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Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2024
Assessing students' answers and in particular natural language answers is a crucial challenge in the field of education. Advances in transformer-based models such as Large Language Models (LLMs), have led to significant progress in various natural language tasks. Nevertheless, amidst the growing trend of evaluating LLMs across diverse tasks,…
Descriptors: Student Evaluation, Computer Assisted Testing, Artificial Intelligence, Comprehension
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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
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Diana Owen; Alissa Irion-Groth – Grantee Submission, 2024
This study examines the effectiveness of the Center for Civic Education's Project Citizen teacher professional development program and curriculum intervention in producing positive student learning outcomes that support civic engagement. Through Project Citizen, students identify and research a problem in their community, explore solutions,…
Descriptors: Civics, Citizenship Education, Faculty Development, Problem Solving
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Diana Owen – Grantee Submission, 2024
Project-based learning (PBL) is an instructional approach that provides civics, social studies, and American government students with the opportunity to actively and cooperatively engage with real-world issues and situations. Students typically identify a problem in their community or school, research the problem and policy-based solutions,…
Descriptors: Student Projects, Active Learning, Social Studies, Citizen Participation
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Seth A. McCall; Jessica Yusaitis Pike; Ellen B. Meier; Babette Moeller – Grantee Submission, 2024
The general expectation for many successful educational innovations is to "scale up" the project. Based on interviews with participating teachers, facilitators and administrators, this research shares findings from the "scaling up" stage of a federally funded mathematics project designed to help teachers reach a wide range of…
Descriptors: Educational Innovation, Mathematics Education, Faculty Development, Program Design
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Liyang Sun; Eli Ben-Michael; Avi Feller – Grantee Submission, 2024
The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…
Descriptors: Evaluation Methods, Comparative Analysis, Computation, Data Analysis
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Oscar Clivio; Avi Feller; Chris Holmes – Grantee Submission, 2024
Reweighting a distribution to minimize a distance to a target distribution is a powerful and flexible strategy for estimating a wide range of causal effects, but can be challenging in practice because optimal weights typically depend on knowledge of the underlying data generating process. In this paper, we focus on design-based weights, which do…
Descriptors: Evaluation Methods, Causal Models, Error of Measurement, Guidelines
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Feng, Mingyu; Heffernan, Neil; Collins, Kelly; Heffernan, Cristina; Murphy, Robert F. – Grantee Submission, 2023
Math performance continues to be an important focus for improvement. The most recent National Report Card in the U.S. suggested student math scores declined in the past two years possibly due to COVID-19 pandemic and related school closures. We report on the implementation of a math homework program that leverages AI-based one-to-one technology,…
Descriptors: Homework, Artificial Intelligence, Computer Assisted Instruction, Feedback (Response)
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Lee, Hollylynne S.; Thrasher, Emily P.; Grossman, Matt; Mojica, Gemma F.; Graham, Bruce; Kuhlman, Adrian – Grantee Submission, 2023
This paper presents the design of an innovative platform to support teachers' personalized learning related to teaching statistics and data science in grades 6-12 (http://instepwithdata.org). Through a study of 32 pilot users, the authors describe how teachers utilized supports such as personalization surveys, tracking of progress on a dashboard,…
Descriptors: Secondary School Teachers, Faculty Development, Statistics Education, Data Science
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Nicula, Bogdan; Panaite, Marilena; Arner, Tracy; Balyan, Renu; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2023
Self-explanation practice is an effective method to support students in better understanding complex texts. This study focuses on automatically assessing the comprehension strategies employed by readers while understanding STEM texts. Data from 3 datasets (N = 11,833) with self-explanations annotated on different comprehension strategies (i.e.,…
Descriptors: Reading Strategies, Reading Comprehension, Metacognition, STEM Education
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Corlatescu, Dragos; Watanabe, Micah; Ruseti, Stefan; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2023
Reading comprehension is essential for both knowledge acquisition and memory reinforcement. Automated modeling of the comprehension process provides insights into the efficacy of specific texts as learning tools. This paper introduces an improved version of the Automated Model of Comprehension, version 3.0 (AMoC v3.0). AMoC v3.0 is based on two…
Descriptors: Reading Comprehension, Models, Concept Mapping, Graphs
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Oli, Priti; Banjade, Rabin; Narayanan, Arun Balajiee Lekshmi; Brusilovsky, Peter; Rus, Vasile – 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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Morris, Wesley; Crossley, Scott; Holmes, Langdon; Ou, Chaohua; McNamara, Danielle; Dascalu, Mihai – Grantee Submission, 2023
As intelligent textbooks become more ubiquitous in classrooms and educational settings, the need arises to automatically provide formative feedback to written responses provided by students in response to readings. This study develops models to automatically provide feedback to student summaries written at the end of intelligent textbook sections.…
Descriptors: Textbooks, Electronic Publishing, Feedback (Response), Formative Evaluation
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Vanacore, Kirk; Sales, Adam; Liu, Allison; Ottmar, Erin – Grantee Submission, 2023
Computer-assisted learning platforms (CALPS) increasingly include gamified elements to improve student outcomes by enhancing their engagement with content. Although evidence exists that gamified programs increase engagement and learning outcomes, there is little causal research on what programmatic mechanisms drive the effect between engagement…
Descriptors: Educational Games, Gamification, Algebra, Mathematics Instruction
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Herrmann-Abell, Cari F.; DeBoer, George E. – Grantee Submission, 2023
This study describes the role that Rasch measurement played in the development of assessments aligned to the "Next Generation Science Standards," tasks that require students to use the three dimensions of science practices, disciplinary core ideas and cross-cutting concepts to make sense of energy-related phenomena. A set of 27…
Descriptors: Item Response Theory, Computer Simulation, Science Tests, Energy
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