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Showing 1 to 15 of 22 results Save | Export
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Smith, Jennifer; Musharraf, Mashrura; Veitch, Brian; Khan, Faisal – IEEE Transactions on Learning Technologies, 2022
For the offshore energy industry, virtual environment technology can enhance conventional training by teaching basic offshore safety protocols such as onboard familiarization and emergency evacuation. Virtual environments have the added benefit of being used to investigate the impact of different training approaches on competence. This pilot study…
Descriptors: Energy, Industry, Computer Simulation, Training
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Srour, F. Jordan; Karkoulian, Silva – International Journal of Social Research Methodology, 2022
The literature provides multiple measures of diversity along a single demographic dimension, but when it comes to studying the interaction of multiple diversity types (e.g. age, gender, and race), the field of useable measures diminishes. We present the use of decision trees as a machine learning technique to automatically identify the…
Descriptors: Diversity, Decision Making, Artificial Intelligence, Correlation
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González-Esparza, Lydia Marion; Jin, Hao-Yue; Lu, Chang; Cutumisu, Maria – AERA Online Paper Repository, 2022
Detecting wheel-spinning behaviors of students who interact with an Intelligent Tutoring System (ITS) is important for generating pertinent and effective feedback and developing more enriching learning experiences. This analysis compares decision tree and bagged tree models of student productive persistence (i.e., mastering a skill) using the…
Descriptors: Student Behavior, Intelligent Tutoring Systems, Feedback (Response), Persistence
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McLean, Sarah; Meadows, Ken N.; Heffernan, Austin; Campbell, Nicole – Advances in Physiology Education, 2020
Failed experiments are a common occurrence in research, yet many undergraduate science laboratories rely on established protocols to ensure students are able to obtain results. While it is logistically challenging to facilitate students' conducting their own experiments in the laboratory, allowing students to "fail" in a safe environment…
Descriptors: Decision Making, Internet, Self Efficacy, Science Experiments
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Toprak, Emre; Gelbal, Selahattin – International Journal of Assessment Tools in Education, 2020
This study aims to compare the performances of the artificial neural network, decision trees and discriminant analysis methods to classify student achievement. The study uses multilayer perceptron model to form the artificial neural network model, chi-square automatic interaction detection (CHAID) algorithm to apply the decision trees method and…
Descriptors: Comparative Analysis, Classification, Artificial Intelligence, Networks
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Kemper, Lorenz; Vorhoff, Gerrit; Wigger, Berthold U. – European Journal of Higher Education, 2020
We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…
Descriptors: Foreign Countries, Predictor Variables, Potential Dropouts, School Holding Power
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Seftor, Neil; Shannon, Lisa; Wilkerson, Stephanie; Klute, Mary – Regional Educational Laboratory Appalachia, 2021
Classification and Regression Tree (CART) analysis is a statistical modeling approach that uses quantitative data to predict future outcomes by generating decision trees. CART analysis can be useful for educators to inform their decision-making. For example, educators can use a decision tree from a CART analysis to identify students who are most…
Descriptors: Flow Charts, Decision Making, Statistical Analysis, Data Use
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Paassen, Benjamin; McBroom, Jessica; Jeffries, Bryn; Koprinska, Irena; Yacef, Kalina – Journal of Educational Data Mining, 2021
Educational data mining involves the application of data mining techniques to student activity. However, in the context of computer programming, many data mining techniques can not be applied because they require vector-shaped input, whereas computer programs have the form of syntax trees. In this paper, we present ast2vec, a neural network that…
Descriptors: Data Analysis, Programming Languages, Networks, Novices
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Tang, Marc – Teaching Statistics: An International Journal for Teachers, 2020
University students in other disciplines without prior knowledge in statistics and/or programming language are introduced to the statistical method of decision trees in the programming language R during a 45-minute teaching and practice session. Statistics and programming skills are now frequently required within a wide variety of research fields…
Descriptors: Statistics, Teaching Methods, Programming, Programming Languages
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Fleischer, Yannik; Biehler, Rolf; Schulte, Carsten – Statistics Education Research Journal, 2022
This study examines modelling with machine learning. In the context of a yearlong data science course, the study explores how upper secondary students apply machine learning with Jupyter Notebooks and document the modelling process as a computational essay incorporating the different steps of the CRISP-DM cycle. The students' work is based on a…
Descriptors: Statistics Education, Educational Research, Electronic Learning, Secondary School Students
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dos Santos, Roberta Alvarenga; Paulista, Cássio Rangel; da Hora, Henrique Rego Monteiro – Technology, Knowledge and Learning, 2023
The demand for in-depth studies on educational data presupposes the application of technologies that allow data analysis of vast quantities, and subsequently, drawing relevant information and knowledge. The research objective herein is to employ data mining techniques on PISA databases to identify potential patterns that may explain the…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students
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Coté, Murray J.; Smith, Marlene A. – Decision Sciences Journal of Innovative Education, 2022
Popular game shows offer educators the opportunity to develop active-learning exercises that provide students with a real-world connection to analytical reasoning and methods. We describe a classroom assignment developed for quantitative business courses based on the Monty Hall Problem (MHP), a probability puzzle with ties to the long-running…
Descriptors: Experiential Learning, Business Administration Education, Probability, Games
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Smith, Jennifer; Musharraf, Mashrura; Blundon, Allison; Veitch, Brian – International Journal of Training Research, 2020
To prepare personnel for offshore emergencies, safety training should focus on transferability. Virtual environment (VE) training is designed to support the transfer of acquired egress skills to novel offshore emergencies. Decision trees (DT) are useful tools to evaluate training transfer. DTs use performance data collected during VE training to…
Descriptors: Safety Education, Virtual Classrooms, Transfer of Training, Curriculum Design
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Spratto, Elisabeth M.; Leventhal, Brian C.; Bandalos, Deborah L. – Educational and Psychological Measurement, 2021
In this study, we examined the results and interpretations produced from two different IRTree models--one using paths consisting of only dichotomous decisions, and one using paths consisting of both dichotomous and polytomous decisions. We used data from two versions of an impulsivity measure. In the first version, all the response options had…
Descriptors: Comparative Analysis, Item Response Theory, Decision Making, Data Analysis
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Groos, Lukas; Maass, Kai; Graulich, Nicole – Journal of Chemical Education, 2021
More than ever, there is an increasing need for digital experimental learning environments in chemistry. The variety of digital learning approaches provided to students range from simple videos showing experiments to highly interactive virtual laboratories. Regardless of which approach is chosen, a digital learning environment should be adapted to…
Descriptors: Student Centered Learning, Electronic Learning, Science Experiments, Chemistry
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