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This study explores what kinds of social media services children use in their everyday lives, how children describe their strategies for spotting fake news, and what kinds of fake news they report having encountered in their lived experiences. The article is based on an online questionnaire conducted in Finnish comprehensive schools with children and young people (N = 167) aged 12-15. The results show that children are active users of various social media services and that they accessed social media every day. Children perceived fake news as much more than fabricated news reports and weaved these reports together with ordinary lies, rumors, and false information shared in the form of links, videos, posts, messages, and stories. Children recognized that fake news can be produced and shared by anyone with various intentions, including financial and ideological gains, but also personal gains of digital capital, causing confusion, cheating, pranking, and bullying. Children provided examples of various kinds of myths, rumors, and false information spreading in their online communities. Notably, children typically described fake news in terms of its believability and intentions, but deeper-level evaluation strategies, such as the evaluation of the quality and consistency of evidence, were much less discussed. The results contribute to the body of literature by providing children's perspectives regarding the complex problem of fake news and signal the need to develop pedagogical approaches that help children to better understand the basic mechanisms of machine learning, including tracking and profiling, behavior/attention engineering, and psychometrics-based advertising.

Previous research on player profiles or types is based on players' in-game behaviors and their motivations to play games. However, there are many other activities related to digital games beyond playing the games properly. Using learning analytics methods, the study investigates the prevalence and interconnections between these different metagame activities and classifies gamers based on their use thereof into distinct profiles. The results show that digital game–related information-seeking activities are key metagame activities with connections to other metagame activities. Three distinct profiles of players were identified based on their metagame activities: versatile metagamers, strategizers, and casual metagamers. The results contribute to the existing literature on metagaming and provide insights for game studies, game design and marketing, and digital games and learning. [ABSTRACT FROM AUTHOR]

This study investigates the effects of optional difficulty settings, badges, points, and educational rewards on intrinsic motivation. We provide insights into how reward structures affect intrinsic motivation and in-game progression, tested in a bird-matching game where players match species with names. These findings are significant for designing educational games that effectively engage and motivate players. We created two versions of the game: one version with 'pointification' rewards (badges and points) and another with educational rewards (learning materials and bird sounds). The effect of voluntarily increasing the difficulty of the game is also investigated. In-game analytics of 66 sessions are examined. In addition, the players' Intrinsic Motivation Inventory (IMI) survey scores are calculated. Further statistical analyses (ttests, visualizations and other calculations) were performed using R software. The analyses indicate that 'pointification' and educational rewards show no statistically significant difference in either the in-game progression or IMI scores of players. The findings show that intrinsic motivation is unaffected by either points and badges or educational rewards. However, voluntarily increasing the difficulty is shown to increase the IMI scores of players. This study expands on the discussion of alternatives to 'pointification' and provides new insights on the optional difficulty systems in educational games. [ABSTRACT FROM AUTHOR]

While much has been written about the personal, social, and democratic benefits of networked communities and participatory learning, critics have begun to draw attention to the ubiquitous data collection and computational processes behind mass user platforms. Personal and behavioral data have become valuable material for statistical and machine learning techniques that have the potential to profile, infer, and predict people's needs, values, and behavior. As a response, researchers are calling for data literacies and computational thinking to facilitate people's capacity and volition to make informed actions in their digital world. Yet, efforts and curricula towards a greater understanding of computational mechanisms of new media ecology are sorely missing from K12-education as well as from teacher education. This paper provides an overview of tensions that teachers and educators will face when they attempt to bridge participatory learning with a more robust understanding of machine learning and algorithmic production of social and cultural practices.

This paper investigates the validity of ChatGPT as a tool to generate meaningful input for the serious game design process. Input is collected from game designers, students and teachers via surveys, individual interviews and group discussions inspired by a description of a simple educational drilling game and its context of use. In these mixed methods experiments ChatGPT 3.5 and 4.0 is prompted with the same description to validate findings with expert participants. In addition, the impact on the models' suggestions from integrating the expert's role (e.g., "Answer as if you were a teacher.", "game designer", or a "student") into the prompt is investigated. The findings show that ChatGPT can produce statistically similar input, depending on the group of experts. ChatGPT 3.5 outperforms 4.0 with the student input. The integration of expert's role in prompt is found to be unreliable, and necessary only with game designer input with the version 3.5 of ChatGPT. The practical implications are that multiple ChatGPT versions should be used when collecting input. In addition, it is shown that experts can provide unique insight to the development process. This research opens the discussion on the trustworthiness of ChatGPT generated input for serious game development. [ABSTRACT FROM AUTHOR]

The integration of artificial intelligence (AI) topics into K–12 school curricula is a relatively new but crucial challenge faced by education systems worldwide. Attempts to address this challenge are hindered by a serious lack of curriculum materials and tools to aid teachers in teaching AI. This article introduces the theoretical foundations and design principles for implementing co-design projects in AI education, empirically tested in 12 Finnish classrooms. The article describes a project where 4th- and 7th-graders (N = 213) explored the basics of AI by creating their own AI-driven applications. Additionally, a framework for distributed scaffolding is presented, aiming to foster children’s agency, understanding, creativity, and ethical awareness in the age of AI. [ABSTRACT FROM AUTHOR]

With growing concerns over children's data agencies, researchers have begun to draw attention to children's and young people's privacy practices in social media environments. However, little is known about the experiences of pre-service teachers who play a key role in educating future generations. This study aimed to address this gap by exploring Finnish pre-service teachers' conceptions and experiences of data agency in social media environments. Drawing from in-depth interviews of pre-service teachers (N = 14), the analysis revealed that pre-service teachers construct their data agency in terms of social frames and shared social norms, and they also recognize the lack of understanding regarding wider socio-technical systems within which data agencies are situated. This research argues that without a sophisticated understanding of algorithmic governance and commercial use of data, it is unlikely that these future teachers would be prepared to facilitate children's and youth's agentive actions in a data-driven society. [ABSTRACT FROM AUTHOR]

In addition to gaming, there are many other activities around digital games. These metagame activities have so far been studied from the perspective of single metagame phenomena and rarely from the perspective of the children who play digital games. This exploratory, qualitative study provides an overview of children's metagame activities. A total of 142 children's essays and lists of their metagame activities were analyzed using qualitative content analysis. The children's metagame activities included game-enabling activities, strategizing activities, discussing activities, information-seeking activities, creating and sharing activities, and consuming activities. The results contribute to the body of literature on metagaming and provide an overview of children's metagame activities around digital games, as well as new perspectives on digital games and learning. [ABSTRACT FROM AUTHOR]

Previous research on learning-related digital games has focused on studying learning outcomes with mostly adult participants. This study explores what children have experienced they have learned by playing digital games, how these learning experiences relate to 21st-century skills, and in which contexts do the children benefit from playing digital games. The data were collected from children's essays, which were analyzed using qualitative content analysis. Results reveal that children's learning experiences are often related to 21st-century core subjects and skills, but they also reported improved physical abilities and sports competences from digital games. Children felt that the skills they had gained were beneficial in the contexts of school, sports, and friendships. The results contribute to our understanding of digital games and children by providing children's perspective on digital games and learning. [ABSTRACT FROM AUTHOR]