Projects

Providing computer science (CS) education to students prior to high school is critical for catalyzing their interest in CS and closing achievement and development gaps. However, the retention rate for underrepresented group participants in middle school CS teacher preparation programs is lower than that for their peers. The resulting lack of diversity in CS teachers contributes to students’ inequitable access to quality middle school CS education. In this project will investigate effective design and implementation strategies of CS teacher preparation programs aimed to increase the number of middle school CS teachers from underrepresented groups.

Artificial intelligence (AI) is transforming numerous industries and catalyzing scientific discoveries and engineering innovations. To prepare for an AI-ready workforce, young people must be introduced to core AI concepts and practices early to develop fundamental understandings and productive attitudes. Neural networks, a key approach in AI development, have been introduced to secondary students using various approaches. However, more work is needed to address the interpretability of neural networks and human-machine collaboration in the development process. This exploratory project will develop and test a digital learning tool for secondary students to learn how to interpret neural networks and collaborate with the algorithm to improve AI systems. The learning tool will allow students to interact with complex concepts visually and dynamically. It will also leverage students’ knowledge and intuition of natural languages by contextualizing neural networks in natural language processing systems.

This EAGER project aims to conduct a study designed to operationalize a culturally responsive computing framework, from theory to empirical application, by exploring what factors can be identified and later used to develop items for an instrument to assess youths' self-efficacy and self-perceptions in computing and technology-related fields and careers.

This project will develop a set of educative resources, assessment tools and teacher professional development (PD) activities to support teachers in developing knowledge of CS standards and improving their instructional pedagogy. Teachers will learn to use formative assessments related to these standards to determine student understanding. Improved CS instruction that is responsive to the needs and challenges of the student population is particularly critical in school districts with a large population of students who are typically underserved and under-represented in computer science. The project, a partnership between SRI International and the Milwaukee Public School District, will provide professional development experiences tied to standards instead of a specific curriculum in order to support diverse teachers teaching a variety of computer science curricula using different programming languages. Teachers will receive training via a combination of virtual webinars and face-to-face instruction. Teachers will have opportunities to evaluate their own teaching and measure their students' progress towards the standards.

This project addresses the need for a computationally-enabled STEM workforce by equipping teachers with the skills necessary to prepare students for future endeavors as computationally-enabled scientists and citizens, and by investigating the most effective ways to provide this instruction to teachers. The project also addresses the immediate challenge presented by NGSS to prepare middle school science teachers to implement rich computational thinking experiences within science classes.

This project uses a new theoretical framework that specifies criteria for developing scientific thinking skills that include the value that people place on scientific aims, the cognitive engagement needed to evaluate scientific claims, and the scientific skills that will enable one to arrive at the best supported explanation of a scientific phenomenon. The project will work with high school biology teachers to investigate their own understanding of scientific thinking, how it can be improved through professional development, and how this improvement can translate into practice to support student learning.

This project will study the influence on positive student achievement and engagement (particularly among populations traditionally under-represented in computer science) of an intervention that integrates a computational music remixing tool -EarSketch- with the Computer Science Principles, a view of computing literacy that is emerging as a new standard for Advanced Placement and other high school computer science courses.

Using high school statewide longitudinal data from Maryland from 2012-2022, this study will first document who has taught STEM-CTE courses over this period. After exploring the teaching landscape, the study will then explore whether qualifications (i.e., education, credentials, teaching experience) of teachers in STEM-CTE high school courses were associated with their students’ success.

This project builds on a successful introductory computer science curriculum, called Scratch Encore, to explore ways to support teachers in bringing together—or harmonizing—existing Scratch Encore instructional materials with themes that reflect the interests, cultures, and experiences of their students, schools, and communities. In designing these harmonized lessons, teachers create customized activities that resonate with their students while retaining the structure and content of the original Scratch Encore lesson.

This project builds on a successful introductory computer science curriculum, called Scratch Encore, to explore ways to support teachers in bringing together—or harmonizing—existing Scratch Encore instructional materials with themes that reflect the interests, cultures, and experiences of their students, schools, and communities. In designing these harmonized lessons, teachers create customized activities that resonate with their students while retaining the structure and content of the original Scratch Encore lesson.

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.

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 project will explore PK-2 teachers' content knowledge by investigating their understanding of the design and implementation of culturally relevant computer science learning activities for young children. The project team will design a replicable model of PK-2 teacher professional development to address the lack of research in early computer science education.

This project will design and study new learning environments integrating mathematical and computational thinking. The project will examine how to design learning modules that place mathematics concepts. By exploring how different kinds of designs support learning and engagement, the project will establish a set of design principles for supporting mathematical and computational thinking.

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.

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 addresses a major educational barrier, namely that rural students are less likely to choose a major in STEM and have far less access to advanced STEM courses taught by highly qualified teachers. The LogicDataScience (LogicDS) curriculum and virtual delivery are expected to relieve the resource constraints significantly and thus reach rural students. The strategy behind this curriculum development for data science explores the utility of emphasizing how the foundations of data science in computing, mathematics, and statistics are unified by mathematical logic. The project is studying the impacts of the new curriculum on students’ learning of computing, mathematics, and statistics.

This project addresses a major educational barrier, namely that rural students are less likely to choose a major in STEM and have far less access to advanced STEM courses taught by highly qualified teachers. The LogicDataScience (LogicDS) curriculum and virtual delivery are expected to relieve the resource constraints significantly and thus reach rural students. The strategy behind this curriculum development for data science explores the utility of emphasizing how the foundations of data science in computing, mathematics, and statistics are unified by mathematical logic. The project is studying the impacts of the new curriculum on students’ learning of computing, mathematics, and statistics.

The project will develop and research a new Mixed Reality environment (MR), called GEM-STEP, that leverages play and embodiment as resources for integrating computational modeling into the modeling cycle as part of science instruction for elementary students.

The project will develop and research a new Mixed Reality environment (MR), called GEM-STEP, that leverages play and embodiment as resources for integrating computational modeling into the modeling cycle as part of science instruction for elementary students.

The project will create opportunities for teachers to develop programming content knowledge and new understandings of the creative possibilities in computer science education, thereby increasing opportunities for students to develop conceptual and creative fluency with programming.

The Graphing Research on Inquiry with Data in Science (GRIDS) project will investigate strategies to improve middle school students' science learning by focusing on student ability to interpret and use graphs. GRIDS will undertake a comprehensive program to address the need for improved graph comprehension. The project will create, study, and disseminate technology-based assessments, technologies that aid graph interpretation, instructional designs, professional development, and learning materials.

This project will provide a virtual environment for completing the Food, Energy, and Water (FEW) graduate student experience. The proposed work facilitates a transition from interdisciplinary to transdisciplinary training of existing faculty and current graduate students through a virtual resource center to help develop systematic processes for interdisciplinary thinking about large societal problems, especially those at the nexus of food, energy, and water.