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Keser, Sinem Bozkurt; Aghalarova, Sevda – Education and Information Technologies, 2022
Education plays a major role in the development of the consciousness of the whole society. Education has been improved by analyzing educational data related to student academic performance. By using data mining techniques and algorithms on data from the educational environment, students' performances can be predicted. In this study, a novel Hybrid…
Descriptors: Grade Prediction, Academic Achievement, Data Analysis, Data Collection
Luna, J. M.; Fardoun, H. M.; Padillo, F.; Romero, C.; Ventura, S. – Interactive Learning Environments, 2022
The aim of this paper is to categorize and describe different types of learners in massive open online courses (MOOCs) by means of a subgroup discovery (SD) approach based on MapReduce. The proposed SD approach, which is an extension of the well-known FP-Growth algorithm, considers emerging parallel methodologies like MapReduce to be able to cope…
Descriptors: Online Courses, Student Characteristics, Classification, Student Behavior
Basnet, Ram B.; Johnson, Clayton; Doleck, Tenzin – Education and Information Technologies, 2022
The nature of teaching and learning has evolved over the years, especially as technology has evolved. Innovative application of educational analytics has gained momentum. Indeed, predictive analytics have become increasingly salient in education. Considering the prevalence of learner-system interaction data and the potential value of such data, it…
Descriptors: Prediction, Dropouts, Predictive Measurement, Data Collection
Arnold, Pip; Franklin, Christine – Journal of Statistics and Data Science Education, 2021
The statistical problem-solving process is key to the statistics curriculum at the school level, post-secondary, and in statistical practice. The process has four main components: formulate questions, collect data, analyze data, and interpret results. The Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education (GAISE) emphasizes…
Descriptors: Statistics Education, Problem Solving, Data Collection, Data Analysis
Pavelko, Stacey L.; Owens, Robert E., Jr. – Perspectives of the ASHA Special Interest Groups, 2023
Purpose: The purposes of this tutorial are (a) to describe a method of language sample analysis (LSA) referred to as SUGAR (Sampling Utterances and Grammatical Analysis Revised) and (b) to offer step-by-step instructions detailing how to collect, transcribe, analyze, and interpret the results of a SUGAR language sample. Method: The tutorial begins…
Descriptors: Sampling, Language Tests, Data Collection, Data Analysis
Kai Li – International Association for Development of the Information Society, 2023
Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…
Descriptors: Student Evaluation, Online Courses, Electronic Learning, Computer Literacy
National Forum on Education Statistics, 2021
"The Forum Guide to Strategies for Education Data Collection and Reporting (SEDCAR)" was created to provide timely and useful best practices for education agencies that are interested in designing and implementing a strategy for data collection and reporting, focusing on these as key elements of the larger data process. It builds upon…
Descriptors: Data Collection, Educational Research, Statistical Data, Data Analysis
Eva Reimers – British Journal of Religious Education, 2025
Starting with the question of why there is so much religiously motivated resistance against compulsory sex education, this article explores and discusses entanglements of norms about sexuality, gender, and religion in education. Based on predominantly Swedish data, the aim of the paper is to offer perspectives on connections between religiosity…
Descriptors: Sex Education, Role of Religion, Resistance (Psychology), Compulsory Education
Qiling Wu; Annemarie H. Hindman – Child & Youth Care Forum, 2025
Research indicates that parents' involvement in early literacy, particularly through book reading, matters for young children's language and literacy development. OBJECTIVE: However, little is known about the nature and extent of family book reading across the U.S. nation or about which factors support parents' involvement in book reading. In…
Descriptors: Kindergarten, Family Environment, Parents, Reading Habits
Liang Zhang; Jionghao Lin; John Sabatini; Conrad Borchers; Daniel Weitekamp; Meng Cao; John Hollander; Xiangen Hu; Arthur C. Graesser – IEEE Transactions on Learning Technologies, 2025
Learning performance data, such as correct or incorrect answers and problem-solving attempts in intelligent tutoring systems (ITSs), facilitate the assessment of knowledge mastery and the delivery of effective instructions. However, these data tend to be highly sparse (80%90% missing observations) in most real-world applications. This data…
Descriptors: Artificial Intelligence, Academic Achievement, Data, Evaluation Methods
Matt Giani; Madison E. Andrews; Tasneem Sultana; Fortunato Medrano – Annenberg Institute for School Reform at Brown University, 2025
This study examines College and Career Readiness (CCR) policy implementation through the lens of "decoupling." We investigate how high schools have jointly implemented Career and Technical Education (CTE) and Industry-Based Certifications (IBCs), and whether there is evidence of "curricular-credential decoupling" via…
Descriptors: Educational Policy, Credentials, High Schools, Data
Allison Davidson – Teaching Statistics: An International Journal for Teachers, 2025
This paper describes an in-class activity to introduce random assignment, paired data, and learning effect. The activity requires minimal materials, can be completed in a single class period, and is suitable for those using technology to conduct data exploration but can also be adapted for use in a technology-free classroom. The activity consists…
Descriptors: Class Activities, Paired Associate Learning, Data, Handedness
Silvia Testa; Renato Miceli; Renato Miceli – Educational Measurement: Issues and Practice, 2025
Random Equating (RE) and Heuristic Approach (HA) are two linking procedures that may be used to compare the scores of individuals in two tests that measure the same latent trait, in conditions where there are no common items or individuals. In this study, RE--that may only be used when the individuals taking the two tests come from the same…
Descriptors: Comparative Testing, Heuristics, Problem Solving, Personality Traits
Clare Waterman; Katherine Shields; Tracy McMahon – Education Development Center, Inc., 2022
This Toolkit presents lessons learned from the process of implementing a new system for collecting student-level work-based learning (WBL) data in high school career and technical education (CTE) programs. As part of a study on career academies and WBL, a research team worked closely with a district CTE office and school staff to design and…
Descriptors: Vocational Education, Work Experience Programs, Data Collection, Goal Orientation
Maria Eftychia Angelaki; Fragkiskos Bersimis; Theodoros Karvounidis; Christos Douligeris – IEEE Transactions on Education, 2024
Contributions: This article explores the impact of environmental education interventions about e-waste recycling and management practices as well as about the energy usage of data centers (DCs) into the Information and Communication Technologies (ICTs) university curricula. Intended Outcomes: An education program was implemented aiming to raise…
Descriptors: Information Technology, Communications, Conservation Education, Sanitation