seguir las reglas de la ley de protección de datos o GDPR. Este artículo tiene como objetivo explicar: 1) cómo la CC se comunica y promueve en los sitios web; 2) cómo se diseñan, desarrollan y aplican los métodos de web scraping y las técnicas de anonimización para recopilar información en línea; y 3) cómo se podrían usar estos datos con fines educativos. Tras el análisis de 72 webs algunos de los resultados son que solo el 24,8% incluye información detallada sobre el proyecto, y el 48,61% incluye información sobre propósitos o materiales educativos.

Over the past decade, Citizen Science (CS) has shown great potential to transform the power of the crowd into knowledge of societal value. Many projects and initiatives have produced high quality scientific results by mobilizing peoples' interest in science to volunteer for the public good. Few studies have attempted to map citizen science as a field, and assess its impact on science, society and ways to sustain its future practice. To better understand CS activities and characteristics, CS Track employs an analytics and analysis framework for monitoring the citizen science landscape. Within this framework, CS Track collates and processes information from project websites, platforms and social media and generates insights on key issues of concern to the CS community, such as participation patterns or impact on science learning. In this paper, we present the operationalization of the CS Track framework and its three-level analysis approach (micro-meso-macro) for applying analytics techniques to external data sources. We present three case studies investigating the CS landscape using these analytical levels and discuss the strengths and limitations of combining web-analytics with quantitative and qualitative research methods. This framework aims to complement existing methods for evaluating CS, address gaps in current observations of the citizen science landscape and integrate findings from multiple studies and methodologies. Through this work, CS Track intends to contribute to the creation of a measurement and evaluation scheme for CS and improve our understanding about the potential of analytics for the evaluation of CS.

Social media have become an integral part of our lives, expanding our interlinking capabilities to new levels. There is plenty to be said about their positive effects. On the other hand, however, some serious negative implications of social media have been repeatedly highlighted in recent years, pointing at various threats to society and its more vulnerable members, such as teenagers. We thus propose a theoretical framework based on an adaptive "Social Media Virtual Companion" for educating and supporting an entire community, teenage students, to interact in social media environments in order to achieve desirable conditions, defined in terms of a community-specific and participatory designed measure of Collective Well-Being (CWB). This Companion combines automatic processing with expert intervention and guidance. The virtual Companion will be powered by a Recommender System (CWB-RS) that will optimize a CWB metric instead of engagement or platform profit, which currently largely drives recommender systems thereby disregarding any societal collateral effect.We put an emphasis on experts and educators in the educationally managed social media community of the Companion. They play five key roles: (a) use the Companion in classroom-based educational activities; (b) guide the definition of the CWB; (c) provide a hierarchical structure of learning strategies, objectives and activities that will support and contain the adaptive sequencing algorithms of the CWB-RS based on hierarchical reinforcement learning; (d) act as moderators of direct conflicts between the members of the community; and, finally, (e) monitor and address ethical and educational issues that are beyond the intelligent agent's competence and control. Preliminary results on the performance of the Companion's components and studies of the educational and psychological underlying principles are presented.

Learning to program is an important subject for students of Computer Science. Mentoring these students is a time-consuming and complex task. In this paper, we present a learning and tutoring environment that integrates task/solution delivery, assessment support and tutor's annotations, by extending Eclipse to a "Real World Integrated Development Environment". We will present a distributed system that uses Tuple Space architecture to integrate Eclipse with an evaluation module and a hand-writing annotation feature.

This paper describes the rationale behind a workshop on using data-intensive computational methods of analysis for empirical-analytical studies of collaborative and networked learning, with a particular focus on how learning takes place in the technically-mediated interplay between individual, small group and collective levels of agency. This workshop is primarily designed for researchers interested in empirical-analytical studies using data-intensive computational methods of analysis (including social-network analysis, log-file analysis, data mining, video analysis) usc Refereed/Peer-reviewed

It is still very common that students become disengaged or bored during the learning process by using intelligent educational systems. On the other hand, there is a growing interest in gamification as well as its applications and implications in the field of Artificial Intelligence in Education since it provides an alternative to engage and motivate students, and thereby help students to reach flow state during the learning process. The term Gamification originated in the digital media industry, however, such a term only gained widespread acceptance after late 2010. Since then most of the research on gamification in educational systems was about conceptualization, modelling and impact of use. The goal of this workshop is to provide participants the opportunity to: (i) present and discuss the empirical studies of gamification in Intelligent Educational Systems; (ii) discuss and promote innovative initiatives in educational settings with the use of gamification; and iii) motivate and solidify the research on gamification of intelligent educational systems in order to leverage the development of such systems.

This paper describes experimentations in the introduction of Computational Thinking in Denmark. An example being the new mandatory information technology course Informatik in the Danish high school system, which aims to strengthen digital literacy. Furthermore, we also describe how Computational Thinking is being taught in volunteer organizations. Given the need for recognizing typical patterns in the deployment and adaptation of Computational Thinking in national contexts, the author is currently engaged in a PhD project aiming at compiling a collection of best practices to teach programming, from Asia and Scandinavia.