Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 2 |
| Since 2017 (last 10 years) | 2 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Algorithms | 2 |
| Comparative Analysis | 2 |
| Correlation | 2 |
| Learning Analytics | 2 |
| Prediction | 2 |
| Algebra | 1 |
| Anxiety | 1 |
| Behavior Patterns | 1 |
| Computer Assisted Instruction | 1 |
| Computer Games | 1 |
| Concept Formation | 1 |
| More ▼ | |
Source
| Interactive Learning… | 2 |
Author
| Amisha Jindal | 1 |
| Ashish Gurung | 1 |
| Erin Ottmar | 1 |
| Ji-Eun Lee | 1 |
| Reilly Norum | 1 |
| Sanika Nitin Patki | 1 |
| Xia, Xiaona | 1 |
Publication Type
| Journal Articles | 2 |
| Reports - Evaluative | 1 |
| Reports - Research | 1 |
Education Level
| Junior High Schools | 1 |
| Middle Schools | 1 |
| Secondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkXia, Xiaona – Interactive Learning Environments, 2023
The interactive learning is a continuous process, which is full of a large number of learning interaction activities. The data generated between learners and learning interaction activities can reflect the online learning behaviors. Through the correlation analysis among learning interaction activities, this paper discusses the potential…
Descriptors: Behavior Patterns, Learning Analytics, Decision Making, Correlation
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
