Forecasting the enrollments of new students in bachelor's systems became an urgent desire in the majority of higher education institutions. It represents an important stage in the process of making strategic decisions for new course's accreditation and optimization of resources. To gain a deep view of the educational forecasting context, the most…

Background: Traditional survey efforts to gather outcome data at scale have significant limitations, including cost, time, and respondent burden. This pilot study explored new and innovative large-scale methods of collecting and validating data from publicly available sources. Taking advantage of emerging data science techniques, we leverage…

Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…

This guide is designed for use by school, district, and state education agency staff to improve the effectiveness of efforts to collect and use discipline data, including reporting accurate and timely data to the federal government. It explains the importance of collecting discipline data, identifies key considerations for agencies implementing…

A large dataset of word recognition behavior from nonnative speakers (NNS) of English was collected using an online crowdsourced lexical decision task. Lexical features were used to predict NNS lexical decision latencies and accuracies. Predictors of NNS latencies and accuracy included contextual diversity, age of acquisition, and contextual…

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…

The educational recommendation system to provide support for academic guidance and adaptive learning has always been an important issue of research for smart education. A bad guidance can give rise to difficulties in further studies and can be extended to school dropout. This paper explores the potential of Educational Data Mining for academic…

School psychologists regularly use decision rules to interpret student response to intervention in reading. Recent research suggests that the accuracy of those decision rules depends on the duration of progress monitoring, the number of observations available, and the amount of measurement error present. In this study, we extended existing…

The need for data-informed decisions is not limited to national policy, state systems, or senior leadership of postsecondary institutions. Decisions that impact the achievement of higher education missions are also made by students, faculty, frontline staff, and program administrators--all of who deserve data and information to support their…

This article advocates using Leventhal's (1980) justice judgment theory to incorporate distributive and procedural justice into summative assessment of student learning in higher education. It reviews important commonalities between the process of employee performance appraisal in organizations and practices to assess student learning in academe…

The development in information science has enabled an explosive growth of data, which attracts more and more researchers to engage in the field of big data analytics. Noticeably, in many real-world applications, large amounts of data are imbalanced data since the events of interests occur infrequently. Classification of imbalanced data is an…

Most data-informed decision-making in education is undermined by flawed interpretations. Educator-driven interventions to improve data use are beneficial but not omnipotent, as data misunderstandings persist at schools and school districts commended for ideal data use support. Meanwhile, most data systems and reports display figures without…

The usage of data mining has dramatically increased over the past few years and the education sector is leveraging this field in order to analyze and gain intuitive knowledge in terms of the vast accumulated data within its confines. The primary objective of this study is to compare the results of different classification techniques such as Naïve…