Encouraging teachers to reflect on their instructional practices and course design has been shown to be an effective means of improving instruction and student learning. However, the process of encouraging reflection is difficult; reflection requires quality data, thoughtful analysis, and contextualized interpretation. Because of this, research on…

The large rates of students' failure is a very frequent problem in undergraduate courses, being even more evident in exact sciences. Pointing out the reasons of such problem is a paramount research topic, though not an easy task. An alternative is to use Educational Data Mining techniques (EDM), which enables one to convert data from educational…

This article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…

The MUSIC (eMpowerment, Usefulness, Success, Interest, Caring) Model of Academic motivation was developed to help instructors promote student motivation in the classroom. This study examines relationships among student perceptions of motivation and effort compared with their performance in undergraduate business analytics courses. Specifically,…

This paper analyzes the dataset collected from students participating in the Boy With A Ball (BWAB) program, a faith-based community outreach group, through the Hemingway Measure of Adult Connectedness©, a questionnaire measuring the social connectedness of adolescents. This paper first approaches the data in the conventional method provided by…

In classrooms, some transitions between activities impose (quasi-)synchronicity, meaning there is a need for learners to move between activities at the same time. To make real-time decisions about when to move to the next activity, teachers need to be able to balance the progress of their students as they work at different paces. In this paper, we…

Purpose: This study aims to investigate the feasibility of developing general predictive models for using the learning management system (LMS) data to predict student performances in various courses. The authors focused on examining three practical but important questions: are there a common set of student activity variables that predict student…

The use of learner modelling approaches is critical for providing adaptive support in educational computer games, with predictive learner modelling being among the key approaches. While adaptive supports have been shown to improve the effectiveness of educational games, improperly customized support can have negative effects on learning outcomes.…

Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…

For outsiders to higher education institutions (HEIs) in South Korea, predicting the outcomes of the International Education Quality Assurance System (IEQAS)--a Korean institutional accreditation system for HEIs--is challenging. The annual IEQAS accreditation has been conducted behind closed doors; the assessment process is confidential, and there…

This dissertation's two primary purposes were to construct an alternative socioeconomic status model and estimate how it predicts student success in higher education. This research filled a gap in knowledge about the widely acknowledged disparities in higher education based on socioeconomic status. Prior research has often relied on parental…

Research shows college readiness can be predicted using a variety of measures, including test scores, grades, course-taking patterns, noncognitive instruments, and surveys of how well students understand the college admissions process. However, few studies provide guidance on how educators can prioritize predictors of college readiness across…

The purpose of the study is to analyse and identify the stages of adoption of the blended learning (BL or b-learning) methodology in higher education contexts, and to assess the relationship of these stages with a set of variables related to personal and professional characteristics, attributes perceived on BL and contextual variables. About 980…

We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…

This article provides an analysis of the academic performance of higher education institutions (HEIs) in Vietnam with 50 universities and 50 colleges in 2011/12. The two-stage semiparametric data envelopment analysis is used to estimate the efficiency of HEIs and investigate the effects of various factors on their performance. The findings reveal…