Decreasing Design Presence

With the Humanizing Online Learning MOOC in full swing, I wanted to dig more into a topic that I tend to allude to at conference presentations. While educators often talk (rightly so) about increasing teaching, social, and cognitive presence, there is also one form of presence that needs to be decreased when designing and teaching courses: design presence.

I’m using “design presence” here to cover a wide range of user interface, instructional design, and learning theory issues. In my mind, there are at least three areas that are heavy on design presence, and therefore design presence needs to be decreased in these areas:

  1. Technological Design Presence: tool/technology interfaces and instructions
  2. Instructional Design Presence: tool and content instructional design decisions
  3. Epistemological Design Presence: underlying learning theory choices

While some might notice there is some overlap with these areas and teacher, social, and cognitive presence, I have found that there are still some differences. Working to decrease design presence also ends up helping to increase teaching, social, and cognitive presence in the long-run.

Technological Design Presence

This is an area where user interface and instructional design collide, and for many courses designers the options are pre-determined by institutional adoptions. However, where choices are allowed, utilizing tools that have the least complex user interface options is ideal. For example, if you really want to use a listserv, but the tool you have to use is complex to sign-up and use, why not use Twitter? The user interface on Twitter is very simple compared to some older mass email tools. If you have to have a really complex set of instructions to use a tool, why not consider using something with less instructions and stress on the learner?

Or if you have a listserv tool that is easier to use than Twitter, why not use that instead of Twitter?

Where there are several options within a tool (like an LMS), why not choose the least confusing, most ready-to-use tool? Newer features in larger LMS tool sets often have a steep learning curve. For example, the blog feature in Blackboard was very confusing when it was first released, and it really worked more as a re-arranged discussion board. If you have to stay within Blackboard, then stick with the tools that take the least amount of time to explain to learners.

Additionally, think about other issues that cause unnecessary technology confusion. Blackboard was infamous for allowing course designers to set-up boxes within boxes within boxes. Avoid using tools and content structures just because you can. Avoid using desktop tools that make no sense online (like “folders” inside of online content). Avoid using complex navigational structures just because you can.

Once learners have to click around a half dozen times just to get somewhere, or dig through complex tool instructions, or spend too much time figuring out what you want them to do, they are running into too much technological design presence. Decrease what you can where you can.

Instructional Design Presence

This next facet has many connections to the first one, so there will probably be some overlap. Many times, course designers will make tool and content design decisions that are unnecessarily complex. For example, complex grading schemes that require dense explanations and calculators to figure out. Why go there? Obviously, there is merit to the idea that grades are problematic altogether, but many instructors are stuck with them. So why make them so complex? Why not just base course grades on a 100 point scale (which most people understand already), and make each assignment a straight portion of that grade. Complex structures based on weighted grades and 556 point scales and what not are a burden for both the instructor and the learner.

Rubrics are also a part of this area. Complex rubrics with too many categories and specific point values are, again, a burden for learners and instructors. Compare the complexity of this rubric with this one. I realize some people like the first one because it has so much detail, but to be honest, it is something most readers aren’t going to read through, because just glancing at it could cause stress.

Or another issue might be design choices that add unnecessary complexity, like having students upload Word docs to discussion forums for class discussion. Why not just use blogs? That is basically what you are doing with Word Docs and discussion forums.

Course designers typically make many choices with tools and content in their courses. Do these choices increase the instructional design presence of those decisions? Or do they decrease the design presence and allow learners to focus on learning rather than figuring out your designs?

Epistemological Design Presence

This area is a bit more difficult to get at, as it probably affects overarching decisions that affect everything in your course. For instance, if you lean more towards instructivism that places yourself at the center of everything in a course, you will probably choose many tools and interfaces that support your instructivist leanings: lecture capture, content heavy videos, long reading assignments, multiple choice tests, etc.

Now, just to point out, I am not a person to bash instructivist lectures across the board no matter what. There are times when learners need a well executed lecture. However, in education, many instructors use lectures too much. They use lectures to fill time when learners should be doing something hands on and/or active. If you are using lectures on video (or textbook readings) when learners should be creating their own knowledge, or applying concepts hands-on, or collaborating in groups, you have increased the epistemological design presence of your preferred learning theory at the expense of what the learners really needed. Time to decrease that facet of design presence.

There are times when learners don’t need to socially connect or listen to lectures, but work on their own. There are times when they need to connect with others rather than work individually. Don’t stick with instructivism or social constructivism or connectivism or any other theory you love just because you like it best. Put the learner first.

But what about the times where learners are at different levels and need different theories? Or, when no one theory fits and it is really up to the learner? I say, give them the choice. Build in multiple pathways for learning in your course. Build in scaffolding for learners to change into different theories. But avoid the mistakes I have made in the past and make sure to decrease the design presence of those options and pathways as much as possible. Don’t focus on the difference between the pathways – just focus on the fact that learners can make the choices they need at any given moment and then show the choices.

Decreasing Design Presence

edugeek-journal-avatarIf you are a good course designer, you probably already know everything I have touched on here. There is nothing new or different about what I am outlining here – this is solid instructional design methodology taught in most instructional design courses or learned on the job. However, it is seldom examined from the angle of decreasing design presence, and since I am one of the “wayfinders” in a course on the Community of Inquiry framework that covers teaching, social, and cognitive presence, I thought it would be a good idea to have a place to point to every time I mention “decreasing design presence.”

(image credit: Human Presence by Manu Mohan)

Posted: November 28, 2016
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Self-Determined Learning: The Lesser-Explored Side...

Self-Determined Learning: The Lesser-Explored Side of Open Learning

OpenEd 16 is in full swing and I am already kicking myself for not going this year. I seem to miss at least half of the cool conferences. Adam Croom has already provided a fascinating analysis of the abstract topics, which reveals a great list of important topics. However, I do notice something that is (possibly?) missing.

There is a lot about resources, textbooks, pedagogy, etc. Much of this focuses on removing barriers of access to education, which is a topic that we should all support. But what about the design of this education that they are increasing access to?

“Open pedagogy” seems to be the main focus of the design side of the equation. Of course, it is hard to tell from this analysis what people will really present on. When I think of open pedagogy, I think of David Wiley’s important work on the topic. Wiley’s description of open pedagogy is focused on being open about the design and assessment process, as well as allowing learners to remix and create their own open content.

So the question is – where is the learner agency, the self-determined learning, and the heutagogical side of “open learning”? It is probably there, but just not as explicitly named or explored. When you unleash your learners to determine their own pathway, their own context, their own content, and so on – that is also a part of open learning that needs to be specifically mentioned.

Open pedagogy is definitely a scaffold-ed step into self-determined open learning. Maybe some would argue that self-determined learning is implicitly a form of open pedagogy. I wouldn’t disagree, although I tend to avoid using pedagogy as a catch-all term for all forms of learning design due to the co-opting nature of expanding the use of pedagogy beyond “to guide a child.” But that really isn’t a huge deal to me as it is to the early childhood educators that feel left out of most academic educational discussions and usually don’t appreciate the college educators that typically leave them out also stealing the technical term for their design methodology.

Even when looking at the Wikipedia article on open learning, many of the topics touched on get close to self-determined learning, but not quite: self-regulated learning, active learning, life-long learning, etc. Almost there, but not quite.

edugeek-journal-avatarAgain, I know there are people out there that include the topics of learner agency and self-determined learning in the open learning / open education sphere, and that there are some people working in those topics. I just think there should be more. In my opinion, you can offer all the free content you want to and allow people to remix and re-use as much as you want… but if the design still focuses on the instructor (or the pre-determined content) as the center of the course, you have just created an open-licensed “sage on the stage” learning experience. Which I am sure many people will need, but for many others, this falls short of the concepts of learning how to be a learner.

Posted: November 2, 2016
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We are the Monster at the End of the Book

I wanted to circle back to a thought I had while reading Maha Bali’s excellent post Reproducing Marginality? The whole post is excellent, but one line made me think more than others. In it, she quotes something that she wrote with Paul Prinsloo and Kate Bowles that says:

…for most of us not in the US (or the UK), this [edtech] vision has often signalled top-down, US-to-world, Anglo-oriented, decontextualized, culturally irrelevant, infrastructure-insensitive, and timezone-ignorant aspirations, even when the invitation for us to join in may be well-intentioned.

Many of us in the Western world of EdTech are trying to figure out how to fix Education and Ed Tech, looking for the evil monsters out there that are causing the problems, and then fixing those monsters with research, technology, design, or methods.

And sometimes we are afraid to see what those monsters are that are damaging education, because they may be too big for us to fix.

This all reminds me of one of my favorite books as a kid: The Monster at the End of the Book.

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In this book, Grover notices the title of the book and spends every page trying to stop you, the reader, from reaching the end of the book. He nails pages together, builds brick walls, and pleads with you NOT to get to the end of the book and face the monster lurking there.

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Grover is terrified of the monster at the end of the book. But when he gets to the end of the book, he finds that he was the monster all along and that he had nothing to fear.

We (in the western world) are pretty much the monster at the end of the book when it comes to education reform. We are doing everything we can to avoid that possibility – looking to everything but ourselves to fix the problems. But is is our (sometimes) extreme ethno-centrism, socio-cultural centrism, whatever you want to call it, that is the problem all along. I would even go so far to say that as long as we are the center of the education world, we are always going to be the problem.

edugeek-journal-avatarEducation is about learning. Learners do the learning. Learning needs to be the center of what we do. Learners can live anywhere in the world, in any context. We need to examine the structures that keeps the wrong things at the center of education. We need to skip to the end of the book, realize we are the monster at the end of the book, and turn the story around. Learner agency is the only true “innovation” was have left to explore deeply in the education world.

Posted: September 27, 2016
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Big (Scary) Education (Retention) Data (Surveillan...

Big (Scary) Education (Retention) Data (Surveillance)

Big data in education might be the savior of our failing learning system or the cement shoes that drags the system to the bottom of the ocean depending on who you talk to. No matter what your view of big data is, it is here and we need to pay attention to it regardless of our views.

My view? It is a mixture of extreme concern for the glaring problems mixed with hope that we can correct course on those problems and do something useful for the learners with the data.

Yesterday at LINK Lab we had a peak behind the scenes at a data collection tool that UTA is implementing. The people that run the software at UTA are good people with good intentions. I also hope they are aware of the problems already hard coded in the tool (and I suspect they are).

Big Data can definitely look scary for a lot of reasons. What we observed was mostly focused on retention (or “persistence” was the more friendly term the software uses I believe). All of the data collected basically turns students into a collection of numbers on hundreds of continuums, and then averages those numbers out to rank them on how likely they are to drop out. To some, this is scary prospect.

Another scary prospect is that there is the real danger of using that data to see which students to ignore (because they are going to stick around anyways) and which students to focus time and energy on (in order to make the university more money). This would be data as surveillance more than educational tool.

While looking at the factors in this data tool that learners are ranked by led to no surprises – we have known from research for a long time what students that “persist” do and what those that don’t “persist” do (or don’t do). The lists of “at risk” students that these factors produce will probably not be much different from the older “at risk” lists that have been around for decades. The main change will be that we will offload the process of producing those lists to the machines, and wash our hands of any bias that has always existed in producing those lists in the first place.

And I don’t want to skip over the irony of spending millions or dollars on big data to find out that “financial difficulties” are the reason that a large number of learners don’t “persist.”

The biggest concern that I see is the amount of bias being programmed into the algorithms. Even the word “persistence” implies certain sociocultural values that are not the same for all learners. Even in our short time looking around in the data collection program, I saw dozens of examples of positivist white male bias hard coded in the design.

For example, when ranking learners based on grades, one measure ranked learners in relation to the class average. Those that fell too far below the class average were seen as having one risk factor for not “persisting.” This is different than looking at just grades as a whole. If the class average is a low B but a learner has a high B, they would be above the class average and in the “okay” zone for “persistence.”

But that is not how all cultures view grades. My wife is half Indian and half Australian. We have been to India and talked to many people that were under intense stress to get the highest grades possible. It is a huge pressure for many in certain parts of that culture. But even a low A might not register as a troubling signal if the class average is much lower. But to someone that is facing intense pressure to get the best grades or else come home and work in Dad’s business… they need help.

(I am not a fan of grades myself, but this is one area that stuck out to me while poking around in the back end of the data program)

This is an important issue since UTA is designated as a Hispanic Serving Institute. We have to be careful not get into the same traps that education has fallen into for centuries related to inequalities. But as our LINK director Lisa Berry pointed out, this is also why UTA needs to dive into Big Data. If we don’t get in there with our diverse population and start breaking the algorithms to expose where they are biased, who else will?  Hopefully there are others, but the point is that we need to get in there and critically ask the hard questions, or else we run the risk of perpetuating educational inequalities (by offloading them to the machines).

For now, a good place to start is by asking the hard questions about privacy and ownership in our big data plan:

Are the students made aware that this kind of data is being collected?

If not, they need to be made aware. Everywhere that data is collected, there should be a notification.

Beyond that, are they given details on what specific data points are being collected?

If not, they need to know that as well. I would suggest a centralized ADA-compliant web page that explains every data point collected in easy to understand detail (with as many translations to other languages as possible).

Can students opt-out of data collection? What about granular control over the data that they do allow to be collected?

Students should be able to opt out of data collection. Each class or point of collection should have permissions. Beyond that, I would say they should be able to say yes or no to specific data points if they want to. Or even beyond that, what about making data collection opt-in?

Who owns the students’ data (since it is technically their actions that create the data)?

This may seem radical to some, but shouldn’t the student own their own data? If you say “no,” then they should at least have the right to access it and see what is being collected on them specifically.

Think of it this way: How will the very substantial Muslim population at UTA feel about a public school, tied to the government, collecting all of this data on them? How will our students of color feel about UTA collecting data on them while they are voicing support for Black Lives Matter? How would the child of illegal immigrants feel about each class at UTA collecting data about them that could incriminate their parents?

edugeek-journal-avatarThese issues are some of the hard things we have to wrestle with in the world of Big Data in Education. If we point it towards openness, transparency, student ownership, and helping all learners with their unique sociocultural situations, then it has potential. If not, then we run the risk of turning Big Education Data into Scary Retention Surveillance.

Posted: September 22, 2016
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Utilizing Innovative Customizable Pathways / Dual-...

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Utilizing Innovative Customizable Pathways / Dual-Layer MOOC Course Design For True Individualized Learning

About This Presentation:

Presentation at the OLC Innovate Conference in New Orleans, Louisiana on April 20, 2016. From the session abstract:

Recent work on customizable pathways course design points to interesting possibilities for individualized learning. This session will discuss how to create dual-layer courses.

See also the online extended abstract

Presentation Date: April 20, 2016
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The Impact of MOOCs on Traditional Online Courses

About This Presentation:

Presentation with lead presenter Justin T. Dellinger at the Digital Learning Research Network in Stanford, California on October 16, 2015. From the session abstract:

Starting in 2008, the MOOC became an overhyped buzzword that some felt posed a major threat to traditional higher education systems. These courses would replace the professor with fully automated platforms and change the landscape of the university at large. As they have continued to evolve, it has become increasingly evident that MOOCs are a symptom of learner and system needs, and serve to complement fully online, blended, and face-to-face classrooms rather than replace them. In the post-hype period, it is valuable to look at how these courses address the aforementioned needs, if they actually do, and how MOOC design strategies can affect traditional online courses, both in positive and negative ways. This session will include a brief case study of a large fully-online history course at the University of Texas at Arlington attempting to incorporate elements learned from MOOCs, such as multimodal pathways, microlearning, moving out of the learning management system, and use of social media. More importantly, this session will posit larger questions to the group about feasibility, conceptualization, and implementation to spur further discussion.

Presentation Date: October 16, 2015
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Customizable Modalities for Individualized Learnin...

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Customizable Modalities for Individualized Learning: Examining Patterns of Engagement in Dual-Layer MOOCs

About This Presentation:

Presentation with Justin T. Dellinger, Vitomir Kovanovic, and Srecko Joksimovic at the Digital Learning Research Network in Stanford, California on October 16, 2015. From the session abstract:

Dual-layer MOOCs are a recent attempt to transfer control over learning experience to MOOC participants in ways that personalized learning designs often cannot accomplish. A dual-layer MOOC design involves creating two complete and complementary learning pathways for the course, with each pathway focusing on different epistemological modalities. The overarching idea is to allow MOOC participants to navigate the course pathways in a way that best suits their particular learning needs, by utilizing one modality, both modalities, or a custom combination of either modality at different timeframes in the course. Any pathway through the modalities would count as “completing” the course. A dual-layer MOOC might have an instructivist modality focused on traditional content delivery and discussion paired with a connectivist modality focused on networked and social learning. This study will seek to investigate the experiences of participants in the “Data, Analytics, and Learning” MOOC (DALMOOC), a dual-layer MOOC organized in Fall 2014. Using a mixed-methods approach, course participant patterns of engagement will be analyzed to investigate the differences between participation strategies, as well as to identify participants that utilized different pathways through course modalities. After initial quantitative analysis of course participation traces, a subset of participants will be invited to participate in follow-up semi-structured qualitative interviews with the goal of providing more depth to the analysis of their patterns of engagement. Additionally, online discussion postings and social media activity created during DALMOOC will be analyzed to help inform interview questions. Thus, the main goal of this study will be to examine differences in participation strategies across both course modalities as well as to utilize study findings to refine, improve, and focus future research and design of the dual-layer model of MOOCs.

Presentation Date:
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Challenges and Opportunities of Dual-Layer MOOCs: ...

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Challenges and Opportunities of Dual-Layer MOOCs: Reflections from an edX Deployment Study

About This Presentation:

Paper presentation with lead author/presenter Carolyn P Rose along with co-presenters Oliver Ferschke, Gaurav Tomar, DiYi Yang, Iris Howley, Vincent Aleven, George Siemens, Dragan Gasevic, and Ryan Baker at the 11th International Conference on Computer Supported Collaborative Learning (CSCL 2015) in Gothenburg, Sweden on June 9-10, 2015. From the paper abstract:

This interactive event is meant to engage the CSCL community in brainstorming about what affordances in MOOCs would enable application of and research extending theories and best practices from our field. To provide a concrete focus as a foundation for this discussion, we present the innovative design of a recent edX MOOC entitled Data, Analytics, and Learning (DALMOOC). We have integrated several innovative forms of support for discussion based learning, social learning, and self-regulated learning. In particular, we have integrated a layer referred to as ProSolo, which supports social learning and self-directed learning. In further support of self-directed learning, intelligent tutor style exercises have been integrated, which offer immediate feedback and hints to students. We have integrated a social recommendation approach to support effective help seeking in the threaded discussion forums as well as collaborative reflections in the form of synchronous chat exercises facilitated by software agents. The event will include an overview, offering the opportunity for active engagement in the MOOC, structured brainstorming, and interactive, whole group feedback.

See also the online paper

Presentation Date: June 9, 2015
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From Instructivism to Connectivism: Theoretical ...

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From Instructivism to Connectivism: Theoretical Underpinnings of MOOCs

About This Publication:

While the first MOOCs were connectivist in their approach to learning, later versions have expanded to include instructivist structures and structures that blend both theories. From an instructional design standpoint the differences are important. This paper will examine how to analyze the goals of any proposed MOOC to determine what the epistemological focus should be. This will lead to a discussion of types of communication needed—based on analysis of power dynamics—to design accurately within the determined epistemology. The paper also explores later stages of design related to proper communication of the intended power structure or theoretical design as these relate to various activities and expectations in the MOOC.

Published: April 12, 2016
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What’s Cooking in the MOOC Kitchen: Layered MO...

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What’s Cooking in the MOOC Kitchen: Layered MOOCs

About This Publication:

During several panel presentations at the AECT Annual Convention in Indianapolis in November 2015, concerns with MOOCs were raised. In this paper the authors discuss a few of those concerns of extra interest, and explain the relatively new customizable dual-layer MOOC course design. This new paradigm of MOOC design holds promise to alleviate some of the concerns with open global MOOCs.

(co-authored with Dr. Jenny S. Wakefield)

Published: March 17, 2016
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Understanding Instructional Designs and Teaching...

Full Title:

Understanding Instructional Designs and Teaching Strategies of Massive Open Online Courses

About This Publication:

This study examined instructional designs and teaching strategies of Massive Open Online Courses (MOOCs), with a focus on the activities and expectations for students to complete the courses. It is hoped that such an examination will help in the development of a course taxonomy which will help learners set better expectations before they take college-level courses. This effort will also provide guidance for instructional design and technology choices beyond MOOC settings in a global learning environment, since emerging designs such as MOOCs are often designed for learners who would otherwise not having an opportunity to learn. Therefore, this taxonomy could be helpful to learners from different cultures, due to differences in language backgrounds and cultural experiences of learning.

(co-authored with Dr. Lin Lin)

Published: April 17, 2015
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Cyberbullying at a Texas University – A Mi...

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Cyberbullying at a Texas University – A Mixed Methods Approach to Examining Online Aggression

About This Publication:

Co-authored this research paper along with lead author Dr. Katie Crosslin. From the abstract: “Cyberbullying is characterized by utilizing digital technology repeatedly to purposefully send information about another person to inflict harm. The objective of this mixed-methods study was to identify the prevalence for victimization and bullying behaviors, as well as to examine undergraduate students’ perceptions and experiences with cyberbullying.”

Published: July 27, 2014
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Virtual Reality and Wearables in Online Learning...

Full Title:

Virtual Reality and Wearables in Online Learning: Finding the Human at the Center of the Technology

About This Research Study:

Several studies are currently in the planning stages to investigate the overlap between Virtual Reality, wearable devices, and humanizing online instruction. Various grants and journal articles are being explored along this line of research.

Posted: June 17, 2016

Customizable Modality Pathway Learning Design: E...

Full Title:

Customizable Modality Pathway Learning Design: Exploring Personalized Learning Choices Through a Lens of Self-Regulated Learning

About This Research Study:

This study was conducted to complete my dissertation. From the abstract: “Open online courses provide a unique opportunity to examine learner preferences in an environment that removes several pressures associated with traditional learning. This mixed methods study sought to examine the pathways that learners will create for themselves when given the choice between an instructor-directed modality and learner-directed modality. Study participants were first examined based on their levels of self-regulated learning. Follow-up qualitative interviews were conducted to examine the choices that participants made, the impact of the course design on those choices, and what role self-regulation played in the process. The resulting analysis revealed that participants desired an overall learning experience that was tailored to personal learning preferences, but that technical and design limitations can create barriers in the learning experience. The results from this research can help shape future instructional design efforts that wish to increase learner agency and choice in the educational process.”

Further research and grant opportunities are being explored to continue this topic.

Posted: May 15, 2016

Participants’ Experiences Regarding Engagement...

Full Title:

Participants’ Experiences Regarding Engagement and Self-Directed Learning in Open Online Courses

About This Research Study:

Massive Open Online Courses (MOOCs) give researchers a unique window into examining engagement in online courses. Without the typical motivation of grades or the possible threat of failure, learners are left to self-direct their engagement with course content and activities. By investigating the reasons why learners either complete or drop-out of MOOCs, this mixed-methods study sought to gain insight into participants’ experiences of self-directed learning in MOOCs. The research from this study has been presented at several conferences, and a journal article is currently in development.

Posted: April 12, 2015

Understanding Instructional Designs and Teaching...

Full Title:

Understanding Instructional Designs and Teaching Strategies of Massive Open Online Courses

About This Research Study:

This study examined instructional designs and teaching strategies of Massive Open Online Courses (MOOCs), with a focus on the activities and expectations for students to complete the courses. It is hoped that such an examination will help in the development of a course taxonomy which will help learners set better expectations before they take college-level courses. This effort will also provide guidance for instructional design and technology choices beyond MOOC settings in a global learning environment, since emerging designs such as MOOCs are often designed for learners who would otherwise not having an opportunity to learn. Therefore, this taxonomy could be helpful to learners from different cultures, due to differences in language backgrounds and cultural experiences of learning. This study was conducted with Dr. Lin of the University of North Texas and submitted to the American Educational Research Association for consideration.

Posted: July 27, 2014