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Yamashita, Takashi; Smith, Thomas J.; Cummins, Phyllis A. – Journal of Educational and Behavioral Statistics, 2021
In order to promote the use of increasingly available large-scale assessment data in education and expand the scope of analytic capabilities among applied researchers, this study provides step-by-step guidance, and practical examples of syntax and data analysis using Maples. Concise overview and key unique aspects of large-scale assessment data…
Descriptors: Learning Analytics, Computer Software, Syntax, Adults
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Valentina Albano; Donatella Firmani; Luigi Laura; Jerin George Mathew; Anna Lucia Paoletti; Irene Torrente – Journal of Learning Analytics, 2023
Multiple-choice questions (MCQs) are widely used in educational assessments and professional certification exams. Managing large repositories of MCQs, however, poses several challenges due to the high volume of questions and the need to maintain their quality and relevance over time. One of these challenges is the presence of questions that…
Descriptors: Natural Language Processing, Multiple Choice Tests, Test Items, Item Analysis
Yamashita, Takashi; Smith, Thomas J.; Cummins, Phyllis A. – Grantee Submission, 2020
Background: Several statistical applications including Mplus, STATA, and R are available to conduct analyses such as structural equation modeling and multi-level modeling using large-scale assessment data that employ complex sampling and assessment designs and that provide associated information such as sampling weights, replicate weights, and…
Descriptors: Learning Analytics, Computer Software, Syntax, Adults
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Li, Jiawei; Supraja, S.; Qiu, Wei; Khong, Andy W. H. – International Educational Data Mining Society, 2022
Academic grades in assessments are predicted to determine if a student is at risk of failing a course. Sequential models or graph neural networks that have been employed for grade prediction do not consider relationships between course descriptions. We propose the use of text mining to extract semantic, syntactic, and frequency-based features from…
Descriptors: Course Descriptions, Learning Analytics, Academic Achievement, Prediction
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Rzepka, Nathalie; Müller, Hans-Georg; Simbeck, Katharina – International Educational Data Mining Society, 2021
The ability to spell correctly is a fundamental skill for participating in society and engaging in professional work. In the German language, the capitalization of nouns and proper names presents major difficulties for both native and nonnative learners, since the definition of what is a noun varies according to one's linguistic perspective. In…
Descriptors: Spelling, German, Punctuation, Nouns
Danielle S. McNamara; Laura K. Allen; Scott A. Crossley; Mihai Dascalu; Cecile A. Perret – Grantee Submission, 2017
Language is of central importance to the field of education because it is a conduit for communicating and understanding information. Therefore, researchers in the field of learning analytics can benefit from methods developed to analyze language both accurately and efficiently. Natural language processing (NLP) techniques can provide such an…
Descriptors: Natural Language Processing, Learning Analytics, Educational Technology, Automation