Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…

The use of large-scale assessments (LSAs) in education has grown in the past decade though analysis of LSAs using multilevel models (MLMs) using R has been limited. A reason for its limited use may be due to the complexity of incorporating both plausible values and weighted analyses in the multilevel analyses of LSA data. We provide additional…

Psycholinguistics is the research of language in the mind: The architecture of storing the different components of language in our memory, and the ways we access that knowledge when processing and producing language. Psycholinguists usually conduct quantitative experimental research in which certain standards of experimental design, data…

The increased use of quantitative education data is often regarded by scholars as evidence of the emergence of 'governing by numbers'. These scholars ascribe major stakeholders such as the OECD and nation states agency as they produce, distribute and consume data, and respond to these with policy and management initiatives. This paper argues that…

The process of quantification is a powerful development shaping many domains of life today. In the area of education, for example, performance measurement, testing and ranking have become common tools of governance. Quantification is not a neutral way of describing society, but a process of valorisation. It has three sociologically relevant…

In an increasingly data-driven society, making decisions with data is a requirement not only for research scientists but also for navigating life more generally (Kjelvik & Schultheis, 2019). An informed citizenry must be prepared to discover patterns, predict outcomes, make decisions with data, and evaluate data-based claims for legitimacy and…

Longitudinal data analysis has been widely employed to examine between-individual differences in within-individual changes. One challenge of such analyses is that the rate-of-change is only available indirectly when change patterns are nonlinear with respect to time. Latent change score models (LCSMs), which can be employed to investigate the…

Monte Carlo methods are an accepted methodology in regards to generation critical values for a Maximum test. The same methods are also applicable to the evaluation of the robustness of the new created test. A table of critical values was created, and the robustness of the new maximum test was evaluated for five different distributions. Robustness…

This article provides an overview of the instructional activity implemented to introduce the authors' first-grade students to the concept of measuring, collecting, and recording temperature data as part of a unit on weather. The activities introduced involved approximately one week of instructional time. However, the application of the skill…

Education is undergoing various transformations due to new data-driven educational technologies and the management of educational data through data infrastructures. These technologies are frequently promoted to parents and the profession as being 'revolutionary' because they represent a new generation of learning. While computer adaptive tests may…

This is the second of a series of reports on trends in national community college enrollments. National community college enrollments continue to decrease, with variations at the state and local levels. The report also examines completion rates published by the U.S. Department of Education (ED) based on institutional level reporting, and those…

There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

In an age of assessment and accountability, academic libraries feel much pressure to prove their value according to new university measurements of student success. This study describes a methodology for how libraries may examine student interactions with services to assess whether library usage impacts student grade point averages (GPAs) and…

The Learning Target Rating Scale (LTRS) is a measure designed to evaluate the quality of teacher-developed learning targets for embedded instruction for early learning. In the present study, we examined the measurement dependability of LTRS scores by conducting a generalizability study (G-study). We used a partially nested, three-facet model to…

The Learning Target Rating Scale (LTRS) is a measure designed to evaluate the quality of teacher-developed learning targets for embedded instruction for early learning. In the present study, we examined the measurement dependability of LTRS scores by conducting a generalizability study (G-study). We used a partially nested, three-facet model to…