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This paper shares findings from a multi-year literacy professional development partnership between a school district and university (2014–2019). We share this case of a Literacy Cohort initiative as an example of cross-institutional professional development situated within several of NAPDS’ nine essentials, including professional learning and leading, boundary-spanning roles and reflection and innovation (NAPDS, 2021).

We asked, “In what ways did the Cohort initiative create conditions for community and collaboration in the service of meaningful literacy reforms?” Drawing on social design methodology (Gutiérrez & Vossoughi, 2010), we sought to generate and examine the educational change associated with this multi-year initiative. Our data set included programmatic data, interviews (N = 30) and artifacts of literacy teaching, learning and leading.

Our findings reflect the emphasis areas that are important to educators in the partnership: diversity by design, building relationships through collaboration and rooting literacy reforms in teacher leadership. Our discussion explores threads of reciprocity, simultaneous renewal and boundary-spanning leadership and their role in sustaining partnerships over time.

This paper contributes to our understanding of building and sustaining a cohort model of multi-year professional development through the voices, perspectives and experiences of teachers, faculty and district administrators.

Governments and organizations worldwide are concerned over the declining number of young people choosing to study Science, Technology, Engineering and Mathematics (STEM), especially after the age of 16. Research has foregrounded that students with positive attitudes toward science are more likely to find it relevant and aspire to a science career. This study aims to understand the factors shaping students’ attitudes as these are pivotal in promoting science learning.

This study uses the framework of science capital to understand what shapes young people’s engagement with or resistance to science. The authors conducted four Computational Thinking making-based workshops with 106 children aged 15–16 years, of which 58 filled in a questionnaire and 22 were interviewed. Statistical and content analyses were performed respectively.

The results indicate that children who are more exposed to science-related activities and contexts are more likely to have higher self-efficacy, and that those with higher prior coding experience scored higher in their self-efficacy and science capital. Six themes emerged from the content analysis, highlighting the diverse factors shaping students’ attitudes, such as teaching methods, stereotypes and the degree of difficulty encountered while engaging with science in and out of school.

By combining qualitative and quantitative methods with the use of science capital, the authors found a number of aspects of the school experience that shape students’ attitudes to science learning in and out of school, as well as their science career aspirations.

Design-based research (DBR) involves multiple iterations, and innovations are needed in analytical methods for understanding how learners experience a learning experience in ways that both embrace the complexity of learning and allow for data-driven changes to the design of the learning experience between iterations. The purpose of this paper is to propose a method of crafting design moves in DBR using network analysis.

This paper introduces learning experience network analysis (LENA) to allow researchers to investigate the multiple interdependencies between aspects of learner experiences, and to craft design moves that leverage the relationships between struggles, what worked and experiences aligned with principles from theory.

The use of network analysis is a promising method of crafting data-driven design changes between iterations in DBR. The LENA process developed by the authors may serve as inspiration for other researchers to develop even more powerful methodological innovations.

LENA may provide design-based researchers with a new approach to analyzing learner experiences and crafting data-driven design moves in a way that honors the complexity of learning.

LENA may provide novice design-based researchers with a structured and easy-to-use method of crafting design moves informed by patterns emergent in the data.

To the best of the authors’ knowledge, this paper is the first to propose a method for using network analysis of qualitative learning experience data for DBR.

Issues around informal, non-formal and formal learning, intended and unintended learning and competencies and capabilities have been considered in work-based learning (WBL). However, demarcated modes of learning, or what can be called strategies or pedagogies of learning, associated with experience of work environments have yet to be examined. One mode of learning which has been highlighted in relation to work is reflective practice, and its centrality to learning at work has been established. But reflective practice as a core skill, and its relation to other approaches to learning and research in WBL, remains uncovered. The purpose of the present study therefore is to identify different modes of learning as they appear in the literature and to present a proto-theoretical “learning by …” model for WBL and research founded on learning by reflection.

Proto-theoretical modelling and qualitative descriptions of each mode of learning.

Work environments, and the higher degree WBL programmes which support them, should provide learning via every available mode of learning, thereby allowing students to find their own best orientation to learning and encourage it by any means.

The proto-theoretical model and 12 modes of learning applied to WBL are unique to this study. WBL provides participants of work with multiple opportunities and approaches to learn and similarly provides multiple modes through which learning can occur on the basis of knowledge and skills in reflective practice.

The purpose of this paper is to re-center playfulness as a humanizing approach in teacher education. As teachers navigate the current moment of heightened control, surveillance, and systemic inequity, these proposed moves in teacher education can be transgressive. Rather than play as relegated to childhood or infancy, what does it look like to continue to be “playful” in teaching and teacher education?

To examine how teacher educators may design for teachers’ critical playful literacies, the authors offer three “worked examples” (Gee, 2009) of preservice teachers’ playful practices in an English literacies teacher education course.

The authors highlight instructional design elements pertinent to co-designing for teachers’ play and playful literacies in teacher education: generative constraints to practice everyday ingenuity, figuring it out to foster teacher agency and debriefs to interrupt the teaching’s perpetual performance.

The term “playful,” as a descriptor of practice and qualifier of activity appears frequently in educational literature across domains. The relationship of play to critical literacies – and, more specifically, educators’ literacies and learning – is less frequently explored.

In light of a need for more critical education about datafication, this paper aims to develop a framework for critical datafication literacy that is grounded in theoretical and empirical research. The framework draws upon existing critical data literacies, an in-depth analysis of three well-established educational approaches – media literacy, the German “(politische) Bildung” and Freirean “critical pedagogy” – and empirical analyses of online educational resources about datafication.

The study interconnects theoretical analyses with an empirical mixed methods investigation that includes expert interviews with creators of online educational resources about datafication and a qualitative survey with educators interested in teaching about data technologies.

The research identified novel findings on the goals of resource creators and educators, such as a focus on empowering and emancipatory approaches, fostering systemic understanding of datafication and encouraging collective action. Such perspectives are rare in existing critical data literacy conceptualisations but show resemblance to traditional education scholarship. This highlights how much can be learnt from practitioners and from these more established educational approaches. Based on these findings, a framework for critical datafication literacy is suggested that aims for systemic understanding of datafication, encouraging critical thinking and enabling learners to make enlightened choices and take different forms of action.

The study is unique in its interconnection of theoretical and empirical research, and it advances previous research by suggesting a grounded framework for critical datafication literacy.

Arts-integration is a promising approach to building students’ abilities to create and critique arguments with data, also known as informal inferential reasoning (IIR). However, differences in disciplinary practices and routines, as well as school organization and culture, can pose barriers to subject integration. The purpose of this study is to describe synergies and tensions between data science and the arts, and how these can create or constrain opportunities for learners to engage in IIR.

The authors co-designed and implemented four arts-integrated data literacy units with 10 teachers of arts and mathematics in middle school classrooms from four different schools in the USA. The data include student-generated artwork and their written rationales, and interviews with teachers and students. Through maximum variation sampling, the authors identified examples from the data to illustrate disciplinary synergies and tensions that appeared to support different IIR processes among students.

Aspects of artistic representation, including embodiment, narrative and visual image; and aspects of the culture of arts, including an emphasis on personal experience, the acknowledgement of subjectivity and considerations for the audience’s perspective, created synergies and tensions that both offered and hindered opportunities for IIR (i.e. going beyond data, using data as evidence and expressing uncertainty).

This study answers calls for humanistic approaches to data literacy education. It contributes an interdisciplinary perspective on data literacy that complements other context-oriented perspectives on data science. This study also offers recommendations for how designers and educators can capitalize on synergies and mitigate tensions between domains to promote successful IIR in arts-integrated data literacy education.