The research of multi-category learning behaviors is a hot issue in interactive learning environment, and there are many challenges in data statistics and relationship modeling. We select the massive learning behaviors data of multiple periods and courses and study the decision application of regression analysis. First, based on the definition of…

Background/Context: Methodological background: Meta-analysis typically depends on the assumption that true effects follow the normal distribution. While assuming normality of effect "estimates" is often supported by a central limit theorem, normality for the distribution of interventions' "true" effects is a computational…

The increasing use of the Learning Management Systems (LMSs) is making available an ever-growing, volume of data from interactions between teachers and students. This study aimed to develop a model capable of predicting students' academic performance based on indicators of their self-regulated behavior in LMSs. To accomplish this goal, the authors…

Educational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students' behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this…

The future of education is human expertise and artificial intelligence working in conjunction, a revolution that will change the education as we know it. The Intelligent Tutoring System is a key component of this future. A quantitative measurement of efficacies of practice to heterogeneous learners is the cornerstone of building an effective…

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…

Bayesian techniques have become increasingly present in the social sciences, fueled by advances in computer speed and the development of user-friendly software. In this paper, we forward the use of Bayesian Asymmetric Regression (BAR) to monitor intervention responsiveness when using Curriculum-Based Measurement (CBM) to assess oral reading…

Recently, researchers have investigated differences in decision making based on description and experience. We address the issue of when experience-based judgments of probability are more accurate than are those based on description. If description is well understood ("transparent") and experience is misleading ("wicked"), it…

Bipolar disorder is frequently clinically diagnosed in youths who do not actually satisfy Diagnostic and Statistical Manual of Mental Disorders (4th ed., text revision; DSM-IV-TR; American Psychiatric Association, 1994) criteria, yet cases that would satisfy full DSM-IV-TR criteria are often undetected clinically. Evidence-based assessment methods…

Professional psychologists are often confronted with the task of making binary decisions about individuals, such as predictions about future behavior or employee selection. Test users familiar with linear models and Bayes's theorem are likely to assume that the accuracy of decisions is consistently improved by combination of outcomes across valid…

The classification problem in educational testing is a decision problem. One must assign subjects to one of several available treatments on the basis of test scores, where the success of each treatment is measured by a different criterion. Examples of classification decisions include individualized instruction, counseling, and clinical settings.…

The issues of treatment assignment is ordinarily dealt with within the framework of testing aptitude treatment interaction (ATI) hypothesis. ATI research mostly uses linear regression techniques, and an ATI exists when the aptitude treatment (AT) regression lines cross each other within the relevant interval of the aptitude variable. Consistent…

The economic utility of the following 5 weighting methods for evaluating consumer loan applications was determined using a sample of 443 loans: (1) unit; (2) weighted application blank; (3) chi square; (4) Bayes; and (5) regression. The unit and weighted application blank procedures were the best approaches. (SLD)

Differences between traditional linear regression and a Bayesian approach to classification are discussed. Classification consists of assigning subjects to one of several available treatments on the basis of their test scores when the success of each treatment is measured by a different criterion. Formulating this problem as an empirical Bayes…