While Child–Computer Interaction (CCI) research frequently reports successful outcomes, challenges and failures in studies conducted in school context are rarely examined in detail. This paper addresses this gap through a collective reflection on when and how research with children in school contexts can be considered successful, and what challenges threaten such success. Based on decades of CCI experience from fifteen researchers across multiple countries, the study used a structured, multi-phase process informed by confessional research and child-centered ethics. The analysis identifies nine aspects of success across three areas (stakeholder experience, data generation, and children’s engagement) alongside fifteen recurring challenges organised into seven areas. We also map the relationships between successes and challenges, revealing ethically consequential tensions often overlooked in published accounts. The paper offers practical guidance, an analytical vocabulary, and a reflective method to foster more transparent and ethical CCI research in school settings.

This paper advances a collective research manifesto for Computational Empowerment (CE) in Child–Computer Interaction (CCI), grounded in diverse practices across global contexts. Drawing on five cases from Asia, Europe, and North America, we examine how CE commitments materialize in real world settings, revealing both their transformative potential and the tensions they introduce. Our cases illustrate that CE is inherently context dependent, socially situated, and shaped by surrounding structures. We identify key directions for extending CE: embedding critical and ethical perspectives, foregrounding situatedness and relationality, challenging convenient choices, and questioning design assumptions. This involves strengthening children’s agency in shaping computational systems and widening CE’s reach through more inclusive, sustainable practices. We offer this work as intentionally incomplete—an invitation to ongoing dialogue and collective action toward empowering children in computing.

Even the most comprehensive plans may go awry when working with children and in places such as schools, which results in unexpected challenges or sometimes failures. Yet, research publications seldom report on these failures and events, and meaningful second hand experiences are rarely shared beyond the project or research team, if at all. To break this cycle, we propose a half-day workshop at IDC 2026 for collectively reflecting on project experiences - from (un)fortunate events to failures, to learn and grow as a community. We invite researchers and practitioners, young and experienced, to bring their experiences and to collectively compile a list of lessons for the CCI community. This workshop builds on prior initiatives on learning from failures, with the goal of incorporating regular collective reflections as a practice at IDC.

Who gets to decide how generative AI tools enter students’ classrooms? We report on a five-week participatory design program in which three 11th-grade Latinx students and three high school teachers in California negotiated how generative AI tools would be used and taught about in learning environments. Drawing on video recordings and designed artifacts, we ask: what critical AI literacy practices emerged as students and teachers jointly designed how generative AI tools would be used and taught about? Our analysis reveals three practices: collectively unsettling assumptions about AI, mutual learning through complementary expertise, and grounding AI critique in cultural knowledge and creative practice. Students and teachers developed these practices through the design work itself. This case contributes strategies for designing with youth around an emergent technology like generative AI toward critical AI literacy. It extends work on youth as protagonists by showing how this approach enables students to shape both the adoption and the interrogation of these tools in their learning environments.

In this paper, we use the Child-Centred Ethics framework to critically reflect on the planning, implementation, and impact of twelve (2-4 year) projects with children (ages 2-18 years) in Finland, the UK, India, Japan, and the USA. Our analysis reveals diverse ethical challenges and experiences: adapting materials based on the abilities, interests and agendas of the children, teachers, and schools, considering consent and assent as continuous processes, and exploring impacts beyond the project duration. We also discuss handling data ownership among participants and international collaborators, and managing difficult situations that arise, such as, participants pushing the boundaries of technology and people, technical breakdowns, and in situ negotiations of roles among teachers and researchers. We use our analysis to extend the CCE Framework in two distinct ways; incorporating adult stakeholders and impacts beyond a projects’ lifecycle. Our work contributes to research on ethics in Child-Computer Interaction (CCI) research, addressing how to plan, implement, and create an impact in CCI projects with children.

Data-driven systems play a significant role in shaping children's experiences, as they interact with data-centric technologies daily through various platforms, including social media.Recent studies have highlighted children's perspectives on these technologies, offering insights into their awareness, concerns, and interactions with data-driven systems.This empirical study positions children as coresearchers, employing participatory and speculative approaches to collaboratively explore the futures of data-driven systems, with a particular focus on social media.Methodologically, we build on nexus analysis to bring understanding on children's ability to articulate concerns on data-centric technologies and imagine alternatives in ways that reflect their needs, aspirations, and social realities.Our findings showcase children's primary concerns about data-centric technologies and illuminate various expressions of agency identified in their speculative fictions.Consequently, we call for the promotion of critical data literacy to foster children's agency within data-driven systems.

As generative AI becomes increasingly integrated into children's creative lives, designing responsible and meaningful tools for Child-AI co-creation is a growing concern in HCI and education.This paper presents a scoping review of 20 studies on Child-AI co-creation, analyzing the types of creative activities involved, the age groups studied, and the roles AI systems play.Based on this synthesis, we identify six key design considerations: protecting child data privacy, minimizing bias and hallucinations, fostering appropriate reliance on AI, balancing support and creative freedom, encouraging peer and family collaboration, and making AI's creative process understandable.This work contributes an initial framework to guide the design of child-centered and developmentally appropriate AI co-creation systems, and highlights directions for future research.

The integration of AI technologies in all domains of life raises ethical debates. Children and young people are not exempt from these discussions since AI is also an increasing part of their lives. This study explores teenagers’ (aged 13 to 16 years) views on AI with a focus on ethical thinking. This is a retrospective empirical study in which data from three cases involving young people in technology learning activities have been analysed to answer the following research questions: (i) What ethical challenges around AI do young people reflect upon and (ii) what ethical dimensions do these reflections connect to? We have adapted an existing framework outlining dimensions of ethical thinking to identify young people’s ethical reflections on AI in various learning activities. Our findings show how young people reflect on AI ethics, even without dedicated teaching on it and are able to consider various dimensions and make connections to everyday uses of AI raising ethical issues. Based on our findings, we advocate for an integrated approach of AI and ethics in learning activities about technology. We believe the framework presented in this study can be a valuable tool to inform further research and practice.

The use of learning analytics is entering in the field of research in education as a promising way to support learning. However, in many cases data are not transparent for the learner. In this regard, Educational institutions shouldn’t escape the need of making transparent for the learners how their personal data is being tracked and used in order to build inferences, as well as how its use is going to affect in their learning. In this contribution, we sustain that learning analytics offers opportunities to the students to reflect about learning and develop metacognitive skills. Student-centered analytics are highlighted as a useful approach for reframing learning analytics as a tool for supporting self-directed and self-regulated learning. The article also provides insights about the design of learning analytics and examples of experiences that challenge traditional implementations of learning analytics.