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Kole Norberg; Husni Almoubayyed; Stephen E. Fancsali; Logan De Ley; Kyle Weldon; April Murphy; Steve Ritter – Grantee Submission, 2023
Large Language Models have recently achieved high performance on many writing tasks. In a recent study, math word problems in Carnegie Learning's MATHia adaptive learning software were rewritten by human authors to improve their clarity and specificity. The randomized experiment found that emerging readers who received the rewritten word problems…
Descriptors: Word Problems (Mathematics), Mathematics Instruction, Artificial Intelligence, Intelligent Tutoring Systems
Matthew A. Kraft; Virginia S. Lovison – Annenberg Institute for School Reform at Brown University, 2024
Budget constraints and limited supplies of local tutors have caused many K-12 school districts to pivot from individual tutoring in-person toward small-group tutoring online to expand access to personalized instruction. We conduct a field experiment to explore the effect of increasing student-tutor ratios on middle school students' math…
Descriptors: Tutoring, Teacher Student Ratio, Middle School Students, Small Group Instruction
Mark Duffy; Kri Burkander – Annenberg Institute for School Reform at Brown University, 2024
Drawing on qualitative data collected in a sample of colleges as part of a larger study on the implementation and impact of Assembly Bill 705 in California, this paper explores the rollout of corequisite reforms, focusing on the use of embedded tutors in introductory math and English courses as a strategy to meet to the needs of students. This…
Descriptors: Community Colleges, Community College Students, Tutoring, Mathematics Instruction
Mark Duffy; Kri Burkander – Annenberg Institute for School Reform at Brown University, 2024
Drawing on qualitative data collected in a sample of colleges as part of a larger study on the implementation and impact of Assembly Bill 705 in California, this paper explores the rollout of corequisite reforms, focusing on the use of embedded tutors in introductory math and English courses as a strategy to meet to the needs of students. This…
Descriptors: Community Colleges, Community College Students, Tutoring, Mathematics Instruction
Shih, Shu-Chuan; Chang, Chih-Chia; Kuo, Bor-Chen; Huang, Yu-Han – Education and Information Technologies, 2023
A one-on-one dialogue-based mathematics intelligent tutoring system (ITS) for learning multiplication and division of fractions was developed and evaluated in this study. This system could identify students' error types and misconceptions in real-time by using a block-based matching method. The adaptive dialogue-based instruction was supported by…
Descriptors: Mathematics Instruction, Intelligent Tutoring Systems, Multiplication, Division
Mills, Melissa; Rickard, Brian; Guest, Bob – International Journal of Mathematical Education in Science and Technology, 2022
Mathematics tutoring centres exist in varying forms at universities across the United States of America. Despite having similar goals, these centres vary a great deal in their practices, resources, and organizational structures. In this study, the researchers conducted a survey of mathematics tutoring centres in the United States in an effort to…
Descriptors: Tutoring, Mathematics Instruction, Tutorial Programs, Program Effectiveness
Husni Almoubayyed; Rae Bastoni; Susan R. Berman; Sarah Galasso; Megan Jensen; Leila Lester; April Murphy; Mark Swartz; Kyle Weldon; Stephen E. Fancsali; Jess Gropen; Steve Ritter – Grantee Submission, 2023
We present a recent randomized field trial delivered in Carnegie Learning's MATHia's intelligent tutoring system to a sample of 12,374 learners intended to test whether rewriting content in a selection of so-called "word problems" improves student mathematics performance within this content, especially among students who are emerging as…
Descriptors: Word Problems (Mathematics), Intelligent Tutoring Systems, Mathematics Achievement, English Learners
Linxuan Yi; Di Liu; Tiancheng Jiang; Yucheng Xian – International Journal of Science and Mathematics Education, 2025
Artificial intelligence (AI) shows increasing potential to improve mathematics instruction, yet integrative quantitative evidence currently is lacking on its overall effectiveness and factors influencing success. This systematic review and meta-analysis investigate the effectiveness of AI on improving mathematics performance in K-12 classrooms…
Descriptors: Program Effectiveness, Artificial Intelligence, Technology Uses in Education, Elementary School Students
Kylie Flynn; Alice Klein; Jaime Thomas; Ruchita Patel; Sierra Eisen – Society for Research on Educational Effectiveness, 2024
Background: Early math knowledge is the strongest predictor of later academic achievement (Duncan et al., 2007), but math achievement gaps that are present during preschool prior to kindergarten entry (Starkey & Klein, 2008) persist in elementary school. This is especially true for young children who are very low-performing in math relative to…
Descriptors: Mathematics Instruction, Mathematics Skills, Tutoring, COVID-19
Deacon, Grady; Chojnacki, Greg – Mathematica, 2023
UPchieve is a free online and on-demand tutoring platform for students in grades 8 to 12 who attend Title I schools where large shares of students are experiencing poverty. UPchieve matches students with unpaid volunteer tutors one on one and in an online setting. In this setting, students can take advantage of a chat feature and virtual…
Descriptors: High School Students, Grade 9, Grade 10, Tutoring
DeJarnette, Anna Fricano; Hord, Casey – Teacher Education and Special Education, 2022
Posing questions is a direct way for teachers to push students to verbalize justifications and make connections among ideas--a crucial component of giving students with learning disabilities access to high levels of mathematical reasoning--but this skill is difficult to learn. We recruited four pre-service special education teachers to provide 1-1…
Descriptors: Questioning Techniques, Preservice Teachers, Special Education Teachers, Algebra
Benz, Sarah A.; Powell, Sarah R. – Remedial and Special Education, 2021
Some elementary students may exhibit challenging externalizing or internalizing behaviors in addition to difficulty with mathematics. In this study, we explored the behavioral patterns of 441 third-grade students with and without mathematics difficulty (MD). Compared with students without MD, students with MD demonstrated higher rates of…
Descriptors: Word Problems (Mathematics), Intervention, Mathematics Instruction, Learning Problems
Benz, Sarah A.; Powell, Sarah R. – Grantee Submission, 2021
Some elementary students may exhibit challenging externalizing or internalizing behaviors in addition to difficulty with mathematics. In this study, we explored the behavioral patterns of 441 3rd-grade students with and without mathematics difficulty (MD). Compared to students without MD, students with MD demonstrated higher rates of externalizing…
Descriptors: Word Problems (Mathematics), Intervention, Mathematics Instruction, Learning Problems
Maniktala, Mehak; Cody, Christa; Isvik, Amy; Lytle, Nicholas; Chi, Min; Barnes, Tiffany – Journal of Educational Data Mining, 2020
Determining "when" and "whether" to provide personalized support is a well-known challenge called the assistance dilemma. A core problem in solving the assistance dilemma is the need to discover when students are unproductive so that the tutor can intervene. Such a task is particularly challenging for open-ended domains, even…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Helping Relationship, Prediction
Gortazar, Lucas; Hupkau, Claudia; Roldán, Antonio – Centre for Economic Performance, 2023
We provide evidence from a randomized controlled trial on the effectiveness of a novel, 100-percent online math tutoring program, targeted at secondary school students from highly disadvantaged neighborhoods. The intensive, eight-week-long program was delivered by qualified math teachers in groups of two students during after-school hours. The…
Descriptors: Tutoring, Computer Mediated Communication, Electronic Learning, At Risk Students