Publication Date
In 2025 | 0 |
Since 2024 | 2 |
Since 2021 (last 5 years) | 4 |
Since 2016 (last 10 years) | 4 |
Since 2006 (last 20 years) | 4 |
Descriptor
Algorithms | 4 |
Mathematics Tests | 4 |
Middle School Students | 4 |
Models | 4 |
Scores | 4 |
Algebra | 3 |
Anxiety | 3 |
Comparative Analysis | 3 |
Computer Assisted Instruction | 3 |
Computer Games | 3 |
Concept Formation | 3 |
More ▼ |
Author
Ashish Gurung | 4 |
Amisha Jindal | 3 |
Erin Ottmar | 3 |
Ji-Eun Lee | 3 |
Reilly Norum | 3 |
Sanika Nitin Patki | 3 |
Christopher Santorelli | 1 |
Eamon Worden | 1 |
Neil Heffernan | 1 |
Sami Baral | 1 |
Wen-Chiang Lim | 1 |
More ▼ |
Publication Type
Reports - Research | 4 |
Speeches/Meeting Papers | 2 |
Journal Articles | 1 |
Education Level
Junior High Schools | 4 |
Middle Schools | 4 |
Secondary Education | 4 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Sami Baral; Eamon Worden; Wen-Chiang Lim; Zhuang Luo; Christopher Santorelli; Ashish Gurung; Neil Heffernan – Grantee Submission, 2024
The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…
Descriptors: Automation, Scoring, Computer Assisted Testing, Natural Language Processing
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
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