What's New on CADREK12.org
Resource | Webinar Resources: Informational Webinars on DRK-12 Solicitation (23-596)
Resources from the NSF-led webinars on the new DRK-12 Solicitation 23-596. 2023 NSF Information Session on DRK-12 Solicitation 23-596: Recording Led by DRK-12 Program Co-lead Joan Walker. DRK-12 Solicitation 23-596 Q&A Webinar 1 (July 20, 2023): Recording | Slides Led by NSF Program Directors Joan Walker, Jen Noll, and Rob Ochsendorf. Topics: merit review criteria, program strands,…
Resources from the NSF-led webinars on the new DRK-12 Solicitation 23-596. 2023 NSF Information Session on DRK-12 Solicitation 23-596: Recording Led by DRK-12 Program Co-lead Joan Walker. DRK-12 Solicitation 23-596 Q&A Webinar 1 (July 20, 2023): Recording | Slides Led by NSF Program Directors Joan Walker, Jen Noll, and Rob Ochsendorf. Topics: merit review criteria, program strands,…
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Poster | Adapted Measure of Math Engagement: Designing Self-Report Measures of Mathematics Engagement for Black and Latina/o Middle School Students (Collaborative Research: Holquist)
A three year, mixed-methods, critical participatory action research project to develop a culturally sustaining self-report measure of Black and Latina/o student math engagement, called the Adapted Measure of Math Engagement (AM-ME).
A three year, mixed-methods, critical participatory action research project to develop a culturally sustaining self-report measure of Black and Latina/o student math engagement, called the Adapted Measure of Math Engagement (AM-ME).
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Poster | Accessible Computational Thinking in Elementary Science Classes Within and Across Culturally and Linguistically Diverse Contexts (Collaborative Research: Nelson)
Accessible Computational Thinking in Elementary Science Classes within and across Culturally and Linguistically Diverse Contexts (ACT) investigates best practices for helping teachers provide culturally relevant experiences for elementary children to participate in and engage with computational thinking (CT) integrated into science lessons. ACT focuses on the question: how do elementary teachers…
Accessible Computational Thinking in Elementary Science Classes within and across Culturally and Linguistically Diverse Contexts (ACT) investigates best practices for helping teachers provide culturally relevant experiences for elementary children to participate in and engage with computational thinking (CT) integrated into science lessons. ACT focuses on the question: how do elementary teachers…
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Newsletter | July 2023 Newsletter
Dear Colleagues, We are delighted to be back with our newsletter after taking a brief hiatus last month to focus on the 2023 DRK-12 PI Meeting. It was a pleasure to see both familiar and new faces at the event. We thank the NSF program officers who welcomed us and responded to questions, and to Ivory Toldson who gave a compelling talk, Post-Reform Education, the Data Revolution, and DRK–12.…
Dear Colleagues, We are delighted to be back with our newsletter after taking a brief hiatus last month to focus on the 2023 DRK-12 PI Meeting. It was a pleasure to see both familiar and new faces at the event. We thank the NSF program officers who welcomed us and responded to questions, and to Ivory Toldson who gave a compelling talk, Post-Reform Education, the Data Revolution, and DRK–12.…
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Resource | Opportunities for Research within the Data Science Education Community
This webinar provided early career data science education researchers with information on the state of the field; tools, curricula, and other resources for researchers; and insight into funding opportunities and proposal development. Participants explore topics, research interests, and problems of practice in more depth in breakout rooms with session leaders.
This webinar provided early career data science education researchers with information on the state of the field; tools, curricula, and other resources for researchers; and insight into funding opportunities and proposal development. Participants explore topics, research interests, and problems of practice in more depth in breakout rooms with session leaders.
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Poster | Young Mathematicians: Expanding an Innovative and Promising Model Across Learning Environments to Promote Preschoolers' Mathematics Knowledge
Young children’s mathematics development underpins cognitive development, building brain architecture, fostering problem-solving, puzzling, and persevering, and strongly impacting and predicting future success in school – but systemic opportunity gaps have created unequal access to high-quality mathematics learning experiences, with differences in children’s math knowledge beginning before…
Young children’s mathematics development underpins cognitive development, building brain architecture, fostering problem-solving, puzzling, and persevering, and strongly impacting and predicting future success in school – but systemic opportunity gaps have created unequal access to high-quality mathematics learning experiences, with differences in children’s math knowledge beginning before…
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Event | NSF DRK-12 Solicitation Webinar 2
NSF released a pre-recorded information session on the new DRK-12 Solicitation 23-596. DRK-12 Solicitation 23-596 Q&A Webinar 2 (July 25, 2023): Recording | Slides Led by NSF Program Directors Asli Sezen-Barrie, Margret Hjalmarson, Barry Sloane, and Robert Russell. Topics: technical support and budgeting. Visit our NSF Proposal Toolkit for more guidance and resources.
NSF released a pre-recorded information session on the new DRK-12 Solicitation 23-596. DRK-12 Solicitation 23-596 Q&A Webinar 2 (July 25, 2023): Recording | Slides Led by NSF Program Directors Asli Sezen-Barrie, Margret Hjalmarson, Barry Sloane, and Robert Russell. Topics: technical support and budgeting. Visit our NSF Proposal Toolkit for more guidance and resources.
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Event | NSF DRK-12 Solicitation Webinar 1
NSF released a pre-recorded information session on the new DRK-12 Solicitation 23-596. DRK-12 Solicitation 23-596 Q&A Webinar 1 (July 20, 2023): Recording | Slides Led by NSF Program Directors Joan Walker, Jen Noll, and Rob Ochsendorf. Topics: merit review criteria, program strands, and project types. Visit our NSF Proposal Toolkit for more guidance and resources.
NSF released a pre-recorded information session on the new DRK-12 Solicitation 23-596. DRK-12 Solicitation 23-596 Q&A Webinar 1 (July 20, 2023): Recording | Slides Led by NSF Program Directors Joan Walker, Jen Noll, and Rob Ochsendorf. Topics: merit review criteria, program strands, and project types. Visit our NSF Proposal Toolkit for more guidance and resources.
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Announcement | New DRK-12 Solicitation: Informational Webinars and Resources
CADRE will host NSF-led informational sessions on the new DRK-12 Solicitation 23-596. If you are planning to submit a DRK-12 proposal (deadline November 8, 2023), we encourage you to register and attend one of the following events and access the resources listed below. Office Hours with NSF Program Directors Monday, August 7, 2023 | 1:00-2:00 PM ET Tuesday, August 15, 2023 | 1:00-2:00…
CADRE will host NSF-led informational sessions on the new DRK-12 Solicitation 23-596. If you are planning to submit a DRK-12 proposal (deadline November 8, 2023), we encourage you to register and attend one of the following events and access the resources listed below. Office Hours with NSF Program Directors Monday, August 7, 2023 | 1:00-2:00 PM ET Tuesday, August 15, 2023 | 1:00-2:00…
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Survey | 2023 PI Meeting Lunch Survey
Boxed lunches will be provided for the informal networking lunch on June 29. If you require a gluten-free and/or vegetarian meal, please respond to this quick survey as soon as possible, and by ___ at the latest.
Boxed lunches will be provided for the informal networking lunch on June 29. If you require a gluten-free and/or vegetarian meal, please respond to this quick survey as soon as possible, and by ___ at the latest.
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Survey | 2023 PI Meeting Session RSVP
If you plan to attend either of the following sessions, please RSVP as soon as possible and by June 12 at the latest.
If you plan to attend either of the following sessions, please RSVP as soon as possible and by June 12 at the latest.
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Announcement | New DRK-12 Solicitation!
NSF has released the DRK-12 NSF 23-596 solicitation. Proposals are due on November 8, 2023. Review What's New including: New Partnership Development project type; Emphasis on a programmatic commitment to research in the Teaching Strand as STEM workforce development; Emphasis on communication / dissemination plans as one component of knowledge mobilization or the reciprocal exchange or…
NSF has released the DRK-12 NSF 23-596 solicitation. Proposals are due on November 8, 2023. Review What's New including: New Partnership Development project type; Emphasis on a programmatic commitment to research in the Teaching Strand as STEM workforce development; Emphasis on communication / dissemination plans as one component of knowledge mobilization or the reciprocal exchange or…
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Resource | What’s New in the 2023 DRK-12 Solicitation
The new DRK-12 solicitation (NSF 23-596) introduces several changes and updates compared to the previous solicitation (NSF 20-572). Proposal writers should take note of the differences outlined in this document.
The new DRK-12 solicitation (NSF 23-596) introduces several changes and updates compared to the previous solicitation (NSF 20-572). Proposal writers should take note of the differences outlined in this document.
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Event | Discovery Research PreK-12 (DRK-12) Full Proposal Deadline
Learn more at https://new.nsf.gov/funding/opportunities/discovery-research-prek-12-dr…
Learn more at https://new.nsf.gov/funding/opportunities/discovery-research-prek-12-dr…
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Resource | Socio-Scientific Learning During the COVID-19 Pandemic: Comparing In-person and Virtual Science Learning Using Model-Evidence Link Diagrams
Science learning is an important part of the K-12 educational experience, as well as in the lives of students. This study considered students’ science learning as they engaged in the instruction of scientific issues with social relevance. With classroom environments radically changing during the COVID-19 pandemic, our study adapted to teachers and students as they were forced to change from more…
Science learning is an important part of the K-12 educational experience, as well as in the lives of students. This study considered students’ science learning as they engaged in the instruction of scientific issues with social relevance. With classroom environments radically changing during the COVID-19 pandemic, our study adapted to teachers and students as they were forced to change from more…
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Resource | Integrative Analysis Using Big Ideas: Energy Transfer and Cellular Respiration
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated…
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated…
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Resource | Integrative Analysis Using Big Ideas: Energy Transfer and Cellular Respiration
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated…
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated…
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Resource | Integrative Analysis Using Big Ideas: Energy Transfer and Cellular Respiration
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated…
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated…
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Resource | A Model Comparison Approach to Posterior Predictive Model Checks in Bayesian Confirmatory Factor Analysis
Posterior Predictive Model Checking (PPMC) is frequently used for model fit evaluation in Bayesian Confirmatory Factor Analysis (BCFA). In standard PPMC procedures, model misfit is quantified by comparing the location of an ML-based point estimate to the predictive distribution of a statistic. When the point estimate is far from the center posterior predictive distribution, model fit is poor. Not…
Posterior Predictive Model Checking (PPMC) is frequently used for model fit evaluation in Bayesian Confirmatory Factor Analysis (BCFA). In standard PPMC procedures, model misfit is quantified by comparing the location of an ML-based point estimate to the predictive distribution of a statistic. When the point estimate is far from the center posterior predictive distribution, model fit is poor. Not…
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Resource | A Gibbs Sampling Algorithm with Monotonicity Constraints for Diagnostic Classification Models
Diagnostic classification models (DCMs) are restricted latent class models with a set of cross-class equality constraints and additional monotonicity constraints on their item parameters, both of which are needed to ensure the meaning of classes and model parameters. In this paper, we develop an efficient, Gibbs sampling-based Bayesian Markov chain Monte Carlo estimation method for general DCMs…
Diagnostic classification models (DCMs) are restricted latent class models with a set of cross-class equality constraints and additional monotonicity constraints on their item parameters, both of which are needed to ensure the meaning of classes and model parameters. In this paper, we develop an efficient, Gibbs sampling-based Bayesian Markov chain Monte Carlo estimation method for general DCMs…
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Resource | The Impact of Sample Size and Various Other Factors on Estimation of Dichotomous Mixture IRT Models
The purpose of this study was to examine the effects of different data conditions on item parameter recovery and classification accuracy of three dichotomous mixture item response theory (IRT) models: the Mix1PL, Mix2PL, and Mix3PL. Manipulated factors in the simulation included the sample size (11 different sample sizes from 100 to 5000), test length (10, 30, and 50), number of classes (2 and 3…
The purpose of this study was to examine the effects of different data conditions on item parameter recovery and classification accuracy of three dichotomous mixture item response theory (IRT) models: the Mix1PL, Mix2PL, and Mix3PL. Manipulated factors in the simulation included the sample size (11 different sample sizes from 100 to 5000), test length (10, 30, and 50), number of classes (2 and 3…
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Resource | Investigating Teachers’ Understanding Through Topic Modeling: A Promising Approach to Studying Teachers’ Knowledge
Examining teachers’ knowledge on a large scale involves addressing substantial measurement and logistical issues; thus, existing teacher knowledge assessments have mainly consisted of selected-response items because of their ease of scoring. Although open-ended responses could capture a more complex understanding of and provide further insights into teachers’ thinking, scoring these responses is…
Examining teachers’ knowledge on a large scale involves addressing substantial measurement and logistical issues; thus, existing teacher knowledge assessments have mainly consisted of selected-response items because of their ease of scoring. Although open-ended responses could capture a more complex understanding of and provide further insights into teachers’ thinking, scoring these responses is…
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Resource | Estimation of Multidimensional Item Response Theory Models with Correlated Latent Variables Using Variational Autoencoders
Artificial neural networks with a specific autoencoding structure are capable of estimating parameters for the multidimensional logistic 2-parameter (ML2P) model in item response theory (Curi et al. in International joint conference on neural networks (IJCNN), 2019), but with limitations, such as uncorrelated latent traits. In this work, we extend variational auto encoders (VAE) to estimate…
Artificial neural networks with a specific autoencoding structure are capable of estimating parameters for the multidimensional logistic 2-parameter (ML2P) model in item response theory (Curi et al. in International joint conference on neural networks (IJCNN), 2019), but with limitations, such as uncorrelated latent traits. In this work, we extend variational auto encoders (VAE) to estimate…
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Resource | Modification Indices for Diagnostic Classification Models
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 and/or Q-matrix misspecification is a known problem with limited avenues for remediation. To address this problem, this paper defines a one-sided score statistic that is a…
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 and/or Q-matrix misspecification is a known problem with limited avenues for remediation. To address this problem, this paper defines a one-sided score statistic that is a…
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Resource | Patterns of Using Multimodal External Representations in Digital Game-based Learning
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 tasks in digital game-based learning (DGBL) environments. This exploratory study was to examine the salient patterns problem solvers demonstrated using MERs when they engaged in…
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 tasks in digital game-based learning (DGBL) environments. This exploratory study was to examine the salient patterns problem solvers demonstrated using MERs when they engaged in…
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Resource | Exploring Students’ Learning Support Use in Digital Game-based Math Learning: A Mixed-Methods Approach Using Machine Learning and Multi-cases Study
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 mathematics education places an emphasis. Literature on learning support in digital game-based learning (DGBL) rarely investigate learners' support-use behaviors and interaction…
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 mathematics education places an emphasis. Literature on learning support in digital game-based learning (DGBL) rarely investigate learners' support-use behaviors and interaction…
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Resource | Effects of Game-based Learning Supports on Students’ Math Performance and Perceived Game Flow
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 successful math problem solving and students’ perceived game flow. Forty-one sixth-grade students participated in the study and played a 3D architecture game that aims to promote…
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 successful math problem solving and students’ perceived game flow. Forty-one sixth-grade students participated in the study and played a 3D architecture game that aims to promote…
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Resource | Infect, Attach or Bounce off?: Linking Real Data and Computational Models to Make Sense of the Mechanisms of Diffusion
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-based environment and approach that integrates model-based and data-based features in the same display which facilitates the comparison of models and real-world data. Further, we…
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-based environment and approach that integrates model-based and data-based features in the same display which facilitates the comparison of models and real-world data. Further, we…
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Resource | MoDa: Designing a Tool to Interweave Computational Modeling with Real-world Data Analysis for Science Learning in Middle School
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 wildfire smoke spread in MoDa, a web-based environment that integrates computational modeling side-by-side with real-world data for comparison and validation. Epistemic network…
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 wildfire smoke spread in MoDa, a web-based environment that integrates computational modeling side-by-side with real-world data for comparison and validation. Epistemic network…
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