Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 2 |
| Since 2007 (last 20 years) | 6 |
Descriptor
| Models | 7 |
| Pattern Recognition | 7 |
| Data Analysis | 3 |
| Factor Analysis | 3 |
| Information Retrieval | 3 |
| Computer Software | 2 |
| Data Processing | 2 |
| Decision Making | 2 |
| Grades (Scholastic) | 2 |
| Information Seeking | 2 |
| Information Technology | 2 |
| More ▼ | |
Source
| International Educational… | 2 |
| Online Submission | 2 |
| Academic Medicine | 1 |
| Association for Institutional… | 1 |
| International Association for… | 1 |
Author
| Cen, Hao | 2 |
| Koedinger, Kenneth R. | 2 |
| Aswani Yaramala | 1 |
| Chung, Cheng-Yu | 1 |
| Hamid Karimi | 1 |
| Hsiao, I-Han | 1 |
| Levin, Ilya | 1 |
| Michalski, Greg V. | 1 |
| Papa, Frank | 1 |
| Pavlik, Philip I. Jr. | 1 |
| Pavlik, Philip I., Jr. | 1 |
| More ▼ | |
Publication Type
| Speeches/Meeting Papers | 7 |
| Reports - Research | 4 |
| Reports - Evaluative | 2 |
| Journal Articles | 1 |
| Reports - Descriptive | 1 |
Education Level
| Higher Education | 3 |
| Postsecondary Education | 1 |
Audience
Location
| Florida | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Aswani Yaramala; Soheila Farokhi; Hamid Karimi – International Educational Data Mining Society, 2024
This paper presents an in-depth analysis of student behavior and score prediction in the ASSISTments online learning platform. We address four research questions related to the impact of tutoring materials, skill mastery, feature extraction, and graph representation learning. To investigate the impact of tutoring materials, we analyze the…
Descriptors: Student Behavior, Scores, Prediction, Electronic Learning
Chung, Cheng-Yu; Hsiao, I-Han – International Educational Data Mining Society, 2021
The distributed practice effect suggests that students retain learning content better when they pace their practice over time. The key factors are practice dosage (intensity) and timing (when to practice and how in between). Inspired by the thriving development of image recognition, this study adopts one of the successful techniques,…
Descriptors: Models, Drills (Practice), Pacing, Computer Uses in Education
Shafat, Gabriel; Levin, Ilya – International Association for Development of the Information Society, 2012
This paper deals with two types of logical problems--recognition problems and reverse engineering problems, and with the interrelations between these types of problems. The recognition problems are modeled in the form of a visual representation of various objects in a common pattern, with a composition of represented objects in the pattern.…
Descriptors: Foreign Countries, Information Seeking, Online Searching, Search Strategies
Pavlik, Philip I. Jr.; Cen, Hao; Koedinger, Kenneth R. – Online Submission, 2009
This paper describes a novel method to create a quantitative model of an educational content domain of related practice item-types using learning curves. By using a pairwise test to search for the relationships between learning curves for these item-types, we show how the test results in a set of pairwise transfer relationships that can be…
Descriptors: Instructional Design, Test Results, Models, Pattern Recognition
Pavlik, Philip I., Jr.; Cen, Hao; Koedinger, Kenneth R. – Online Submission, 2009
Knowledge tracing (KT)[1] has been used in various forms for adaptive computerized instruction for more than 40 years. However, despite its long history of application, it is difficult to use in domain model search procedures, has not been used to capture learning where multiple skills are needed to perform a single action, and has not been used…
Descriptors: Performance Factors, Factor Analysis, Computer Software, Computer Assisted Instruction
Michalski, Greg V. – Association for Institutional Research (NJ1), 2011
Excessive college course withdrawals are costly to the student and the institution in terms of time to degree completion, available classroom space, and other resources. Although generally well quantified, detailed analysis of the reasons given by students for course withdrawal is less common. To address this, a text mining analysis was performed…
Descriptors: College Instruction, Courses, Withdrawal (Education), College Students
Peer reviewedPapa, Frank; And Others – Academic Medicine, 1990
In this study an artificial intelligence assessment tool used disease-by-feature frequency estimates to create disease prototypes for nine common causes of acute chest pain. The tool then used each subject's prototypes and a pattern-recognition-based decision-making mechanism to diagnose 18 myocardial infarction cases. (MLW)
Descriptors: Artificial Intelligence, Clinical Diagnosis, Construct Validity, Decision Making


