Understanding probability is essential for daily life. Probabilistic reasoning is critical in decision making not only for people but also for artificial intelligence (AI). AI sets a modern context to connect probability concepts to real-life situations. It also provides unique opportunities for reciprocal learning that can advance student understanding of both AI systems and probabilistic reasoning. This project aims to improve the current practice of high school probability education and to design AI problem-solving to connect probability and AI concepts. Set in a game-based environment, students learn and practice applying probability theory while exploring the world of probability-based AI algorithms to solve problems that are meaningful and relevant to them.
Projects
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.
Understanding probability is essential for daily life. Probabilistic reasoning is critical in decision making not only for people but also for artificial intelligence (AI). AI sets a modern context to connect probability concepts to real-life situations. It also provides unique opportunities for reciprocal learning that can advance student understanding of both AI systems and probabilistic reasoning. This project aims to improve the current practice of high school probability education and to design AI problem-solving to connect probability and AI concepts. Set in a game-based environment, students learn and practice applying probability theory while exploring the world of probability-based AI algorithms to solve problems that are meaningful and relevant to them.
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.
EarthX is a design-based research project that supports the integration of Earth science into high school biology, chemistry, and physics courses in Baltimore City Public Schools, while also supporting the district’s transition to three-dimensional (3D), ambitious and equitable science teaching aligned with the Next Generation Science Standards (NGSS). EarthX builds on the success of the Integrating Chemistry and Earth Science (ICE) DRK-12 project, which developed innovative chemistry course curriculum materials and PD strategies, to support Earth science integration into biology and physics course curriculum development and 3D teaching. EarthX will develop, test, and refine embedded and unit assessments for all three courses, along with providing an online system for assessment administration; real-time reporting to teachers and students; and provision of data to PD leaders, administrators, and researchers for multiple purposes. Assessments will be 3D, featuring core concepts from both Earth science and the course discipline combined with a science or engineering practice and a crosscutting concept.
Three-dimensional figures can now be represented as diagrams that appear to extend into space in ways that are free of material or physical constraints. They can be rendered at any size, in any orientation, and at any position in space, and can thereby realize a far more varied set of mathematical concepts than what is possible with physical models. The goal of this project is to investigate the transformative educational potential of these representations and to generate a knowledge base that teachers, teacher educators, and researchers can use to reimagine the learning and teaching of geometry.
This project supports the development of a collaborative digital learning environment that embeds rich middle school mathematics tasks. The project aims to understand how students' individual and collaborative engagement in learning mathematics is enhanced by the digital platform, and how student engagement and learning is affected over the course of a year-long seventh grade course.
In this project, the research team will create a computer-mediated design environment that enables students in grades 7-10 to collaboratively explore, make connections, generate, and evaluate design ideas that address environmental science challenges. A unique feature of the project is its use of an artificial intelligent (AI) design mentor that relies on Design Heuristics, a research-based creativity tool that guides students through exploration of ideas and “learns” from students’ design processes to better assist them. The project will examine students’ perceptions of science and engineering, their ability to integrate academic and personal or community knowledge, their confidence for engaging in engineering, and their design thinking.
The project continues and completes the development and refinement of an electronic Test of Early Numeracy (e-TEN) in English and Spanish, focused on number and operations for young learners. The assessment incorporates a learning trajectory approach that describes students' development of the understanding of numbers. The electronic assessment allows for the test to adapt to students' responses and incorporate games increasing children's engagement with the tasks.
This project will investigate the potential of a novel approach to mathematics intervention that leverages the affordances of technology and evidence-based pedagogy to improve mathematics learning for middle school students. The mathematics intervention entitled EMPIRES is a collaborative activity set in Ancient Mesopotamia that offers a multifaceted approach in which (1) rich, narrative math problems increase conceptual comprehension; (2) animated representations of mathematics concepts support mathematical understanding; (3) multiplayer collaboration leads to peer instruction and modeling; (4) simulations offer exciting challenges that increase mathematics resiliency; and (5) a bridge curriculum aids transfer of learning to multiple contexts, including traditional standardized tests.
The project aims to develop and research Intelligent Science Stations, a new genre of interactive science experiences. The Intelligent Science Stations will provide students in kindergarten to 4th grade with hands-on science experiences, augmented by an intelligent agent that offers feedback based on artificial intelligence computer vision. This innovative approach offers evidence-based, personalized support and feedback to children, while also assisting teachers in integrating more inquiry-based science learning into their classrooms. By modeling behaviors like asking questions, making predictions, and explaining scientific phenomena, the interactive AI system helps teachers enhance their classroom experiences.
This project aims to create and test an innovative educational approach for bringing STEM learning experiences to underserved youth. It will co-create and study an outdoor robotic-augmented playground called the “Smart Playground” and a corresponding series of classroom lessons. The Smart Playground will be co-designed with Latinx families and educators to engage children in developing computational thinking skills and learning about robotics in a physical environment using a culturally sustaining approach. Research and evaluation will examine whether exposure to the Smart Playground and corresponding classroom activities have an impact on the development of computational thinking in young children.
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.
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 project aims to create and test an innovative educational approach for bringing STEM learning experiences to underserved youth. It will co-create and study an outdoor robotic-augmented playground called the “Smart Playground” and a corresponding series of classroom lessons. The Smart Playground will be co-designed with Latinx families and educators to engage children in developing computational thinking skills and learning about robotics in a physical environment using a culturally sustaining approach. Research and evaluation will examine whether exposure to the Smart Playground and corresponding classroom activities have an impact on the development of computational thinking in young children.
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.
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 project aims to create and test an innovative educational approach for bringing STEM learning experiences to underserved youth. It will co-create and study an outdoor robotic-augmented playground called the “Smart Playground” and a corresponding series of classroom lessons. The Smart Playground will be co-designed with Latinx families and educators to engage children in developing computational thinking skills and learning about robotics in a physical environment using a culturally sustaining approach. Research and evaluation will examine whether exposure to the Smart Playground and corresponding classroom activities have an impact on the development of computational thinking in young children.
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 project will build an interactive and integrated curricular and professional development technological system: the Building Blocks Toolset (BBToolset). The BBToolset is designed to benefit all early childhood educators and their students. Young children will learn from engaging, effective digital educational games and face-to-face activities. Teachers will receive just-in-time professional development related to their students' development and guidance on curricular choices and culturally sensitive pedagogical strategies.
Teachers are extraordinarily important to student learning, but researchers have surprisingly little data about what teachers do moment-to-moment with students. What are the instructional moves and improvisational responses that characterize highly effective practice? To better understand and support U.S. K-12 STEM teachers, this Incubator project will develop a network of "tutor observatories." Tutor observatories are learning environments that record teacher engagements with students along with information about the context of the interaction. From these data, researchers will be able to gain a deeper understanding of STEM teacher practice, identify highly effective practices, and develop training data that can inform a new generation of artificially intelligent tools to support teachers and student learning.
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.
While more accessible online learning opportunities that reflect everyday teaching challenges are becoming more available, most of these more flexible professional development experiences are being offered by colleges and universities to teachers who are not yet in the classroom. This situation provides an opportunity to explore how innovations in teacher professional development can be woven into school districts’ regular professional development work with its teachers. This partnership development project will create a shared vision and plan for making digitally-based teaching tasks available to elementary math and science teachers so they can learn at any time and from anywhere.
Providing students with exposure to high quality computational thinking (CT) activities within science classes has the possibility to create transformative educational experiences that will prepare students to harness the power of CT for authentic problems. By building upon foundational research in human-AI partnership for classroom support and effective practices for integrating CT in science, this collaborative research project will advance understanding of how to empower teachers to lead computationally enriched science activities with adaptive pedagogical tools.