Lincoln, Yvonna, and Egon Guba, "Postpositivism and the Naturalist Paradigm," pp. 14-46 in Yvonna Lincoln and Egon Guba, Naturalistic Inquiry . Beverly Hills, CA: Sage, 1985.*

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 research project investigating which student online activities accurately predict academic achievement. Analysis of LMS tracking data from a Blackboard Vista-supported course identified 15 variables demonstrating a significant simple correlation with student final grade. Regression modelling generated a best-fit predictive model for this course which incorporates key variables such as total number of discussion messages posted, total number of mail messages sent, and total number of assessments completed and which explains more than 30% of the variation in student final grade. Logistic modelling demonstrated the predictive power of this model, which correctly identified 81% of students who achieved a failing grade. Moreover, network analysis of course discussion forums afforded insight into the development of the student learning community by identifying disconnected students, patterns of student-to-student communication, and instructor positioning within the network. This study affirms that pedagogically meaningful information can be extracted from LMS-generated student tracking data, and discusses how these findings are informing the development of a customizable dashboard-like reporting tool for educators that will extract and visualize real-time data on student engagement and likelihood of success.

Mining LMS data to develop an early warning system for educators: A proof of concept

As enrolments in online courses continue to increase, there is a need to understand how students can best apply self-regulated learning strategies to achieve academic success within the online environment. A search of relevant databases was conducted in December 2014 for studies published from 2004 to Dec 2014 examining SRL strategies as correlates of academic achievement in online higher education settings. From 12 studies, the strategies of time management, metacognition, effort regulation, and critical thinking were positively correlated with academic outcomes, whereas rehearsal, elaboration, and organisation had the least empirical support. Peer learning had a moderate positive effect, however its confidence intervals crossed zero. Although the contributors to achievement in traditional face-to-face settings appear to generalise to on-line context, these effects appear weaker and suggest that (1) they may be less effective, and (2) that other, currently unexplored factors may be more important in on-line contexts.

Self-regulated learning strategies & academic achievement in online higher education learning environments: a systematic review

Understanding Web-based learning continuance intention: The role of subjective task value

Recently, learning analytics (LA) has drawn the attention of academics, researchers, and administrators. This interest is motivated by the need to better understand teaching, learning, “intelligent content,” and personalization and adaptation. While still in the early stages of research and implementation, several organizations (Society for Learning Analytics Research and the International Educational Data Mining Society) have formed to foster a research community around the role of data analytics in education. This article considers the research fields that have contributed technologies and methodologies to the development of learning analytics, analytics models, the importance of increasing analytics capabilities in organizations, and models for deploying analytics in educational settings. The challenges facing LA as a field are also reviewed, particularly regarding the need to increase the scope of data capture so that the complexity of the learning process can be more accurately reflected in analysis....

Learning Analytics The Emergence of a Discipline

The purpose of this research was to examine student engagement in totally asynchronous online courses through an empirical analysis of student behavior online and its relationship to persistence and achievement. A total of 13 sections of three undergraduate, general education courses provided the setting for the study. Three hundred fifty-four students were used in the data analysis. Using student access computer logs, student behaviors defined as frequency of participation and duration of participation were documented for eight variables. The descriptive data revealed significant differences in online participation between withdrawers and completers and between successful completers and non-successful completers. A multiple regression analysis was used to evaluate how well student participation measures predicted achievement. Approximately 31% of the variability in achievement was accounted for by student participation measures, and three of the eight variables were statistically significant.

Tracking student behavior, persistence, and achievement in online courses

A classification rule was developed to predict undergraduate students& withdrawal from or completion of fully online general education courses. A multivariate technique, predictive discriminant analysis (PDA), was used. High school grade point average and SAT mathematics score were shown to be related to retention in the online university courses. Locus of control and financial aid were able to identify dropout and completion with 74.5% accuracy.

Predicting Retention in Online General Education Courses

Four research studies of students and faculty engaged in fully online undergraduate courses are analyzed to generate best practices for teaching and learning online. These studies investigated the ...

Best Practices in Predicting and Encouraging Student Persistence and Achievement Online

Developing a course for online instruction requires content knowledge and understanding of the interactivity, technological requirements, and possibilities in the asynchronous environment. Using a case study method, the researchers investigated the development of an online humanities course by a team of faculty and instructional designers. Data were collected through observation of face-to-face planning meetings, document analysis of group postings at the online site, and interviews with the team members. Using Berge’s typology of online facilitator roles and Stark and Luttuca’s framework on academic plans, this study examined the roles assumed by team members and the curricular decisions.

Collaborative Course Development for Online Courses

Although the availability of web-based education and the number of totally asynchronous courses have grown exponentially in the last decade, the literature on online instruction offers limited empirical guidance to faculty teaching in this environment. Much of the literature is anecdotal and prescriptive, and much more research needs to be done to situate research in practice settings. This study examines faculty roles in the online environment through the perceptions of faculty teaching online and through the archival analysis of their courses. Data were collected through document analysis of ten online courses and from interviews with thirteen instructors in the humanities and social sciences. Using Berge’s typology of online facilitator roles, this study examined the relationship between roles as perceived and enacted by faculty, identified wide variations in faculty roles and participation between experienced and novice instructors, and explored the relationship between faculty workload and perception of facilitation in the online environment. Directions for future research are suggested.

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Libby V. Morris

Papers

Tracking student behavior, persistence, and achievement in online courses

Predicting Retention in Online General Education Courses

Best Practices in Predicting and Encouraging Student Persistence and Achievement Online

Collaborative Course Development for Online Courses

Roles of faculty in teaching asynchronous undergraduate courses