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Yang, Junhe; Kinshuk; An, Yunjo – Education and Information Technologies, 2023
The massive amount of text related to education provides rich information to support education in many aspects. In the meantime, the vast yet increasing volume of text makes it impossible to analyze manually. Text mining is a powerful tool to automatically analyze large-scaled texts and generate insights from the texts. However, many educational…
Descriptors: Scholarship, Educational Researchers, Information Retrieval, Pattern Recognition
Cheung, Kason Ka Ching; Tai, Kevin W. H. – Research in Science & Technological Education, 2023
Background: Intercoder reliability is a statistic commonly reported by researchers to demonstrate the rigour of coding procedures during data analysis. Its importance is debatable in the analysis of qualitative interview data. It raises a question on whether researchers should identify the same codes and themes in a transcript or they should…
Descriptors: Interrater Reliability, Data Analysis, Interviews, Research Methodology
Baek, Clare; Doleck, Tenzin – Interactive Learning Environments, 2023
To examine the similarities and differences between two closely related yet distinct fields -- Educational Data Mining (EDM) and Learning Analytics (LA) -- this study conducted a literature review of the empirical studies published in both fields. We synthesized 492 LA and 194 EDM articles published during 2015-2019. We compared the similarities…
Descriptors: Data Analysis, Learning Analytics, Literature Reviews, Educational Research
Veri, Francesco – Sociological Methods & Research, 2023
This article aims to clarify fundamental aspects of the process of assigning fuzzy scores to conditions based on family resemblance (FR) structures by considering prototype and set theories. Prototype theory and set theory consider FR structures from two different angles. Specifically, set theory links the conceptualization of FR to the idea of…
Descriptors: Evaluation Methods, Theories, Concept Formation, Models
M. Nazir; A. Noraziah; M. Rahmah – International Journal of Virtual and Personal Learning Environments, 2023
An effective educational program warrants the inclusion of an innovative construction that enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational decision support system has currently been a hot topic in educational systems, facilitating the pupil…
Descriptors: Data Analysis, Academic Achievement, Artificial Intelligence, Prediction
Nicole M. Dalzell; Ciaran Evans – Journal of Statistics and Data Science Education, 2023
Statistical competitions like ASA DataFest and the Women in Data Science (WiDS) Datathon give students valuable experience working with real, challenging data. By participating, students practice important statistics and data science skills including data wrangling, visualization, modeling, communication, and teamwork. However, while advanced…
Descriptors: Access to Education, Readiness, Statistics Education, Competition
Danny L'Boy; R. Nazim Khan – International Journal of Mathematical Education in Science and Technology, 2023
Statistical literacy has a large and important role in the teaching of statistics. Most mathematics and statistics courses are hierarchical, and the earlier material forms the foundation for later material. We construct a hierarchical structure for an introductory statistics course using Rasch analysis of the student scripts for the final…
Descriptors: Statistics Education, Statistics, Literacy, Introductory Courses
Greg R. Johnson; Melanie D. Janzen – Critical Education, 2023
In 2009, John Hattie's book Visible Learning: A Synthesis of over 800 Meta-Analyses Relating to Achievement brought big data to education. In the decade and a half since Visible Learning was originally published it has been aggressively marketed and has now grown into a large suite of branded books, tools, and products. Visible Learning continues…
Descriptors: Literary Criticism, Meta Analysis, Data Use, Data Analysis
Yi, Zhihui; Schreiber, James B.; Paliliunas, Dana; Barron, Becky F.; Dixon, Mark R. – Journal of Behavioral Education, 2021
The recent commentary by Beaujean and Farmer (2020) on the original paper by Dixon et al. (2019) serves a cautionary tale of selective p-values, the law of small N sizes, and the type-II error. We believe these authors have crafted a somewhat questionable argument in which only 57% of the original Dixon et al. data were re-analyzed, based on a…
Descriptors: Research Problems, Data Analysis, Statistical Analysis, Probability
Marciano, Joanne E.; Beymer, Alecia – English Teaching: Practice and Critique, 2022
Purpose: The purpose of this paper is to examine how youth from varied cultural and socioeconomic backgrounds came together to collaboratively analyze data they collected across two research projects in a community-based Youth Participatory Action Research (YPAR) initiative, a less understood aspect of YPAR. Specifically, this study discusses how…
Descriptors: Data Analysis, Participatory Research, Action Research, Youth
Goffin, Evelyn; Janssen, Rianne; Vanhoof, Jan – Review of Education, 2022
Formal achievement data such as test scores and school performance feedback from standardised assessments can be a powerful tool for data-based decision making and school improvement. However, teachers' and school leaders' usage of these data is not necessarily straightforward or predictable. In order to illuminate how educational professionals…
Descriptors: Teacher Attitudes, Administrator Attitudes, Academic Achievement, Data Analysis
Burns, Timothy; Sherman, Cherie – Information Systems Education Journal, 2022
This article presents the details of a business analytics minor that we created at our institution in the fall of 2019. In the two years since, our program has successfully met our enrollment goals. Out of over 50 minors offered at our institution, our business analytics minor is currently ranked fourth in enrollment. In this article we will…
Descriptors: Curriculum Development, Business Administration Education, Data Analysis, Course Descriptions
Savaiano, Mackenzie E.; Shanahan Bazis, Pamela; Hebert, Michael; Rodgers, Derek B.; Bosilevac, Madison; Leutzinger, Bridget; Thompson, Madison – Journal of Visual Impairment & Blindness, 2022
Introduction and Methods: We do not have an accurate count of the number of teachers of students with visual impairments working in the field, and it is a difficult number to estimate. As part of a national survey, states were contacted to estimate how many teachers of students with visual impairments are working in the United States and compared…
Descriptors: Visual Impairments, Computation, Data Analysis, Students
Vance, Eric A.; Alzen, Jessica L.; Smith, Heather S. – Journal of Statistics and Data Science Education, 2022
Statisticians and data scientists have been called upon to increase the impact they have through their collaborative projects. Statistics and data science practitioners and their educators can achieve and enable greater impact by learning how to create shared understanding with their collaborators as well as teaching this concept to their…
Descriptors: Statistics Education, Data Analysis, Teaching Methods, Misconceptions
Praveen Kumar Guraja – ProQuest LLC, 2022
Public higher education in the United States (US) is funded through two primary forms: one is through state higher education appropriation funds, and the other is student financial aid that is directly given to students. Increasing postsecondary full-time equivalent (FTE) enrollment and graduation rate are becoming a crucial economic priority in…
Descriptors: Data Analysis, Budgeting, Retrenchment, Public Colleges