Knowledge tracing is a fundamental area of educational data modeling that aims at gaining a better understanding of the learning occurring in tutoring systems. Knowledge tracing models fit various parameters on observed student performance and are evaluated through several goodness of fit metrics. Fitted parameter values are of crucial interest in…

A great deal of research in educational data mining is geared towards predicting student performance. Bayesian Knowledge Tracing, Performance Factors Analysis, and the different variations of these have been introduced and have had some success at predicting student knowledge. It is worth noting, however, that very little has been done to…

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…

Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…

Conducting research and engaging in discussions with administrators and legislators can be important contributions toward alleviating the trend toward lower graduation rates among college students. This study used archival data obtained from the university registrar to examine how engagement in a credit-bearing undergraduate career course related…

In this study, we analyse the predictive power of home and school environment-related factors for determining pupils' aggression. The multiple regression analyses are performed for fourth- and eighth-grade pupils based on the Trends in Mathematics and Science Study (TIMSS) 2007 (N = 8394) and TIMSS 2011 (N = 9415) databases for Slovenia. At the…

Research and practice on knowledge management (KM) have shown that information technology alone cannot guarantee that employees will volunteer and share knowledge. While previous studies have linked motivational factors to knowledge sharing (KS), we took a further step to thoroughly examine this theoretically and empirically. We developed a…

We develop a model of induced innovation that applies to medical research. Our model yields three empirical predictions. First, initial death rates and subsequent research effort should be positively correlated. Second, research effort should be associated with more rapid mortality declines. Third, as a byproduct of targeting the most common…

This study examined pre-service teachers' self-reported intention to use technology. One hundred fifty-seven participants completed a survey questionnaire measuring their responses to six constructs from a research model that integrated the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB). Structural equation modeling was…

This study proposes a new method named the IIS-map-based method for analyzing interactions in face-to-face collaborative learning settings. This analysis method is conducted in three steps: firstly, drawing an initial IIS-map according to collaborative tasks; secondly, coding and segmenting information flows into information items of IIS; thirdly,…

A large sample of 33,000 university alumni records were cluster-analyzed to generate six groups relatively unique in their respective attribute values. The attributes used to cluster the former students included average gift to the university's foundation and to the alumni association for the same institution. Cluster detection is useful in this…

Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international…

A major problem in most predictions of school enrollment is the forecaster's failure to express adequately his certainty or uncertainty in his estimates. Describes a method whereby a forecaster can prepare probability distributions of enrollment predictions. The Monte Carlo computer simulation calculates enrollments by the multivariable method,…

Tested models of interests by examining the significance of disconfirmed ordinal predictions. Examined data regarding Holland's hexagonal model and Roe's circular ordering. Tested adequacy of the hierarchical model and compared significance of the disconfirmed predictions of the hierachical model to that of the hexagonal-circular model. (Author)