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…

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…

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…

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…

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…

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…

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…

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…

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…

This paper explores the potential of abductive reasoning to enhance the analysis of international large-scale assessments which have traditionally relied on deductive and inductive reasoning. While these conventional methods have provided valuable insights into global student achievement, they often fail to capture the complexity of educational…

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…

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…

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…

"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…

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…