scholarly journals Back to the Future, the Learner Strikes Back: Feedback and Reflection as Key Elements in MOOC re-Design

2019 ◽  
pp. 374-381
Author(s):  
Conchur Mac Lochlainn ◽  
Mairead Nic Giolla Mhichil ◽  
Elaine Beirne ◽  
Mark Brown
Keyword(s):  
Large Scale ◽  
Qualitative Data ◽  
Online Courses ◽  
General Trend ◽  
Massive Open Online Courses ◽  
Massive Open Online ◽  
Course Materials ◽  
Quantitative Studies ◽  
Positive Attitudes ◽  
Preliminary Study

A general trend within research into Massive Open Online Courses (MOOCs) has been the study of learner behaviour and motivations using large-scale, quantitative studies to measure, correlate and predict forms of interaction and participation. Far few studies have focused on contextual, local and qualitative forms of inquiry, despite the great potential of such methods. In this paper, we discuss a preliminary study making use of qualitative data generated on an Irish language MOOC, namely learner comments on reflective steps each week. This data was analysed using an interpretive framework for elucidating both positive and negative forms of learner feedback. Three major themes are defined, relating to opinions regarding course materials, positive attitudes towards interaction and a broad metacognitive awareness of the process of learning. Implications for the design process and the importance of using such methods are briefly discussed.

Understanding learner participation at scale: How and why

2020 ◽  
Vol 17 (3) ◽  
pp. 236-252
Author(s):  
Samaa Haniya ◽  
Luc Paquette
Keyword(s):  
Teaching And Learning ◽  
Large Scale ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Online Course ◽  
Massive Open Online ◽  
Learner Participation ◽  
Massive Open Online Course ◽  
Motivation For Learning ◽  
E Learning

Understanding learner participation is essential to any learning environment to enhance teaching and learning, especially in large scale digital spaces, such as massive open online courses. However, there is a lack of research to fully capture the dynamic nature of massive open online courses and the different ways learners participate in these emerging massive e-learning ecologies. To fill in the research gap, this paper attempted to investigate the relationship between how learners choose to participate in a massive open online course, their initial motivation for learning, and the barriers they faced throughout the course. This was achieved through a combination of data-driven clustering approaches—to identify patterns of learner participation—and qualitative analysis of survey data—to better understand the learners’ motivation and the barriers they faced during the course. Through this study we show how, within the context of a Coursera massive open online course offered by the University of Illinois, learners with varied patterns of participation (Advanced, Balanced, Early, Limited, and Delayed Participation) reported similar motivations and barriers, but described differences in how their participation was impacted by those factors. These findings are significant to gain insights about learners’ needs which in turn serve as the basis to innovate more adaptive and personalized learning experiences and thus advance learning in these large scale environments.

scholarly journals MOOCs: a differentiation by pedagogy, content and assessment

2018 ◽  
Vol 35 (1) ◽  
pp. 2-11 ◽  
Author(s):  
Misrah Hamisah Mohamed ◽  
Michael Hammond
Keyword(s):  
Instructional Design ◽  
Design Methodology ◽  
Online Courses ◽  
Peer Assessment ◽  
Massive Open Online Courses ◽  
Discussion Forums ◽  
Massive Open Online ◽  
Content Type ◽  
Fine Grained ◽  
Course Materials

Purpose Massive open online courses (MOOCs) have often been divided between connectivist MOOCs and extended MOOCs (xMOOCs). Each form of MOOC proposes a distinctive view about knowledge acquisition. However, the breakdown between the two MOOCs is too broad in practice, and a more fine-grained approach is needed. Thus, the purpose of this paper is to describe the organisational features of exemplar MOOCs and their differences. Design/methodology/approach The study observed the ten newly available MOOCs aimed at teachers of English as a second language and included examples from existing providers: NovoEd, Coursera, FutureLearn and Canvas. These MOOCs were analysed and compared using a matrix with three main focuses: pedagogical assumptions, content materials and assessment. Findings The findings revealed that all courses corresponded to the idea of an xMOOC in that they were run on a model of instructional design. However, the course materials varied in respect to media used, use of networking, discussion forums and degree of openness. In terms of assessment, all MOOCs used formative approaches, all had automated responses but only some had summative and peer assessment. Originality/value The study succeeded in showing the variation in courses, thus enabling the range of possibilities open to course designers and providers.

scholarly journals Massive open online courses for professional certificate programs? Perspectives on professional learners’ longitudinal participation patterns

2021 ◽  
pp. 136-147
Author(s):  
Hengtao Tang ◽  
Wanli Xing
Keyword(s):  
Higher Education ◽  
Large Scale ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Massive Open Online ◽  
Certificate Programs ◽  
Learner Participation ◽  
Professional Degree ◽  
The Impact ◽  
Professional Learners

Massive open online courses (MOOCs) have been integrated into higher education systems as an option for delivering online professional degree and certificate programs; however, concerns about whether employed professionals actively participate in MOOCs remain unresolved. Some researchers have described learners’ employment as the major cause of attrition from MOOCs, but research has not addressed how employed learners interact with MOOCs over time. Understanding employed professionals’ trajectory of participation patterns across course time is thus essential to improving the effectiveness of MOOCs. This study investigated the log data of learner participation to explore how attrition occurs in a professional MOOC, focusing on whether students’ employment status was associated with learner participation. The results revealed learners’ longitudinal participation patterns and confirmed the impact of sustained engagement on course performance. The study also found that employed learners were more likely than their peers without jobs to become cramming learners with initially infrequent engagement in a course but investing intensive time at the end for certificates. We discuss practical implications for designing and facilitating large-scale professional degree and certificate programs in higher education institutions. Implications for practice or policy: Educators can apply MOOCs with a lower weekly workload and a slower pace to support employees’ professional development. Educators should develop professional learners’ interests in the course topic to avoid only cramming for the course certificates. Educators may consider longitudinal patterns of learner participation when assessing learner performance.

scholarly journals Technological Innovations in Large-Scale Teaching: Five Roots of Massive Open Online Courses

2017 ◽  
Vol 56 (5) ◽  
pp. 623-644 ◽  
Author(s):  
Sandra Sanchez-Gordon ◽  
Sergio Luján-Mora
Keyword(s):  
Large Scale ◽  
Online Courses ◽  
Careful Consideration ◽  
Open Educational Resources ◽  
Educational Resources ◽  
Massive Open Online Courses ◽  
Technological Innovations ◽  
Computer Assisted ◽  
Successful Implementation ◽  
Massive Open Online

There are millions of people worldwide—of all ages, conditions, backgrounds, and motivations—with significant learning needs. Unfortunately, traditional education is not efficient enough to meet these needs. That is, the available educational resources are not fully exploited to help cover the demand. There is an increasing need for large-scale access to cost-effective and high-quality education. The use of technological innovations for large-scale teaching might be part of the solution. In this context, the goals of this study were to identify technological innovations that can be considered historical milestones in large-scale teaching, to systematize experts’ opinions about the topic, and to propose strategies for the successful implementation of massive open online courses (MOOCs). The researchers identified and analyzed a documentary corpus and found that, in the use of technologies for large-scale teaching, there has been a parallel evolution that have led to the emergence of MOOCs and includes five roots: distance education and online learning, testing or teaching machines and computer-assisted instruction, learning management systems, open education and open educational resources, and online massive teaching. The researchers propose three strategies for the successful implementation of MOOCs: careful consideration of the c/x MOOC pedagogical spectrum characteristics, selection of an appropriate MOOC model, and management of implementation challenges.

scholarly journals Macro MOOC Learning Analytics: Exploring Trends Across Global and Regional Providers

2019 ◽  
Author(s):  
José A. Ruipérez-Valiente ◽  
Matt Jenner ◽  
Thomas Staubitz ◽  
Xitong Li ◽  
Tobias Rohloff ◽  
...  
Keyword(s):  
Learning Analytics ◽  
Large Scale ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Massive Open Online ◽  
Level Of Education ◽  
Preliminary Results ◽  
Gender And Age ◽  
The World ◽  
Limited Generalizability

Massive Open Online Courses (MOOCs) have opened new educational possibilities for learners around the world. Numerous providers have emerged, which usually have different targets (geographical, topics or language), but most of the research and spotlight has been concentrated on the global providers and studies with limited generalizability. In this work we apply a multi-platform approach generating a joint and comparable analysis with data from millions of learners and more than ten MOOC providers that have partnered to conduct this study. This allows us to generate learning analytics trends at a macro level across various MOOC providers towards understanding which MOOC trends are globally universal and which of them are context-dependent. The analysis reports preliminary results on the differences and similarities of trends based on the country of origin, level of education, gender and age of their learners across global and regional MOOC providers. This study exemplifies the potential of macro learning analytics in MOOCs to understand the ecosystem and inform the whole community, while calling for more large scale studies in learning analytics through partnerships among researchers and institutions.

Auto Grouping and Peer Grading System in Massive Open Online Course (MOOC)

2015 ◽  
Vol 13 (3) ◽  
pp. 25-43 ◽  
Author(s):  
Yi Chiou ◽  
Timothy K. Shih
Keyword(s):  
Flipped Classroom ◽  
Online Courses ◽  
Peer Assessment ◽  
Massive Open Online Courses ◽  
Online Course ◽  
Massive Open Online ◽  
Course Materials ◽  
Massive Open Online Course ◽  
Learning Platform ◽  
E Learning

E-learning is a progressive way of learning through online courses. Instructors pass information to learners via context and videos embedded in active webpages, so that learners intake knowledge of what they need. Now e-learning is not simply providing course materials, while the trend of Massive Open Online Courses (MOOCs) is recently applied widely, the concept of flipped classroom is well deployed everywhere. Courses are designed more practical, suitable, and problem-solving inclined. By this way, learners' learning effectiveness and learning motivation are triggered. In this research, the authors will develop an online learning platform and improve the existing methods of peer grouping and peer assessment, to promote the concept of MOOCs.

scholarly journals Computer-Assisted Reading and Discovery for Student Generated Text in Massive Open Online Courses

2014 ◽  
Vol 2 (1) ◽  
Author(s):  
Justin Reich ◽  
Dustin Tingley ◽  
Jetson Leder-Luis ◽  
Margaret E. Roberts ◽  
Brandon Stewart
Keyword(s):  
Language Processing ◽  
Large Scale ◽  
Topic Model ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Course Evaluations ◽  
Computer Assisted ◽  
Discussion Forums ◽  
Massive Open Online ◽  
Daunting Challenge

Dealing with the vast quantities of text that students generate in Massive Open Online Courses (MOOCs) and other large-scale online learning environments is a daunting challenge. Computational tools are needed to help instructional teams uncover themes and patterns as students write in forums, assignments, and surveys. This paper introduces to the learning analytics community the Structural Topic Model, an approach to language processing that can 1) find syntactic patterns with semantic meaning in unstructured text, 2) identify variation in those patterns across covariates, and 3) uncover archetypal texts that exemplify the documents within a topical pattern. We show examples of computationally aided discovery and reading in three MOOC settings: mapping students’ self-reported motivations, identifying themes in discussion forums, and uncovering patterns of feedback in course evaluations. 

Unfolding Sentimental and Behavioral Tendencies of Learners' Concerned Topics From Course Reviews in a MOOC

2018 ◽  
Vol 57 (3) ◽  
pp. 670-696 ◽  
Author(s):  
Sannyuya Liu ◽  
Xian Peng ◽  
Hercy N. H. Cheng ◽  
Zhi Liu ◽  
Jianwen Sun ◽  
...  
Keyword(s):  
Large Scale ◽  
Topic Model ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Video Production ◽  
Feedback Channel ◽  
Massive Open Online ◽  
Behavioral Tendencies ◽  
Negative Sentiment ◽  
Interactive Feedback

Course reviews, which is designed as an interactive feedback channel in Massive Open Online Courses, has promoted the generation of large-scale text comments. These data, which contain not only learners' concerns, opinions and feelings toward courses, instructors, and platforms but also learners' interactions (e.g., post, reply), are generally subjective and extremely valuable for online instruction. The purpose of this study is to automatically reveal these potential information from 50 online courses by an improved unified topic model Behavior-Sentiment Topic Mixture, which is validated and effective for detecting frequent topics learners discuss most, topics-oriented sentimental tendency as well as how learners interact with these topics. The results show that learners focus more on the topics about course-related content with positive sentiment, as well as the topics about course logistics and video production with negative sentiment. Moreover, the distributions of behaviors associated with these topics have some differences.

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