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Zirou Lin; Hanbing Yan; Li Zhao – Journal of Computer Assisted Learning, 2024
Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…
Descriptors: Peer Evaluation, Automation, Grading, Models
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Abulela, Mohammed A. A.; Harwell, Michael M. – Educational Sciences: Theory and Practice, 2020
Data analysis is a significant methodological component when conducting quantitative education studies. Guidelines for conducting data analyses in quantitative education studies are common but often underemphasize four important methodological components impacting the validity of inferences: quality of constructed measures, proper handling of…
Descriptors: Educational Research, Educational Researchers, Novices, Data Analysis
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Raj, Gaurav; Mahajan, Manish; Singh, Dheerendra – International Journal of Web-Based Learning and Teaching Technologies, 2020
In secure web application development, the role of web services will not continue if it is not trustworthy. Retaining customers with applications is one of the major challenges if the services are not reliable and trustworthy. This article proposes a trust evaluation and decision model where the authors have defined indirect attribute, trust,…
Descriptors: Trust (Psychology), Models, Decision Making, Computer Software
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Soland, James – Research & Practice in Assessment, 2017
Research shows college readiness can be predicted using a variety of measures, including test scores, grades, course-taking patterns, noncognitive instruments, and surveys of how well students understand the college admissions process. However, few studies provide guidance on how educators can prioritize predictors of college readiness across…
Descriptors: College Readiness, Predictor Variables, Data Analysis, Measures (Individuals)
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Capuano, Nicola; Loia, Vincenzo; Orciuoli, Francesco – IEEE Transactions on Learning Technologies, 2017
Massive Open Online Courses (MOOCs) are becoming an increasingly popular choice for education but, to reach their full extent, they require the resolution of new issues like assessing students at scale. A feasible approach to tackle this problem is peer assessment, in which students also play the role of assessor for assignments submitted by…
Descriptors: Participative Decision Making, Models, Peer Evaluation, Online Courses
Castro, Francisco Enrique Vicente; Adjei, Seth; Colombo, Tyler; Heffernan, Neil – International Educational Data Mining Society, 2015
A great deal of research in educational data mining is geared towards predicting student performance. Bayesian Knowledge Tracing, Performance Factors Analysis, and the different variations of these have been introduced and have had some success at predicting student knowledge. It is worth noting, however, that very little has been done to…
Descriptors: Models, Student Behavior, Intelligent Tutoring Systems, Data Analysis
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Oversby, John – Education in Science, 2014
Education research is an academic activity, and is often carried out by teachers (see, for example, Lavonen & Reinikainen, 2014). Lavonen and Reinikainen report that Finnish teachers are required to have a Masters degree involving education research. In the UK, the PGCE and its equivalent, from a schools-HEI partnership, usually carries…
Descriptors: Science Instruction, Teaching Methods, Visual Aids, Protocol Analysis
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Zarkadis, Nikolaos; Papageorgiou, George; Stamovlasis, Dimitrios – Chemistry Education Research and Practice, 2017
Science education research has revealed a number of student mental models for atomic structure, among which, the one based on Bohr's model seems to be the most dominant. The aim of the current study is to investigate the coherence of these models when students apply them for the explanation of a variety of situations. For this purpose, a set of…
Descriptors: Cognitive Structures, Schemata (Cognition), Models, Nuclear Physics
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Liu, Ran; Koedinger, Kenneth R. K – International Educational Data Mining Society, 2017
Research in Educational Data Mining could benefit from greater efforts to ensure that models yield reliable, valid, and interpretable parameter estimates. These efforts have especially been lacking for individualized student-parameter models. We collected two datasets from a sizable student population with excellent "depth" -- that is,…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Bayesian Statistics, Pretests Posttests
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Pelanek, Radek – Journal of Educational Data Mining, 2015
Researchers use many different metrics for evaluation of performance of student models. The aim of this paper is to provide an overview of commonly used metrics, to discuss properties, advantages, and disadvantages of different metrics, to summarize current practice in educational data mining, and to provide guidance for evaluation of student…
Descriptors: Models, Data Analysis, Data Processing, Evaluation Criteria
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Yeo, Seungsoo; Kim, Dong-Il; Branum-Martin, Lee; Wayman, Miya Miura; Espin, Christine A. – Journal of School Psychology, 2012
The purpose of this study was to demonstrate the use of Latent Growth Modeling (LGM) as a method for estimating reliability of Curriculum-Based Measurement (CBM) progress-monitoring data. The LGM approach permits the error associated with each measure to differ at each time point, thus providing an alternative method for examining of the…
Descriptors: Curriculum Based Assessment, Models, Reliability, Measurement
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Ruscio, John; Walters, Glenn D.; Marcus, David K.; Kaczetow, Walter – Psychological Assessment, 2010
A number of recent studies have used Meehl's (1995) taxometric method to determine empirically whether one should model assessment-related constructs as categories or dimensions. The taxometric method includes multiple data-analytic procedures designed to check the consistency of results. The goal is to differentiate between strong evidence of…
Descriptors: Methods, Comparative Analysis, Data Analysis, Reliability
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Aldridge, Jill M.; Fraser, Barry J.; Bell, Lisa; Dorman, Jeffrey – Journal of Science Teacher Education, 2012
This article reports the development, validation and use of an instrument designed to provide teachers with feedback information, based on students' perceptions, about their classroom environments. The instrument was developed to provide teachers with feedback that they could use to reflect on their teaching practices and, in turn, guide the…
Descriptors: Feedback (Response), Student Attitudes, Action Research, Measures (Individuals)
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Sabourin, Jennifer L.; Rowe, Jonathan P.; Mott, Bradford W.; Lester, James C. – Journal of Educational Data Mining, 2013
Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…
Descriptors: Student Behavior, Classification, Learner Engagement, Data Analysis
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Lane, Kathleen Lynne; Kalberg, Jemma Robertson; Menzies, Holly; Bruhn, Allison; Eisner, Shanna; Crnobori, Mary – Remedial and Special Education, 2011
In this article the authors provide practitioners and researchers with three illustrations of how to use systematic screening tools within the context of three-tiered models of support to (a) measure the overall level of risk present in a school over time and (b) identify students who may require more targeted supports in the form of secondary and…
Descriptors: Elementary Secondary Education, Prevention, Program Implementation, Data Analysis
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