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Li, Ak Wai; Sinnamon, Luanne S.; Kopak, Rick – Information and Learning Sciences, 2022
Purpose: The purpose of this study is to explore open data portals as data literacy learning environments. The authors examined the obstacles faced and strategies used by university students as non-expert open data portal users with different levels of data literacy, to inform the design of portals intended to scaffold informal and situated…
Descriptors: Data Collection, Multiple Literacies, Data, College Students
Center for IDEA Early Childhood Data Systems (DaSy), 2022
The value of data is increasingly recognized by organizations and programs, including Individuals with Disabilities Education Act (IDEA) Part C and Part B 619 programs. Data can help Part C and Part B 619 program coordinators, data managers and staff improve outcomes for children and families by strengthening their understanding of the needs of…
Descriptors: Equal Education, Educational Legislation, Federal Legislation, Students with Disabilities
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
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
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
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
Freddy Juarez; Jarred Pernier; Brittany Devies – New Directions for Student Leadership, 2025
The organizational change framework is a tool for understanding and facilitating organizational change and success, grounded in the principles of design thinking and the foundational leadership and organizational wellness (FLOW) model. This article dives into the components of the organizational change framework--collect the information, connect…
Descriptors: Organizational Change, Models, Data Collection, Program Implementation
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
J. Patrick Biddix; Amber Williams; Sean C. Basso; Melissa A. Brown; Kelsey Kyne – Journal of College Student Retention: Research, Theory & Practice, 2025
Assessment data play a crucial role in facilitating informed decision-making. In the context of student affairs professionals aiming to empirically demonstrate the significance of connection, belonging, and wellness within a holistic campus learning environment, the need for formative data is becoming increasingly valuable. The article outlines…
Descriptors: Formative Evaluation, Student Surveys, College Students, Data Use
Sandip Sinharay; Randy E. Bennett; Michael Kane; Jesse R. Sparks – Journal of Educational Measurement, 2025
Personalized assessments are of increasing interest because of their potential to lead to more equitable decisions about the examinees. However, one obstacle to the widespread use of personalized assessments is the lack of a measurement toolkit that can be used to analyze data from these assessments. This article takes one step toward building…
Descriptors: Test Validity, Data Analysis, Advanced Placement Programs, Art
Wan-Chong Choi; Chan-Tong Lam; António José Mendes – International Educational Data Mining Society, 2025
Missing data presents a significant challenge in Educational Data Mining (EDM). Imputation techniques aim to reconstruct missing data while preserving critical information in datasets for more accurate analysis. Although imputation techniques have gained attention in various fields in recent years, their use for addressing missing data in…
Descriptors: Research Problems, Data Analysis, Research Methodology, Models

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