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.
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.
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.
Education 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.
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?
These 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.
How can you tell if an innovator is pulling your leg? Their lips are moving. Or their fingers are typing. I write that knowing fully well that it says a lot about my current title of “learning innovation coordinator.” To come clean about that title: we were allowed to choose them to some degree. I chose that one for pure political reasons. I knew that if I wanted to help bring some different ideas to my university (like Domain of One’s Own, Learning Pathways, Wearables, etc), I would need a title beyond something like “instructional technologist” to open doors.
But beyond a few discussions that I have on campus, you will rarely hear my talking about “innovation,” and I reject the title of “innovator” for almost anyone. Really, if you think any technology or idea or group is innovative, put that technology or idea into Google followed by “Audrey Watters” and get ready for the Ed-Tech history lesson the “innovators” tend to forget to tell you about.
In a broad sense, many would say that the concept of “innovation” involves some kind of idea or design or tool or whatever that is new (or at least previously very very “popular”). Within that framework of innovation, disruption is no longer “innovative.” Disruption is really a pretty old idea that gained popularity after the mp3 supposedly “disrupted” the music business and/or the digital camera disrupted the camera industry.
Of course, that is not what happened – mp3s and digital cameras just wrenched some power out of the hands of the gatekeepers of those industries, who then responded by creating the “disruption narrative” (which is what most are referring to when they just say “disruption”). And then proceeded to use that narrative to gain more control over their industry than before (for example, streaming music services). Keep this in mind any time you read someone talking about “disruption” in education. Who is saying it, what do they want it to do, and how much more control do they get over the educational process because of their disruption narrative?
Of course, there is debate over whether disruption is real or not. Both sides have good points. Regardless of if you believe that disruption is real or not, our current disruption narrative has been around for over two decades now… probably long past the expiration date that gets slapped on any “innovative” idea. If you are still talking disruption, you are not an innovator.
If you want to convince me that you are an innovator, I don’t want to know what cool ideas or toys you have. I want to know who you read and follow. Are you familiar with Audrey Watters? Have you read Gayatri Chakravorty Spivak’s Can the Subaltern Speak? Are you familiar with Adeline Koh’s work on Frantz Fanon? Do you follow Maha Bali on Twitter? If I mention Rafranz Davis and #EdtechBlackout, do I get a blank stare back from you?
If you were to chart the people that influence your thinking – and it ends up being primarily white males… I am not sure how much of an innovator you really are. Education often operates as a “one-size-fits-all” box (or at best, a “one-set-of-ideas-fits-all” box), and that box has mostly been designed by white males. Usually a small set of white males that think all people learn best like they do. How can your idea or technology be that “new” if it is influenced by the same people that influenced all of the previous ones?
So what has this “one-set-of-ideas-fits-all” box created for education? Think tanks and university initiatives that sit around “innovating” things like massive curriculum rethinking, “new” pedagogical approaches, and “creative new applications of a range of pedagogical and social technologies.” They try to come up with the solutions for the learners. Many of these are probably some great ideas – but nothing new.
Why not find ways to let the learners set their own curriculum, follow their own pedagogical approaches, or create their own ways of applying technology? Instead of walling ourselves up in instructional design teams, why not talk to the learners themselves and find out what hinders their heutagogical development? Why not look to learners as the instructors, and let them into the design process? Or dump the process and let learners be the designers?
What I am getting at is helping learners create and follow their own learning pathway. Each one will be different, so we need massive epistemological and organizational shifts to empower this diversity. Why not make “diversity” the new “innovative” in education? Diversity could be the future of educational innovation, if it could serve as a way to humanize the learning process. This shift would need people that are already interacting with a diverse range of educators and students to understand how to make that happen.
I would even go as far to say that it is time to enter the “post-innovation” era of Ed-Tech, where any tool or idea is framed based on whether it supports a disruption mindset or a diversity mindset. What does that mean about emerging ideas like big data or wearables? Post-innovation would not be about the tool or the system around it, but the underlying narrative. Does this “thing” support disruption or diversity? Does it keep power with the gatekeepers that already have it, or empower learners to explore what it means for them to be their one unique “human” self in the digital age?
For example, if “big data” is just used to dissect retention rates, and then to find ways to trick students into not dropping out… that is a “disruption” mindset. “We are losing learners/control, so let’s find a way to upend the system to get those learners back!” A diversity mindset looks at how the data can help each individual learner become their own unique, self-determined learner, in their particular sociocultural context: “Based on the this data that you gave us permission to collect, we compared it anonymously to other learners and they were often helped by these suggestions. Do any of these look interesting to you?” Even of the learner looks at these options and rejects all of them, the process of thinking through those options will still help them learn more about their unique learning needs and desires. It will help them celebrate their unique, diverse human self instead of becoming another percentage point in a system designed to trick them into producing better looking numbers for the powers that be.
This is also a foundational guiding aspect of the dual-layer/learning pathways idea we are working on at the LINK Lab. It is hard to come up with a good name for it, as we are not really looking at it as a “model” but something that turns the idea of a “model” or “system” inside out, placing each individual learner in the role of creating their own model/pathway/system/etc. In other words, a rejection of “disruption” in favor of “diversity.” We want to embrace how diversity has been and always will be the true essence of what innovation should have been: each learner defining innovation for themselves.
Personalized learning is popular right now. But is that a good or bad thing? I can buy all kinds of personalized gadgets online, but do I really like or need any of them? If you decided to get me a custom dinner place mat that says “Matt’s Grub” – sure that is personalized. But its also a pretty useless personalized item that I have no interest in.
Many prominent personalized learning programs/tools are a modern educational version of the Choose Your Own Adventure book series from the 1908s. As I have written before, these books provided a promise of a personalized adventure for the reader, which was entertaining for a while. But you were really just choosing from a series of 50 pre-written paths, hoping to pick one of the ones that led to a happy ending. Of course, If you happened to have any physical characteristics that were different than the ones written into the story (I remember a classmate that had shaved his head making fun of one page that had the main character doing something with his hair – yes they were sometimes gendered stories even), then the “your” in “Choose Your Own Adventure” fell flat.
These eventually evolved into more complex books like the Lone Wolf gamebooks that had you doing your own battles, collecting objects, and other activities that were closer to role playing games.
But let’s face it – the true “Choose Your Own Adventure” scenarios in the 1980s were really role playing games. And few were as personalizable as Dungeons and Dragons.
Now, whether you love or hate D&D, or even still think it is Satanic… please hear me out. D&D, at least in the 80s, was personalizable because it was provide different pathways that were scaffolded. New players could start out with the Basic D&D boxset – which came with game rules, pre-designed characters, basic adventures to go on, etc. And that wasn’t even really the starting point. If basic D&D was too unstructured for you, there were books like the Dragonlance Chronicles or the Shannara series that would give you this completely guided tour of what D&D could look like. Oh, and even a Saturday morning cartoon series if the books were too much for you.
But back to D&D, once you mastered the Basic set, there were more sets (Expert, Companion, Master, and Immortal) – all of which gave you more power and control. Then, when you were ready (or if you found Basic D&D too pre-determined), there was Advanced Dungeons and Dragons. This was a set of books that laid out some basic ideas to create your own characters and worlds and adventures. And you were free to change, modify, add to, or completely re-invent those basics. Many people did, and shared their modifications in national magazines like Dragon Magazine. Oh, and what if you want to make your own world but are still unsure? You had a whole range of pre-designed adventures called Dungeon Modules. Just buy one, play, and get inspired to create your own. Or, maybe the opposite is true: you were just tired of your creation and wanted to take a break in someone else’s world.
To me, Dungeons and Dragons in the 1980s was a much better metaphor for what personalized learning should look like. You had completely mindless escapism entertainment (aka lectures) when you needed it, like the books and cartoons. You had the structured environment of Basic D&D to guide you through the basics (aka instructivism). You had a series of games and accessories like Dungeon Modules and Companion Sets to guide you (aka scaffold you) to the advanced stage. You had the Advanced books that set a basic structure for creating your own world (aka the Internet). Then you had a network of people sharing ideas and designs to keep new ideas flowing (aka connectivism). Many gamers would go back and forth between these various parts – creating their own world, sharing their ideas in the magazines, playing dungeon modules on occasion, reading the books, and dipping back to basic D&D when the mood hit them.
This scene from The Big Bang Theory shows how players can customize, adapt, and personalized the game experience, even as they play:
Of course, there were problems with the gaming community. It was expensive, and often sexist and/or racist. So I am not painting the Dungeon and Dragons world of the 1980s as some perfect utopia. I am looking at the design of the tools and system here. It is one that in some fashion pre-ceded and informed what we are doing with pathways learning, and one that I think is closer to true “personalization” than what some personalized learning situations offer.
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.
Customizable Modalities for Individualized Learnin...
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.
Challenges and Opportunities of Dual-Layer MOOCs: ...
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.
From Instructivism to Connectivism: Theoretical ...
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.
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.
Understanding Instructional Designs and Teaching...
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.
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.”
Virtual Reality and Wearables in Online Learning...
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.
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...
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...
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.