The effectiveness of synchronous massive online courses at The University of Texas at Austin

Is online education an effective and viable alternative to face-to-face education? The purpose of this dissertation was to evaluate the effectiveness of online education at The University of Texas at Austin (UT-Austin). The dissertation focused on Synchronous Massive Online Courses (SMOCs) at The University of Texas at Austin since 2012. This dissertation analyzed the extent to which course effectiveness varies as a function of lecture environment, comparing SMOCs to similar face-to-face (FTF) courses. In total, 25,726 students across 53 courses at UT-Austin were included in analyses. Researchers compiled all relevant student and course data archived in university databases and merged that with course data compiled from archived course syllabi. Then, Hierarchical Linear Modeling was used to test how (a) final course grades vary as a function of lecture environment (SMOC or FTF), controlling for socioeconomic status, scholastic aptitude, and course exam frequency, (b) subsequent semester grades vary as a function of lecture environment (SMOC or FTF), controlling for socioeconomic status, scholastic aptitude, and course exam frequency, and (c) course completion rates vary as a function of lecture environment (SMOC or FTF), controlling for socioeconomic status, scholastic aptitude, and course exam frequency. The primary goal of this project was to examine the effectiveness of SMOCs in comparison to FTFs. Course effectiveness was operationally defined with three objective outcomes: final course grades, subsequent semester GPAs, and course completions. Findings show that there were no significant differences between SMOCs and FTFs on any of these objective measures. That is, SMOCs neither outperform nor underperform FTFs in final grades, subsequent semester GPAs, or course completions. Because previous studies propose that increasing exam frequency may reduce SES-based achievement gaps (e.g., Pennebaker, Gosling, & Ferrell, 2013), and there are some mixed results in the literature about the effectiveness of frequent testing (e.g., Bell, Simone, & Whitfield, 2015), a secondary goal of this dissertation focused on the interaction of SES and exam frequency in the context of course effectiveness outcomes. Exam frequency interacted with lecture environment; such that for FTFs, there was no substantial difference in final course grades by exam frequency; however, for SMOCs, students with more exams had higher final course grades than students with fewer exams. The highest final grades were earned by students in SMOCs that provided the highest exam frequencies (while accounting for control variables). Exam frequency also interacted with socioeconomic status (SES); such that for lower SES students, when exam frequencies are lower the probabilities of course completion are lower than when exam frequencies are higher; and when exam frequencies are higher, the probabilities of course completion are higher than when exam frequencies are lower. For higher SES students, the probabilities of course completion did not vary by exam frequency. Given these findings, increasing exam frequencies in course structures is recommended. Looking across a wide range of course topics and courses, and large number of students, this dissertation provides evidence that SMOCs are as effective as FTFs on objective course outcomes, both short- and long-term. This includes final course grades, subsequent semester GPAs, and course completion rates as course effectiveness measures. Economically, SMOCs are able to reach thousands of students by relying on fewer faculty without the need for large classrooms. At the same time, it frees faculty to teach more and smaller upper division courses. Although the results of the SMOC and FTF courses were generally similar, the additional payoffs of the SMOCs make them a promising tool for the future of undergraduate education. If the high standard of educational course effectiveness is based in the traditional FTF course, then a comparable SMOC course meets that high standard.Psycholog

Towards the Differentiation of Initial and Final Retention in Massive Open Online Courses

Following an accelerating pace of technological change, Massive Open Online Courses (MOOCs) have emerged as a popular educational delivery platform, leveraging ubiqui-tous connectivity and computing power to overcome longstanding geographical and financial barriers to education. Consequently, the demographic reach of education delivery is extended towards a global online audience, facilitating learning and development for a continually ex-panding portion of the world population. However, an extensive literature review indicates that the low completion rate is the major issue related to MOOCs. Due to a lack of in-person inter-action between instructors and learners in such courses, the ability of tutors to monitor learners is impaired, often leading to learner withdrawals. To address this problem, learner drop out patterns across five courses offered by Harvard and MIT universities are investigated in this paper. Learning Analytics is applied to address key factors behind participant dropout events through the comparison of attrition during the first and last weeks of each course. The results show that the number of attired participants during the first week of the course is higher than during the last week, low percentages of attired learners are found prior to course closing dates. It is indicated therefore that assessment fees may not represent a significant reason for learners withdrawal. We introduce supervised machine learning algorithms for the analysis of learner retention and attrition within MOOC platform. Results show that machine learning represents a viable direction for the predictive analysis of MOOCs, with highest performances yielded by Boosted Tree classification for initial attrition and Neural Network based classification for final attrition

An investigation into the attraction and completion rates of MOOCs

Many studies are dedicated to MOOCs, however there was no clear answer to what makes a particular MOOC popular. This study was an attempt to answer this question. Data about MOOC distribution was collected for this research, including category data, university types and MOOC platforms, data regarding MOOC popularity in different time periods, and regarding MOOC completion rates. It was determined that university type and MOOC category did not influence the number of enrolled students. However, Coursera and edX attracted many more students than the other MOOC platforms. Besides these facts, the number of students who really completed the course was much higher for the MOOCs created by top universities. Thus, courses by top universities did not have higher enrolment, however they became more well-known because of the number of students who really took them. The assessment format had a high influence on the completion rates as well. A traditional MOOC format and auto grading caused higher completion rates than other formats. Thus, popular MOOCs could be created in any category by each university, however Coursera and edX’s courses attracted more students, and an auto grading course format involved them in studying the course

A pedagogically-informed model of Massive Open Online Courses (MOOCS) for Mauritian higher education

The purpose of this research was to determine how MOOCs (Massive Open Online Courses) can be introduced and implemented in Higher Education institutions in Mauritius. The study explored the perspectives of students, teachers and educational leaders using an exploratory case study approach, and involved the implementation of short MOOC-based courses in three areas of higher education in Mauritius. While much of the existing literature on MOOCs has used quantitative data to explore patterns of enrolment and retention, this study explicitly focused on student experience, and used Garrison, Anderson and Archer’s (2000) Community of Inquiry (COI) model to explore patterns of ‘presence’ and pedagogical preferences and needs of learners. In order to explore how these preferences, together with other contextual factors might affect the adoption of MOOCs in Mauritius, Venkatesh and Davis’s (2000) Technology Acceptance Model2 (TAM2) was used. The COI and TAM2 models were used both as analytical frameworks, but also to develop a new composite model that also can function as a boundary object (Bowker and Star, 1999; Fox, 2011) enabling different stakeholders to understand each other’s needs and expectations and communicate better with each other. For Mauritian learners, teaching presence in online environments is of critical importance: this is reflected in different scenarios of MOOC implementation identified, and in a proposed staged model for MOOC adoption across the HE sector in Mauritius. This involves further pilots and preliminary research (stage 1), integration of MOOCs into practice (stage 2), customisation and development of MOOCs (stage 3) and a MOOC for Mauritius (stage 4), with each stage informing the implementation of subsequent stages as part of a broad action research framework. The original contributions made by the research to the knowledge base of its possible audiences include: providing models of practice for teachers and educational leaders; informing the educational leaders and policy makers about how MOOCs can be successfully implemented in Mauritius; providing detailed case studies on MOOCs to the academic audience interested in MOOCs specifically; and proposing a new composite, pedagogically-informed, technology acceptance model to those academics who are interested in online pedagogy and technology acceptance. The results of this PhD research can also inform the introduction and effective implementation of MOOCs in other less-economically developed countries