This study involves the development and validation of a survey that measures college students' digital readiness for academic engagement in terms of their perceived digital competencies for academic work. Both exploratory and confirmatory analyses were employed to assess the factorial structure of the Digital Readiness for Academic Engagement…

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…

The purpose of this study is to propose a 6-T model (Tool, Toy, Telephone, Territory, Treasure of Information, and Trade) to explore college students' Internet-related attitudes, and to examine whether gender and grade level make any difference in their attitudes. Data from 1069 participants were collected from 96 Taiwanese universities and…

Purpose: In western countries, a model to explain student engagement in college or university has long been established. However, there is a lack of research to develop and validate a model which may help to better understand student engagement in the local university context. There is currently no established instrument to measure student…

A confirmatory factor analysis (CFA) tested the fit of Kelly and Lee's six-factor model of career decision problems among 188 college students. The six-factor model did not fit the data well, but a five-factor (Lack of Information, Need for Information, Trait Indecision, Disagreement with Others, and Choice Anxiety) model did provide a good fit.…