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Peer reviewed
Direct linkShin-Yu Kim; Inseong Jeon; Seong-Joo Kang – Journal of Chemical Education, 2024
Artificial intelligence (AI) and data science (DS) are receiving a lot of attention in various fields. In the educational field, the need for education utilizing AI and DS is also being emerged. In this context, we have created an AI/DS integrating program that generates a compound classification/regression model using characteristics of compounds…
Descriptors: Chemistry, Science Instruction, Laboratory Experiments, Artificial Intelligence
Leher Singh; Mihaela D. Barokova; Heidi A. Baumgartner; Diana C. Lopera-Perez; Paul Okyere Omane; Mark Sheskin; Francis L. Yuen; Yang Wu; Katherine J. Alcock; Elena C. Altmann; Marina Bazhydai; Alexandra Carstensen; Kin Chung Jacky Chan; Hu Chuan-Peng; Rodrigo Dal Ben; Laura Franchin; Jessica E. Kosie; Casey Lew-Williams; Asana Okocha; Tilman Reinelt; Tobias Schuwerk; Melanie Soderstrom; Angeline S. M. Tsui; Michael C. Frank – Developmental Psychology, 2024
Culture is a key determinant of children's development both in its own right and as a measure of generalizability of developmental phenomena. Studying the role of culture in development requires information about participants' demographic backgrounds. However, both reporting and treatment of demographic data are limited and inconsistent in child…
Descriptors: Data Collection, Young Children, Demography, Cultural Traits
Download full textWhite, Jamison – National Alliance for Public Charter Schools, 2020
Everyone knows what a school is, but the question of what constitutes an individual school is more complex than one would expect. Since not all individual records that appear in state or federal data files are schools, this creates a persistent challenge for educational researchers. In order to ensure that we have an accurate accounting of charter…
Descriptors: Charter Schools, Educational Research, Research Problems, Data Collection
Jasinski, Lisa; Nokkala, Terhi; Juusola, Henna – European Journal of Higher Education, 2021
When conceived of as both a research strategy and mode to present findings, vignettes can be combined with various qualitative methodologies in higher education research. Rather than being a discipline unto itself, higher education research is best understood as a multi and cross-disciplinary field of study that, we contend, is made richer by its…
Descriptors: Vignettes, Educational Research, Educational Benefits, Research Methodology
Jia, Yuchen; Zhang, Limei – International Journal of Educational Technology in Higher Education, 2021
With the development of information technology and the advent of Massive Open Online Course (MOOC) and Small Private Online Course (SPOC), various online courses which include a lot of new resources and new teaching methods have appeared. The application of advanced teaching resources and educational concepts can improve students' learning…
Descriptors: Online Courses, Small Group Instruction, Blended Learning, Teaching Methods
Zehner, Fabian; Eichmann, Beate; Deribo, Tobias; Harrison, Scott; Bengs, Daniel; Andersen, Nico; Hahnel, Carolin – Journal of Educational Data Mining, 2021
The NAEP EDM Competition required participants to predict efficient test-taking behavior based on log data. This paper describes our top-down approach for engineering features by means of psychometric modeling, aiming at machine learning for the predictive classification task. For feature engineering, we employed, among others, the Log-Normal…
Descriptors: National Competency Tests, Engineering Education, Data Collection, Data Analysis
Motz, Benjamin; Busey, Thomas; Rickert, Martin; Landy, David – International Educational Data Mining Society, 2018
Analyses of student data in post-secondary education should be sensitive to the fact that there are many different topics of study. These different areas will interest different kinds of students, and entail different experiences and learning activities. However, it can be challenging to identify the distinct academic themes that students might…
Descriptors: Data Collection, Data Analysis, Enrollment, Higher Education
Sinharay, Sandip – Educational Measurement: Issues and Practice, 2016
Data mining methods for classification and regression are becoming increasingly popular in various scientific fields. However, these methods have not been explored much in educational measurement. This module first provides a review, which should be accessible to a wide audience in education measurement, of some of these methods. The module then…
Descriptors: Data Collection, Information Retrieval, Classification, Regression (Statistics)
Hughes, John; Petscher, Yaacov – Regional Educational Laboratory Southeast, 2016
The high rate of students taking developmental education courses suggests that many students graduate from high school unready to meet college expectations. A college readiness screener can help colleges and school districts better identify students who are not ready for college credit courses. The primary audience for this guide is leaders and…
Descriptors: College Readiness, Screening Tests, Test Construction, Predictor Variables
Dietze, Stefan; Taibi, Davide; Yu, Hong Qing; Dovrolis, Nikolas – British Journal of Educational Technology, 2015
Reusable educational resources became increasingly important for enhancing learning and teaching experiences, particularly in the medical domain where resources are particularly expensive to produce. While interoperability across educational resources metadata repositories is yet limited to the heterogeneity of metadata standards and interface…
Descriptors: Medical Education, Educational Resources, Databases, Metadata
Sabitha, Sai; Mehrotra, Deepti; Bansal, Abhay – Electronic Journal of e-Learning, 2015
The most important dimension of learning is the content, and a Learning Management System (LMS) suffices this to a certain extent. The present day LMS are designed to primarily address issues like ease of use, search, content and performance. Many surveys had been conducted to identify the essential features required for the improvement of LMS,…
Descriptors: Convergent Thinking, Management Systems, Integrated Learning Systems, Knowledge Management
Casey, Kevin – Journal of Learning Analytics, 2017
Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…
Descriptors: Keyboarding (Data Entry), Educational Research, Data Collection, Data Analysis
Warriner, Doris S.; Wyman, Leisy T. – International Multilingual Research Journal, 2013
Sociolinguists have made considerable headway in identifying and describing the relationship between mobility, linguistic resources, and forms of inequality. Despite such advances, however, we argue that it is as important as ever to continue to rethink what kinds of phenomena are analyzed, the distinctions and categories that might be imposed on…
Descriptors: Sociolinguistics, Ideology, Correlation, Classification
Tijdens, Kea G.; De Ruijter, Judith; De Ruijter, Esther – European Journal of Training and Development, 2012
Purpose: The purpose of this article is to evaluate a method for measuring work activities and skill requirements of 160 occupations in eight countries, used in EurOccupations, an EU-FP6 project. Additionally, it aims to explore how the internet can be used for measuring work activities and skill requirements. Design/methodology/approach: For the…
Descriptors: Foreign Countries, Occupational Information, Job Skills, Activities
Geverdt, Douglas E. – National Center for Education Statistics, 2015
The National Center for Education Statistics (NCES) Education Demographic and Geographic Estimates (EDGE) program develops geographic data to help policymakers, program administrators, and the public understand relationships between educational institutions and the communities they serve. One of the commonly used geographic data items is the NCES…
Descriptors: Demography, Geographic Distribution, Classification, Geographic Location
