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Showing 1 to 15 of 19 results Save | Export
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Clayton Cohn; Surya Rayala; Caitlin Snyder; Joyce Horn Fonteles; Shruti Jain; Naveeduddin Mohammed; Umesh Timalsina; Sarah K. Burriss; Ashwin T. S.; Namrata Srivastava; Menton Deweese; Angela Eeds; Gautam Biswas – Grantee Submission, 2025
Collaborative dialogue offers rich insights into students' learning and critical thinking. This is essential for adapting pedagogical agents to students' learning and problem-solving skills in STEM+C settings. While large language models (LLMs) facilitate dynamic pedagogical interactions, potential hallucinations can undermine confidence, trust,…
Descriptors: STEM Education, Computer Science Education, Artificial Intelligence, Natural Language Processing
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Jessica Brown; Jacqueline DeLisi; Lukas Winfield; Makoto Hanita; Anne Wang – Grantee Submission, 2025
The EIR-funded Work-Based Learning for Computer Science (WBL4CS) grant implemented a three-course, two-year Computer Science (CS) pathway in 20 Rhode Island High Schools. Evaluators from Education Development Center (EDC) employed a cluster randomized controlled trial to study the impact of integrating a Work-Based Learning course into the first…
Descriptors: Work Based Learning, Computer Science Education, High School Students, Career Pathways
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Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages
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Arun-Balajiee Lekshmi-Narayanan; Priti Oli; Jeevan Chapagain; Mohammad Hassany; Rabin Banjade; Vasile Rus – Grantee Submission, 2024
Worked examples, which present an explained code for solving typical programming problems are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide…
Descriptors: Coding, Computer Science Education, Computational Linguistics, Artificial Intelligence
Saira Anwar; Ahmed Ashraf Butt; Muhsin Menekse – Grantee Submission, 2023
This study explored the effectiveness of scaffolding in students' reflection writing process. We compared two sections of an introductory computer programming course (N=188). In Section 1, students did not receive any scaffolding while generating reflections, whereas in Section 2, students were scaffolded during the reflection writing process.…
Descriptors: Scaffolding (Teaching Technique), Writing Instruction, Writing Processes, Writing (Composition)
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Jacqueline DeLisi; Jessica Brown; Lukas Winfield; Makoto Hanita; Anne Wang – Grantee Submission, 2025
In 2019, the Rhode Island Department of Education (RIDE), in partnership with the University of Rhode Island (URI), launched the Work-Based Learning for Computer Science (WBL4CS) project through an Education Innovation Research (EIR) grant. The initiative aimed to expand access to computer science (CS) education for high school students,…
Descriptors: Work Based Learning, Computer Science Education, High School Students, Career Pathways
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Stephen Hiller; Jessica Campbell; Patricia Muller; Anne-Maree Ruddy – Grantee Submission, 2024
The Green River Regional Educational Cooperative (GRREC) and its partners administered the STEM-CS intervention to support the professional learning of middle and high school STEM teachers in rural southcentral Kentucky counties. The goals of the STEM-CS intervention were to improve teacher STEM-CS knowledge, practice, implementation, and…
Descriptors: High School Teachers, Rural Schools, Faculty Development, STEM Education
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Kathy Dowell; Catherine Snyder; Stephanie Marshall – Grantee Submission, 2025
METRICS was a 5-year grant program funded by the U.S. Department of Education designed to immerse elementary school students in computer science. METRICS components included 1) creation and implementation of rigorous computer science curriculum units and assessments to support STEM coursework connected across all subjects through problem-based…
Descriptors: Computer Science Education, Elementary School Curriculum, STEM Education, Problem Based Learning
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Priti Oli; Rabin Banjade; Arun Balajiee Lekshmi Narayanan; Peter Brusilovsky; Vasile Rus – Grantee Submission, 2023
Self-efficacy, or the belief in one's ability to accomplish a task or achieve a goal, can significantly influence the effectiveness of various instructional methods to induce learning gains. The importance of self-efficacy is particularly pronounced in complex subjects like Computer Science, where students with high self-efficacy are more likely…
Descriptors: Computer Science Education, College Students, Self Efficacy, Programming
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Janice D. Gobert; Haiying Li; Rachel Dickler; Christine Lott – Grantee Submission, 2024
An intelligent tutoring system (ITS, henceforth) is currently defined as a computer system that delivers personalized instruction to students by using computational techniques to evaluate the learner in a variety of ways, including (but not limited to) their prior knowledge, competency/skill levels, motivation, and affective states. ITSs are…
Descriptors: Artificial Intelligence, Scaffolding (Teaching Technique), Computer Science Education, Teaching Methods
Allen, Laura K.; Creer, Sarah D.; Poulos, Mary Cati – Grantee Submission, 2021
Research in discourse processing has provided us with a strong foundation for understanding the characteristics of text and discourse, as well as their influence on our processing and representation of texts. However, recent advances in computational techniques have allowed researchers to examine discourse processes in new ways. The purpose of the…
Descriptors: Natural Language Processing, Computation, Discourse Analysis, Computer Science
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Sarah K. Mason; Matt Hancock; Izzy Thornton – Grantee Submission, 2024
Rural Mississippi schools often face challenges in providing equitable access to Advanced Placement (AP) courses, particularly in STEM fields. This lack of access limits opportunities for high-achieving students to pursue rigorous STEM coursework and related careers. The AP STEM program aims to improve access to AP STEM courses for high-achieving…
Descriptors: Rural Schools, STEM Education, Advanced Placement Programs, Access to Education
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Joseph R. Cimpian; Jo R. King – Grantee Submission, 2024
Men significantly outnumber women in physics, engineering, and computer science (PECS) majors, with a recent male-to-female ratio of approximately 4:1, a stark contrast to the near parity in other science, technology, engineering, and mathematics (STEM) disciplines (1). This gender disparity in PECS carries wide-reaching implications for equity,…
Descriptors: Gender Differences, Physics, Engineering Education, Computer Science Education
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Grantee Submission, 2024
Recruiting schools to participate in research projects has become increasingly challenging in the past several years. Research in schools was next-to-impossible during the COVID-19 pandemic, and the aftermath of the pandemic has made research a lower priority for schools trying to regain COVID-related academic losses. The School Recruitment…
Descriptors: Research Projects, COVID-19, Pandemics, Guides
Master, Allison; Meltzoff, Andrew N.; Cheryan, Sapna – Grantee Submission, 2021
Societal stereotypes depict girls as less interested than boys in computer science and engineering. We demonstrate the existence of these stereotypes among children and adolescents from first to 12th grade and their potential negative consequences for girls' subsequent participation in these fields. Studies 1 and 2 (n = 2,277; one preregistered)…
Descriptors: Sex Stereotypes, Student Interests, Gender Discrimination, Computer Science
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