Designing and delivering education at scale effectively is a challenge faced by many higher education institutions (Kagan & Diamond, 2019). This challenge is both an economic one, where the costs of magnifying and multiplying education offerings needs to be matched and exceeded by the revenue, and a pedagogical one, ensuring the quality of the teaching and learning does not fade with repetition or lose students in a sea of faces. It is also an intrinsically vague and abstract term with little objective codification or agreement in literature or practice. This is the second part of this blog post and will look at how we understand scale in the context of educational development and learning design, and how we can use it to nurture and leverage a true learning community. You can read the first part here.
Scale in context
Debates about scale are not limited to a single discipline or faculty. Scale is not just the physical number of students in a classroom or those logged into a VLE. Like most numbers, using them to describe the impact of scale is relative, subjective, and rarely comparable. It is, after all, just a number. Scale is a complex ecosystem of multipliers and influences that define how it is experienced and the impact it has on the design of teaching and learning. The management of scale has defined the architecture of the buildings we work in, the logistics of IT infrastructure and pressures placed on systems like exams, the library and academic support.
The move to remote teaching during the pandemic ameliorated some of these pressures, expanding the deployment of asynchronous lectures and supporting larger scale small-group tutorials delivered through social media-like platforms online. Teaching at scale, either remotely or on campus, can change the social experience and materiality of learning, re-locating it to learning spaces inside and outside the campus, where self-directed learning and the intersections of life, work, play and learning reside. Some students experience a profound sense of social isolation in this at-scale learning environment (Gibbs et al., 1996). The limitations of space on campus, the commercialisation of learning commons and the fragmentation of the timetable can shatter their exposure to, and connection with, other students. The teaching at scale classroom becomes a site for passive reception of knowledge and fleeting connections in large groups focused on the teacher. The social media networks of students and their extended networks become the place for the creation of personal ecosystems of engagement and relationship building.
It is in this context that developing an understanding of how different types of teaching and learning at scale impact on the holistic learning environment, both influencing and multiplying practice. How do we leverage the opportunities and possibilities that scale affords educators and students, embracing the diffusion of knowledge, connections, spaces and places to build a purposefully designed learning experience?
A model for education at scale
Large versus small cohort/group size
This is the most common differentiator of scale. What defines scale in the context of cohort or group sizes is relative to the discipline area it is taught within (theoretical vs practical is one distinction), the type of institution (teaching or research intensive, for example), the mode of teaching (face-to-face, hybrid or online) and the cost/benefit analysis undertaken by staff and students leveraging scale against intimacy. Scale in this context influences some university ranking metrics, the workload of staff, the balance between teaching and research and the capacity for personalisation and pastoral care. Cohort/group sizes initiates institutional and educational decision-making processes around staffing (increased staffing numbers, casualised versus establishment and staff/student ratios), technology and estate (room sizes, AV requirements, ICT infrastructure) and pedagogical design (the efficacy of active learning, the prevalence of broadcast pedagogy, the use of asynchronous online learning) and the relative satisfaction students have with their experiences, noting that access to staff and personal tutoring time are two critical determinants of satisfaction as measured by online student satisfaction surveys (Grey & Osborne, 2020).
One of the challenges of designing for learning at scale is to unhide much of the unquestioned norms of educating large cohorts/groups. For example, why are there still passionately debated arguments about the efficacy and role of lectures in giant tiered lecture theatres? (did we forget/remember the arguments of the late Graham Gibbs in his 1981 paper ‘20 terrible reasons for lecturing‘? Why do we assume that unless students are in a lecture and listening intently (undistracted by computers and social media) they cannot deeply learn (Holstead, 2015)? Why do we create pejorative positions about scale being the manifestation of the neo-liberal agenda in higher education (Wanner & Wanner, 2019)? Before the pandemic the assumptions of learning through large-scale lectures were rarely challenged at an institutional level. Instead, what it meant to be a learner was constructed through at-scale experiences that become rusted on in timetable systems, campus design and curriculum. In this environment, pedagogical or technological change at scale was often not much more than tinkering around the edges through tools like personal response systems or better AV that made the established experience more effective/interactive/scalable but didn’t challenge the orthodoxy itself. The real challenge of scale is how it can radically transform the design of curriculum and teaching and learning practice and take advantage of the capabilities of students being part of the crowd.
Small to large span of units/programs
A conceit of scale is that the way institutions understand it and make it manifest is predicated (in the main) on the breadth and depth of student cohort/group. But as I note earlier, numbers are just numbers. Understanding scale through the lens of complexity strips the debate of the arbitrary limitations of seats (or user licenses) and exposes the tensions and affordances of a system built on an ever-increasing set of plates in the air. An example of this kind of complexity is the scope of units (core, electives, specialisations, majors) and programs (the proliferation of programs across multiple in-discipline and multidisciplinary areas) running within a faculty. The impacts of scale in this context are created through equally complex ecosystems of multipliers such as decisions around student recruitment and pathways, progression and staffing breadth and depth (and equally as with large cohorts increasing casualisation). Program/unit span can also influence the scope of the institution (where does it place its priorities for activities other than teaching), reputation (what is it considered world-leading at delivering), research diversity (with the linkages between research and scholarship), flexibility (the degree to which economies can be made across programs) and creating opportunities for interdisciplinarity. Complexity in programs/units can also be hidden, within course maps, marketable statements of course aims and the striving for a unique selling point based on mode of delivery or employment outcome. These can blur the cost/benefit analysis of unit/program scale.
Making the most of scale
Scale represents opportunity for educators and students. Over the course of these two posts much has been made of the negative environment in which scale emerged and the challenges to making something of it in higher education. My experience is that scale creates possibilities for learning and teaching that can only be realised within the complex ecosystem of the massive. MOOCs missed that shot by replicating and diluting smaller scale learning for a large, disconnected and often asynchronous audience. If teaching and learning are designed for scale, then scale is not a burden or an impost, it is truly educative and transformative. We can design activities and assessments with the nuances and capacities of scale built into their DNA, and not be scaled up replications of what we have always done. The technology, the crowd and the connections that can be made at scale enact the adage that the whole is better than the sum of its parts, without ignoring the glorious and empowering capabilities of individuals to learn and share. Design matters in the context of pedagogical change because design makes changes and adapts practices in purposeful and critical ways. Design is built on the application of knowing and doing to the solution of difficult challenges. You cannot leverage scale without first designing for it.
A case in point – crowdsourcing
Crowdsourcing is a manifestation of the power of collective intelligence to crack problems, ideate solutions and create new things. Crowdsourcing is not a single practice or pedagogy. Within its communities a crowdsourcing pedagogy can explore innovative teaching and learning practices like making, ideation, creation, critique, sociality, connected practice, entrepreneurship, digital citizenship, media-making, identity, politics, and policy. And that is just the start. The crowd isn’t homogeneous. It can support lurkers, talkers, loudmouths, itinerants, and learners. But the crowd can equally support learning, explicit and tacit and expected and unexpected. A crowdsourcing community (class, cohort etc) is made up of experts, emerging experts, novices and those members seeking to gain expertise through engagement. A well-designed crowdsourcing experience makes people feel welcome within the crowd, building connections through a sense of making a difference and finding others. For examples of how we have used crowdsourcing to design for scale, you can check out Crowdsourcing the UK Constitution run by the London School of Economics and Future Makers here at the University of Sydney.
And therein lies the design challenge at scale. How do we build a community rather than a series of repeated (often to the point of fading) class experiences? This is important because in a community there are possibilities for what I call resonant learning, which is learning that influences and evolves over time past the immediate gateways of assessment and graduate employability, and through and into your work, life, play and learning. It is learning that is not measured by the capacity to repeat but the capability to reuse, remix and remodel learning for new, unknown and yet to be experienced situations.
I have used this quote by John Seely Brown (2001) many times over the years, but it never fails to bring home the power of the crowd (the massive, the at-scale, the increased student load, however you want to describe it) to make learning better:
…it’s through participation in communities that deep learning occurs. People don’t learn to become physicists by memorizing formulas; rather it’s the implicit practices that matter most. Indeed, knowing only the explicit, mouthing the formulas, is exactly what gives an outsider away. Insiders know more. By coming to inhabit the relevant community, they get to know not just the “standard” answers, but the real questions, sensibilities, and aesthetics, and why they matter.
Community is something that people (staff, students, alumni) crave for within a university experience. Being part of a learning community (as opposed to a community of learners) is empowering. But equally when that community can crowd-source knowledge and solve problems, when that community can leverage the power of the massive and through technology can span location, engage in social behaviours, and create and share knowledge then it becomes truly transformative. Community learning experiences build on the social aspects of learning, collaboration, collective assessment and engagement, group work etc. In that context, the behaviours, practices and creative possibilities of social media (however balanced against the negative aspects) changes the scale game entirely. And when they are designed as part of the teaching and learning experience as appropriately used tools and safe spaces to experiment, they create opportunities to make something better through scale and become more connected.
It is this challenge that informs the design and deployment of our Connected Learning at Scale project, which embraces the complexity of scale through deep and reflective transformation of the student experience. It informs the work the Business School has done to better understand the lived student experience before and during the pandemic. It is how we are building an environment for students to collectively develop as leaders for good, at scale. It is how we leverage scale, by design.
2 thoughts on “What do we mean when we talk about scale? Towards a definition of ‘at scale’ in higher education – part 2”
Perhaps an order of magnitude larger (ten times) would be a rough guide to scale. So if you normally teach 20 students, then 200 is at scale. If you teach 200 (as I do), the 2,000 would be at scale. But I do remember telling a visiting academic from India proudly how I had a lot of students. They had 3 million. 😉
Learning online, or face to face can be made to scale, by using technology, pedagogy, and administrative processes. You can send stuff out on the LMS, you can form students into groups (so they are not isolated), and you can hire a lot of tutors.
Some of us stopped worrying about lectures a decade ago. If you want them, fine, but don’t expect more than one quarter to a third of students who happen to live nearby to turn up. More will watch the recordings, but if you want students to learn something, provide something more active. https://blog.tomw.net.au/2008/08/my-last-lecture.html