BackgroundThis paper offers a retrospective analysis of three iterations of a Social Design-Based Experiment (SDBE) focused on refining a learning ecology for undergraduate men of color by centering their needs, experiences, identities, and interests through data-driven inquiry cycles.MethodsWe applied principles of SDBE to guide the re-design of the learning ecology and to analyze the change process retrospectively. The voices of men of color served as a central source of data, informing successive refinements to program structures and practices.FindingsThrough iterative inquiry cycles, we refined the program's design by re-mediating two categories of activity structures: (1) those shaping participants' relationships to institutional structures, and (2) those fostering relationships with themselves and other program participants. These changes aimed to make institutional navigation more relational and responsive while strengthening community-building and identity-centered practices that support belonging and agency.ContributionWe offer a model of how the principles of SDBE can guide the re-design of a learning ecology by centering the voices of men of color. By examining a multi-year, holistic initiative, we illustrate how iterative refinements to various activity structures can lead to the design of learning environments that are responsive to the communities that they serve.
BackgroundWhile children interact with AI applications, they are not often given opportunities to develop a sociotechnical understanding of machine learning systems. Research is needed to understand how children make sense of AI, including algorithmic bias. We draw on sociocultural perspectives to examine how two children, aged 10 and 11, used symbolic and material tools to critique issues of bias and create personally valuable machine learning designs.MethodsThe research design is a descriptive single case study with embedded units. After purposeful sampling of the data, we inductively coded interviews, discussions, and digital artifacts to examine how children understood machine learning concepts and critically engaged with algorithmic bias.FindingsFindings suggest using dialogue alongside model design helps children connect concepts to personal experiences and think critically about AI. Guided discussions deepened their understanding of algorithmic bias and its real-world impacts, fostering visions for more equitable technologies. However, both children developed their understanding in distinct ways.ContributionWe conclude that a sociocultural approach promoting open dialogic spaces, tool appropriation, and the personal creation of machine learning applications fosters children's understanding of sociotechnical machine learning concepts through multiple pathways, ultimately empowering them to emerge as thoughtful, responsible AI technology users and creators.
Background:The learning science has intensified its focus on the sociopolitical dimensions of learning, yet creating environments where learners can productively engage with uncomfortable truths regarding power and privilege remains a significant pedagogical challenge. While the field often draws on critical pedagogues like Paulo Freire, the humanistic, person-centered psychology of Carl Rogers has remained largely unacknowledged despite its potential to support these goals. Methods: This article proposes a conceptual dialogue between current sociopolitical perspectives in the learning sciences and Rogerian person-centered psychology. This paper synthesizes core tenets-unconditional positive regard, empathy, and congruence-and examines the here-and-now encounter group modality as a site for relational and sociopolitical learning. Findings: This article frames the two fields as intellectual cousins with synergistic toolkits. It argues that a person-centered approach provides how to critical pedagogy, offering a methodology to foster the psychological safety and vulnerability required for transformative dialogue. Contribution: This paper contributes a critically updated Rogerian framework that enriches the learning sciences pedagogical toolkit for social design. By integrating relational wisdom with structural analysis, it offers a path toward designing learning environments that are simultaneously safe, brave, and humane.
BackgroundWe report from a case study of an "oldtimer" and design study with prospective teachers as "newcomers" telling stories about models made with open large datasets (OLDs).MethodsUsing a "foraging and design" approach, we present a case study of Hans Rosling, a public health professor who developed a data repository and visualization tools (Gapminder). Drawing on sociolinguistic studies of storytelling, we analyzed Rosling's TED talks to describe how he structured data, models, and stories in performances. Using findings and materials from this case, we conducted a design study with prospective secondary mathematics and social studies teachers, who used Gapminder to develop their own storytelling performances. We analyzed the oldtimer's and newcomers' performances using similar methods.FindingsOur oldtimer and newcomers both invited epistemic, moral, and affective stances as they presented discoveries and challenged audiences' understandings. Their performances drew upon personal experiences, displayed forms of disciplined perception, and invited critical reflection on what to value in studying global development. Prospective teachers also critiqued Gapminder data and storytelling with OLDs as a trustworthy pedagogical activity.ContributionOur studies explicate how stories are told about models made with OLDs and how inviting personal relationships toward data can support critical data literacy.
BackgroundSituated in a design-based project, this empirical investigation of learning theory explores collaborative construction's educational potential via a case of four graduate students collaboratively building a body-scale icosahedron without a step-by-step assembly manual. Drawing on Learning Sciences perspectives on cognition and interaction, we aim to characterize how participants succeeded in building the structure and what geometric content they may have learned in the process.MethodWe microgenetically analyzed multimodal interaction in an exploratory activity, coordinating ecological dynamics (attentional anchors) with co-operative action (semiotic substrates; professional vision). We analyzed post-construction problem solving to trace shifts from embodied know-how to formal know-what.FindingsParticipants constructed the model through iterative cycles: detecting constraints; imagining attentional anchors; collaboratively negotiating discursive strategies for coordinating co-operative action; materially realizing goal structures that generated new unanticipated circumstances. Emergent perceptual forms were communicated multimodally, sedimenting individual know-how into the substrate-a curated archive of heterogeneous semiotic contributions that scaffolded the team's evolving professional vision.ContributionWe submit a networked synthesis comprising embodiment theories of perceptual learning and cognitive-anthropological models of joint action, theorizing how sensorimotor percepts become publicly shared knowledge through multimodal coordination. This integration models how attentional anchors emerge and stabilize within a semiotic substrate, thus bridging embodied know-how and discursive know-what in collective mathematical reasoning and construction. We speculate on the pedagogical utility of learning environments that simulate culturally-historically authentic mathematical semiosis as emerging in, for, and from collective practice of coordinated action.
BackgroundUnderstanding complex scientific phenomena, such as natural selection, requires engaging with emergent patterns and causal mechanisms, which are often misunderstood due to persistent misconceptions. Traditional instruction may not adequately support conceptual change in this domain.MethodsThis study explores the integration of the PAIR-C (Pattern, Agents, Interactions, Relations, and Causality) Framework with agent-based models (ABMs) to enhance conceptual understanding of natural selection. Fifty undergraduate students participated online and were randomly assigned to two groups. One group received instruction that follows the PAIR-C framework, while the other was taught using traditional Darwinian principles, both employing ABM scenarios. Assessments included pre-posttests, video recordings, surveys, and interviews, with misconceptions analyzed through epistemic network analysis (ENA).FindingsThe PAIR-C approach significantly improves students' deep understanding of natural selection, more effectively reducing misconceptions compared to the traditional method. Further, ENA revealed d88istinct characteristics of misconception between the groups, with the intervention group showing a more focused pattern compared to the control group. Video analysis also showed different types of interactions occurring during the PAIR-C modules.ContributionThis study demonstrates that the PAIR-C framework, when combined with ABMs, can foster deeper scientific understanding and conceptual change, with implications for broader application in complex systems education.
BackgroundIn a moment of escalating coloniality, carcerality and fascism, this commentary deliberately begins with a broader anti-colonial perspective of the central focus of this special issue-the application of strength-based approaches to assessment, particularly via cultural responsiveness, relevance and sustenance, as well as funds of knowledge.ContributionThis commentary seeks to bring into consideration how provincialist approaches to knowledge production have continued to frame our collective works within enclosed and decontextualized ways. Grounded in a broader anti-colonial tradition, I elucidate what can be learned from scholarship in this special issue, and ultimately argue that we need to go further in how we think about sustaining a world for our children and future generations.
Background: This study investigates how K-2 students' Funds of Knowledge (FoK) can inform the design of formative, asset-based assessments for computational thinking (CT). Traditional assessments often perpetuate deficit narratives, particularly for racially and ethnically minoritized students, overlooking the rich computational practices they already engage in at home and in their communities. Methods: Anchored in a design-based research approach, we engaged in three phases: (1) family interviews to surface FoK; (2) co-development of assessment tasks grounded in everyday practices; and (3) clinical interviews to evaluate students' CT engagement. Data analysis involved identifying FoK themes from transcripts, developing tasks through collaborative teacher-researcher design, and testing them for inclusivity, adaptability, and alignment with CT constructs. Findings: Our findings complicate dominant deficit narratives by revealing that (1) children from minoritized populations already engage in rich forms of CT in home and community contexts, and (2) assessment tasks grounded in students' lived experiences offer more asset-based insights into their learning potential in computer science contexts. Contribution: By centering FoK in CT assessment design, this work reimagines assessment as a culturally responsive, asset-based process that validates students' lived experiences while illuminating their computational competencies.
BackgroundTo improve and create more-equitable schools, education policies can support technical, normative, and political change. Educational leaders are consequential in policy design, as their sensemaking about educational issues shapes how teachers learn about and enact policy. This is important because policy implementation requires that individuals develop new skills, knowledge, and practices.MethodsIn this multicase study of two school districts, I analyzed interviews with school and district leaders, observations of policymaking, and policy artifacts to understand how educational leaders make sense of equity in their policymaking, especially for mathematics.FindingsDistrict leaders made sense of equity in mathematics mainly in terms of access and achievement, with technical changes in tools, routines, and roles constituting the primary policy response. At the same time, community politics, district organizational contexts, and meaning-making about mathematics constrained political change in the distribution of resources and status and in normative shifts around identity, culture, and belonging.ContributionMy findings reveal how sensemaking about the subject and equity interact, posing learning demands that policy design can address. This raises implications important for education leaders and learning scientists designing for equity in specific subjects." No apostrophe after scientists.
BackgroundAssessment has historically reinforced exclusion in science by positioning certain ways of knowing as legitimate and devaluing others. Rather than treating assessment as a neutral mechanism for measuring learning, we argue that it must be seen as a deeply cultural, relational, and creative dialogic process that can reproduce exclusion or open up new possibilities for participation.MethodsWe engaged in micro-ethnographic analysis of videos across two dance-based assessment activities, observing the multiple ways youth participants incorporated their creative and cultural resources, identities, languages, and ways of knowing into the development, expression, and assessment of physics ideas.FindingsUsing the lens of culturally sustaining formative assessment, we illustrate how assessment that draws on the cultural practices, ways of knowing, and identities of historically marginalized learners as resources can be leveraged to support physics sense-making. Our findings show how positioning youth as knowledgeable and centering their embodied and multimodal forms of expression as epistemic resources can support them in sharing their developing ideas, insights, and perspectives.ContributionThis paper offers a model of formative science assessment as an ongoing dialogic process for building understanding that is multimodal, embodied, and relational, rooted in cultural expression and collective sense-making.
Recent developments in the learning sciences and the design of STEM learning environments have co-occurred with an increasing focus on justice and equity for youth, particularly those who have been historically underrepresented. While advances have been made in curriculum and instruction to these ends, assessment has not caught up with this vision. In this Special Issue, we collectively ask how culturally sustaining approaches can inform assessment in and beyond school settings. Drawing on expansive views on learning, the papers in the special issue explore how we can re-envision assessments that sustain and revitalize multiple ways of knowing, talking and being centering humanity, ethics, and justice.
Background: A long-standing challenge in the learning sciences is how to visualize qualitative data, such as video and transcripts, in ways that illuminate the layered, relational, and dynamic nature of teaching and learning. Methods: This methodological article integrates methods of interaction analysis (IA) with recent developments in interactive and alternative visualization to expand the kinds and qualities of representations used to conceptualize teaching and learning. Findings: We introduce three open-source visualization tools we designed to support IA that offer different framings of video as qualitative data. Transcript Explorer frames video as playscript-like records, offering ways to dynamically explore transcripts of multimodal interaction linked to video. The Interaction Geography Slicer frames video through the lens of movement, providing an approach to dynamically visualize interaction over geographic space and time. The Pointillizer frames images in video to characterize material and affective dimensions of a scene. Contribution: We illustrate how these tools embody distinct epistemological commitments and foster new researcher-data-relationships that enliven the analysis and experience of teaching and learning. In doing so, we contribute to broader shifts in the methodological landscape of the learning sciences, with practical implications for fields such as teacher education and the use of artificial intelligence in educational research.
BackgroundMuch of learning sciences research focuses on the design of learning innovations. However, curricula developed by learning scientists are seldomly widely adopted. One reason is that scaling programs beyond local, carefully tended contexts is difficult and is often unsuccessful. This problem suggests a need for research aimed at understanding how learning innovations scale beyond initial implementations.MethodsWe take a distributed sensemaking approach to analyzing the micro-level processes through which actors make sense of and align themselves with new programs. We examine one learning innovation, FUSE Studios, an integrated suite of STEAM (science, technology, engineering, arts, and math) learning activities, which has spread from two afterschool implementations to over 250, primarily in-school implementations. We present an analysis of classroom video and interviews with students and teachers from 17 focal schools, including a detailed case analysis of one school.FindingsOur findings demonstrate how distributed sensemaking and adaptation among networks of humans and non-humans shaped local implementations and how, despite local adaptations, the program was able to maintain integrity of implementation, delivering similar experiences to students across contexts.ContributionThese findings improve our understanding of how learning innovations scale and demonstrate the value of a distributed sensemaking perspective on implementation processes.
BackgroundWe build on prior research suggesting the made-for-school, history-oriented videogame Mission US offers entry-level opportunities for students to practice "thinking like historians"-a phrase the game uses to indicate key historical reasoning and thinking skills.MethodsWe leverage quantitative ethnography (QE) and epistemic network analysis (ENA) to examine how these opportunities co-occur.FindingsWe find significant differences between two groups of game missions focusing on different historical time periods with different player characters. One group appears to focus more heavily on historical thinking and reasoning, while a second appears to constrain historical thinking and reasoning to a function of protagonists' marginalized identities. Further exploration of these differences revealed the game's developers appear to have designed an ideological game world that positions White avatars to more freely engage in historical thinking and reasoning practices, while Black, Brown, and Indigenous avatars are substantively constrained in doing so.ContributionThis study illustrates the power of QE and ENA to uncover hard-to-see aspects of the ideological worlds baked into teaching and learning environments, especially those potentially harmful to young people's capacity to see themselves within disciplinary Discourses.
This article provides commentary for the special issue on culturally sustaining assessment. It highlights that the articles focus on transforming assessment from a focus on judgment to one of attunement-an orientation that sustains, rather than marginalizes, students' cultural practices and identities. Across diverse contexts, the included articles propose both tactical and strategic shifts toward culturally sustaining assessment practices. These include integrating students' funds of knowledge and identity, inviting self-documentation, and cultivating feedback as a relational, dialogical act. Examples span from early elementary classrooms to arts-based youth programs to communities partnering to build systems of assessment that protect Indigenous sovereignty, demonstrating both the promise and challenges of assessment rooted in recognition of multiple ways of knowing and being. Together, the contributions argue for attunement as a core stance-where educators notice, respond to, and learn from students' ways of being and knowing. In doing so, the issue reimagines assessment not as a tool for sorting, but as a generative space for connection, resistance, and collective meaning-making within more just educational systems.
BackgroundThe value of causal reasoning is widely appreciated by educators, yet little research has been dedicated to determining how it develops in social contexts. This study examined children's construction of causal reasoning during collaborative discussions in elementary school classrooms and investigated whether they were able to transfer causal reasoning displayed during the discussions to individual tasks.MethodsMultilink causal chain models were tracked in 24 collaborative discussions involving 160 underserved fifth-graders, 154 individually written essays about the question addressed in the discussion, and 95 individual oral interviews about an analogous question. Path analyses were conducted to document connections between learning processes and products.FindingsRecurrent patterns of multilink causal reasoning were identified in 92% of the collaborative discussions. Students were found to use what they had learned about the construction of multilink causal chains in collaborative groups in an independently written essay and a knowledge transfer interview. Peer modeling played a key role in fostering the transfer of multilink causal reasoning for children who could not produce causal chains themselves.ContributionOverall, this analysis of the social construction of multilink causal chains provides distinctive new evidence that enabling meaningful interaction among children promotes higher-level cognitive development.
BackgroundDespite its potential, collaborative learning is not always successful. Learners often have difficulties to overcome regulation problems such as diverging goals within their group. If group members have different (i.e. heterogeneous) perceptions of the group's current regulation problems, and fail to homogenize them, this may endanger successful collaboration.MethodsN = 311 pre-service teachers collaborated online to analyze a fictional classroom case. Afterward, they individually rated (a) what problems they encountered during collaboration (to arrive at a measure for homogeneity of problem perceptions), (b) their awareness of the heterogeneity of the problem perceptions within their group, and (c) different indicators of regulation success. We additionally analyzed videos and video-recall interviews of groups with pronounced heterogeneous or homogeneous problem perception ratings to better understand how homo-/heterogeneous problem perceptions affect collaboration.FindingsPath models suggest that the homogeneity of problem perceptions was positively related with regulation success. However, awareness of heterogeneity of the problem perceptions within the group was not. Video and interview data indicate that despite knowing about their heterogeneous problem perceptions, learners may be unable to align these perceptions successfully.ContributionGroup members should be supported to arrive at homogeneous problem perceptions to positively influence regulation success in collaborative learning.
BACKGROUNDProject-based learning (PBL) centers authenticity as a core principle, meaning that learning is personally meaningful to students, seen as necessary by others, and calls for disciplinary tools. However, science curriculum developed for scale is challenged to predict authentic events. Developers are unfamiliar with students, their context, and the ways tools will emerge.MethodsUsing Portraiture, this study traces how a third-grade Bilingual class, while enacting a prepackaged science curriculum, appeared to experience authenticity. Portraiture allowed for thick description of two episodes, highlighting authenticity in contrived and spontaneous events.FindingsThe teacher followed the curriculum as designed and students seemed to experience learning as authentic. However, a spring snowstorm created the need for the teacher to depart from lessons as written. When responding to the spontaneous event, unlike events with contrived authenticity, students became part of crafting authentic tools and authenticity to others, including nonhumans.ContributionThis study suggests that teacher expertise is critical for recognizing and seizing on the potential for authenticity, such as responding to spontaneous events. We advocate, through the lens of social justice unionism, for future research to explore how to trust and support teachers in departing from pre-planned science lessons and to investigate the authentic learning that ensues.
