Project Grant 2327447
- This $199,503 Project Grant awarded by the National Science Foundation (NSF) under the STEM Education (CFDA 47.076) program will fund a large-scale, mixed-methods study to understand perceptions and use of artificial intelligence (AI) technologies in K-12 education. The one-year project will survey a nationally representative sample of parents, teachers, and youth to identify opportunities, risks, and supports needed for integrating AI-driven learning tools. The study will employ both...
- This National Science Foundation project grant of $399,894 will fund the development of an augmented reality tool to support STEM learning for students with executive functioning difficulties. Awarded on September 1, 2022 under the Social, Behavioral, and Economic Sciences program (CFDA 47.075), the grant provides funding to Terc, Inc. through August 31, 2025. Specifically, the grantee will create an open-source tool using deep learning algorithms to detect off-task behavior in undergraduate...
- This Project Grant awarded by the National Science Foundation (NSF) Division of Research on Learning in Formal and Informal Settings supports the development of a network of "tutor observatories" to capture and analyze data on teacher-student interactions in STEM (science, technology, engineering, and mathematics) education. The project, titled "Capturing and Leveraging Data from Teacher-Student Interactions to Improve STEM Learning: An Incubator Project," aims to create a...
- The National Science Foundation (NSF) awarded a $900,000 Project Grant under its STEM Education (CFDA 47.076) program to Northeastern University. The grant, awarded on November 1, 2024, supports the development of an "AI-Empowered Reflective Learning" tool that aims to deepen and accelerate learning through the use of AI-supported prompts and feedback across different interaction contexts, including digital learning environments, virtual reality simulations, and augmented reality...
- The National Science Foundation (NSF) awarded a $250,000 Project Grant under the STEM Education program (CFDA 47.076) to the University of Pittsburgh to conduct collaborative research on enhancing teacher professional learning through AI-enabled formative feedback systems. The project, titled "Collaborative Research [FW-HTF-RL]: Enhancing the Future of Teacher Practice via AI-Enabled Formative Feedback for Job-Embedded Learning", will work with teachers to co-design and test...
- This Project Grant award of $342,906 from the National Science Foundation's STEM Education (CFDA 47.076) program supports research at Rutgers, The State University of New Jersey's Newark campus. The project aims to explore how children's early media experiences shape their expectations for learning from digital media devices, and how those expectations impact their STEM learning outcomes. Using a combination of behavioral, physiological, and computational approaches, the research will examine...
- This $1.7 million project grant from the National Science Foundation's STEM Education program (CFDA 47.076) will fund the development of a novel AI-powered student support system to improve metacognitive calibration skills at the University of Illinois from August 2022 to July 2025. The project aims to research methods for enhancing students' ability to accurately estimate their own level of knowledge using short, personalized training exercises delivered through a decentralized AI framework....
- This $400,000 project grant awarded by the National Science Foundation (NSF) under the STEM Education program (CFDA 47.076) aims to develop and evaluate the T-PRACTISE system, a framework for fostering engaged asynchronous online and hybrid learning among diverse students, such as adult learners. The project plans to: 1) design, implement, and pilot a proof-of-concept T-PRACTISE system to reduce training and engagement disparities in an asynchronous online environment; 2) adapt and extend...
- This $349,999 Project Grant award from the National Science Foundation (NSF) STEM Education program (CFDA 47.076) will support a research project at the University of North Carolina at Chapel Hill (UNC-CH) to investigate how to design and integrate artificial intelligence (AI) to support equitable K-12 science education. The project plans to explore the use of multimodal AI to provide automated feedback for formative science assessments, with the goal of generating design principles to develop...
- This Project Grant award from the National Science Foundation (NSF) under the STEM Education program (CFDA 47.076) provides $900,000 to North Carolina State University to develop innovative, AI-powered online learning environments that promote the learning-by-teaching approach. The project aims to design and empirically evaluate a novel integration of a teachable agent, reinforcement learning, and explainable AI to support students' acquisition of both procedural and conceptual knowledge...
WHEN TEACHERS AREN'T THERE: DETECTING, EVALUATING, AND LEARNING FROM ROTE TEACHING ACROSS DEVELOPMENT -THIS PROJECT EXPLORES THE EFFECTS OF AUTOMATED TEACHING ON CHILDREN?S LEARNING AND DEVELOPMENT. IN CONTRAST TO LIVE, ENGAGED TEACHING, AUTOMATED TEACHING OCCURS WHEN A TEACHER IS NOT WITH THE STUDENT, SUCH AS IN CASES OF ASYNCHRONOUS LEARNING, PRE-RECORDED LECTURES, AND VIRTUAL CLASSROOMS. AUTOMATED TEACHING CAN ALSO INCLUDE IN-PERSON CASES WHEN THE TEACHER IS NOT ACTIVELY ENGAGED OR THINKING ABOUT THE INDIVIDUAL LEARNER?S NEEDS AND BELIEFS. RECENTLY, AND PARTICULARLY SINCE THE COVID-19 PANDEMIC, THE USE OF ASYNCHRONOUS LEARNING, PRE-RECORDED LECTURES, AND VIRTUAL CLASSROOMS IN EDUCATION HAS BEEN ON THE RISE. GIVEN THIS, IT IS CRUCIAL TO UNDERSTAND HOW AND WHY AUTOMATED APPROACHES AFFECT CHILDREN?S LEARNING. THIS PROJECT TAKES A FIRST STEP IN EXPLAINING WHY YOUNG CHILDREN MIGHT LEARN DIFFERENTLY FROM TEACHERS WHO ARE ?NOT REALLY THERE?. THERE ARE MANY BROADER IMPACTS OF THIS WORK. FIRST, RESULTS FROM THIS RESEARCH WILL HELP EXPLAIN HOW TO CONTINUE TO LEVERAGE TECHNOLOGY IN EDUCATION WHILE MAKING SURE CHILDREN?S LEARNING OUTCOMES DO NOT SUFFER AS A RESULT. SECOND, THROUGH SCIENCE COMMUNICATION AND DISSEMINATION EFFORTS, THE PROJECT WILL SPREAD THE WORD ABOUT ITS FINDINGS TO A DIVERSE AUDIENCE OF EDUCATORS, PARENTS, AND RESEARCHERS. THIRD, THIS PROJECT WILL PROVIDE RESEARCH OPPORTUNITIES FOR STUDENTS FROM BACKGROUNDS THAT ARE TYPICALLY UNDERREPRESENTED IN STEM FIELDS. FINALLY, THE PROJECT?S RESEARCH APPROACH WILL DRAW FROM AND INTEGRATE ACROSS MANY DIFFERENT DISCIPLINES, INCLUDING EARLY CHILDHOOD EDUCATION, COGNITIVE DEVELOPMENT, NEUROSCIENCE, AND COMPUTATIONAL MODELING. BY USING A MULTIDISCIPLINARY APPROACH, THE PROJECT WILL ANSWER QUESTIONS ABOUT CHILDREN?S LEARNING FROM AUTOMATED TEACHING FROM MULTIPLE DIFFERENT PERSPECTIVES AND WITH IMPLICATIONS FOR MULTIPLE DIFFERENT FIELDS. THE INCREASING USE OF AUTOMATED APPROACHES IN EDUCATION MAKES IT IMPERATIVE TO UNDERSTAND THEIR IMPACT ON CHILDREN?S LEARNING. PAST WORK IN EDUCATION AND DEVELOPMENTAL PSYCHOLOGY RAISES ONE CAUSE FOR CONCERN: EFFECTIVE TEACHING REQUIRES ENGAGING WITH STUDENTS? REAL-TIME LEARNING GOALS AND INDIVIDUAL NEEDS, WHICH MAY BE DIFFICULT IN LARGE-SCALE AUTOMATIC TEACHING. PUT TOGETHER, THIS LEADS TO A TROUBLING DYNAMIC: STUDENTS WHO DETECT THAT A TEACHER OR SOURCE OF INFORMATION IS ?NOT REALLY THERE?, ENGAGING WITH THEM IN THE MOMENT, MAY BE MORE LIKELY TO DISENGAGE FROM IT, IGNORE IT, AND GENERALLY LEARN LESS FROM IT. VERY LITTLE IS KNOWN ABOUT HOW CHILDREN REASON ABOUT AUTOMATICITY IN TEACHING; EVEN THE MORE BASIC QUESTION OF WHETHER CHILDREN UNDERSTAND THAT SOCIAL PARTNERS IN GENERAL CAN EITHER BE MORE AUTOMATIC AND SCRIPTED, VERSUS REFLECTIVE AND ENGAGED, IS NOT WELL UNDERSTOOD. IN ORDER TO DESIGN FUTURE EDUCATIONAL EXPERIENCES THAT EFFECTIVELY UTILIZE AUTOMATED TEACHING APPROACHES, HOW CHILDREN REASON ABOUT AUTOMATIC BEHAVIOR WHEN LEARNING FROM OTHERS MUST FIRST BE UNDERSTOOD. THEREFORE, THIS PROJECT HAS THREE SPECIFIC AIMS. AIM 1 (THREE STUDIES, N = 430), WILL INVESTIGATE WHETHER LEARNERS NOTICE WHEN TEACHERS ARE ACTING AUTOMATICALLY AND HOW THIS AFFECTS EVALUATIONS OF THEIR TEACHING. AIM 2 (TWO STUDIES, N = 60) WILL ASK HOW LEARNING DIFFERS BETWEEN AUTOMATIC VERSUS REFLECTIVE TEACHING, LEVERAGING BEHAVIORAL AND NEUROLOGICAL METHODS. AIM 3 (TWO STUDIES, N = 180) WILL TEST WHETHER DIFFERENCES IN LEARNING BETWEEN AUTOMATIC AND REFLECTIVE TEACHING COULD BE MITIGATED WITH MINIMAL INTERVENTION. THESE QUESTIONS WILL BE ANSWERED USING BEHAVIORAL EXPERIMENTS AND NEUROLOGICAL MEASURES, WHILE ALSO DRAWING INFLUENCE FROM RESEARCH IN EDUCATION AND COGNITIVE SCIENCE. THE PROJECT WILL RECRUIT PARTICIPANTS FROM A BROAD TARGET AGE RANGE (5- TO 10-YEAR-OLDS), IN ORDER TO UNDERSTAND HOW THESE PROCESSES CHANGE WITH DEVELOPMENT DURING THE FORMATIVE YEARS IN EARLY- TO MIDDLE-CHILDHOOD. THIS PROJECT IS FUNDED BY THE STEM EDUCATION POSTDOCTORAL RESEARCH FELLOWSHIP (STEM ED PRF) PROGRAM THAT AIMS TO ENHANCE THE RESEARCH KNOWLEDGE, SKILLS, AND PRACTICES OF RECENT DOCTORATES IN STEM, STEM EDUCATION, EDUCATION, AND RELATED DISCIPLINES TO ADVANCE THEIR PREPARATION TO ENGAGE IN FUNDAMENTAL AND APPLIED RESEARCH THAT ADVANCES KNOWLEDGE WITHIN THE FIELD. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 7/3/25 | ||
| Not listed | $338.2k | 9/11/23 |