Performance management in university-based scientific research institutions is essential for driving reform, advancing education quality, and fostering innovation. However, current performance evaluation models often focus solely on research indicators, neglecting the critical interdependence between the education and research systems. This…

State education departments find themselves pressured to reduce costs while improving student performance. To do so, state education departments must measure the performance of each school district in an objective, data-informed manner. We present a benchmarking methodology and illustrate its application in New York State school districts. We…

In this paper, we put forward the OTTO Model as a means for developing data literacy in pre-service teacher education. The OTTO Model was developed using a combination of quantitative and qualitative data drawn from a three-year study investigating the nature and development of pre-service teachers' data literacy. The aim of the study was to…

Since 2016, the Advanced Distributed Learning (ADL) Initiative has been developing the Total Learning Architecture (TLA), a 4-pillar data strategy for managing lifelong learning. Each pillar describes a type of learning-related data that needs to be captured, managed, and shared across an organization. Each data pillar is built on a set of…

This study compared the direct, indirect, and total effects of information, communication, and technology (ICT) variables on math achievement for second-generation immigrant, first-generation immigrant, and nonimmigrant students. A path model was used to analyze U.S. nationally representative data from the Program for International Student…

With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…

In educational technology and learning sciences, there are multiple uses for a predictive model of whether a student will perform a task correctly or not. For example, an intelligent tutoring system may use such a model to estimate whether or not a student has mastered a skill. We analyze the significance of data recency in making such…

The objective of this paper is to present value-added calculation methods that were applied to determine whether online schools performed at the same or different levels relative to standardized testing. This study includes information on how we approached our value added model development and the results for 32 online public high schools in…

Peer assessment has been increasingly integrated in educational settings as a strategy to foster student learning. Yet little has been studied about how students at different learning levels may benefit from peer assessment. This study examined how peer-assessment and students' learning levels influenced students' project performance using a…

We present "Science Assistments," an interactive environment, which assesses students' inquiry skills as they engage in inquiry using science microworlds. We frame our variables, tasks, assessments, and methods of analyzing data in terms of "evidence-centered design." Specifically, we focus on the "student model," the…

When validating assessment models built with data mining, generalization is typically tested at the student-level, where models are tested on new students. This approach, though, may fail to find cases where model performance suffers if other aspects of those cases relevant to prediction are not well represented. We explore this here by testing if…

The purpose of the study is to describe student's performance in tutorial online (tuton) of Social Studies through developing the 5Es--Engage Explore, Explain, Elaborate, and Evaluate--Learning Cycle Model (the 5Es-LCM). The study conducted at UT-Online portal uses the Research and Development (R&D) method. The research subjects consisted of…

A key component to the new wave of performance-based pay initiatives is the use of student achievement data to evaluate teacher performance. As greater amounts of student achievement data are being collected, researchers have been developing and applying innovative statistical and econometric models to longitudinal data to develop measures of an…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…

As the general public demands to know what and how students are learning, schools face some unprecedented issues of accountability regarding student performance. In order to acquire data which is accurate and useful, teachers are turning to more formative assessment methods. These methods convey the ideas that assessment should engage students in…