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Liu, Ran; Stamper, John; Davenport, Jodi – Grantee Submission, 2018
Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…
Descriptors: Intelligent Tutoring Systems, Learning, Data Analysis, Student Development
Ting, Choo-Yee; Ho, Chiung Ching – British Journal of Educational Technology, 2015
This paper presents the dataset collected from student interactions with INQPRO, a computer-based scientific inquiry learning environment. The dataset contains records of 100 students and is divided into two portions. The first portion comprises (1) "raw log data", capturing the student's name, interfaces visited, the interface…
Descriptors: Inquiry, Educational Environment, Scientific Methodology, Interaction
Levy, Sharona T.; Wilensky, Uri – Computers & Education, 2011
This study lies at an intersection between advancing educational data mining methods for detecting students' knowledge-in-action and the broader question of how conceptual and mathematical forms of knowing interact in exploring complex chemical systems. More specifically, it investigates students' inquiry actions in three computer-based models of…
Descriptors: Test Content, Mathematical Models, Prior Learning, Data Processing
Madhyastha, Tara; Hunt, Earl – Journal of Educational Data Mining, 2009
This paper introduces a method for mining multiple-choice assessment data for similarity of the concepts represented by the multiple choice responses. The resulting similarity matrix can be used to visualize the distance between concepts in a lower-dimensional space. This gives an instructor a visualization of the relative difficulty of concepts…
Descriptors: Diagnostic Tests, Multiple Choice Tests, Concept Formation, Schematic Studies
Peer reviewedRushinek, Avi; And Others – AEDS Journal, 1982
Describes the methodology and procedures, as well as the findings of an investigation of the relationship between the use of computer-assisted instruction and students' attitudes toward the instructor and the course in the teaching of undergraduate business data processing. An 11-item bibliography and a copy of the survey are included. (JL)
Descriptors: Business, Comparative Analysis, Computer Assisted Instruction, Course Evaluation

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