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.
Projects
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.
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.
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 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.
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 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 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 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.
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.
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.
The focus of this project is the design of learning experiences in different high school science courses to help students gain experience in computational thinking. The project uses a partnership between two universities and school district to develop and refine the units as a collaboration between researchers, teachers, and school leaders. The goal is to help all students have opportunities to learn about computational thinking in multiple science courses.
The focus of this project is the design of learning experiences in different high school science courses to help students gain experience in computational thinking. The project uses a partnership between two universities and school district to develop and refine the units as a collaboration between researchers, teachers, and school leaders. The goal is to help all students have opportunities to learn about computational thinking in multiple science courses.
This project will study a model of pre-service teacher preparation that is designed to to increase teachers' and students' skills and confidence with computational thinking and develop teachers as designers of inclusive learning environments to promote computational thinking. The project will engage elementary (grades K-5) pre-service teachers (who are concurrently involved in school-based teacher preparation programs) as facilitators in an existing family technology program called Family Creative Learning (FCL).
This project will address the need for engineering resources by applying an innovative pedagogy called Imaginative Education (IE) to create middle school engineering curricula. In IE, developmentally appropriate narratives are used to design learning environments that help learners engage with content and organize their knowledge productively. This project will combine IE with transmedia storytelling.
This project will address the need for engineering resources by applying an innovative pedagogy called Imaginative Education (IE) to create middle school engineering curricula. In IE, developmentally appropriate narratives are used to design learning environments that help learners engage with content and organize their knowledge productively. This project will combine IE with transmedia storytelling.
This five-year project investigates how to provide continuous assessment and feedback to guide students' understanding during science inquiry-learning experiences, as well as detailed guidance to teachers and administrators through a technology-enhanced system. The assessment system integrates validated automated scorings for students' written responses to open-ended assessment items into the "Web-based Inquiry Science Environment" (WISE) program.
This project will examine the relationships among the factors that influence the implementation of the Exploring Computer Science (ECS), a pre-Advanced Placement curriculum that prepares students for further study in computer science. This study elucidates how variation in curricular implementation influences student learning and determines not only what works, but also for whom and under what circumstances.
This project aims to engage students in meaningful scientific data collection, analysis, visualization, modeling, and interpretation. It targets grades 9-12 science instruction. The proposed research poses the question "How do learners conceive of and interact with empirical data, particularly when it has a hierarchical structure in which parameters and results are at one level and raw data at another?"
This project builds on prior efforts to create teaching resources for high-school Advanced Placement Statistics teachers to use an open source statistics programming language called "R" in their classrooms. The project brings together datasets from a variety of STEM domains, and will develop exercises and assessments to teach students how to program in R and learn the underlying statistics concepts.
Computational and algorithmic thinking are new basic skills for the 21st century. Unfortunately few K-12 schools in the United States offer significant courses that address learning these skills. However many schools do offer robotics courses. These courses can incorporate computational thinking instruction but frequently do not. This research project aims to address this problem by developing a comprehensive set of resources designed to address teacher preparation, course content, and access to resources.
The project at Spelman College includes activities that develop computational thinking and encourage middle school, African-American girls to consider careers in computer science. Over a three-year period, the girls attend summer camp sessions of two weeks where they learn to design interactive games. Experts in Computational Algorithmic Thinking as well as undergraduate, computer science majors at Spelman College guide the middle-school students in their design of games and exploration of related STEM careers.
This project will study the effect of integrating computing into preservice teacher programs. The project will use design-based research to explore how to connect computing concepts and integration activities to teachers' subject area knowledge and teaching practice, and which computing concepts are most valuable for general computational literacy.
This project focuses on fostering equitable and inclusive STEM contexts with attention to documenting and reducing adolescents' experiences of harassment, bias, prejudice and stereotyping. This research will contribute to understanding of the current STEM educational climates in high schools and will help to identify factors that promote resilience in the STEM contexts, documenting how K-12 educators can structure their classrooms and schools to foster success of all students in STEM classes.