Adapting interventions based on learner progress is paramount to the effectiveness of interventions in special education and applied behavior analysis. Although there is some research on effective methods for training practitioners to make general instructional decisions (e.g., modify an intervention) based on graphed performance data, research on…

Institutional researchers are acutely aware of the systemic inequities pervasive throughout higher education in the United States because the data that we collect, analyze, visualize, and disseminate quantifies and reveals them. As calls for addressing issues of equity have intensified across campuses, the question of how institutional research…

Learning analytics (LA) provides insight into student performance and progress, allowing for targeted interventions and support to improve the student learning experience. Uses of LA are diverse, including measuring student engagement, retention, progression, student well-being and curriculum development. This article provides perspectives on the…

Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…

Data-based decision-making, which involves evaluating students' progress and making instructional decisions, is an integral competency for preservice teachers. Several studies have found that visual aids, such as decision-making models, may be an effective way to train preservice teachers to make instructional decisions. The purpose of this study…

In recent years, there has been growing interest in the use of data-driven learning (DDL) in L2 writing instruction. This paper examined whether and to what extent DDL activities could enhance the writing complexity, accuracy, and fluency (CAF) of 30 Thai EFL learners. The presentation of DDL in this study was hands-on concordancing with the…

Through time-series graphs, teachers often evaluate progress monitoring data to make both low- and high-stakes decisions for students. The construction of these graphs--specifically, the presence of an aimline and the data points per x- to y-axis ratio (DPPXYR)--may impact decisions teachers make. The purpose of this study was to evaluate the…

This study uses the log data from Moodle learning management system for predicting student learning performance in the first third of a semester. Since the quality of the data has great influence on the accuracy of machine learning, five major data transmission methods are used to enhance data quality of log file in the data preprocessing stage.…

The current study used theories on expertise development (the holistic model of image perception and the information reduction hypothesis) as a starting point to identify and explore potentially relevant process measures to monitor and evaluate expertise development in radiology residency training. It is the first to examine expertise development…

Presenting novel numbers about climate change to people after they estimate those numbers can shift their attitudes and scientific conceptions. Prior research suggests that such science learning can be supported by encouraging learners to make use of given benchmark information, however there are several other numerical estimation skills that may…

Learning analytics (LA) has gained increasing attention for its potential to improve different educational aspects (e.g., students' performance and teaching practice). The existing literature identified some factors that are associated with the adoption of LA in higher education, such as stakeholder engagement and transparency in data use. The…

Abstract: This study evaluated whether or not teachers of students with severe disabilities reported implementing specific data-based decision guidelines to make instructional decisions (Browder, Liberty, Heller, & D'Huyvetters, 1986; Browder, Demchak, Heller, & King, 1989) following completion of their teacher preparation program. A…

Critical success factors (CSFs) have been around since the late 1970s and have been used extensively in information systems implementations. CSFs provide a comprehensive understanding of the multiple layers and dimensions of implementation success. In the specific context of learning analytics (LA), identifying CSFs can maximise the possibilities…

Engaging students in the creation of learning resources is an effective way of developing a repository of revision items. However, a selection process is needed to separate high- from low-quality resources as some of the materials created by students can be ineffective, inappropriate or incorrect. In this study, we share our experiences and…

Objective: In the first study of its kind, the impact of excluding noncredit enrollments in calculations of spending in community colleges is explored. Noncredit enrollments are not reported to Integrated Postsecondary Education Data System (IPEDS), but expenditures for these efforts are. This study corrects for this omission and provides new…