Learning trekking easier and cheaper with Moocs method.

Difficulties of the trekking. Honestly and without grimaces.

It is necessary to cany a heavy backpack. The shoulders are gradually getting used to the load, but the weight is always pressing, especially when you are walking uphill. And it takes 6 … 8 hours a day. And tomorrow too…

Dirty, sometimes knee-deep, trails. Lying across the trail are trees. Stones and roots on the path and strive to turn your legs. Wandering cold rivers should be in shoes. The nights are cool and shivering, but there is nobody to warm it up. You can use best Police flashlight to get more light during the trekking.

Branches cling and tear clothes and body. The rains and the wind are ready to freeze you. The sun – are fry alive. And so it can be in turn for an hour.

To women: unwashed head, dirty clothes, no romance, no “comforts”, scratched hands and feet, men are mating, mosquitoes bite, and «no personal life”. And just hard! Loving nature happens in fragments, it is more necessary to look under the feet, so as not to roll your neck. And the leader-sadist again ran forward. Your head does not take into account your “logical reasoning”. Believe me, he knows better.

Positive sides. Well, not all is so “bad»…

It is so beautiful around only in the mountains. There, nature is untouched by civilization. Active outdoor movement is very useful. After the hike, it will be something new and interesting to tell friends, and then all the stories -about gossip and about “booze.”

There may be new Friends who have passed with you windbreaks, fords and passes. You understand that without a telephone and a TV7 you can live very much. You will learn a lot about yourself new. And good and not very … Something can be proud of! The physical form (in those who had it) is greatly improved.

I hope that these simple notes and tips can make your life easier during the hike.

And, accordingly, you will have more time to enjoy the wildlife. Unfortunately, the English – not my mother tongue. I maintain my notes in Spanish and Portuguese. Some notes may appear overly formalized, but that does not deprive them of their valuables.

A few simple rules in the hike

  • The leader of the hike is always right.
  • No one forced anyone to go on a campaign and even dissuaded.
  • Each participant carries his own backpack or goes home.
  • If the muscles hurt – it means they are, but it was possible to train better.
  • Collect firewood for the campfire all the participants of the hike, and not just the attendants. You can prepare some  best bipod for AR 15 to defense thief and beast.
  • Crying songs around the fire in the middle of the night is possible, but only in a whisper.
  • On the path, remember who goes behind you, because someone is also ahead.
  • Nature has no bad weather, and there is bad equipment.
  • There is no tasteless food, but there are unhappy tourists. You will also be on duty.
  • The thing left by the fire, has a habit of burning in it.
  • Attempts to cross the river on stones with dry boots result in a fall into the river.
  • A good stash is not superfluous, but a Hero of the day does.
  • Together, nobody is frozen in one sleeping bag.
  • Sometimes, it’s better to bypass than climb over, and it’s better to step over than to turn up.
  • The morning is wiser than the evening. It is better to sleep through a difficult decision.
  • If you forgot to take something, then you do not need it, but there can be problems.
  • In the campaign all are equal; there are no ages and posts.
  • For everything that happens to you, in the answer only you yourself.
  • The size of the problem depends on the size of the desire to solve it.
  • Most terrible beast is a Chipmunk.
  • The more isolated the terrain, the safer, cleaner and more beautiful.
  • Do not offend Nature – it may not calculate the strength and size of the surrender.
  • Parking after the group should remain clean, with a stock of firewood and without any forgotten things.
  • I would very much like you to follow these rules in any campaign.
  • Still no one was hurt by doing them.
  • And jww we will get acquainted with several practical recommendations for preparing for the campaign.
  • These are useful notes.
  • For example, I always try to follow them.
  • And till now I had everything in order.

Thank you for reading my short article about how to trek and useful tips that you have never forget to get a better trip with your family and friends. Cheers!

Update for you:

Interesting tips for backpacking

  • To begin with, buy digital scales of small size or digital bezmen. It is perfectly suitable scales with a load capacity7 of up to 10 kg. Now you can safely take your exact instrument to the store and weigh what you buy. Do not be afraid to scare sellers. And let them do not frighten you anymore, now everything is under control!
  • The most reliable and affordable way to lose weight is to reduce your own weight. A few pounds to lose are not difficult, and the ease and endurance
    that you will get is irreplaceable!
  • Think carefully about the list of equipment, much you can just leave at home!
  • Try to avoid fees at the last minute; this is the best way to avoid unnecessary and unnecessary things, for example, to sort out with clothes.
  • If you are planning to go camping with a companion, think over the general equipment, such as awning and dishes.
  • Develop your serving skills; be more creative, most of the expensive equipment can be made with your own hands.

Candace Thille

Candace Thille is a senior research fellow in the Office of the Vice Provost for Online Learning and an assistant professor in the Graduate School of Education at Stanford University. She is the founding director of the Open Learning Initiative at Carnegie Mellon University and at Stanford University. The focus of her work is in applying the results from research in the science of learning to the design and evaluation of open web-based learning environments.

Dr. Thille serves as a redesign scholar for the National Center for Academic Transformation; as a fellow of the International Society for Design and Development in Education; on the Assessment 2020 Task Force of the American Board of Internal Medicine; on the advisory committee for the Association of American Universities STEM initiative; on the advisory committee for the NSF Directorate for Education and Human Resources; and on the board of directors of the Association of American Colleges and Universities. She served on the U.S. Department of Education working group, co-authoring the National Education Technology Plan, and on the working group of the President’s Council of Advisors on Science and Technology that produced the Engage to Excel report.

Richard Clark

Richard Clark is CEO of Atlantic Training Inc., Professor Emeritus of Educational Psychology and Technology in the Rossier School of Education, Clinical Research Professor of Surgery in the Keck School of Medicine and Co-Director of the Center for Cognitive Technology at the University of Southern California. Before coming to USC he was a faculty member in Psychology and Education at Stanford and Syracuse Universities. He also served as Chief Science Advisor for Expert Knowledge Solutions LLC.

Dick is the author of over 300 published articles and book chapters as well as three recent books Learning from Media: Arguments, analysis and evidence, Second Edition (2012, Information Age Publishers); Handling Complexity in Learning Environments: Research and Theory (2006, Elsevier) and Turning Research into Results: A guide to selecting the right performance solutions (2008, Information Age Publishers) which received the International Society for Performance Improvement (ISPI) Award of Excellence. In recent years he has received the 2013 USC Faculty Lifetime Achievement Award, the Thomas F. Gilbert distinguished professional achievement award and a Presidential Citation for Intellectual Leadership from ISPI, the SITE Foundation Excellence in Research Award, the ASTD research study of the year award for his work on performance incentives, the 2010 Thalheimer Neon Elephant Award for bridging the gap between science and practice, the 2011 Presidential Award for Intellectual Leadership from AECT, the Socrates award for excellence in teaching from the graduate students at USC and the Outstanding Civilian Service Award from the U. S. Army for his work in distance learning.

Dick is an elected Fellow of the American Psychological Association (Division 15, Educational Psychology), the American Educational Research Association and the Association of Applied Psychology and is a Founding Fellow of the Association for Psychological Science.

His current research interests include the design and evaluation of online and blended instruction for adults on highly complex tasks, cognitive load theory for multimedia and simulation training, the development of the Guided Experiential Learning design systems for pedagogical applications and the use of Cognitive Task Analysis to capture and teach the complex knowledge used by advanced experts in all fields.

Tools to Enable the Design and Reuse of MOOC Materials

Brandon Muramatsu, Jeffrey Merriman, Cole Shaw

The rush to develop MOOCs has led faculty and course development teams to move quickly to produce the course’s materials. In many cases the only instantiation of the course is in a specific MOOC platform. If we examine the contents of each MOOC we tend to find discrete elements that have a potential to be used elsewhere. However, as faculty and course development teams move from the first offering to subsequent offerings, and as faculty move to use MOOCs more broadly in their residential teaching, they are faced with the question of how, exactly, will they be able to reuse course materials if they are integrally tied to the offering? Will it be the whole MOOC? What affordances do the platforms and development processes have for using individual elements might be video snippets, or text content or formative assessments elsewhere?

The MIT Office of Digital Learning, in collaboration with our faculty, have been developing a set of tools to help manage the granularity of learning activities available on MOOC platforms, such as edX. These tools focus on learning outcomes/learning objectives/individual concepts and their relationships with content and assessments; they help create a growing assessment bank, along with the ability to use assessments outside of a single platform; and they enable pre-production of new courses. These tools focus on the individual components that comprise a course—and begin to move the conversation from the course as the end state to one in which individual, instructionally sound learning activities are the focus.

In particular we would like the opportunity to share our work on:
• The MIT Core Concept Catalog (MC3, http://mc3.mit.edu/): The core concept catalog
anchors much of the work—it provides an infrastructure allowing faculty and instructional designers describe the “core concepts” in a course. These “core concepts” are ideally clearly defined learning outcomes that are clearly measurable. Faculty can use tools we’re developing to describe their courses in terms of these concept banks, and we can present novel navigation structures based on these concept banks within courses and learning experiences.
• Applications of MC3 such as the Video Concept Browser (VCB, http://vcb.mit.edu/ requires a login). VCB was originally designed to allow faculty to design a concept map, associate portions of traditional lecture videos with those concepts, and enable students to watch the video by concept instead of by lecture date. More recently, we’ve been using VCB to create the concept maps and as a pre-production tool when moving from a traditional course to a MOOC.
• Embedded Assessment and Assessment banks: One of the most intriguing aspects of MOOCs is the potential for nearly limitless practice and formative assessment. As MOOCs continue to develop, this collection of assessment items continues to grow in size and potential but they are oftentimes locked into the course and platform in which they are offered. We are building tools to extract assessment items from MOOC course materials1 manage them, as well as reuse them in any web-accessible content.

Four Types of MOOC Research: From Fishing in the Exhaust to Design Research in the Core

Justin Reich

Much has been heralded about the research possibilities inherent in the massive clickstream databases produced by MOOC platforms. If these databases, however, fail to capture important data about students’ learning experiences, then having vast quantities of data will not compensate for having the wrong data. Even in the era of big data, good research depends on good design.

To draw attention to these design considerations, in this presentation I will present a taxonomy of four kinds of MOOC research:
• fishing in the exhaust: post-hoc analyses of courses designed and taught without any particular research agenda, yielding descriptive, observational insights
• experiments in the periphery: A/B type experiments of particular pedagogical approaches that test domain-independent teaching strategies (e.g. commitment devices, priming experiments, or motivational messages) that can be conducted
• observations in the field: qualitative research from interviews and observations that seeks to investigate the contexts in which MOOC students learn and the ways in which they make meaning of their experiences
• design research in the core: design research conducted in partnership with course faculty, instructional designers, and learning scientists to investigate pedagogical questions that attend to core issues in the design of a learning environment (e.g. the effect of using block-based programming languages in introductory computer science courses).

The past year of MOOC research has been characterized by “fishing in the exhaust,” and while some useful initial descriptions of user behavior have emerged from these approaches, there are strict limits to what we can learn from observational research (even observational research with lots of data). The coming year of MOOC research will see more fishing, but also a growth of experiments in the periphery. These kinds of experiments are typically dreamed up by educational researchers and not by course faculty, and as a result they explore issues that are potentially interesting but not central to the learning goals of any particular course. These studies are easy to facilitate in the complex ecosystem of MOOC production, but they may not investigate the most important domains of large-scale online learning.

In order for MOOC research to reach its full potential, the field needs stronger lines of research in both qualitative research and in design research in the pedagogical core of our courses.

Powerful design processes in education begin with empathizing with the learner, and at present we have trillions of cells of data about what people have clicked and we know very little about what has changed in their heads. While the best qualitative research will be conducted by trained specialists, a wide variety of roles in the MOOC production ecosystem—producers, developers, instructional designers, teaching assistants, and researchers—can and should contribute to this important work.

With a better sense of the needs of our learners, the most important and impactful research that will be done with MOOCs will be design research in the core. This difficult work will require close collaboration among teams of diverse researchers and practitioners, but it will investigate questions that pertain directly to the central pedagogical theory in a course or discipline.

Participants will leave the session with both a richer understanding of the importance of research design, and ideas about how to create MOOC production workflows and ecosystems that support ambitious, collaborative research.

MOOCs and the Older Learner

Susan Hoffman, Chelsea Crown

The Osher Lifelong Learning Institute @ Berkeley (OLLI @Berkeley) is a year-round program of courses, lectures, special events, and interest circles for adults age 55+ through the University of California, Berkeley. Since September of 2013, our research team has been investigating Massive Open Online Courses (MOOCs) as a teaching and learning tool in lifelong learning. We have launched two small, informal case studies of MOOCs and the older learner. Our first investigation was specific to the experience of learners over the age of 80, the “high olds,” who enrolled in the Coursera MOOC “What a Plant Knows” and participated in three consecutive monthly meetings discussing their experiences. In January 2014, we expanded our investigation by holding a hybrid MOOC-classroom course, another Coursera course called The History and Future of (Mostly) Higher Education, open to all OLLI @Berkeley members 55+. Participants engaged in the MOOC in their own time and at their own pace during the week and attended 1.5 hour weekly classroom discussions to discuss the experience as well as content.

The MOOC learning experience of older learners is a crucial missing piece of the MOOC puzzle, an oversight in this era of profound demographic change. Concentrating on accessibility for older learners is important for many reasons, as this group may experience multiple barriers to MOOCs including challenges using technology, auditory and visual decline, and cognitive decline. However, this group may reap the most benefits from MOOCs, and thus deserve to be included in discussions. Given that the over 80 demographic is the fastest growing demographic in the country, as well as the most at-risk for social isolation, cognitive decline, and hearing and vision loss, the MOOC-as-intervention is an especially interesting concept to explore in further research. Potential benefits of MOOCs and the older learner may include advantages for homebound older adults who are able to remain intellectually stimulated and socially engaged as well as the neurocognitive advantages of continuing to learn stimulating new skills and knowledge, such as navigating technology and the multitude of subject areas MOOCs offer.

For the above reasons, at OLLI @Berkeley, we have highlighted MOOCs and the older learner as an important focus of our research team and believe that other researchers nationwide should also be aware of the importance of this age-specified investigation. The main takeaway from our research is to stress the importance and notion of universal access. The changes that could be made in MOOCs to make them more universally user-friendly and inclusive are changes that will go beyond age to benefit diverse students worldwide, including other groups that experience similar barriers, such as those with disabilities; English-language learners; and those with limited knowledge or experience of technology due to access issues, to name a few. Testing the platforms and presentations on a wide range of ages and abilities should be an important component of every MOOC development process. By making MOOCs more inclusive and accessible, everyone benefits. The revolutionary effects promised by MOOCs ring hollow if the target population remains limited to mostly traditional-aged able-bodied university students.

Our investigations have yielded several important and concrete findings that could be incorporated into various MOOC platforms with the intention of increased accessibility and user-friendliness. The first need is around better demonstrations and as-you-go assistance of how to navigate a MOOC. The need for an easily searchable and simply navigated demonstration of how to use a MOOC on any given platform has proven most important in group of learners over the age of 80, as they generally experience the least comfort with technology. The demos we explored together often came up short, were difficult to find, and did not serve the special needs of our population. It may make sense to modify platforms to include large, bold buttons indicating where students can access help and receive assistance in navigating various components of MOOCs as they go along, perhaps even offer a virtual MOOC assistant in the spirit of the old Microsoft Word office assistant paperclip icon that offered suggestions and assistance within documents. Simply put, adaptations for differing levels of technology mastery as well as disabilities need to be more overt in MOOCS. For a recent Coursera MOOC, one of our over 80 members with hearing loss expressed extreme frustration that she needed to press the closed caption (CC) button each and every lecture in order to be able to follow along via captions. Among our ideas is the institution of a short quiz during the sign-up stage that results in a tailored experience for the learner. By simply asking a few short questions about level of comfort and experience with technology, hearing or vision difficulties, English-proficiency level, and other barriers to engaging in a MOOC, an algorithm could automatically adjust the user’s personal experience and interface in response to these identified barriers. Another finding from our research is that the presentations of many MOOCs are not age-friendly, such as the instructor using their own scribbled writing on a board to highlight key points, not keeping slides on screen for an adequate period of time, or having otherwise hard-to-read slides or distractions on screen. The frustrations caused by these challenges dominated our research discussions with our older learners. Instituting elements of universal and inclusive design in the way that information is presented are easy adjustments that can become part of the “formula” for MOOCs, such as making sure that writing is clear and large for any accompanying slides, with ideal colors and contrast for aging eyes. Many studies have shown the various ways to make websites and print materials more age-friendly; it is just a matter of incorporating those same ideas into MOOCs. We make constant adjustments in our classrooms at OLLI @Berkeley based on cutting-edge aging research and student feedback and evaluations. It only makes sense for MOOCs to have the same level of responsiveness to the different needs of the older learner.

Even though our research subjects were highly-motivated and self-selected groups with professed interest in taking a MOOC, the barriers outlined in this abstract often led to experiences of frustration and resulted in individuals dropping-out of the course before completion, despite encouragement and support to keep going from peers and our faculty. By focusing on removing barriers, MOOCs can help reduce drop-out rates; as it stands now some estimates are that only 6% of enrollees actually finish a course. Adjusting MOOCs using ideas of universal and inclusive design is a change that will not only serve to better engage older learners, but should have ripple effects across the age and diversity spectrum of MOOC participants.

The Impact of MOOC Blended Instruction to Teach Programming

Velma Latson

Web 2.0 software applications are influencing the change from formal, traditional learning environments that are instructor-directed to more student-centered /open- learning environments where learns have more control. In student-centered/open-learning environments, the focus is on the learner and their ability to use thinking skills to solve problems. Teachers are no longer the authority in the classroom, but co-learners and guides while learners are making their own discoveries (Brown, 2000) about what is important in the learning experience. Learners are encouraged to use prior background knowledge of content to collaborate with experts and peers and new Web 2.0 software applications are making this more open.

MOOCs are web 2.0 teaching applications that are connecting people throughout the world into one classroom environment. MOOCs help learners collaborate, explore and create artifacts that will help them acquire the critical thinking skills to expand their learning. These new theories for instruction using computer technology and social software applications are changing the way people interact in society and gain knowledge in educational environments. New computer software applications are socially constructed for the user’s ability to collaborate and exchange ideas with others.

The University System of Maryland (USM) and Ithaka S+R (2013), initiated a research study on how effective different online learning platforms would be on student outcomes and could these different platforms reduce costs for students enrolled in traditional institutions. The purpose of this presentation is to describe the impact of using the MOOC in a blended instructional environment to teach programming to undergraduate, non-STEM major students. The presentation will describe the lessons learned from implementing MOOC blending instructional environments in a side by side comparison of approximately 100 student participants in the experimental group learning to program from the MOOC and approximately 100 students in the control group learning to program in a traditional classroom setting.

Brown, J.S. (2000). Growing up digital: how the web changes work, education, and the ways people learn. [Electronic version] Change Mar/April.
Ithaka S+R. (2013). Interim Report: A Collaborative Effort to Test MOOCs and Other Online Learning Platforms on Campuses of the University System of Maryland.

Universal MOOC Metrics? How should researchers talk to one another about MOOC data?

Sara Shrader and Jason Mock

Since partnering with Coursera in 2012, the University of Illinois has gathered massive amounts of data from our MOOCs, including data from course surveys (beginning and end of semester), clickstream data, as well as activity data consisting of quiz scores and forum posts. In trying to organize and understand this data, the Illinois Learning Analytics team has considered countless questions regarding the efficacy of MOOCs on student learning. For example, we have explored questions of completion and retention, as well as questions of opportunity and engagement of learners from developing countries. Furthermore, we have encouraged our faculty who are teaching MOOCs to think about the MOOC platform in novel ways, in order to leverage the rich research opportunities available to them.

However, despite having numerous robust discussions surrounding the value of our MOOC data, we have made less headway in answering some of the more fundamental questions about the nature and purpose of MOOCs. In particular, our research group has spent considerable time unpacking the various definitions of traditional metrics for student learning, such as “who counts as a participant?” and “what does learning mean in the context of MOOCs?” One of the most exciting – as well as frustrating – aspects of researching student learning in the context of MOOCs is having the ability to create standards by which to measure success. Unlike traditional online courses, MOOC students hail from a variety of backgrounds with diverse motivations. As such, we need a new “language” for talking about MOOCs, one which takes into account the unique and varied backgrounds and intentions of MOOC students.

This pressing need – creating common metrics for understanding MOOC data – creates some interesting conceptual challenges. On the one hand, our group believes that first and foremost the metrics used to describe MOOC data should serve a greater utilitarian purpose of bringing cohesion to the emerging field of MOOC research. Yet, on the other hand, we recognize the situated and contextualized nature of MOOCs, and understand that creating universal labels may unintentionally mask some of the more nuanced and interesting things to be learned from MOOC data.

In this workshop we would like to share some of the conceptual roadblocks we have encountered in trying to understand MOOC data, as well as to discuss ideas for creating inclusive MOOC metrics that aid researchers in better understanding student learning. In fostering discussion with other researchers, our goal is to generate useful MOOC metrics that enable cross-comparisons of MOOC data.

Understanding Student Engagement in MOOCs

Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume Iii and Lise Getoor

The large number of students participating and the availability of interaction data in massive open online courses (MOOCs) provides an opportunity to study and uncover student engagement patterns, develop technology that can help improve student engagement and facilitate instructor interventions. Our work looks at several problems in MOOCs: 1) modeling student engagement to predict course completion, 2) analyzing changes in engagement patterns, and 3) understanding discussion forum content and the relationship to course completion.

When users interact on a MOOC, they leave behind cues suggestive of their engagement with the course and intention to complete the course. We have developed a data-driven model of student engagement in MOOCs using features from users’ interaction with the MOOC, and use that to predict course completion (course survival) [3]. Our model uses behavioral cues (course related activities such as viewing lectures, giving assignments, participating in discussion forum), forum content (po- larity and subjectivity of forum posts), and forum interaction structure to distinguish between forms of student engagement (active and passive). The engagement types are represented as latent variables in our model and are learned from observed data. We then use the latent variables to predict student survival. We use probabilistic soft logic (PSL) [2], to represent ob- served features, (latent and target) variables as logical predicates and construct rules over these to capture domain knowledge. We evaluated our models on predicting learner survival across three MOOCs—Surviving Disruptive Technologies, Women and the Civil Rights Movement and Gene and Human Condition. We demonstrated that incorporating latent engagement variables helps in predicting student survival.

In order to design effective interventions, we need to identify students at a risk of dropping out early-on in the course. We conducted experiments to predict student survival early-on in the course, by training our models on data from the initial part of the course. Our experiments show that our models, especially the latent model, is able to predict student survival reliably at an early stage when compared to the model without latent variables. In addition to improved prediction accuracy, our latent engagement model also unveils interesting patterns in student engagement. Analyzing latent engagement estimates predicted by our model, we find that passive engagement dominates in the beginning and there is an increase in active forms of en- gagement toward the end. Examining the transition between engagement types, we observed that most passive users show an increase in active engagement levels prior to dropping out. This is suggestive of help-seeking/complaining/expressing dissat- isfaction or difficulty in following course materials in discussion forums before dropping out. Probing these forum-posts, we can uncover reasons leading to student disengagement and dropout and identify students that can be helped via intervention. This leads us to perform a more close analysis of forum content.

Our second contribution is looking more closely at discussion forum content for student survival indicators. MOOC discussion forums are the principal means of interaction among MOOC participants. Negative sentiment can indicate dissatisfaction with the class, however it can also be used to express an opinion showing high levels of engagement. Negative sentiment in course related discussions does not imply attitude toward the course and does not mean disengagement, but in logistics or feedback posts it signifies disengagement. Discerning between the two types of sentiment is vital as we are trying to identify students at a risk of dropping out. We make use of recent improvements in topic modeling, Seeded Topic Modeling (SeededLDA) [1], to extract posts corresponding to course-logistics, feedback and course-related material [under review]. We leverage the knowledge of course syllabus and general nature of logistics and feedback posts to seed our model. We enhance our survival models described above with topic distribution from SeededLDA. Our rules capture sentiment and topic of posts to assess signs of engagement and disengagement. We demonstrate that inclusion of features from topic distribution in our survival models helps in predicting student survival.

Our current research focuses on applying our models to courses as they progress and identify possible instructor interventions.

[1] Jagadeesh Jagarlamudi, Hal Daume ́, III, and Raghavendra Udupa. Incorporating lexical priors into topic models. In Proceedings of EACL, 2012.
[2] Angelika Kimmig, Stephen H. Bach, Matthias Broecheler, Bert Huang, and Lise Getoor. A short introduction to proba- bilistic soft logic. In NIPS Workshop on Probabilistic Programming: Foundations and Applications, 2012.
[3] Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume ́, III, and Lise Getoor. Learning latent engagement patterns of students in online courses. to appear in AAAI 2014.

MOOC Learner Motivation and Course Completion

Yuan Elle Wang and Ryan Baker

In this talk, we will discuss our work to investigate the relationships between the motivations of MOOC learners and completion rates, to study the motivational differences between students who complete the course and those who do not.

The research context is the Coursera MOOC “Big Data in Education”, with a total enrollment of over 48,000. As of the end of the course, the pre-course survey (consisting of subscales of the PALS and MOOC-specific items) received 2,792 responses. Our research results show that this combination of survey measures can be useful for studying students’ motivational directions early in a MOOC. Specifically, we find 4 relationships with the potential to inform future intervention for both instructors and learning designers:
• Students who were more interested in the MOOC learning environment as a new platform of learning than aspects related to the course content area will less likely to complete the course. In specific, non-completers rated higher on items such as “Course is offered by a prestigious university”, “Geographically isolated from educational institutions” when asked their reasons for enrolling in this course.
• Mastery-goal orientation and academic efficacy were not useful predictors of whether a learner will successfully complete the course or not. Learners were generally high in mastery-goal orientation, a finding potentially generally characteristic of students who choose to take a MOOC for no formal credit.
• Early self-reported confidence in completing the course was a successful indicator of whether a student will complete the course or not, with more confident students being more likely to complete.
• Students self-identified as non-English native speakers exhibited higher confidence in completing the course than native speakers, from the beginning of the course. However, this difference was not linked to a difference in course completion.

In considering these findings, it is worth noting that course completion is only one of many metrics that can be used to study persistence and learning in the context of MOOCs; many students enter MOOCs with the goal of learning a specific subset of course material rather than completing the course. Nonetheless, our results suggest that initial student motivation can play an important role in whether students persist in and complete a MOOC.