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Erin Ottmar; Ji-Eun Lee; Kirk Vanacore; Siddhartha Pradhan; Lauren Decker-Woodrow; Craig A. Mason – Grantee Submission, 2023
This paper provides information on datasets for the research project that examined the efficacy of three educational technologies including "From Here to There!", a research-based game for improving algebraic understanding. The dataset contains 4,092 7th-grade students' data collected through a randomized control trial conducted in…
Descriptors: Data, Mathematics Achievement, Algebra, Educational Technology
Jenny Yun-Chen Chan; Avery H. Closser; Vy Ngo; Hannah Smith; Allison S. Liu; Erin Ottmar – Grantee Submission, 2023
Background: Prior work has shown that middle school students struggle with algebra and that game-based educational technologies, such as DragonBox and From Here to There!, are effective at improving students' algebraic performance. However, it remains unclear which aspects of algebraic knowledge shift as a result of playing these games and what…
Descriptors: Game Based Learning, Educational Technology, Mathematics Education, Algebra
Implications of Bias in Automated Writing Quality Scores for Fair and Equitable Assessment Decisions
Michael Matta; Sterett H. Mercer; Milena A. Keller-Margulis – Grantee Submission, 2023
Recent advances in automated writing evaluation have enabled educators to use automated writing quality scores to improve assessment feasibility. However, there has been limited investigation of bias for automated writing quality scores with students from diverse racial or ethnic backgrounds. The use of biased scores could contribute to…
Descriptors: Bias, Automation, Writing Evaluation, Scoring

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
Deborah K. Reed – Grantee Submission, 2023
Middle schools implementing a multi-tiered system of supports will provide adolescents with or at risk for reading difficulties supplemental, small-group reading intervention classes. Although numerous studies have established that peer collaboration, blended learning, differentiation, and sufficient time for instruction are effective practices…
Descriptors: Intervention, Reading Comprehension, Reading Instruction, Middle School Students
Yang Qu; Varun Devakonda; Zeyi Shi; Beiming Yang; Qian Wang – Grantee Submission, 2022
Adolescence is often portrayed in a negative light in Western culture, with teens being viewed as rebellious and irresponsible. Yet, there is substantial cultural and individual variability in views of teens. The empirical research to date is limited in that it mainly examines whether teen stereotypes are influential at the individual level. Teen…
Descriptors: Foreign Countries, Adolescents, Stereotypes, Student Adjustment
S. Andrew Garbacz; Caleb Flack; Qi Huang; Anne Bowen; Elizabeth A. Stormshak; Laura Lee McIntyre – Grantee Submission, 2025
The purpose of this study was to examine the psychometric properties of the parent-report Short Form Positive Family Support Strengths and Needs Assessment (PFS-SaNA). The PFS-SaNA is designed to reduce the time and burden of collaborative mental health screening. Parents of 245 students in the Northwest completed the screener at third, fourth,…
Descriptors: Family Programs, Mental Health, Parents, Elementary School Students
Mingyu Feng; Neil Heffernan; Kelly Collins; Cristina Heffernan; Robert F. Murphy – 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)
Mingyu Feng; Chunwei Huang; Kelly Collins – Grantee Submission, 2023
Math performance continues to be an important focus for improvement. Many districts adopted educational technology programs to support student learning and teacher instruction. The ASSISTments program provides feedback to students as they solve homework problems and automatically prepares reports for teachers about student performance on daily…
Descriptors: Grade 7, Students, Mathematics Instruction, Homework
Yasemin Copur-Gencturk; Jingxian Li; Allan S. Cohen; Chandra Hawley Orrill – Grantee Submission, 2024
Scholars and practitioners have called for personalized and widely accessible professional development (PD) for teachers. Yet, a long-standing tension between customizing support and increasing access to such support has hindered the scale-up of high-quality PD for individual teachers. This study addresses this challenge by developing a…
Descriptors: Professional Development, Electronic Learning, Individualized Instruction, Program Effectiveness
Lauren E. Decker-Woodrow; Craig A. Mason; Ji-Eun Lee; Jenny Yun-Chen Chan; Adam Sales; Allison Liu; Shihfen Tu – Grantee Submission, 2023
The current study investigated the effectiveness of three distinct educational technologies--two game-based applications (From Here to There and DragonBox 12+) and two modes of online problem sets in ASSISTments (an Immediate Feedback condition and an Active Control condition with no immediate feedback) on Grade 7 students' algebraic knowledge.…
Descriptors: Educational Technology, Algebra, COVID-19, Pandemics
Kirk P. Vanacore; Ashish Gurung; Adam C. Sales; Neil T. Heffernan – Grantee Submission, 2024
Gaming the system is a persistent problem in Computer-Based Learning Platforms. While substantial progress has been made in identifying and understanding such behaviors, effective interventions scarce. This study uses a method of causal moderation known as Fully Latent Principal Stratification to explore the impact of two types of interventions --…
Descriptors: Gamification, Student Behavior, Computer Uses in Education, Intervention
Allison Liu; Jenny Yun-Chen Chan; Ji-Eun Lee; Lauren E. Decker-Woodrow; Shihfen Tu; Adam Sales; Craig A. Mason – Grantee Submission, 2022
The current study investigated how prior knowledge moderated the effects of three educational technologies ("From Here to There," "DragonBox 12+," and problem sets in "ASSISTments") on seventh-grade students' later algebraic knowledge. Pretest scores only moderated effects of "From Here to There," with…
Descriptors: Prior Learning, Program Effectiveness, Game Based Learning, Intervention
Ashish Gurung; Morgan P. Lee; Sami Baral; Adam C. Sales; Kirk P. Vanacore; Andrew A. McReynolds; Hilary Kreisberg; Cristina Heffernan; Aaron Haim; Neil T. Heffernan – Grantee Submission, 2023
Solving mathematical problems is cognitively complex, involving strategy formulation, solution development, and the application of learned concepts. However, gaps in students' knowledge or weakly grasped concepts can lead to errors. Teachers play a crucial role in predicting and addressing these difficulties, which directly influence learning…
Descriptors: Error Patterns, Mathematical Applications, Grade 6, Grade 7

Cindy Peng; Conrad Borchers; Vincent Aleven – Grantee Submission, 2024
Prior studies identified effective, but mainly non-digital, homework aids. This research involved 18 middle school students in a lo-fi prototyping study to integrate traditional homework support tools with intelligent tutoring systems (ITS), leveraging rich log data for personalized learning. Feature investigations in standardized diaries, goal…
Descriptors: Middle School Students, Intelligent Tutoring Systems, Homework, Design