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1. Programming as a language for young children to express and explore mathematics in school

   https://doi.org/10.1111/bjet.13080  

   Goldenberg, E. Paul ; Carter, Cynthia J. ( May 2021 , British Journal of Educational Technology)

   Natural language helps express mathematical thinking and contexts. Conventional mathematical notation (CMN) best suits expressions and equations. Each is essential; each also has limitations, especially for learners. Our research studies how programming can be a advantageous third language that can also help restore mathematical connections that are hidden by topic‐centred curricula. Restoring opportunities for surprise and delight reclaims mathematics' creative nature. Studies of children's use of language in mathematics and their programming behaviours guide our iterative design/redesign of mathematical microworlds in which students, ages 7–11, use programming in their regular school lessonsas a language for learning mathematics. Though driven by mathematics, not coding, the microworlds develop the programming over time so that it continues to support children's developing mathematical ideas. This paper briefly describes microworlds EDC has tested with well over 400 7‐to‐8‐year‐olds in school, and others tested (or about to be tested) with over 200 8‐to‐11‐year‐olds. Our challenge was to satisfy schools' topical orientation and fit easily within regular classroom study but use and foreshadow other mathematical learning to remove the siloes. The design/redesign research and evaluation is exploratory, without formal methodology. We are also more formally studying effects on children's learning. That ongoing study is not reported here.

   What is already known

   Active learning—doing—supports learning.

   Collaborative learning—doingtogether—supports learning.

   Classroom discourse—focused, relevantdiscussion, not just listening—supports learning.

   Clear articulation of one's thinking, even just to oneself, helps develop that thinking.

   What this paper adds

   The common languages we use for classroom mathematics—natural language for conveying the meaning and context of mathematical situations and for explaining our reasoning; and the formal (written) language of conventional mathematical notation, the symbols we use in mathematical expressions and equations—are both essential but each presents hurdles that necessitate the other. Yet, even together, they are insufficient especially for young learners.

   Programming, appropriately designed and used, can be the third language that both reduces barriers and provides the missing expressive and creative capabilities children need.

   Appropriate design for use in regular mathematics classrooms requires making key mathematical content obvious, strong and the ‘driver’ of the activities, and requires reducing tech ‘overhead’ to near zero.

   Continued usefulness across the grades requires developing children's sophistication and knowledge with the language; the powerful ways that children rapidly acquire facility with (natural) language provides guidance for ways they can learn a formal language as well.

   Implications for policy and/or practice

   Mathematics teaching can take advantage of the ways children learn through experimentation and attention to the results, and of the ways children use their language brain even for mathematics.

   In particular, programming—in microworlds driven by the mathematical content, designed to minimise distraction and overhead, open to exploration and discoveryen routeto focused aims, and in which childrenself‐evaluate—can allow clear articulation of thought, experimentation with immediate feedback.

   As it aids the mathematics, it also builds computational thinking and satisfies schools' increasing concerns to broaden access to ideas of computer science.

    

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2. Co‐designing teacher support technology for problem‐based learning in middle school science

   https://doi.org/10.1111/bjet.13363  

   Hutchins, Nicole M. ; Biswas, Gautam ( July 2023 , British Journal of Educational Technology)

   This paper provides an experience report on a co‐design approach with teachers to co‐create learning analytics‐based technology to support problem‐based learning in middle school science classrooms. We have mapped out a workflow for such applications and developed design narratives to investigate the implementation, modifications and temporal roles of the participants in the design process. Our results provide precedent knowledge on co‐designing with experienced and novice teachers and co‐constructing actionable insight that can help teachers engage more effectively with their students' learning and problem‐solving processes during classroom PBL implementations.

   What is already known about this topic

   Success of educational technology depends in large part on the technology's alignment with teachers' goals for their students, teaching strategies and classroom context.

   Teacher and researcher co‐design of educational technology and supporting curricula has proven to be an effective way for integrating teacher insight and supporting their implementation needs.

   Co‐designing learning analytics and support technologies with teachers is difficult due to differences in design and development goals, workplace norms, and AI‐literacy and learning analytics background of teachers.

   What this paper adds

   We provide a co‐design workflow for middle school teachers that centres on co‐designing and developing actionable insights to support problem‐based learning (PBL) by systematic development of responsive teaching practices using AI‐generated learning analytics.

   We adapt established human‐computer interaction (HCI) methods to tackle the complex task of classroom PBL implementation, working with experienced and novice teachers to create a learning analytics dashboard for a PBL curriculum.

   We demonstrate researcher and teacher roles and needs in ensuring co‐design collaboration and the co‐construction of actionable insight to support middle school PBL.

   Implications for practice and/or policy

   Learning analytics researchers will be able to use the workflow as a tool to support their PBL co‐design processes.

   Learning analytics researchers will be able to apply adapted HCI methods for effective co‐design processes.

   Co‐design teams will be able to pre‐emptively prepare for the difficulties and needs of teachers when integrating middle school teacher feedback during the co‐design process in support of PBL technologies.

    

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3. Leveraging complexity frameworks to refine theories of engagement: Advancing self‐regulated learning in the age of artificial intelligence

   https://doi.org/10.1111/bjet.13340  

   Hilpert, Jonathan C. ; Greene, Jeffrey A. ; Bernacki, Matthew ( May 2023 , British Journal of Educational Technology)

   Capturing evidence for dynamic changes in self‐regulated learning (SRL) behaviours resulting from interventions is challenging for researchers. In the current study, we identified students who were likely to do poorly in a biology course and those who were likely to do well. Then, we randomly assigned a portion of the students predicted to perform poorly to a science of learning to learn intervention where they were taught SRL study strategies. Learning outcome and log data (257 K events) were collected fromn = 226 students. We used a complex systems framework to model the differences in SRL including the amount, interrelatedness, density and regularity of engagement captured in digital trace data (ie, logs). Differences were compared between students who were predicted to (1) perform poorly (control,n = 48), (2) perform poorly and received intervention (treatment,n = 95) and (3) perform well (not flagged,n = 83). Results indicated that the regularity of students' engagement was predictive of course grade, and that the intervention group exhibited increased regularity in engagement over the control group immediately after the intervention and maintained that increase over the course of the semester. We discuss the implications of these findings in relation to the future of artificial intelligence and potential uses for monitoring student learning in online environments.

   What is already known about this topic

   Self‐regulated learning (SRL) knowledge and skills are strong predictors of postsecondary STEM student success.

   SRL is a dynamic, temporal process that leads to purposeful student engagement.

   Methods and metrics for measuring dynamic SRL behaviours in learning contexts are needed.

   What this paper adds

   A Markov process for measuring dynamic SRL processes using log data.

   Evidence that dynamic, interaction‐dominant aspects of SRL predict student achievement.

   Evidence that SRL processes can be meaningfully impacted through educational intervention.

   Implications for theory and practice

   Complexity approaches inform theory and measurement of dynamic SRL processes.

   Static representations of dynamic SRL processes are promising learning analytics metrics.

   Engineered features of LMS usage are valuable contributions to AI models.

    

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4. The biodesign studio: Constructions and reflections of high school youth on making with living media

   https://doi.org/10.1111/bjet.13081  

   Walker, Justice T. ; Kafai, Yasmin B. ( March 2021 , British Journal of Educational Technology)

   Most constructionist efforts have focused on supporting learners with tools for designing with digital and/or physical media. Recent developments in life sciences now allow K‐12 learners to design with living materials, or to biodesign. In this paper, we report on the development of a biodesign studio activity called biocakes wherein teams of high school youth genetically modified a yeast strain to bake a nutrient fortified food product. Using a qualitative deductive analysis of classroom observations, interviews and projects, we examined high school youth experiences and reflections of these activities to answer three research questions: (1) What kind of artefacts did youth make with living media? (2) How did youth engage in biodesign? and (3) What did youth have to say about their biodesign experiences? We discuss how our analyses of biodesign applications highlight the importance of assembly practices, social engagement and imaginative design for constructionist learning. These insights provide compelling examples for designing with living media in K‐12 education.

   What is already known about this topic?

   Constructionist perspectives shape important ideas about what we know about science learning, and notably in computer science fields.

   One widely taken up example includes making, where learners use crafts to make interactive computational objects.

   In life science, constructionism also provides insights about learning using digital media to model biological systems or interact with living materials.

   What this paper adds?

   This paper extends these perspectives by examining production and engagement when learners constructwithliving materials—an approach that has only recently been possible with the development of accessible wet lab tools.

   We frame learning activities as a studio model—that emphasised application design, iteration and critique—to better assess the roles assembly, construction and speculative design play in production that uses living materials.

   Our findings suggest that assembly is important for creating accessible points of entry to complex biological fabrication processes.

   We also find that speculative design provides an opportunity for learners to extend their existing abilities beyond what is otherwise available given their expertise or access to resources, and thus expansively explore related ideas.

   Implications for practice and/or policy

   Assembly and speculative design have important places in constructionist‐driven production with living materials and could, therefore, be leveraged in practice.

    

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5. Constructionist co‐design: A dual approach to curriculum and professional development

   https://doi.org/10.1111/bjet.13084  

   Kelter, Jacob ; Peel, Amanda ; Bain, Connor ; Anton, Gabriella ; Dabholkar, Sugat ; Horn, Michael S. ; Wilensky, Uri ( May 2021 , British Journal of Educational Technology)

   This paper reports on the first iteration of the Computational Thinking Summer Institute, a month‐long programme in which high school teachers co‐designed computationally enhanced mathematics and science curricula with researchers. The co‐design process itself was a constructionist learning experience for teachers resulting in constructionist curricula to be used in their own classrooms. We present three case studies to illustrate different ways teachers and researchers divided the labour of co‐design and the implications of these different co‐design styles for teacher learning and classroom enactment. Specifically, some teachers programmed their own computational tools, while others helped to conceptualise them but left the construction to their co‐design partners. Results indicate that constructionist co‐design is a promising dual approach to curriculum and professional development but that sometimes these two goals are in tension. Most teachers gained considerable confidence and skills in computational thinking, but sometimes the pressure to finish curriculum development during the institute led teachers to leave construction of computational tools to their co‐design partners, limiting their own opportunities for computational learning.

   What is already known about this topic?

   Computational tools can support constructionist science and math learning by making powerful ideas tangible.

   Supporting teachers to learn computational thinking and to use constructionist pedagogies is challenging.

   What this paper adds?

   Constructionist co‐design is a promising approach to simultaneously support curriculum development and professional development, but there are tensions to navigate in trying to accomplish both goals simultaneously.

   Implications for practice and/or policy

   Designers of professional development should consider constructionist co‐design as an approach but should be aware of potential tensions and prepare for them.

    

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