Here’s what my email spam folder looks like some days:
Predatory open access publishing: “an exploitative open-access publishing business model that involves charging publication fees to authors without providing the editorial and publishing services associated with legitimate journals.”
Jeffrey Beal gathers information on predatory open access publishers and journals. If you are ever unsure, double-check before submitting your paper. Better yet, start with a list of reputable open access journals in your field, such as the one below, which comes from page 33 in Perkins, R., & Lowenthal, P. R. (2016). Open access journals in educational technology: results of a survey of experienced users. Australasian Journal of Educational Technology, 32(3), 1-37.
Australasian Journal of Educational Technology
Canadian Journal of Learning and Technology
Contemporary Issues in Technology and Teacher Education
Educational Technology & Society
Electronic Journal of e-Learning
European Journal of Open and Distance Learning
IEEE Transactions on Learning Technologies*
International Journal of Artificial Intelligence in Education*
International Journal of Designs for Learning
International Journal of Educational Research and Technology
International Review of Research in Open and Distance Learning
Journal of Asynchronous Learning Networks
Journal of Computer-Mediated Communication
Journal of Distance Education
Journal of Information Technology Education
Journal of Online Learning and Teaching
Journal of Technology Education
Online Journal of Distance Learning Administration
Research in Learning Technology (ALT-J)
Turkish Journal of Educational Technology
Turkish Online Journal of Distance Education
What do scholars share on social media? Like the jelly jars below, some topics shared/discussed are familiar. The center jelly nn the top row? I’ve seen many of those. A scholar sharing a link to a paper? I’ve seen many of those, too. Other jellies, and scholarly activities online, are more complex and require a closer look. The bottom right jelly? I’m not quite sure what to make of it. Some scholars disclose challenging professional and personal issues on social media. That’s what Bonnie Stewart and I set out to understand in a our paper Discreet Openness: Scholars’ Selective and Intentional Self-Disclosures Online. Popular literature tends to offer conflicting advice on this topic. Scholars are encouraged to share both personal and professional aspects of their self online, but at the same time they are advised to “watch what they say.” The empirical literature examining scholars’ online self-disclosures and the reasons for making these disclosures remains limited.
DGJ_5184 – Jelly Jars by Dennis Jarvis
Research into emergent forms of scholarship focuses on academics’ use of technology for learning, teaching, and research. Very little attention has been paid in the literature to scholars’ uses of social media to disclose challenging personal and professional issues. This article addresses the identified gap in the literature and presents a qualitative investigation into the types of disclosures that 16 scholars made online and their reasons for doing so. Results identify wide-ranging personal and professional disclosures. Participants disclosed not only about academia-related issues but also about challenges pertaining to family, mental health, physical health, identity, and relationships. Some scholars disclosed as a way to grapple with challenges they faced; others disclosed tactically, sharing information for political rather than personal reasons. Yet others disclosed as a way to welcome care in their lives. In all instances, though, disclosures were selective, intentional, and approached with foresight.
Unlike popular literature that suggests that scholars are “naive users of social media” and must exercise caution, our research shows that people might be thinking deeply about the the ways that the share aspects of their lives.
You can retrieve the paper from here:
Veletsianos, G. & Stewart, B. (2016). Scholars’ open practices: Selective and intentional self-disclosures and the reasons behind them. Social Media + Society, 2(3). doi: 10.1177/2056305116664222
Education Scholars’ Evolving Uses of Twitter as a Conference Backchannel and Social Commentary Platform
The scholarly community faces a lack of large-scale research examining how students and professors use social media in authentic contexts and how such use changes over time. Continuing our investigation into how professors and students use social media, Royce Kimmons and I just published a paper in which we used data mining methods to better understand academic Twitter use during, around, and between the 2014 and 2015 American Educational Research Association annual conferences both as a conference backchannel and as a general means of participating online. The first paper we published using similar methods, data, and comparing students and professors’ social media use is here. All of our research on networked scholarship and students’ and faculty members’ use of social media is gathered here.
Descriptive and inferential analysis is used to explore Twitter use for 1,421 academics and the more than 360,000 tweets they posted. Results demonstrate the complicated participation patterns of how Twitter is used “on the ground.” In particular, we show that:
- tweets during conferences differed significantly from tweets outside conferences
- students and professors used the conference backchannel somewhat equally, but students used some hashtags more frequently, while professors used other hashtags more frequently
- academics comprised the minority of participants in these backchannels, but participated at a much higher rate than their non-academic counterparts
- the number of participants in the backchannel increased between 2014 and 2015, but only a small number of authors were present during both years, and the number of tweets declined from year to year.
- various hashtags were used throughout the time period during which this study occurred, and some were ongoing (ie, those which tended to be stable across weeks) while others were event-based (ie, those which spiked in a particular week)
- professors used event-based hashtags more often than students and students used ongoing hashtags more often than professors
- ongoing hashtags tended to exhibit positive sentiment, while event-based hashtags tended to exhibit more ambiguous or conflicting sentiments
These findings suggest that professors and students exhibit similarities and differences in how they use Twitter and backchannels and indicate the need for further research to better understand the ways that social technologies and online networks are integrated in scholars’ lives.
Here’s the full citation and paper:
Kimmons, R. & Veletsianos, G. (2016). Education Scholars’ Evolving Uses of Twitter as a Conference Backchannel and Social Commentary Platform. British Journal of Educational Technology, 47(3), 445—464.
A number of literature reviews have been published on MOOCs. None has focused exclusively on the empirical literature. In a recent paper, we analyzed the empirical literature published on MOOCs in 2013-2015 to make greater sense of who studies what and how. We found that:
- more than 80% of this literature is published by individuals whose home institutions are in North America and Europe,
- a select few papers are widely cited while nearly half of the papers are cited zero times,
- researchers have favored a quantitative if not positivist approach to the conduct of MOOC research,
- researchers have preferred the collection of data via surveys and automated methods
- some interpretive research was conducted on MOOCs in this time period, but it was often basic and it was the minority of studies that were informed by methods traditionally associated with qualitative research (e.g., interviews, observations, and focus groups)
- there is limited research reported on instructor-related topics, and
- even though researchers have attempted to identify and classify learners into various groupings, very little research examines the experiences of learner subpopulations (e.g., those who succeed vs those who don’t; men vs women).
We believe that the implications arising from this study are important for research on educational technology in general and not jut MOOC research. For instance, given the interest on big data and automated collection/analysis of the data trails that learners leave behind on digital learning environments, a broader methodological toolkit is imperative in the study of emerging digital learning environments.
Here’s a copy of the paper:
Veletsianos, G. & Shepherdson, P. (2016). A Systematic Analysis And Synthesis of the Empirical MOOC Literature Published in 2013-2015. The International Review of Research in Open and Distributed Learning, 17(2).
I have a new paper out that sought to identify and describe faculty members’ open and sharing practices at one North American institution. Part of the goal was to juxtapose open practices and sharing practices. The paper highlights individual and environmental influences on open and sharing practices. The paper also suggests that defaults (e.g., the default youtube license) may be exerting pressures on the ways that scholars share their teaching, research, and scholarship. In other words, one way to instigate further change in this domain might be to rethink the default options.
Although the open scholarship movement has successfully captured the attention and interest of higher education stakeholders, researchers currently lack an understanding of the degree to which open scholarship is enacted in institutions that lack institutional support for openness. I help fill this gap in the literature by presenting a descriptive case study that illustrates the variety of open and sharing practices enacted by faculty members at a North American university.
Open and sharing practices enacted at this institution revolve around publishing manuscripts in open ways, participating on social media, creating and using open educational resources, and engaging with open teaching. This examination finds that certain open practices are favored over others. Results also show that even though faculty members often share scholarly materials online for free, they frequently do so without associated open licenses (i.e. without engaging in open practices). These findings suggest that individual motivators may significantly affect the practice of openness, but that environmental factors (e.g., institutional contexts) and technological elements (e.g., YouTube’s default settings) may also shape open practices in unanticipated ways.
The paper, open access and all, is here in pdf, or directly from the source: Veletsianos, G. (2015). A case study of scholars’ open and sharing practices. Open Praxis, 7(3), 199-209. http://openpraxis.org/index.php/OpenPraxis/article/view/206/168
What do learning experiences in MOOCs look like? Amy Collier, Emily Schneider and I have just published a paper that provides some in-depth answers to this question. Here is a copy of the paper in pdf. The paper is part of a special issue published by the British Journal of Educational Technology which can be found here (there are many excellent pieces in that issue, so be sure to read them).
In addition to trying to understand learner experiences, in the paper we describe that we did this study because “ease of access to large data sets from xMOOCs offered through an increasing number of centralized platforms has shifted the focus of MOOC research primarily to data science and computational methodologies, giving rise to a discourse suggesting that teaching and learning can be fully analyzed, understood and designed for by examining clickstream data”
Our abstract reads:
Researchers describe with increasing confidence what they observe participants doing in massive open online courses (MOOCs). However, our understanding of learner activities in open courses is limited by researchers’ extensive dependence on log file analyses and clickstream data to make inferences about learner behaviors. Further, the field lacks an empirical understanding of how people experience MOOCs andwhy they engage in particular activities in the ways that they do. In this paper, we report three findings derived by interviewing 13 individuals about their experiences in MOOCs. We report on learner interactions in social networks outside of MOOC platforms, notetaking, and the contexts that surround content consumption. The examination and analysis of these practices contribute to a greater understanding of the MOOC phenomenon and to the limitations of clickstream-based research methods. Based on these findings, we conclude by making pragmatic suggestions for pedagogical and technological refinements to enhance open teaching and learning.
We reported 3 main findings:
1. Interactions in social networks outside of the MOOC platform
A number of learners alluded to interactions they have had with individuals who are part of their social networks. These include digital connections with other participants in a MOOC, face-toface interactions with friends and family, and face-to-face interactions with new connections in a MOOC.
Despite the fact that none of the popular MOOC platforms support integrated notetaking at the time of writing this paper, nearly all interviewees reported taking notes while watching lecture videos. Only one interviewee never took notes. However, the tools used to take notes and the subsequent use of notes varied substantially by learner.
3. Consuming content
All individuals participating in this study discussed factors that shaped the ways they consumed MOOC content, shedding light on the context surrounding their participation. Scholars in the learning sciences have long highlighted the critical role of the environment, arguing that learning must be understood as a sociocultural phenomenon situated in context and culture (Brown, Collins & Duguid, 1989). Patterns of MOOC content consumption can be examined by clickstream data, but these contextual factors help explain why learners exhibit particular patterns of participation.
Veletsianos, G., Collier, A., & Schneider, E. (2015). Digging Deeper into Learners’ Experiences in MOOCs: Participation in social networks outside of MOOCs, Notetaking, and contexts surrounding content consumption. British Journal of Educational Technology 46(3), 570-587.
If it wasn’t abundantly clear by now, George Siemens and Stephen Downes are two individuals that are making significant contributions to the field. I respect them both and I enjoy engaging with their work. They have been having a conversation regarding the research and academic diversity in MOOCs, (here and here and here) as a result of a report that George and colleagues released on the history and current state of blended, distance, and online education.
I am writing to add to that conversation because my colleagues and I analyzed some parts of the literature published on MOOCs, and have some results that are relevant and interesting. The paper is under review but the editor gave me permission to share our findings.
We studied the disciplinary distribution of the authors who published MOOC research in 2013-2015 and compared it to the submissions to the MOOC Research Initiative (MRI) reported in Gašević et al., (2014). Our tests showed that the MOOC literature published in 2013-2015 differed significantly from the MRI submissions: our corpus had a greater representation of authors from Computer Science and the Gašević et al., corpus had a greater representation of authors from Education and Industry. In other words, our corpus was less dominated by authors from the field of education than were the MRI submissions. One of Downes criticisms is the following: “the studies are conducted by people without a background in education.” This finding lends some support to his claim, though a lot of the research on MOOCs is from people affiliated with education, but to support that claim further one could examine the content of this papers and identify whether an educational theory is guiding their investigations.
We also compared author affiliation information in our papers with the papers used in Liyanagunawardena et al.’s (2013) review of the 2008-2012 MOOC literature. We found that the two samples differed significantly. For example, the Liyanagunawardena et al. corpus was relatively over-represented in the Independent Researcher category. This result suggests that the bodies of literature published in 2008-2012 and 2013-2015 differ in significant ways. This may or may not hold true for the writing that has occurred in blogs, unpublished reports etc. We don’t know and we haven’t studied that.
Finally, and most significantly, we found that the disciplinary makeup of the literature is changing over time: there’s greater interdisciplinary activity in MOOC research now than in the past. This result is very interesting and its implications are worth examining. Suffice to say that this provides opportunities (can we capitalize on the expertise of one another to improve education?) and challenges (are newcomers to the field capitalizing on what we now about the science of learning?). The move to greater inter- and cross- disciplinarity in the field is evident in other initiatives. See for example, the Digital Learning Research Network.
Keep in mind that this research faces some of the same limitations raised by Downes (i.e. like Siemens, our inclusion criteria mean that some research is included while other is excluded). However, it also addresses some of those criticisms. For example, we tried to verify whether some of our results could have arisen by chance by running 10,000 computer simulations on the samples. The computer is confident that they could not have arisen by chance.
I’m hoping this paper will be out of peer-review soon so that I can share, but I’m thankful to the editor that allowed us to share our findings.
1. Congratulations to the following seven individuals who completed a doctoral degree in 2014.
2. It’s always interesting to explore literature outside of peer-reviewed journals to explore how early career colleagues are thinking about a topic.
3. The doctoral dissertations that follow were all published in 2014 and they focus on various aspects of MOOCs. Undoubtedly, some of the findings reported below will make it into the peer-reviewed literature. As far as I can tell, findings from Kassabian, Kellogg, and Moe have already been published.
3. I believe that it would have been more valuable if these were already published as a series of shorter articles instead of being published as volumes that then need additional effort to be revised/refined for submission to professional journals, a practice that is both frequent and encouraged. My dissertation in 2008 was a 3-paper series. There’s ways to do this, and really good reasons to do so. I’ve discussed this option with 3-4 doctoral students recently that are exploring the option, but institutions need policies and frameworks in place to support such efforts.
4. I digress. Below you can find the citation and abstracts for these seven dissertations. Enjoy!
Gerber, J. (2014). MOOCs: Innovation, Disruption and Instructional Leadership in Higher Education. ProQuest, UMI Dissertations Publishing.
In the beginning rush of attention surrounding MOOCs (Massive Open Online Courses), there was considerable speculation regarding the ideal use and potential impact of this new innovation on teaching, learning, and traditional higher educational structures. Yet universities and colleges were rushing to implement MOOCs despite neither data nor clear understanding regarding their potential disruptive force on the educational landscape. To examine the MOOC phenomenon more closely, I conducted qualitative research that examined MOOCs integration at higher education institutions identified to be at the forefront of the MOOC movement. Framed using Everett Rogers’ model of innovation diffusion (Rogers, 1962), MOOC early adopters were defined as faculty members from US institutions who offered MOOCs between April 2012 and December 2013. This study researched initial MOOC implementation efforts in order to better determine motivations, implications and future impact on higher education, which will provide greater context to this rapidly shifting innovation. My findings indicate that the primary institutional motivation to sponsor MOOCs was to raise and/or enhance their institutional brand. The findings also indicated that faculty that self-selected to participate in MOOCs at the early stage was open to experimentation as well as to the inherent risks associated with the trial of a new educational innovation. This study uncovered important implications on the main pedagogical mission of the university and its professors as a result of instructor and institutional involvement with MOOCs. More specifically, this study revealed that MOOCs have pushed pedagogical issues to the forefront, and faculty early adopters have shifted their classroom teaching in ways believed to improve the classroom experience and create more interactive learning opportunities for students as a result of MOOCs.
Kassabian, D. (2014). Massive Open Online Courses (MOOCs) at elite, early-adopter universities: Goals, progress, and value proposition. ProQuest, UMI Dissertations Publishing.
Massive Open Online Courses (MOOCs) have become a hot topic in higher education and have undergone rapid growth. More than 800 MOOCs have been offered to the public from more than 200 of the most well known universities in the world, with millions of learners taking them. While many elite universities have developed MOOCs, their motivations have not been entirely clear. This qualitative case study research explores what three early adopter universities, Columbia University, Duke University, and Harvard University, hope to achieve by becoming involved and investing in MOOCs, how they are assessing progress toward goals, and what value proposition they seek as a return on their investment. The findings of this research suggest that the studied universities have several goals in common and a few that differ, and importantly, that several of their goals do not directly align with the public narrative around MOOCs in the press. In particular, while the goals of the studied universities do include expanded access to education, their goals may have even more to do with promoting teaching innovation and providing benefits for their residential education. None of the studied universities were focused on improvements to higher education completion challenges through pursuit of MOOC credit, or the use of MOOCs as a way to control higher education costs–both of which are major elements of the public dialogue on MOOCs. Other goals of the early adopters studied included providing more visibility for some of their educational programs and their faculty, and enabling more evidence-based education research. This study concludes that the value proposition for early adopter universities is the ability to simultaneously pursue the goal of improving on-campus teaching and learning while also promoting the university and its faculty and connecting through educational outreach with the public–all while showing leadership in an emerging higher education learning technology.
Kellogg, S. (2014). Patterns of Peer Interaction and Mechanisms Governing Social Network Structure in Three Massively Open Online Courses for Educators. North Carolina State University.
MOOCs, or Massively Open Online Courses, have gained extensive media attention for their vast enrollment numbers and the alliance of prestigious universities collectively offering free courses to learners worldwide. For many, MOOCs are filling the role of continuous education and ongoing professional development, serving to satisfy personal intellectual curiosity or enhance the workplace skills of post-graduates. A recent development in the MOOC space has been courses tailored to educators serving in K-12 settings. MOOCs, particularly as a form of educator professional development, face a number of challenges. Academics as well as pundits from traditional and new media have raised a number of concerns about MOOCs, including the lack of instructional and social supports. It is an assumption of this study that many of the challenges facing MOOCs can be addressed by leveraging the massive number of learners to develop robust online learning communities. Despite the potential benefits for educators, however, building and sustaining online learning communities has generally proved problematic. This study attempts address critical gaps in the literature and address issues of community engagement in MOOCs by examining factors that influence peer interaction among educators. Specifically, this quantitative case study is framed by the social network perspective and utilizes recent advancements in Social Network Analysis to describe the peer discussion networks that develop and model the mechanisms that govern their structure.
Moe, R. (2014). The evolution and impact of the massive open online course. ProQuest, UMI Dissertations Publishing.
An online learning phenomenon emanated 2½ years ago from three courses taught at Stanford University, promising an opportunity for high-quality instruction from elite institutions and professors for no cost to the student. This phenomenon, which came to be known as the MOOC, catalyzed sweeping changes in both higher education’s relationship with distance education, as well as the discussion of higher education in society, in a remarkably short period of time. While people have questioned the effectiveness of MOOC learning and the potential negative consequences of adopting MOOC systems either in support of or to replace existing educational infrastructure, the MOOC movement has continued to grow at a rapid pace. This research study sought to define the characteristics of the MOOC on the terms of learning theory, pedagogy, history, society and policy through the use of an expert-based Delphi study, where participants engaged in a phenomenological dialogue about what constitutes a MOOC in practice, the present state of higher education in the wake of the MOOC movement, the effect the phenomenon has had on education both structurally as well as socially, and visions of the future of the institution of higher education as affected by the MOOC. In summary, panelists focused their agreement on cognitive and pragmatic aspects of the MOOC debate, such as a hope for learning analytics to offer solutions to educational problems as well as the opportunity for the MOOC system to offer tier-based education services to consumers. The Delphi discussion showcased the importance of cognitive theory in MOOC design as well as the relationship between MOOCs and economics, and highlighted the difficulty education experts have in agreeing on how to define educational terminology.
Outland, J. C. (2014). Examining the Market Positioning of Massive Open Online Courses to Maximize Employer Acceptance. ProQuest, UMI Dissertations Publishing.
Massive Open Online Courses (MOOCs) are a new instructional method utilizing many delivery methods common to online academic courses that are being offered in greater frequency as learner interest has increased. Learners may be attending these courses due to a lack of cost and perception that completion of this training may offer some benefit to them as they seek employment. Unfortunately, due to both the relatively recent development of MOOCs and the corresponding variety in delivery and documentation methods, little research had been completed on the acceptability of this instructional method by potential employers. Without this information, learners would be completing training that has little applicable benefit to them as they seek positions or advancement. Additionally, institutions would be offering courses in formats that do not fully benefit students, resulting in a sub-optimal use of institutional resources. The purpose of this qualitative study was to examine the perceptions of U.S.-based employers on instruction using variations of the MOOC model, and to identify traits in this delivery method that make completion of this training advantageous to potential applicants. Human resources and hiring managers were interviewed to determine their preferences using a focus group model. The data collected indicates MOOCS are positively perceived by employers, but not optimally positioned due to a lack of understanding and documentation. Employer perceptions of MOOCs can be enhanced by the consideration and inclusion of industry required skillsets to ensure that learners are focused on employer desired abilities that allow them to meet minimum and preferred job requirements. Additionally, by providing accurate and detailed documentation of the contents of a MOOC, institutions can ensure that a course is readily measurable by employers. This documentation can take many forms, but credentials that detail the topics covered, time spent, and completion evaluation method are preferred. By adopting these identified key requirements of employers, institutions may be able to better position their MOOC offerings into categories that are more easily understood and evaluated during the hiring process. These changes would then enhance the perceived benefits of these classes, and generate additional advantages for job seekers who have completed these courses.
Schulze, A. S. (2014). Massive open online courses (MOOCs) and completion rates: are self-directed adult learners the most successful at MOOCs?. ProQuest, UMI Dissertations Publishing.
Millions of adults have registered for massive open online courses, known as MOOCs, yet little research exists on how effective MOOCs are at meeting the needs of these learners. Critics of MOOCs highlight that their completion rates can average fewer than 5% of those registered. Such low completion rates raise questions about the effectiveness of MOOCs and whether adults enrolling in them have the skills and abilities needed for success. MOOCs have the potential to be powerful change agents for universities and students, but it has previously been unknown whether these online courses serve more than just the most persistent, self-directed learners. This study explored the relationship between self-directed learning readiness and MOOC completion percents among adults taking a single Coursera MOOC. By examining self-directed learning – the ability to take responsibility for one’s own educational experiences – and MOOC completion rates, this research may assist in improving the quality of MOOCs. A statistically significant relationship was found between self-directed learning and MOOC completion percentages. Those stronger in self-directed learning tended to complete a greater percent of the MOOC examined. In addition, English speaking ability demonstrated a mediating effect between self-directed learning and MOOC completion. Learners indicating a strong ability in speaking English were more likely to be ready for self-directed learning and completed a higher percentage of the MOOC. Compared with those that did not complete MOOCs, however, few additional differences in demographics of adult learners that completed MOOCs were found. To better understand the skills and experiences needed to be successful in a MOOC, additional research on factors that influence MOOC completion is warranted. If only a minority of strongly self-directed learners can successfully complete MOOCs, then more resources should be invested into the design and development of MOOCs to meet the needs of many learners. If this does not occur, then MOOC completion rates could continue to suffer and new open education solutions of higher quality may appear, making MOOCs a short-lived phenomenon.
Stefanic, N. M. (2014). Creativity-Based Music Learning: Modeling the Process and Learning Outcomes in a Massive Open Online Course. ProQuest, UMI Dissertations Publishing.
While developing creativity is an important goal of many educational endeavors, creating music, from a music education perspective, is a powerful pedagogical tool. Beyond comparing the relative creativity of individuals’ musical creative products (e.g., melodies, songs, lyrics, beats, etc.), research in musical creativity must consider how engaging in the creative process can be an effective teaching tool, what I have termed creativity-based music learning. If music teachers are to develop students’ abilities “to experience music as meaningful, informed by sensitive discernments and broad understandings, in each particular musical role engagement in which one becomes involved” (Reimer, 2003, p.214), then we must gain a better understanding of how different aspects of the person and context interact during the creative process. Based on the available literature, Webster (1987a, 2002) conceived the Model of Creative Thinking in Music as a conceptual model for understanding the importance of various components that are at work in the musical creative process. Since, generally speaking, learning results from thinking of some sort, Webster’s model represents a reasonable starting point from which to examine how musical creative thinking leads to musical learning. There is much research in music education and the general creativity literature that has investigated how these various component parts (e.g., music aptitude, personality, motivation, previous experience, context) relate to creativity, but there has yet to be any substantive attempt to understand how all of these various elements simultaneously interrelate during a given musical creative process. More importantly, there is limited research on how creativity-based music learning contributes to important learning outcomes such as students’ perceptions of learning from the process, students’ self-evaluations of creative products (e.g., songs they have written), the development of conceptual understandings, and the development of musical creative self-efficacy. The initial primary purpose of this study was to develop and identify a statistical model that best represents the nature of the various interrelationships of components of the musical creative process, as identified in Webster’s (2002) model, and as they relate to learning outcomes. Understanding how all of these components relate and ultimately impact various learning outcomes has important implications for how we educate our music students. Data were collected from students taking a Massive Open Online Course entitled “What is Music?: Finding Your Song,” which was designed, developed, and taught by the researcher, and offered in January 2014 through the Canvas Network. In the course, the question “what is music?” was approached from several perspectives, including Music as Human Activity, Music as Emotion, Music as Physics, and Music as Form. While learning about each perspective, students were encouraged to engage with and complete various musical creative projects (e.g., creating a representative playlist, writing lyrics, writing a melody, writing a song). Such an educational context in which creativity is used as a pedagogical tool provided an opportunity for studying the educational outcomes of such an approach. Embedded within the course were measures of several predictors of learning (based on Webster’s model), including past experience in music, personality, music aptitude, contextual support, musical creative self-efficacy, motivation, and situational engagement. Initial analysis plans included the use of structural equation modeling to (1) compare and contrast the statistical fit of competing models; and (2) examine how each of these constructs not only relate to each other, but also how they each contribute (uniquely and in combination) to various learning outcomes, including perceptions of learning, self-evaluations of creative products, and musical creative self-efficacy. However, a sufficient number of students did not engage in and complete the creative projects, nor did a sufficient number of students complete all of the research items, in order to examine the full structural model. When it became apparent that sufficient data would not be available, the study was re-envisioned to examine questions about why students chose to participate or not participate in the creative music-making projects. Data were collected from 281 students, and although missing data was quite extreme for variables measured late in the course (e.g., motivation), large amounts of data were available regarding students’ past experience in music, their expectations regarding participation as MOOC learners, and demographic information (e.g., age, gender, education, language, geographic region). The available data were used in an exploratory manner to derive a model for predicting creative project participation in the course. The sole important predictor of project participation was whether students identified themselves as an “active participant” at the beginning of the course, although this variable explained only a small amount of variability in project participation. Follow-up analyses for group differences in Active Participant (individuals who identified themselves as “active participants” versus all other Types of Learners) found that “active participants” had significantly higher levels of Musical Creative Self-Efficacy, greater perceptions of the learning context as challenge-supportive, and higher scores on the Openness personality factor. Notably, students’ Past Experience in Music appeared to be unrelated to both whether they intended to participate in the creative music-making projects and whether they actually participated in the projects. In addition to the primary MOOC study, the development and initial validation procedures and results for two new research instruments utilized in the MOOC study, the Past Experience in Music Inventory (PEMI) and the Musical Creative Self-Efficacy Scale (MCSES), are described in detail. The latent class measurement model utilized for measuring Past Experience in Music is a unique and potentially valuable approach for measuring this important variable in music research of all kinds. Finally, an exploratory analysis of all zero-order rank-order intercorrelations of all non-nominal variables indicated some initial support for the General Specified Model of Creativity-Based Learning. It was not possible to take the next step with the model: to prune it, alter it, or reject it altogether, but when viewed as a very large-scale pilot study, this study did provide enough evidence to warrant investing the considerable amount of resources necessary to take that next step. Implications for creativity-based music learning and the significance of MOOCs and MOOC research are discussed. In particular, music MOOCs represent an opportunity to fill in some much needed space for lifelong learning. However, if we are to promote lifelong musical engagement, then the pedagogy within a MOOC should also promote engagement. As such, questions and further research regarding such engagement, especially within a creativity-based learning framework, are central to better understanding how to promote and facilitate lifelong musical engagement and musical learning.