This paper presents an investigation of score prediction based on natural language processing for two targeted constructs within analytic text-based writing: 1) students' effective use of evidence and, 2) their organization of ideas and evidence in support of their claim. With the long-term goal of producing feedback for students and teachers, we…

Online education continues to become an increasingly prominent part of higher education, but many students struggle in distance courses. For this reason, there has been considerable interest in predicting which students will succeed in online courses and which will receive poor grades or drop out prior to completion. Effective intervention depends…

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…

In a sequential OSCE which has been suggested to reduce testing costs, candidates take a short screening test and who fail the test, are asked to take the full OSCE. In order to introduce an effective and accurate sequential design, we developed a model for designing and evaluating screening OSCEs. Based on two datasets from a 10-station…

In the present study, we considered the utility of the prototype/willingness model in predicting alcohol use among North-American Indigenous adolescents. Specifically, using longitudinal data, we examined the associations among subjective drinking norms, positive drinker prototypes, drinking expectations (as a proxy of drinking willingness), and…

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…

The insider security threat causes new and dangerous dimensions in cloud computing. Those internal threats are originated from contractors or the business partners' input that have access to the systems. A study of trustworthiness and transparency might assist the organizations to monitor employees' activity more cautiously on cloud technologies…

This article reviews the origins, conceptual bases, psychometric properties, and limitations of consumer satisfaction measures in social welfare and behavioral health. Based on a systematic review of research reports published between 2003 and 2013, we identify 58 consumer satisfaction measures. On average, these measures have acceptable…

Purpose: This study aims to empirically validate an innovative work behaviour-enhancing model of employability in small- and medium-sized enterprises (SMEs), and to examine possible moderating effects of age. Design/methodology/approach: Data have been collected from 487 pairs of employees and their immediate supervisors who worked in 151 SMEs.…

Ratings are present in many areas of assessment including peer review of research proposals and journal articles, teacher observations, university admissions and selection of new hires. One feature present in any rating process with multiple raters is that different raters often assign different scores to the same assessee, with the potential for…

During the transition period between the use of exclusively old SAT® scores and the use of exclusively new SAT scores, college admission offices will be receiving both types of scores from students. Making an admission decision based on new SAT scores can be challenging at first because institutions have methods, procedures, and models based on…

The determination of Pass/Fail decisions over Borderline grades, (i.e., grades which do not clearly distinguish between the competent and incompetent examinees) has been an ongoing challenge for academic institutions. This study utilises the Objective Borderline Method (OBM) to determine examinee ability and item difficulty, and from that…

A growing body of research suggests that accounting for student specific variability in educational data can improve modeling accuracy and may have implications for individualizing instruction. The Additive Factors Model (AFM), a logistic regression model used to fit educational data and discover/refine skill models of learning, contains a…

The dimensional comparison theory (DCT) focuses on the effects of internal, dimensional comparisons (e.g., "How good am I in math compared to English?") on academic self-concepts with widespread consequences for students' self-evaluation, motivation, and behavioral choices. DCT is based on the internal/external frame of reference model…

Many researchers have explored the relationships between the likelihood of graduating from college and demographic and pre-college factors such as gender, race/ethnicity, high school grade point average (GPA), and standardized test scores. However, additional factors such as a student's college major, home address, or use of learning support in…