Desire lines in online education: learning design

This is the second of two posts that look at the metaphor of ‘desire lines’ as applied to programme design and learning design. In the first post Desire Lines in Programme Design, the unnecessary barriers of formal programme architectures were reconsidered through ideas of flexible programmes, unbundling and microcredentials. In this post, the metaphor is applied at course (or module) activity design level.

Desire lines (recap)

Desire lines is a concept in landscape architecture to describe preferred routes that people may take between two points, which may be different from longer routes created by planners (Wikipedia, 2022). Desire lines exist where people can see where they want to reach, but the designer-planned route appears longer or there are obstacles in the way. This leads to desire paths, which are unplanned routes worn by multiple people treading the same desire line. Eventually, these desire paths may be paved as a reaction to people’s desires, or conversely desire paths may be fenced off to force a planned, paved path.

Learning shortcuts 

Desire lines in a physical space often represent shortcuts. In learning design an element of forced route through a sequence of learning can be of benefit to learners and so shortcuts may result in learners not being able to meet outcomes. Examples might include skipping to answers at the back of a textbook, not following up on incorrect responses to quizzes, or missing out the end of week reflection activity. These actions may enable completion, but they do not enable a learner to take a progressed learning path or evidence their learning outcomes, for example when applying their learning to a new situation. These examples of shortcuts are demonstrating desire lines where the student knows the end goal, from their point of view, but isn’t taking the journey planned for them by the educator. The paved path isn’t taken; obstacles may be avoided; time is saved (in the short term). 

Yet challenge or ‘effort’ is, through many interpretations of how we learn, a required element for learning (Brown et al., 2014). We don’t learn by getting everything right or by not taking on new challenges. Learning is about making new connections, drawing upon what we know and linking that to new problems and ideas to build an understanding and new ideas. In the cognitive sense, learning should be effortful as the conscious activity of acquiring, making connections to prior learning, applying knowledge, reflecting and consolidating understanding. Therefore desire lines which lead to ‘skipping the hard bits’ that would otherwise require cognitive effort may enable travel in the same direction as learners who take the planned path, but the post-journey satisfaction and learning may be considerably lacking. For desire lines to be a useful metaphor to support learning design, we should explore the reasons for desire lines.

Desire lines in online learning

As a counter perspective to desire lines as shortcuts, desire lines can be interpreted as individually selected paths through a designed learning experience. In the open online course domain, with all course content usually available from the start, learners could skip activities to meet their own learning needs. These desire paths are closely aligned to individual outcomes, where learners are able to identify their goals and select materials and activities to reach them. Indeed, in earlier examples of digital education adopting loosely linked collections of assets, learning design layers were added to form self-navigable content to provide recommended routes and to highlight dependencies for progression of learning, whilst still enabling all content to be immediately available and full flexibility of the learner to select the activities appropriate to their goals (Morrey, et al., 2005). There is a parallel with the instant access of all materials in MOOCs and other open formats. For success though, the ability of learners to identify their goals and ability to select activities that meet them must not be overestimated and requires purposeful designing-in. 

Techniques to support learners include pre- and post-course skills and competences audits, to identify needs and reflect on progress. In my own work designing online professional development, I have championed approaches for learners to select content and activities that provide the greatest impact for them, instead of being driven by, for example, certification or completion metrics (Cornock, 2019). However, this flexibility also results in missed opportunities to discover learning on a slower path or a path that is ‘undesirable’ from the start, but which may present new perspectives and new ideas if travelled. This is the tension between planned curricula and flexible, personalised learning experiences that reflect changing needs and diverse objectives.

There are two approaches that recognise the opportunities and mitigate the risks of desire lines in learning. They relate to learners and the learning space.

Co-design and understanding learners

As introduced in the previous post on this topic, Bramley (2018) described the apocryphal tale of Michigan State University’s campus landscaping, where paths were only being paved once students and staff had, by repeated use, created desire paths across the campus lawns and verges. There are parallels between this and co-design or student partnership approaches to learning design, albeit the campus example seems a little more organic than structured co-design methods.

In the creation of curricula and courses, an understanding of who the learner is, what they will bring to the course and what they should take away forms a basic level of accommodation for individual learning goals. Work on learner experience design champions learner personas to reflect the range of attributes that influence the learning experience (Floor, 2021) and models of co-design go further to include students in the curriculum planning and learning design process (Harrington, et al., 2021). Through such planned interventions, a broader range of perspectives can be used to inform course outcomes and meaningful activities. This is not to say that students determine everything in the course, as the role of the educator is still to design a progressive programme of study. However, the connection and understanding of where learners may be at and where they may want to head to after study enables a richer curriculum to be developed. 

Desire lines of learners could be explored through the course design process, allowing flexibility though the design phase, whilst also providing a clear steer during teaching. For example, mapping content and activities and gaining student input at the storyboarding stage of an online course would highlight relevancy of activities to students’ goals and provide opportunities to identify where alternative goals may be met through the same content and activities. Even during teaching there are opportunities to flex the path, for example the content of asynchronous discussions, activities that ask students to apply theory to their own context and layering material to allow students to choose where they go deeper into a particular concept. Paths may diverge, converge or run parallel. It is also possible to ensure that learning outcomes are both specific and broad enough to enable evidence against subject benchmarks, but also tailored learning experiences that motivate and have immediate, practical relevance.

These approaches, combined with a developing understanding of the place of a course in learners’ learning journeys, rather than considering courses in isolation from learners’ contexts, brings greater relevance to study. As an example, in several definitions of microcredentials, one of the significant values of this form of sub-degree qualification is the industry relevance, explicitly involving and partnering with industry to strengthen the learning experience and value of such a form of study (QAA, 2022; Oliver, 2019). The inherent variability of student motivations and interests, including relevance of study to specific careers or broader transferability (Gibbs, 2014), can therefore be addressed through the educator having an awareness of desire paths and seizing the opportunity to design for them, rather than against them.

Finding the balance in online spaces

There is a relationship between the technology platform and flexibility of learning experience. Referring back to the analogy of the physical space, the online learning environment is also constructed with paths, open spaces and barriers in many forms. The navigation links and cues within an online course are the paved paths, but depending on the quality of such navigation they can be manifested as a web of paved paths with little direction (for example, poor instructional direction and endless links) or paths with high walls on either side that prohibit any form of deviation. Wheeler (2019), with reference to desire lines, drew parallels between flexible learning and how professional learners may navigate their own personal learning environment comprising of managed learning spaces, personal and professional online networks, and their own tools and approaches. Learners’ desire lines enable them to navigate across learning spaces that are not laid out for them. Learning design could both hinder and enable this level of flexibility. 

In online training, the highly restricted path is often manifested through content packages that force learners through a predetermined sequence of materials. In some situations this also includes forced delays before a learner can progress to the next step (implemented to ‘ensure’ engagement with the content). This type of experience with compliance training is common and the learning premise is dependent on memory, rather than experience, to achieve measurable outcomes. These packages are rarely designed to respond to learners’ prior knowledge, context or intended learning outcomes. The learner has no choice but to remain on the fixed path.

At the other extreme, in courses that have little instructional design, learners are presented with content and (sometimes) activities, but without the direction of why these are relevant, how to connect activities together, or where the end goal may be. That approach is analogous to the campus without paths. The success of learning is based on learners having a clear sense of self-direction.

Creating learning paths

Instructional design of content and activities provides the signposts to guide learners. Learning design is the street map, highlighted with trunk routes and side streets, but with routes clearly defined to follow. In this way paths are defined, but the map of options is visible, and that map may span multiple learning spaces. A complementary example is curriculum maps that guide students through the relationships between topics, content and activities towards defined learning outcomes (Ellaway, 2007). These maps reflect connections, and in some cases fixed progression paths, and from these there is scope to embed flexibility by allowing choice on which connections and paths to explore in more depth.

However, in order to navigate the options, in order to establish new desire lines or follow established ones, there is still a requirement to have structure in the course pedagogy. An individual learner will need appropriate skills in self-directed learning and a course design that scaffolds the basic principles of assessed learning with feedback and reflection. Boshuizen and van de Wiel (2014) describe ‘deliberate practice’ through cycles of goal setting, assessed performance, and refined goals based on feedback and reflection. With those designed-in stages of learning, a student has the opportunity to review how their current path enables them to develop, or not, towards the course outcomes and their personal goals. The learning design therefore is not simply about the content and activities, but how learners are enabled through the design to develop and awareness of how they are learning.

Conclusion

It may be argued that desire lines for programme design and learning design are more suitable for professional learning. The supporting literature for these two posts does come from predominantly professional (in-work) learning and higher education courses aligned to professional sectors. Yet, there are opportunities to consider how desire lines may influence and inform curriculum choices, learning activity selection and the development of students’ capabilities to select and navigate their own learning. This is especially true in designing activities and assessment that develop students’ abilities to reflect on feedback, refine their goals and adjust their practice. These skills are crucial for lifelong learning, the adaptability of graduates to apply their degrees to a range of professions and approaches that deepen their learning further through independent and self-directed study during and after their programme of study.

From an educator’s perspective, being aware of the potential risks of learners following desire lines provides opportunities to manage those risks and turn them into learning opportunities. Co-design, a fuller awareness of learners’ backgrounds and what they may bring to study, and considering learners’ input at the curriculum and activity design stage enable surfacing of potential desire lines and planning for them. The creativity that can bring, by considering a range of perspectives and accepting that as educators we don’t know all the answers, is surely one of the joys of education. The paths that students wish to follow will offer ideas and connections between the planned curriculum and unintended outcomes to challenge educators’ thinking and provide new applications for knowledge. 

Whilst desire lines as a learning design metaphor is perhaps too fluid and flexible for practical comparison, particularly to structured design principles such as constructive alignment, as a metaphor for lifelong learning and understanding learner-centred design, it holds a range of opportunities to explore. In considering desire lines, the curriculum and learning experience through activity has the potential to increase engagement and learner motivation, as educators are deliberately seeking out opportunities to allow deviation from a set path. In doing so, they plan for desire paths, paving them where they could be more established and of broader benefit, but retain overall purpose to a programme of study by ensuring that there is still a set direction to follow. Desire paths reflect the route, and in some cases the end point of that route, but ultimately whether paved or not, desire lines are leading us to somewhere we may wish to go. 

References

1. Boshuizen, H. P. A. and van de Wiel, M. W. J. (2014). Expertise development through schooling and work, in Littlejohn, A. and Margaryan, A. (eds.) (2014). Technology-enhanced professional learning: processes, practices and tools. Abingdon: Routledge.
2. Bramley, E. V. (2018). Desire paths: the illicit trails that defy urban planners, The Guardian, 5 October 2018.
3. Brown, P.C., Rodiger, H.L, McDaniel, M.A. (2014) Make it stick: the science of successful learning. Cambridge, MA: Belknap Press
4. Cornock, M. (2019). Enabling professional development by letting go of the pedagogical paradigms. ALT-C conference, 3-5 September, Edinburgh.
5. Ellaway, R. (2007). Discipline based designs for learning: the example of professional and vocational education, in Beetham, H. and Sharpe, R. (eds), Rethinking Pedagogy For A Digital Age: Principles and practices of design, 1st Edition. London: Routledge.
6. Floor, N. (2021). Learning Experience Design vs User Experience Design, LXD.org. 
7. Gibbs, G. (2014). Students are trying to get different things out of being at university, 53 Powerful Ideas All Teachers Should Know About, Idea Number 51, February 2014, SEDA Staff and Educational Development Association.
8. Harrington, K., Sinfield, S. and Burns, T. (2021). Student engagement, in Pokorny, H. and Warren, D. Enhancing Teaching Practice in Higher Education, 2nd Edition. London: Sage.
9. Morray, M., Duncan, C. and Douglas, P. () Applying learning design to self-directed learning, in Koper, R. and Tattersall, C. (eds.) Learning Design: A Handbook on Modelling and Delivering Networked Education and Training. 
10. Oliver, B. (2019). Making micro-credentials work for learners, employers and providers. Deakin University.
11. QAA (2022). Microcredentials Characteristic Statement. Quality Assurance Agency.
12. Wheeler, S. (2019) Digital Learning in Organisations. London: Kogan Page.
13. Wikipedia (2022). Desire paths. Wikipedia article retrieved 25 September 2022.