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Phillips, Tanner M.; Saleh, Asmalina; Ozogul, Gamze – International Journal of Artificial Intelligence in Education, 2023
Encouraging teachers to reflect on their instructional practices and course design has been shown to be an effective means of improving instruction and student learning. However, the process of encouraging reflection is difficult; reflection requires quality data, thoughtful analysis, and contextualized interpretation. Because of this, research on…
Descriptors: Reflection, Artificial Intelligence, Natural Language Processing, Data Collection
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Pei Wang – International Journal of Information and Communication Technology Education, 2024
In today's university era, reforming the English teaching model has become a major research topic for researchers. Based on this, this paper adopts a hierarchical and progressive model construction method to further explore the reform model of university English teaching in the context of educational ecology. First, this paper discusses the…
Descriptors: English (Second Language), Second Language Instruction, Educational Change, Change Strategies
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Mahmut Sami Koyuncu; Mehmet Sata – International Journal of Assessment Tools in Education, 2023
The main aim of this study was to introduce the ConQuest program, which is used in the analysis of multivariate and multidimensional data structures, and to show its applications on example data structures. To achieve this goal, a basic research approach was applied. Thus, how to use the ConQuest program and how to prepare the data set for…
Descriptors: Data Analysis, Computer Oriented Programs, Models, Test Items
Susanne DeVore – ProQuest LLC, 2022
The first part of this dissertation conducts a large-scale study comparing general and usage-based indices of syntactic complexity in L2 Mandarin writing samples across a wide range of proficiency levels. To do this, the Tool for the Automated Analysis of Syntactic Sophistication and Complexity (TAASSC; Kyle, 2016) was adapted for Mandarin by…
Descriptors: Syntax, Difficulty Level, Mandarin Chinese, Second Language Learning
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Bonifay, Wes; Cai, Li – Grantee Submission, 2017
Complexity in item response theory (IRT) has traditionally been quantified by simply counting the number of freely estimated parameters in the model. However, complexity is also contingent upon the functional form of the model. The information-theoretic principle of minimum description length provides a novel method of investigating complexity by…
Descriptors: Item Response Theory, Difficulty Level, Goodness of Fit, Factor Analysis
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Rybinski, Krzysztof; Kopciuszewska, Elzbieta – Assessment & Evaluation in Higher Education, 2021
This article presents the first-ever big data study of the student evaluation of teaching (SET) using artificial intelligence (AI). We train natural language processing (NLP) models on 1.6 million student evaluations from the US and the UK. We address two research questions: (1) are these models able to predict student ratings from the student…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Evaluation of Teacher Performance, Natural Language Processing
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Schweizer, Karl; Troche, Stefan – Educational and Psychological Measurement, 2018
In confirmatory factor analysis quite similar models of measurement serve the detection of the difficulty factor and the factor due to the item-position effect. The item-position effect refers to the increasing dependency among the responses to successively presented items of a test whereas the difficulty factor is ascribed to the wide range of…
Descriptors: Investigations, Difficulty Level, Factor Analysis, Models
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Mao, Ye; Zhi, Rui; Khoshnevisan, Farzaneh; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2019
Early prediction of student difficulty during long-duration learning activities allows a tutoring system to intervene by providing needed support, such as a hint, or by alerting an instructor. To be effective, these predictions must come early and be highly accurate, but such predictions are difficult for open-ended programming problems. In this…
Descriptors: Difficulty Level, Learning Activities, Prediction, Programming
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Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
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Koedinger, Kenneth R.; McLaughlin, Elizabeth A. – International Educational Data Mining Society, 2016
Many educational data mining studies have explored methods for discovering cognitive models and have emphasized improving prediction accuracy. Too few studies have "closed the loop" by applying discovered models toward improving instruction and testing whether proposed improvements achieve higher student outcomes. We claim that such…
Descriptors: Educational Research, Data Collection, Task Analysis, Cognitive Processes
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Piantadosi, Steven T.; Kidd, Celeste; Aslin, Richard – Developmental Science, 2014
Studies of infant looking times over the past 50 years have provided profound insights about cognitive development, but their dependent measures and analytic techniques are quite limited. In the context of infants' attention to discrete sequential events, we show how a Bayesian data analysis approach can be combined with a rational cognitive…
Descriptors: Infants, Eye Movements, Infant Behavior, Cognitive Development
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Haupt, Grietjie – International Journal of Technology and Design Education, 2015
Empirical evidence on the way in which expert designers from different domains cognitively connect their internal processes with external resources is presented in the context of an extended cognition model. The article focuses briefly on the main trends in the extended design cognition theory and in particular on recent trends in information…
Descriptors: Design, Expertise, Cognitive Processes, Models
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Yang, Ya-Fei; Lee, Chien-I; Chang, Chih-Kai – Education for Information, 2016
Collaborative learning is an activity in which two or more students learn something together. Many studies have found that collaborative learning improve students' memory retention and motivation to learn. Peer Instruction (PI) is one of the most successful evidence-based collaborative learning methods. This article investigates issues of student…
Descriptors: Learning Motivation, Retention (Psychology), Computer Science Education, Programming
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Yeh, Stuart S. – Teachers College Record, 2015
Background/Context: Despite decades of research, the persistence of the gap in student achievement between disadvantaged minority students and their middle-class peers remains unexplained. Purpose/Objective: The purpose of the current article is to propose a new model of the achievement gap. Research Design: Data were analyzed from three…
Descriptors: Models, Achievement Gap, Disadvantaged, Minority Group Students
Williamson, Ronald; Blackburn, Barbara R. – Eye on Education, 2011
Raise the level of rigor in your school and dramatically improve student learning with the tools in this book. Each illuminating exercise is tailored to educators looking to spread the word on rigor and beat the obstacles to achieving it schoolwide. Formatted for duplication and repeated use, these tools are perfect for those who currently hold a…
Descriptors: Difficulty Level, Academic Achievement, Leadership, Models
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