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Nguyen, Huy; Liew, Chun Wai – International Educational Data Mining Society, 2018
Recent works on Intelligent Tutoring Systems have focused on more complicated knowledge domains, which pose challenges in automated assessment of student performance. In particular, while the system can log every user action and keep track of the student's solution state, it is unable to determine the hidden intermediate steps leading to such…
Descriptors: Bayesian Statistics, Intelligent Tutoring Systems, Data Analysis, Error Patterns
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Wang, Zheng; Zhu, Xinning; Huang, Junfei; Li, Xiang; Ji, Yang – International Educational Data Mining Society, 2018
Academic achievement of a student in college always has a far-reaching impact on his further development. With the rise of the ubiquitous sensing technology, students' digital footprints in campus can be collected to gain insights into their daily behaviours and predict their academic achievements. In this paper, we propose a framework named…
Descriptors: Academic Achievement, Prediction, Data Analysis, Student Behavior
Hiljazi, Sam; Curtis, Trevor – Association Supporting Computer Users in Education, 2018
Asking questions about your data is a constant application of all business organizations. To facilitate decision making and improve business performance, a business intelligence application must be an integral part of everyday management practices. Microsoft Excel added PowerPivot and PowerPivot officially to facilitate this process with minimum…
Descriptors: Introductory Courses, Business Administration Education, Business Skills, Spreadsheets
Pornchanok Ruengvirayudh – ProQuest LLC, 2018
Determining the number of dimensions underlying many variables in the data or many items in the test is a crucial process prior to performing exploratory factor analysis. Failure to do so leads to serious consequences concerning construct validity. Parallel analysis (PA) has been found to be useful to determine the number of dimensions (i.e.,…
Descriptors: Monte Carlo Methods, Tests, Data, Sample Size
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Gallagher, Kerry – State Education Standard, 2016
Digital tools are making it easier than ever for teachers to gather and analyze formative data. Paper exit slips can take a classroom teacher upward of an hour to sort and graph after just one day of classes. But now, that same teacher can pose a question out loud to the class and ask students to type answers on their mobile phones and hit send.…
Descriptors: Data Collection, Formative Evaluation, Technology Uses in Education, Handheld Devices
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Nahornick, Ashley – Canadian Journal of Higher Education, 2016
Education matters. Every year, more students are pursuing postsecondary education. In fact, during the 2012-2013 academic year, over two million students were studying in Canadian postsecondary institutions, making it even more important to ensure that our students are getting the education and training they need to succeed. Notably, it is not…
Descriptors: Foreign Countries, Undergraduate Students, College Mathematics, Mathematics Education
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Souto-Otero, Manuel; Beneito-Montagut, Roser – European Educational Research Journal, 2016
The article argues that current discussions about governance through data in education can be fruitfully extended through: (1) the establishment of connections with wider debates about the role of commensuration processes and governmentality in the recreation of education systems; (2) greater emphasis on the "artefacts" through which…
Descriptors: Governance, Data Collection, Government Role, Alignment (Education)
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Mühling, Andreas – Computer Science Education, 2016
Concept maps have a long history in educational settings as a tool for teaching, learning, and assessing. As an assessment tool, they are predominantly used to extract the structural configuration of learners' knowledge. This article presents an investigation of the knowledge structures of a large group of beginning CS students. The investigation…
Descriptors: Concept Mapping, Computer Science Education, Novices, Knowledge Level
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Karakus, Fatih – International Journal for Mathematics Teaching and Learning, 2016
The analysis of pre-service teachers' concept images can provide information about their mental schema of fractal dimension. There is limited research on students' understanding of fractal and fractal dimension. Therefore, this study aimed to investigate the pre-service teachers' understandings of fractal dimension based on concept image. The…
Descriptors: Preservice Teachers, Mathematics Skills, Geometric Concepts, Schemata (Cognition)
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Kinkead, Karl J.; Miller, Heather; Hammett, Richard – Journal of Continuing Higher Education, 2016
Two purposes existed for initiating this qualitative case study involving adults who had completed a college-level business statistics course. The first purpose was to explore adult challenges with stress and anxiety during the course: a phenomenon labeled statistics anxiety in the literature. The second purpose was to gain insight into adult…
Descriptors: College Students, Student Attitudes, Adult Students, Teaching Methods
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Park, Jungkyu; Yu, Hsiu-Ting – Educational and Psychological Measurement, 2016
The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…
Descriptors: Hierarchical Linear Modeling, Nonparametric Statistics, Data Analysis, Simulation
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Krumm, Andrew E.; Beattie, Rachel; Takahashi, Sola; D'Angelo, Cynthia; Feng, Mingyu; Cheng, Britte – Journal of Learning Analytics, 2016
This paper outlines the development of practical measures of productive persistence using digital learning system data. Practical measurement refers to data collection and analysis approaches originating from improvement science; productive persistence refers to the combination of academic and social mindsets as well as learning behaviours that…
Descriptors: Measurement, Persistence, Electronic Learning, Data Analysis
Parker, Emily; Atchison, Bruce; Workman, Emily – Education Commission of the States, 2016
This report highlights significant investments made by both Republican and Democratic policymakers in state-funded pre-k programs for the fourth year in a row. In the 2015-16 budget year, 32 states and the District of Columbia raised funding levels of pre-k programs. This increased support for preschool funding came from both sides of the…
Descriptors: Preschool Education, State Aid, Annual Reports, Trend Analysis
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Liu, Ran; Davenport, Jodi; Stamper, John – International Educational Data Mining Society, 2016
The increasing use of educational technologies in classrooms is producing vast amounts of process data that capture rich information about learning as it unfolds. The field of educational data mining has made great progress in using log data to build models that improve instruction and advance the science of learning. Thus far, however, the…
Descriptors: Educational Technology, Data Analysis, Automation, Data
Akmon, Dharma R. – ProQuest LLC, 2014
This dissertation examines the role of conceptions of data's value in data practices. Based on a study of three small teams of scientists carrying out ecological research at a biological station, my study addresses the following main question: How do scientists conceive of the value of their data, and how do scientists enact conceptions of value…
Descriptors: Case Studies, Scientists, Interviews, Meta Analysis
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