Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 2 |
| Since 2016 (last 10 years) | 2 |
| Since 2006 (last 20 years) | 2 |
Descriptor
Author
| Butcher, Kirsten R. | 1 |
| Hudson, Michelle A. | 1 |
| Karimov, Ayaz | 1 |
| Kärkkäinen, Tommi | 1 |
| Larson, Madlyn | 1 |
| Orr, Matthew | 1 |
| Poitras, Eric | 1 |
| Saarela, Mirka | 1 |
Publication Type
| Reports - Research | 2 |
| Journal Articles | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
| Junior High Schools | 2 |
| Middle Schools | 2 |
| Secondary Education | 2 |
| Elementary Education | 1 |
| Grade 5 | 1 |
| Grade 6 | 1 |
| Grade 7 | 1 |
| Intermediate Grades | 1 |
Audience
Location
| Azerbaijan | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkPoitras, Eric; Butcher, Kirsten R.; Orr, Matthew; Hudson, Michelle A.; Larson, Madlyn – Interactive Learning Environments, 2022
This study mined student interactions with visual representations as a means to automate assessment of learning in a complex, inquiry-based learning environment. Log trace data of 143 middle school students' interactions with an interactive map in Research Quest (an inquiry-based, online learning environment) were analyzed. Students used the…
Descriptors: Middle School Students, Electronic Learning, Maps, Science Instruction
Download full textKarimov, Ayaz; Saarela, Mirka; Kärkkäinen, Tommi – International Educational Data Mining Society, 2023
Within the last decade, different educational data mining techniques, particularly quantitative methods such as clustering, and regression analysis are widely used to analyze the data from educational games. In this research, we implemented a quantitative data mining technique (clustering) to further investigate students' feedback. Students played…
Descriptors: Student Attitudes, Feedback (Response), Educational Games, Information Retrieval
