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Open Education and Open Pedagogy

Open Education is a set of ideals and practices describing educational systems based on unrestricted sharing and collaboration between students and teachers and facilitated by the internet and Creative Commons licensing. On the internet, the cost of distribution of materials is as close to zero as it will ever be, and the sharing and generation of knowledge made possible by this fact opens the doors for new pedagogical practices that may have wide-reaching implications. As more information becomes more freely available on more diverse topics, the job of universities will no longer be to function as safes from which one can exclusively withdraw knowledge; they must be centres to guide students through knowledge, connect them to other knowers, and assist in application of knowledge. Open Education, through its emphasis on knowledge generation and connectivity, embraces this shift in purpose.

Open Education has two components: Open Educational Pedagogy, and Open Educational Resources. Open Educational Pedagogy (OEP) is the theory and practice of Open Education. One aim of OEP is to centre students as knowledge creators by deemphasizing disposable assignments in favour of renewable assignments. Disposable assignments are the current educational norm. They are created by students and handed to a teacher, who gives the assignment a grade and some comments. The student then gets the assignment back, possibly reads those comments, and either throws it away or buries it in a folder somewhere, subsequently moving on and often forgetting about the whole thing. This structure of assignment has the potential to create insightful work, and, if well-designed, perhaps impart long-lasting learning on a student, but it also lends itself to a feeling of pointlessness, creating detailed, high effort content just so it can be judged and discarded. A renewable assignment is any work that is intended to contribute to a larger accessible body of knowledge after the assessment is complete. In this article, David Wiley explains the concept further, offers some examples of renewable assignments, and outlines the shift in educational philosophy that they inhabit. This is just one way that OEP leads education to openness, alongside encouraging educators to make their materials freely available to reuse, recreate, and redistribute. Below is an article by Miranda Dean outlining her first experiences with an open pedagogy class and how it challenged her preconceived notions of learning and led to a stronger sense of understanding and purpose in her educational experience.

What an Open Pedagogy Class Taught Me About Myself

The Roles of OERs and Open Licensing

It’s hard to teach without a textbook; an Open Pedagogical practice requires Open Pedagogical materials. This is where Open Educational Resources (OERs) come in. OERs are materials like videos, textbooks, podcasts, or interactive games that are publically available not only to access but to redistribute in altered forms for the purpose of catering to particular students, languages or educational settings. Resources that have limited availability and limited ability to be edited and redistributed add inflexibility to the educational process which can be damaging to the accessibility of courses built on top of them, mandating that, in order to achieve the potential of Open Education, OERs be as unrestricted in engagement as possible. This free resource sharing is facilitated by Creative Commons Licences, which can be used to offer up a work as a part of a shared creative commons in our culture, granting it varying levels of restriction ranging from essentially none at all to more restrictive demands against redistributing the work in an edited form or for commercial gain. One example of OERs are the output of the renewable assignments previously discussed. Below is a video by Dr. Jessica Kruger recounting how she assigned a class to collectively write a textbook on the course material and how it engaged students and created work that future students would be able to access and benefit from. Without OERs to take advantage of the low redistribution cost allowed by the advent of the internet age, Open Education would have no place in our culture. The more unrestricted the access to knowledge, the more open our education can be.

Challenges and Solutions

Renewable assignments have a number of issues that tie into larger problems with Open Education. Many relate to whether or not renewable assignments will ever actually become renewed assignments. Looking for information in a repository of student work will likely not be desirable to those with access to more authoritative databases, seeing that trust in student work is generally low. This has rooting in a banker model of education where teachers know everything and students know nothing, but is not wholly illegitimate. In any setting where the barrier to entry is relatively low, information that is spread must be highly scrutinised. It cannot be trusted with certainty that a citation in the work of a first year music education undergraduate student taking a science elective says what the student says that it says, whether out of a lack of competence, time, or effort, and not all instructors interrogate every claim in the hundreds of assignments they mark. Even instructor-produced work released as OER does not necessarily meet a guaranteed standard of scrutiny that you could expect from an academic journal. That being said, you don’t need to look that far to find nonsense claims in said academic journals which later need to get retracted, like the Lancet article that suggested a connection between MMR vaccines and autism and the paper published by Frontiers with conspicuous and absurd AI images of rat testicles. If anything, the potential unreliability of student-produced work should bring into focus the fact that we should always be critically interrogating claims made in work published anywhere, no matter how authoritatively they are made.

In addition to trust issues there would be issues with discoverability. Wholesale adaptation of open pedagogy would create an enormous amount of student produced work which anyone looking for information on a topic would need to sift through. The society we currently live in, and are showing no sign of moving away from, is one where digital sharing is overwhelmingly algorithmically driven. Because of this, the student produced work intended to be renewable would need to be sorted through in some way by a system that brings those deemed worthwhile to the top of the pile. Any way of doing this would inherit many of the problems causing misinformation and driving the potentially harmful form of content on social media today. Highest view count at the top incentivizes academic clickbait, where an outrageous title not representative of the article would succeed, highest engagement at the top would incentivize the production of the most controversial research possible, a poor setting for rigorous work, best rated or most cited at the top would enforce popular views and punish dissent. The algorithm that determines the visibility of work and the people who create and maintain that algorithm would be given enourmous power over the flow of knowledge in an Open Educational setting, and we could never be certain that that power would be used effectively or responsibly. The video below outlines many of the values and challenges of Open Pedagogy, but also offers a discussion of the harm in bringing the function of the public internet into education.

 Perhaps the biggest challenge to Open Education is how it challenges our deeply held notions of ownership. Much has been discussed recently on the subject of the Myth of Barter, elaborated on in the video below. It was the previous assumption of economists that before money was invented, people traded by bartering. If you, the hunter, needed a shirt from the tailor, you would give him some of your meat in exchange for some of his clothes. Though intuitive, this, when further explored, leads to loads of inefficiencies and assumes a high level of immediate transactionality in pre-money relationships that has never been seen in emerging or pre-contact civilizations today. What is in fact seen is more like an “I’ll get the next one” economy. The hunter gives the tailor some meat when he’s hungry because the tailor is his neighbour and quite likely his friend, and he knows that when he is in need the tailor will help him in return. A Hedonist might point out that these situations are fundamentally the same, in each case one giving so that they may benefit themselves. A key difference, however, is that in a barter economy one gives just enough so that they can take just enough in a mutually beneficial but fundamentally adversarial relationship in which each participant is looking for the best deal. In the latter case, one gives because giving freely elevates everyone and strengthens and represents the strength of the community. For all of its potential flaws, the knowledge sharing at the centre of Open Education turns digital pedagogy into an “I’ll get the next one” economy. It returns educational practice to the principles of untied cooperation that are the core of communal living as humans, disrupting the current locked-down internet and working towards truly democratising knowledge. By giving up possessive tendencies we have been trained into through a larger system of strict ownership, Open Education encourages us to be a community first, giving everyone a reason to contribute and moving society forward without the arbitrary scarcity of limited access in the digital age.

Privacy in Digital Learning

As a learner, your privacy can never be perfectly protected. If your learning experience is in any way interactive you must confront the mortifying ordeal of being known whether you like it or not. In order to give you a credential an institution must know to whom they are giving it, which means you can’t be fully anonymous. Beyond these bare minimums, one starts to make some trades. Your university does not need to know your race to educate you, but they do need some details of it if you apply for scholarships benefiting students of colour, and that information will become data that is stored and potentially utilised. Also, demographic surveys given by institutions that have detailed questions can be used to identify students. If an anonymous form says a student is in the music department and identifies as genderqueer anyone who can see the form can already narrow them down to about five. “Choose not to answer” is often an option on these surveys, but as a member of a minority group, picking that option means decreasing your representation in the system, so there is pressure to “show yourself”. There are methods of data collection and storage that can do better or worse to obscure that data, but on a fundamental level it requires students to trust that no abuse of authority will occur, that the current policies around privacy are written and enforced well enough to protect them and will not be changed later in a way that retroactively impacts them. Privacy is the line we draw around what shapes our identity. Our identity is, unsurprisingly, quite personal to us. Crossing that line, therefore, is dehumanising and fundamentally disrespectful of our dignity, which is why an invasion of privacy is wrong, regardless of any material help or harm, and why a principle of minimum required disclosure of personal information should be upheld.

Privacy, ethics, and Educational Needs

Effective education often requires teachers to know things about their students. All student information can be used by a teacher to personalise and optimise learning if they are sufficiently clever, creative, and empathetic. If you know a young student is from a vegetarian family, you know a word problem about the math of buying hamburgers and hot dogs might not be engaging for them. If you know a student is in a house with few books you may offer additional reading support. If you can constantly track a student through a digital learning platform and know how much time a student is spending doing work at a computer in different places, you could see, for example, that they achieve strong results at home, strong results at their friends house, and poor results in the classroom. If you know the student personally you might infer that they are getting other people to do the work for them or that the classroom simply isn’t a conducive learning environment for them and adjust accordingly. Theoretically, every piece of information can be valuable in some way to cater to a student’s individual needs. Privacy, however, is still important. Even if a teacher might benefit from knowing everything about their students, that does not mean that they should or that it is right to probe. Glenn Greenwald’s 2014 TED talk explores the importance of privacy in wider society, in particular dismantling the argument that those with nothing to hide have nothing to worry about. As part of his talk, he highlights how people who feel watched exhibit more conformist, less combative behaviours. Knowing this effect, do we want our students learning under constant supervision? In addition to the previously stated reasons to protect student privacy, without care, an educational system that does not respect it can become a system that forces conformance.

A teacher knowing too much about their students is, in the grand scheme of things, a small issue. Beyond their duty to report, teachers will usually be the only ones to know information that is shared with them. If they start spreading it everywhere they are quite likely to get fired, and, until we get the brain chips going, no one can hack a human teacher, so the data relationship remains largely personal. Giving this data to algorithms that underpin digitally assisted learning platforms offers a new set of challenges. The first is the issue of explicable conclusions. A teacher can make inferences from information, respond to it, and then explain to us exactly how they came to their inferences and what motivates their response. A machine-learning algorithm, however, often operates as a black box, and it cannot offer an explicit report on what information it is specifically responding to or why it does what it does. The design of these models, often by private companies, is many steps removed from the democratic process, leading us to question to whom we are giving such power over the development of our children. The black box of processing makes evaluating the effectiveness of algorithm-assisted learning on an individual level much more difficult. Even if they increase a desirable metric on average, that does not mean they are able to support every student; a 4% increase in average test scores can easily be counted as a success regardless of statistical outliers whose scores dropped by 10%.

As stated, student data accessed by an AI tutor is not contained to an individual. In order to be used it must be processed and stored at a server, and access to that server is politicised. Who gets to see it? School administrators? State or provincial officials? The upper management at the private company running them? What do they get to do with this information? Even if an arrangement that is respectful and effective can be found, if they try to change the rules later, will we have the pressure to stand up to them? Below is a video covering a data breach that leaked large amounts of student information in the Minnesota Department of Education, showing how fragile our privacy really is when so much of our data is stored outside of our hands. It is a general truth of the human condition, in my opinion, that, in all fields, people will take what you give them and use it. Give a tinkerer a gear, they’ll make it spin. Give a parent an iPad, they’ll calm their children down. Give a police officer a gun, they’ll point it at someone. If you give someone information, and incentive sets align with abuse of that information, infringement of privacy will occur. Because of this and regardless of any improvement of efficiency, data surveillance in online tutoring must be checked. This may be seen as stalling progress, but if ethical practice maximised progress and efficiency, we wouldn’t need to talk about ethics.

Universal Design for Learning in Digital Pedagogy

Digital Universal Design for Learning (UDL) is, on a certain level, impossible. Access to technology and digital literacy are themselves not universal, and the barrier set by this membrane of interaction can be alleviated but never fully bypassed, continuing to make digital learning less accessible, serving as another of the many reasons public libraries, which can provide computer access, are necessary to bridge inequality. In other ways, digital learning is particularly well-suited to UDL. UDL is a set of guidelines for developing curriculum and learning activities that cater to the wide variability of learners in a classroom, focused on integrating accessibility accommodations into mainstream learning design rather than separating them into alternate paths. This tunes into an essential and often overlooked aspect of accessibility accommodation: improvements to the lives of the differently abled usually make things better for everyone. Flexibility of deadlines designed for people with chronic illnesses also helps able-bodied people who are in tough times, closed captions for the hearing impaired also help hearing people follow along more easily, and everyone has an easier time moving through a hallway that’s wide and clear enough for wheelchair users. Accessibility is ease of interaction, and whenever it is successful, everyone benefits. The video below gives more specific details of what UDL is and expands on the ways that everyone benefits from universal design.

As a framework based heavily on multimodality of representation and interaction, UDL lends itself well to a digital classroom that can be constructed freely from many physical constraints. Online learning can be delivered as audio, video, text, drawing, or interactive game delivered live, asynchronous, or some combination thereof. The key is that, though online learning can be constructed in many ways, it must be constructed.

Making a video is not easy. Scripting, vocal presentation, filming, recording, graphic design, and editing are all complicated processes that require a certain level of expertise, sometimes in the use of professional tools that are not easily picked up in an afternoon. Corners can be cut, but digital learners are likely also digital livers who are accustomed to high production value content, and a video being unprofessional in its execution can be distracting or harm your credibility. Video and many other digital media have largely moved out of the domain of hobbyists and into the domain of specialists, and because of this, a lot of digital learning is based on finding learning materials that are already available publically. Being able to find publicly available materials that meet the specific needs of your students is predicated on such materials existing, which makes multimodal representation of niche or specific topics considerably more demanding, especially compared to the simple efficiency of a textbook chapter.

All this being considered, a poorly made video that is not perfectly tailored to your lesson still offers learning benefits that would not exist without it; imperfect is not worthless. UDL is not one answer for everyone; learners are not static so neither can be learning; adaptation is at the centre of the framework. In that sense, digital UDL is hardly a new application of the form, but simply a continuation of that adaptation into a new set of media. For all the challenges it provides, we continue learning, we continue building skills, and we get closer to making learning truly universal.

I am Xavier Marican, earning a Bachelor’s of Music in Performance as a classical saxophonist, soon to enter my fourth year of study. All modern classical musicians are educators, out of convenience, as teaching lessons or masterclasses in your instrument is a sizable slice of income and important way of earning status among your peers, and also quite frequently out of an artistic compulsion, as teaching music is often as good or better a way of artistically exploring music as is playing it. The most impactful educational experiences of which I have taken part are mostly very personal: one-on-one if not in small groups in the form of teaching and recieving individual lessons and coaching of small ensembles. These settings lend themselves particularly strongly to student-centred learning, allowing groups or individuals to excel unfettered or falter in their pace without pressure or embarrassment. They give students power to focus on areas of a subject that are most important to them while still being guided by an instructive voice that knows what needs to be prioritized, whether it be glamorous or amusing or not. These values are at the centre of music education outside of large ensembles and are a large part of what makes learning an instrument compelling; building yourself up into whatever musician you want to be alongside an instructor who holds you to account in building with strong foundations.

My interest in open and distributed learning is largely sourced from unfamiliarity and discomfort. A noted weakness of mine as a young person in the digital age is that I have little love for online learning. The human aspect of having a teacher, who in offering knowledge gives to you personally their time and effort and whose face you can look back at in that moment serves as the oil in the spokes of my learning. To treasure this is not in and of itself a weakness, if anything it is a strength as both learner and educator, but in a time where “you can learn anything online” is repeated to the point of aphorism, a reliance on personal instruction can cut one off from a lot of learning. I hope that to gain a better understanding of the workings of open-access digital learning will aid me in effectively engaging with it, and that understanding what elements make for effective open-access learning will give me some help in identifying the sources of learning with which it is worth engaging.