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Remsh Nasser Alqahtani; Ahmad Zaid Almassaad – Education and Information Technologies, 2025
The aim of research is to reveal the effect of a training program based on the TAWOCK model for teaching computational thinking skills on teaching self-efficacy among computer teachers. It used the quasi-experimental approach, with a pre-test and post-test design with a control group. An electronic training program based on the TAWOCK model was…
Descriptors: Models, Teaching Methods, Computation, Thinking Skills
Seyedahmad Rahimi; Russell Almond; Andrea Ramírez-Salgado; Christine Wusylko; Lauren Weisberg; Yukyeong Song; Jie Lu; Ted Myers; Bowen Wang; Xiaomaon Wang; Marc Francois; Jennifer Moses; Eric Wright – Journal of Computer Assisted Learning, 2024
Background: Stealth assessment is a learning analytics method, which leverages the collection and analysis of learners' interaction data to make real-time inferences about their learning. Employed in digital learning environments, stealth assessment helps researchers, educators, and teachers evaluate learners' competencies and customize the…
Descriptors: Competence, Models, Research Methodology, Research Design
Jamie Colwell; Amy Hutchison; Kristie Gutierrez; Jeff Offutt; Anya Evmenova – Computer Science Education, 2024
Background & Context: This research focused on an online professional development (PD), the Inclusive Computer Science Model of PD, to support integrating computer science and computational thinking for all learners into K-5 literacy instruction. Objective: This research was conducted to understand elementary teachers' perceptions of the PD.…
Descriptors: Elementary School Teachers, Teaching Experience, Electronic Learning, Faculty Development
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
Ou, Lu; Hofman, Abe D.; Simmering, Vanessa R.; Bechger, Timo; Maris, Gunter; van der Maas, Han L. J. – International Educational Data Mining Society, 2019
In this study, we fitted a mixed-effects nonlinear continuous-time mutualism model of skill development proposed by van der Maas et al. (2006) to naturally collected irregularly spaced time series data from an online adaptive practice system for mathematics called Math Garden. Results showed that the mutualism model provided a better fit to the…
Descriptors: Mathematics Skills, Skill Development, Time, Models
Ivanova, Malinka – Informatics in Education, 2020
eLearning is fast progressing scientific field proposing novel and specific approaches in a range of domains. It is well established practice in universities, schools and organizations for delivering interactive, adaptive and flexible training, taking advantage of contemporary and emerging technologies. Informatics is a continuously evolving…
Descriptors: Electronic Learning, Learning Analytics, Automation, Information Systems
Varun Mandalapu – ProQuest LLC, 2021
Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…
Descriptors: Models, Student Behavior, Learning Management Systems, Data Use
Ifenthaler, Dirk, Ed.; Sampson, Demetrios G., Ed.; Isaías, Pedro, Ed. – Cognition and Exploratory Learning in the Digital Age, 2022
This book is about inclusivity and open education in the digital age. It reports the latest data on this topic from the 2021 Cognition and Exploratory Learning in the Digital Age (CELDA) conference. This annual conference focuses on challenges pertaining to the evolution of the learning process, the role of pedagogical approaches and the progress…
Descriptors: Teaching Methods, Educational Innovation, Educational Technology, Technology Uses in Education
Lamb, Richard L. – Journal of Science Education and Technology, 2016
Within the last 10 years, new tools for assisting in the teaching and learning of academic skills and content within the context of science have arisen. These new tools include multiple types of computer software and hardware to include (video) games. The purpose of this study was to examine and compare the effect of computer learning games in the…
Descriptors: Cognitive Processes, Computation, Models, Science Laboratories
Kovanovic, Vitomir; Gaševic, Dragan; Dawson, Shane; Joksimovic, Srecko; Baker, Ryan S.; Hatala, Marek – Journal of Learning Analytics, 2015
With widespread adoption of Learning Management Systems (LMS) and other learning technology, large amounts of data--commonly known as trace data--are readily accessible to researchers. Trace data has been extensively used to calculate time that students spend on different learning activities--typically referred to as time-on-task. These measures…
Descriptors: Time on Task, Computation, Validity, Data Analysis
Delgado, M.; Fajardo, W.; Molina-Solana, M. – International Association for Development of the Information Society, 2013
In the last decades there have been several attempts to use computers in Music Education. New pedagogical trends encourage incorporating technology tools in the process of learning music. Between them, those systems based on Artificial Intelligence are the most promising ones, as they can derive new information from the inputs and visualize them…
Descriptors: Electronic Learning, Computer Software, Music Education, Music Activities
Bodea, Constanta Nicoleta; Dascalu, Mariana Iuliana – Journal of Applied Quantitative Methods, 2009
The authors propose a risks evaluation model for research projects. The model is based on fuzzy inference. The knowledge base for fuzzy process is built with a causal and cognitive map of risks. The map was especially developed for research projects, taken into account their typical lifecycle. The model was applied to an e-testing research…
Descriptors: Risk, Research Projects, Inferences, Models
Nallure Balasubramanian, Vineeth – ProQuest LLC, 2010
The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…
Descriptors: World Problems, Intelligence, Lifelong Learning, Prediction
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries

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