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How Do Interdisciplinary Teams Co-construct Instructional Materials Emphasising Both Science and Engineering Practices?
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To build a sustainable future, science and engineering education programmes should emphasise scientific investigation, collaboration across traditional science topics and disciplines, and engineering design, including…
“Should We Build This?”: Student Reasoning in Intentionally Facilitated Socio-technical Design Talks
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We are developing case studies of specific types of teacher-supported conversation in which students are asked to consider design decision-making not just as a technical task, but as a complex socio-technical activity with…
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Mastery goal structures, which communicate value for developing deeper understanding, are an important classroom support for student motivation and engagement, especially in the context of science learning aligned with the…
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Involving students in scientific modeling practice is one of the most effective approaches to achieving the next generation science education learning goals. Given the complexity and multirepresentational features of…
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To best support students in developing competence, assessments that allow students to use knowledge to solve challenging problems and make sense of phenomena are needed. These assessments need to be designed and tested to…
Examining the Influence of COVID-19 on Elementary Mathematics Standardized Test Scores in a Rural Ohio School District
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In the United States, national and state standardized assessments have become a metric for measuring student learning and high-quality learning environments. As the COVID-19 pandemic offered a multitude of learning…
Flip It: An Exploratory (Versus Explanatory) Sequential Mixed Methods Design Using Delphi and Differential Item Functioning to Evaluate Item Bias
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The Delphi method has been adapted to inform item refinements in educational and psychological assessment development. An explanatory sequential mixed methods design using Delphi is a common approach to gain experts'…
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MindHive is an online, open science, citizen science platform co-designed by a team of educational researchers, teachers, cognitive and social scientists, UX researchers, community organizers, and software developers to…
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Students need “critical data literacy” skills to help make sense of the multitude of information available to them, especially as it relates to high-stakes issues of social justice. The authors describe two curriculum…
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Civic Statistics by its nature is highly interdisciplinary. From a cross-curricular perspective, teaching and learning Civic Statistics faces specific challenges related to the preparation of teachers and the design of…
Leading for Justice, Leading for Learning: Conceptualizing Urban School Leadership for Antiracist Mathematics Teaching and Learning
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Urban school leaders can support mathematics instruction that acknowledges and sustains students’ racialized and cultured ways of knowing and being. Yet, leadership for racial justice is often discussed separately from…
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In super-diverse classroom contexts, students come from varied migration channels, immigration statuses, languages, countries of origin, and religions, which contribute to new and complex social configurations of the…
COVID-19 as a Magnifying Glass: Exploring the Importance of Relationships as Education Students Learn and Teach Robotics via Zoom
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Ed+gineering, an NSF-funded program, adapted hands-on robotics instruction for online delivery in response to the COVID-19 pandemic. This qualitative multiple case study shares the experiences of participating education…
Undergraduate Engineering and Education Students Reflect on Their Interdisciplinary Teamwork Experiences Following Transition to Virtual Instruction Caused by COVID-19
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This study explores undergraduate engineering and education students’ perspectives on their interdisciplinary teams throughout the rapid transition to online learning and instruction from a face-to-face to a virtual format…
Examining Elementary Science Teachers' Responses to Assessments Tasks Designed to Measure Their Content Knowledge for Teaching About Matter and its Interactions
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Despite the importance of developing elementary science teachers' content knowledge for teaching (CKT), there are limited assessments that have been designed to measure the full breadth of their CKT at scale. Our overall…
“Unnatural How Natural It Was”: Using a Performance Task and Simulated Classroom for Preservice Secondary Teachers to Practice Engaging Student Avatars in Scientific Argumentation
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Facilitating discussions is a key approach that science teachers use to engage students in scientific argumentation. However, learning how to facilitate argumentation-focused discussions is an ambitious teaching practice…
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Eliciting and interpreting students’ ideas are essential skills in teaching, yet pre-service teachers (PSTs) rarely have adequate opportunities to develop these skills. In this study, we examine PSTs’ patterns of discourse…
Exploring the Potential of an Online Suite of Practice-Based Activities for Supporting Preservice Elementary Teachers in Learning How to Facilitate Argumentation-Focused Discussions in Mathematics and Science
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This study explored the use of a three-part suite of practice-based activities -- one- and two-player online simulations, an avatar-based simulation, and a virtual teaching simulator—for supporting preservice teachers in…
MoDa: Designing a Tool to Interweave Computational Modeling with Real-world Data Analysis for Science Learning in Middle School
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Coordinating modeling and real-world data is central to building scientific theories. This paper examines how a complementary focus on modeling and data contributed to 8th grade students’ learning of mechanisms underlying…
Infect, Attach or Bounce off?: Linking Real Data and Computational Models to Make Sense of the Mechanisms of Diffusion
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This study explores how the interplay between data and model design shifts 6th graders’ students' ideas about diffusion as they build a range of models (“paper and pencil” and computational models). We present a new web-…
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Adopting a pretest–posttest experimental design with repeated measures, this study examined the effects of three types of game-based learning supports in the form of modeling on knowledge development that contributed to…
Exploring Students’ Learning Support Use in Digital Game-based Math Learning: A Mixed-Methods Approach Using Machine Learning and Multi-cases Study
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Digital game-based math learning environments (math DGBLE) are promising platforms that provide students with opportunities to master conceptual understanding and cultivate mathematical thinking, on which the contemporary…
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Although prior research has highlighted the significance of representations for mathematical learning, there is still a lack of research on how students use multimodal external representations (MERs) to solve mathematical…
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Diagnostic classification models (DCMs) are psychometric models for evaluating a student’s mastery of the essential skills in a content domain based upon their responses to a set of test items. Currently, diagnostic model…
Estimation of Multidimensional Item Response Theory Models with Correlated Latent Variables Using Variational Autoencoders
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In this work, we extend variational auto encoders (VAE) to estimate item parameters and correlated latent abilities, and directly compare the ML2P-VAE method to more traditional parameter estimation methods, such as Monte…