Demographic features are commonly used in Educational Data Mining (EDM) research to predict at-risk students. Yet, the practice of using demographic features has to be considered extremely problematic due to the data's sensitive nature, but also because (historic and representation) biases likely exist in the training data, which leads to strong…

Purpose: In this paper, the challenging and thorny issue of assessing graduate attributes (GAs) is addressed. An interdisciplinary team at The University of Alberta -- developed a formative model of assessment centered on students and instructor interaction with course content. Design/methodology/approach: The paper starts by laying the…

Learner categorization has a pivotal role in making e-learning systems a success. However, learner characteristics exploited at abstract level of granularity by contemporary techniques cannot categorize the learners effectively. In this paper, an architecture of e-learning framework has been presented that exploits the machine learning based…

Certain stereotypes can be associated with people from different countries. For example, the Italians are expected to be emotional, the Germans functional, and the Chinese hard-working. In this study, we cluster all 15-year-old students representing the 68 different nations and territories that participated in the latest Programme for…

An underlying theme of this paper is that it can be easier and more efficient to conduct valid and effective research studies in online environments than in traditional classrooms. Taking advantage of the "big data" available in an online university, we conducted a study in which a massive online database was used to predict student…

The efficacy of online learning programs is tied to the suitability of the program in relation to the target audience. Based on the dataset that provides information on student enrollment, academic performance, and demographics extracted from a data warehouse of a large Southwest institution, this study explored the factors that could distinguish…

In the first of two studies of the data processing program at Johnson County Community College (Kansas), students enrolled in data processing classes during spring 1978 were surveyed to collect basic demographic data and to obtain opinions about the program. There were approximately as many men as women enrolled and the median age was 25, slightly…

This study examines the relationship of selected academic characteristics of students to their success in a two-year college program in electronic data processing. Sample selection, procedures, and findings are described together with a discussion of the results. (Author/CT)

A survey of the 49 students who had enrolled in a self-paced, variable-entry data processing course offered by Black Hawk College (BHC) in cooperation with area public libraries was conducted to determine whether the course was serving the students for whom it was intended, that is, non-major, adult students who were employed full-time and for…

This Users Manual is the supporting documentation for the Public Use Data File from the National Longitudinal Study of the High School Class of 1972 (NLS). The data file contains certain merged data from the base year (1972), and first, second, and third follow-up NLS surveys for 22,652 cases. This volume contains only appendices K through Q, as…

A follow-up job placement study of the 228 persons who either graduated or left Johnson County Community College (JCCC) with marketable skills in 1975-76 produced 191 interview respondents. Findings included the following: the average age of respondents was 28 and 34% were 30 years or older; 53% were male; 64% had enrolled to acquire job skills…