Projects

The project will provide the opportunity for upper elementary students to learn computer science and build strong collaboration practices. Leveraging the promise of virtual learning companions, the project will collect datasets of collaborative learning for computer science in diverse upper elementary school classrooms; design, develop, and iteratively refine its intelligent virtual learning companions; and generate research findings and evidence about how children collaborate in computer science learning and how best to support their collaboration with intelligent virtual learning companions.

This project is developing a two-year, intensive professional development model to build middle-grades mathematics teachers’ knowledge and implementation of formative assessment. Using a combination of institutes, classroom practice, and ongoing support through professional learning communities and web-based resources, this model helps teachers internalize and integrate a comprehensive understanding of formative assessment into daily practice.

This project will examine the impact on mathematics learning of an initiative to provide kindergartners in an urban school district with personal tablet devices that include free, widely available digital mathematics resources. The research questions examine how teachers use table-based mathematics resources during instruction, how caregivers and children engage with table-based mathematics resources, and how the resources then relate to kindergartners mathematics learning.

The project will develop a teacher professional learning (PL) model that focuses on middle-school biological sciences in addressing real world problems. Systems thinking is central to understanding biology systems. Game design has been shown to help develop systems thinking in teachers and students. Students will participate in PL to illustrate the value of distributed expertise by sharing their knowledge of computer. Teachers will adapt their existing curriculum and will co-design games with students to experience participatory practices.

Colorado’s PhET project and Stanford’s AAALab will develop and study learning from interactive simulations designed for middle school science classrooms. Products will include 35 interactive sims with related support materials freely available from the PhET website; new technologies to collect real-time data on student use of sims; and guidelines for the development and use of sims for this age population. The team will also publish research on how students learn from sims.

This study can provide a basis for design research focused on developing effective materials and programs for flipped instruction in secondary mathematics, which is already occurring at an increasing rate, but it is not yet informed by empirical evidence. This project will result in a framework for flipped instruction robust enough to be useful at a variety of grade levels and contexts. The framework will provide a better understanding of the relationships among various implementations of flipped instruction and student learning.

In this project, the investigators will explore different ways that elementary school teachers participate in online learning in a platform that includes videos, discussions, and other resources for mathematics teaching. Knowing that teachers may use the platform to different degrees depending on their interest and time available, the study will investigate how different profiles of participation influence teachers' learning.

In this project, the investigators will explore different ways that elementary school teachers participate in online learning in a platform that includes videos, discussions, and other resources for mathematics teaching. Knowing that teachers may use the platform to different degrees depending on their interest and time available, the study will investigate how different profiles of participation influence teachers' learning.

In this project, the investigators will explore different ways that elementary school teachers participate in online learning in a platform that includes videos, discussions, and other resources for mathematics teaching. Knowing that teachers may use the platform to different degrees depending on their interest and time available, the study will investigate how different profiles of participation influence teachers' learning.

This study examines the impact of the newly revised Advanced Placement (AP) Biology and Chemistry courses on students' understanding of and ability to utilize scientific inquiry, on students' confidence in engaging in college-level material, and on students’ enrollment and persistence in college STEM majors. The project provides estimates of the impact of students' AP-course taking on their progress into postsecondary educational experiences and their intent to continue to prepare to be future engineers and scientists.

The project will create a digital environment for middle school mathematics teachers that is combined with a student collaborative platform for a problem-solving curriculum. The goal is to design and develop the digital collaborative platform so networks of teachers can create, use, and share teaching resources for planning, enactment, and reflection on student thinking.

This project envisions a future of work where advanced technologies provide automated, job-embedded, individualized feedback to drive professional learning of the future worker. To achieve this goal, it addresses a fundamental question: Are evaluative or non-evaluative feedback systems more effective in driving professional learning? This question will be tested on professionals where objective, fine-grained feedback is especially critical to improvement--the teaching professions. This research will be situated within English and language arts (ELA) instruction in middle and high school classrooms, where underperformance and inequality in literacy outcomes are persistent problems facing the U.S. Current methods of supporting teacher learning through feedback are sparse, cumbersome, subjective, and evaluative. Thus, a major reconceptualization is needed to provide feedback mechanisms that- meaningfully affect teacher practice and are accessible to all. In partnership with TeachFX, an industry leader in technology-enabled instructional feedback, this project will work with teachers to design and test systems of automated feedback. Insights from the study will lead to feedback systems that empower teaching professionals, generate continued professional learning, and ultimately, increase student achievement.

This project envisions a future of work where advanced technologies provide automated, job-embedded, individualized feedback to drive professional learning of the future worker. To achieve this goal, it addresses a fundamental question: Are evaluative or non-evaluative feedback systems more effective in driving professional learning? This question will be tested on professionals where objective, fine-grained feedback is especially critical to improvement--the teaching professions. This research will be situated within English and language arts (ELA) instruction in middle and high school classrooms, where underperformance and inequality in literacy outcomes are persistent problems facing the U.S. Current methods of supporting teacher learning through feedback are sparse, cumbersome, subjective, and evaluative. Thus, a major reconceptualization is needed to provide feedback mechanisms that- meaningfully affect teacher practice and are accessible to all. In partnership with TeachFX, an industry leader in technology-enabled instructional feedback, this project will work with teachers to design and test systems of automated feedback. Insights from the study will lead to feedback systems that empower teaching professionals, generate continued professional learning, and ultimately, increase student achievement.

This exploratory proposal is researching and developing professional learning activities to help high school teachers use available and emerging social media to teach scientific argumentation. The project responds to the growing emphasis on scientific argumentation in new standards.

This project will develop and test a digital platform for middle school mathematics classrooms to help students deepen and communicate their understanding of mathematics. The digital platform will allow students to collaboratively create representations of their mathematics thinking, incorporate ideas from other students, and share their work with the class.

This project will develop and test a digital platform for middle school mathematics classrooms to help students deepen and communicate their understanding of mathematics. The digital platform will allow students to collaboratively create representations of their mathematics thinking, incorporate ideas from other students, and share their work with the class.

This development and research project designs, develops, and tests a digital game-based learning environment for supporting, assessing and analyzing middle school students' conceptual knowledge in learning physics, specifically Newtonian mechanics. This research integrates work from prior findings to develop a new methodology to engage students in deep learning while diagnosing and scaffolding the learning of Newtonian mechanics.

This project investigates the educational value of computer technologies for learning engineering. The project engages high school students to design, build, and evaluate an energy-efficient model house with the aid of computer simulation and design tools. 

The ReaL Earth Inquiry project empowers teachers to employ real-world local and regional Earth system science in the classroom. Earth systems science teachers need the pedagogic background, the content, and the support that enables them to engage students in asking real questions about their own communities. The project is developing online "Teacher-Friendly Guides" (resources), professional development involving fieldwork, and inquiry-focused approaches using "virtual fieldwork experiences."  

The goal of this project is to study how secondary students come to understand better an underlying logic of natural sciences—the relation between construction of new ideas and critique of them. Science education has traditionally focused mostly on how students construct models of natural phenomena. However, critique is crucial for iterative refinement of models because in professional science, peer critique of explanatory models motivates and guides progress toward better understanding. This project engages students in this process and helps them understand the relation of critique to better explanations, by focusing students on the criteria by which critique and understanding develop together through classroom discussions.

The goal of this project is to study how secondary students come to understand better an underlying logic of natural sciences—the relation between construction of new ideas and critique of them. Science education has traditionally focused mostly on how students construct models of natural phenomena. However, critique is crucial for iterative refinement of models because in professional science, peer critique of explanatory models motivates and guides progress toward better understanding. This project engages students in this process and helps them understand the relation of critique to better explanations, by focusing students on the criteria by which critique and understanding develop together through classroom discussions.

Society has grown to rely on smart, embedded, and interconnected systems. This has created a great need for well-qualified and motivated engineers, scientists, and technicians who can design, develop, and deploy innovative microelectronics and Artificial Intelligence (AI) technologies, which drive these systems. This project will address the need for a more robust computer science and engineering workforce by broadening access to microelectronics and AI education leveraging the cutting-edge technologies of Tiny Machine Learning and low-cost microcontroller systems in diverse high schools. The goal of this project is to engage high-school students and teachers from underresourced communities in the design and creative application of AI-enabled smart, embedded technologies, while supporting their engineering identity development and preparing them for the STEM jobs of tomorrow.

Society has grown to rely on smart, embedded, and interconnected systems. This has created a great need for well-qualified and motivated engineers, scientists, and technicians who can design, develop, and deploy innovative microelectronics and Artificial Intelligence (AI) technologies, which drive these systems. This project will address the need for a more robust computer science and engineering workforce by broadening access to microelectronics and AI education leveraging the cutting-edge technologies of Tiny Machine Learning and low-cost microcontroller systems in diverse high schools. The goal of this project is to engage high-school students and teachers from underresourced communities in the design and creative application of AI-enabled smart, embedded technologies, while supporting their engineering identity development and preparing them for the STEM jobs of tomorrow.

Society has grown to rely on smart, embedded, and interconnected systems. This has created a great need for well-qualified and motivated engineers, scientists, and technicians who can design, develop, and deploy innovative microelectronics and Artificial Intelligence (AI) technologies, which drive these systems. This project will address the need for a more robust computer science and engineering workforce by broadening access to microelectronics and AI education leveraging the cutting-edge technologies of Tiny Machine Learning and low-cost microcontroller systems in diverse high schools. The goal of this project is to engage high-school students and teachers from underresourced communities in the design and creative application of AI-enabled smart, embedded technologies, while supporting their engineering identity development and preparing them for the STEM jobs of tomorrow.

This research investigates how state-of-the-art creative and pedagogical agents can improve students' learning, attitudes, and engagement with computer science. The project will be conducted in high school classrooms using EarSketch, an online computer science learning environments that engages learners in making music with JavaScript or Python code. The researchers will build the first co-creative learning companion, Cai, that will scaffold students with pedagogical strategies that include making use of learner code to illustrate abstraction and modularity, suggesting new code to scaffold new concepts, providing help and hints, and explaining its decisions.