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Nicole M. Hutchins; Gautam Biswas – British Journal of Educational Technology, 2024
This paper provides an experience report on a co-design approach with teachers to co-create learning analytics-based technology to support problem-based learning in middle school science classrooms. We have mapped out a workflow for such applications and developed design narratives to investigate the implementation, modifications and temporal…
Descriptors: Problem Based Learning, Teaching Methods, Science Instruction, Learning Analytics
Peer reviewedDevika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
Dan Zhang – International Journal of Web-Based Learning and Teaching Technologies, 2025
This study explores the application of the task-based teaching method in English education, particularly from the perspective of big data. Traditional English teaching models often fail to meet the diverse needs of students, with the task-based approach, despite being student-centered, encountering challenges such as task difficulty control and…
Descriptors: Task Analysis, Teaching Methods, Learning Analytics, Learner Engagement
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Interactive Learning Environments, 2024
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Zhang, Jiayi; Andres, Juliana Ma. Alexandra L.; Hutt, Stephen; Baker, Ryan S.; Ocumpaugh, Jaclyn; Mills, Caitlin; Brooks, Jamiella; Sethuraman, Sheela; Young, Tyron – International Educational Data Mining Society, 2022
Self-regulated learning (SRL) is a critical component of mathematics problem solving. Students skilled in SRL are more likely to effectively set goals, search for information, and direct their attention and cognitive process so that they align their efforts with their objectives. An influential framework for SRL, the SMART model, proposes that…
Descriptors: Mathematics Instruction, Teaching Methods, Problem Solving, Metacognition
Natalie Brezack; Wynnie Chan; Mingyu Feng – Grantee Submission, 2024
This paper explores how learning analytics data provided by a math problem-solving educational technology platform informed 5th and 6th grade teachers' instructional decisions around socioemotional learning (SEL). MathSpring is an educational technology tool that provides teachers with data on students' effort, progress, and emotions while…
Descriptors: Social Emotional Learning, Mathematics Instruction, Teacher Attitudes, Comparative Analysis
Lee, Ji-Eun; Chan, Jenny Yun-Chen; Botelho, Anthony; Ottmar, Erin – Educational Technology Research and Development, 2022
Online educational games have been widely used to support students' mathematics learning. However, their effects largely depend on student-related factors, the most prominent being their behavioral characteristics as they play the games. In this study, we applied a set of learning analytics methods (k-means clustering, data visualization) to…
Descriptors: Computer Games, Educational Games, Mathematics Instruction, Learning Processes
Lee, Ji-Eun; Chan, Jenny Yun-Chen; Botelho, Anthony; Ottmar, Erin – Grantee Submission, 2022
Online educational games have been widely used to support students' mathematics learning. However, their effects largely depend on student-related factors, the most prominent being their behavioral characteristics as they play the games. In this study, we applied a set of learning analytics methods ("k"-means clustering, data…
Descriptors: Computer Games, Educational Games, Mathematics Instruction, Learning Processes
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2023
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2022
This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Lee, Ji-Eun; Hornburg, Caroline Byrd; Chan, Jenny Yun-Chen; Ottmar, Erin – Grantee Submission, 2021
We investigated the effects of proximal grouping of numbers, problem-solving goals to make 100, and prior knowledge on students' solution strategies in an online mathematics game. Logistic regression on 857 problem-level data points from 227 middle-school students showed that students were more likely to use productive solution strategies on…
Descriptors: Mathematics Instruction, Teaching Methods, Middle School Students, Computer Games
Yang, Kexin Bella; Echeverria, Vanessa; Wang, Xuejian; Lawrence, LuEttaMae; Holstein, Kenneth; Rummel, Nikol; Aleven, Vincent – International Educational Data Mining Society, 2021
Constructing effective and well-balanced learning groups is important for collaborative learning. Past research explored how group formation policies affect learners' behaviors and performance. With the different classroom contexts, many group formation policies work in theory, yet their feasibility is rarely investigated in authentic class…
Descriptors: Grouping (Instructional Purposes), Cooperative Learning, Teaching Methods, Kindergarten
Cook, Michael; Ross, Steven M. – Center for Research and Reform in Education, 2022
The purpose of this evaluation was to examine the impact of i-Ready Personalized Instruction that met Curriculum Associates' recommended usage levels on mathematics achievement, as measured by the Massachusetts Comprehensive Assessment System (MCAS) mathematics assessment. This study compared mathematics achievement growth of students who used…
Descriptors: Mathematics Achievement, Mathematics Instruction, Program Evaluation, Individualized Instruction
Cook, Michael; Ross, Steven M. – Center for Research and Reform in Education, 2022
The purpose of this evaluation was to examine the impact of i-Ready Personalized Instruction that met Curriculum Associates' recommended usage levels on ELA achievement, as measured by the Massachusetts Comprehensive Assessment System (MCAS) ELA assessment. This study compared the ELA achievement growth in the 2020-21 school year of students who…
Descriptors: English, Language Arts, Computer Assisted Instruction, Computer Assisted Testing
Resende, Isabel – ProQuest LLC, 2018
Access to technology in schools has increased dramatically over the past several years, and in turn teachers have had to think differently about their instructional practice. With ubiquitous computing, students access information, create information, share information, and communicate with peers without the confines of time and space (Glazatov,…
Descriptors: Access to Information, Action Research, Learning Analytics, Teaching Methods
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