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Sghir, Nabila; Adadi, Amina; Lahmer, Mohammed – Education and Information Technologies, 2023
The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, Data Collection
Mindorff, David – ProQuest LLC, 2023
Practical work involving laboratory experiments is agreed upon to be an essential component of secondary science education. Practical work encompasses a broad range of activity types. The different forms of practical work are not equal in terms of cognitive demand and learning benefit. Inquiry-based investigations provide experience of cognitive…
Descriptors: Secondary Education, Science Education, Biology, Information Retrieval
UNESCO International Institute for Educational Planning, 2023
Quality, timely, purpose-driven education in emergencies (EiE) data can enable more effective response to education needs in crisis settings and strengthen system resilience. However, a growing body of evidence points to a number of problems related to the production, sharing, and use of EiE data within education information management systems…
Descriptors: Emergency Programs, Crisis Management, Data Analysis, Data Use
Quan Yuan; Lin Lv; Yolanda Cordero – International Journal of Web-Based Learning and Teaching Technologies, 2023
Relying on the nation's first judicial big data research base for people's courts in Southeast University, Southeast University Law School has set up a training direction for graduate students in legal big data and artificial intelligence, and explored the "three-dimensional, small-scale, wide-ranging, and large-scale ecology." The…
Descriptors: Law Schools, Legal Education (Professions), Graduate Students, Data
Christopher Chippewa Tsavatewa – ProQuest LLC, 2023
This paper seeks to empirically validate a sector agonistic instrument that measures the perceived critical success factors in data governance. Twelve constructs (Leadership and Management Commitment; Leadership and Management Alignment; Executive Sponsorship; Robust Data Governance Strategy; Change Management; Training and Education; Governance…
Descriptors: Data, Governance, Stakeholders, Universities
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