To me, learning design is the deliberate and precise creation and arrangement of content, instruction, the learning space and student engagement. A design is necessary in order to maximise understanding, and capitalise on the learning’s purpose. To me, it doesn’t matter what sector you find yourself in, paying attention to how sequences of learning are set up, and how the eventual knowledge and skills are strengthened to ensure they become practical in the future seems to embody the absolute essence of education.
With this frame in mind, Tim Klapdor is right to point out that learning design is more than just the teaching of that aforementioned content and instruction. He exhorts that ‘(learning) Design is the act of thinking about the whole, of negotiating and shaping the experience that the learner will have and the space in which it will happen.’ I believe that in effective educational settings, this ‘whole’ is predominantly shared between the teacher/lecturer and the organisation that implements the systems that shape the learning culture.. When there’s a disjoint, or worse, a chasm between the two, student progress is likely to falter. I use the analogy of the biathlete here to highlight the need for a partnership between academic researchers and learning designers.
Higher education and the learning designer
Contrary to this remarkably uninformed post, higher education’s unique context adds significant import to the role of the learning designer, supporting the academic researcher to ultimately support the student. The academic researcher going it alone, not always, but potentially, alienates their students from a consistency in the learning culture, an inconsistency that unnecessarily adds cognitive load to the learner. The academic researcher going it alone, not always, but potentially, creates a culture of isolation that ultimately renders any support redundant, leading to its removal, inevitably and ironically (in relation to the above article) adding to workload. The academic researcher going it alone, not always, but potentially, alienates their students from the benefit of the evolving landscape of educational theory, a landscape of enormous importance that fundamentally aims to improve the efficiency of learning.
It is the evolving research into education that I want to focus on in this post. A learning designer being abreast of this context is well positioned to be able to advise on educational best practice and improve the efficiency of the learning environment. In the age of the time starved academic researcher unable to dedicate sufficient time to this pursuit, the learning designer’s pedagogical expertise is priceless.
Using the research of the giants who have come before me, below I hypothesise on the possible implications and applications to learning design that their work inspires and present a draft of a pedagogically informed approach to contributing to the design of a course in higher education. I present the body of knowledge in a way that I believe is a highly useful strategy in any educational context: the articulation of the learning journey students will undertake, a narrative that forms the schema of learning. Each section is comprised of many more specific elements, but I will leave that for another time.
The brain builds knowledge, constructively, from learning experiences. This knowledge is stored in long term memory as an interconnected web of information, metaphorically understood as schema. When new information is presented, the brain processes it against what’s already there, trying to build on the schema by either assimilating it if the new knowledge is consistent with existing knowledge, accommodating it if the new knowledge challenges what is already known, or ignoring it if it creates cognitive dissonance.
The depth and extent of a learner’s schema in a given topic determines where they sit on a learning continuum: whether it is a shallow/limited or deep/extensive schema characterises them as either a novice or expert learner respectively, and having an awareness of this level of prior knowledge plays a critical role in determining the types of learning activities learners should undertake to maximise the efficiency of constructing new learning: subsequently, and particularly relevant to higher education, it guides how much independence students can be afforded.
It all comes down to the capability of the brain in processing new content, a capability at the mercy of the working memory. Typically, the working memory can process only 4 items at one time, but when one of the items can be linked to existing schema, the entire schema can be used in the processing, and seems to not affect the working memory. This means that that particular working memory space is still available for new processing. However, when new content is introduced that can’t be linked to existing schema, the learner uses the working memory exclusively, and if the task is too complex the learner will usurp all of the available working memory, inevitably leading to cognitive overload, resulting in very little learning from taking place. This highlights the need for designing learning sequences that incrementally build on prior knowledge, and serves as the overarching pedagogy in effective curriculum design. The pedagogy also applies when learners are sufficiently equipped schematically: too much support usurps working memory as the learner tries to ignore the redundant instruction. Understanding the balance is indeed an artform.
PLANNING and CONNECTING
Excellent programs of learning facilitate a wholistic development of academic, practical and affective skills inspired by a larger vision of what we want learners to be and be able to do by their completion. Program Learning Outcomes (PLOs) serve as the definitive measurement of a domain of knowledge and are used by schools to advertise graduates to respective employers. They are characterised by the accumulation of sets of skills over the duration of a course and are therefore not immediately measurable in a single assessment. Piecing together what can ostensibly appear as disparate subjects to create a cohesive program is challenging, but when successfully achieved can serve to motivate a student as they evidence and experience the development of a range of skills that prepare them for employment.
Articulating what skills constitute the domain of knowledge for each PLO becomes the content outcomes for the curriculum, known as Course Learning Outcomes (CLOs). These are broken down further into more specific skills that are assessed in rubrics. The design of these CLOs should be directed by acknowledgement of the learning continuum and incorporate real world contexts and graduate attributes that encourage and/or support the application of knowledge. Helping students to understand how the whole is the sum of its parts is most effectively done in a visual curriculum map, a map that allows a student to see their immediate progress against the bigger picture and effectively, how their schema is going to develop. Such a map would be featured in the LMS for student reference.
Understanding that the transfer of knowledge is not axiomatic is critical in ensuring enough space is made in curriculum design for the training of students in analogical reasoning and experiential learning. Assessment that requires the application of knowledge will only be valid if students have had sufficient practice and training in being able to apply their understandings. Similarly, outcomes that demand the application of skills are only successfully aligned to assessment if students have had opportunity to develop the skills in such a context.
A strong curriculum provides scope and challenge for a range of learners on the continuum, and is differentiated by design that delivers content in a number of modes in order to increase the efficiency of the working memory. It does not however, attempt to cater to the learning styles myth and unnecessarily increase the workload of the tutor. Curriculum is often designed backwards from assessment, and this is fine. It provides further opportunity to ensure the content is aligned with where you want students to be at the end of their learning, and the use of rubrics when designing assessment strengthens this alignment. It also provides students with opportunities to diagnose their strengths and weaknesses more precisely, and this is crucial in facilitating students being able to effectively self-regulate their learning interventions.
Concomitant with content design must be the consideration of how students can deepen their understanding of it through multiple exposures. The subsequent display of content in the LMS provides students with asynchronous opportunity to consolidate and explore knowledge, and the design of this additional exposure is an artform in itself, guided by cognitive load theory and the acknowledgement of the learning continuum.
Even before the first word is spoken in a lecture, establishing a ‘teacher presence’ that students can consistently rely on via the LMS is imperative. Communicating to students about expectations for success, academic integrity as well as your own passion for the subject helps to set an immediate tone for the course. Visible learning outcomes and a curriculum map that demonstrates the road to achieving them sets students up to be able to negotiate their way through the course metacognitively. Active teaching of how to study and the processes of learning further empowers students to become independent learners, and also increases their capability in providing valid and usable feedback in their SELTS.
Once teaching begins, mitigating against cognitive overload is crucial to maintain consistent student engagement. Awareness of the necessity of retrieval in developing schema that can be called on to free the working memory and help process new learning ensures that lectures are designed with specific opportunities for students to recall knowledge and consciously connect previous learning to the new. Quizzing, lots of verbal questioning, and other formative assessment including discussions are typical strategies. Clarity in explanations abiding by multi-media principles and modelling of problem solving helps to incrementally build student schema and prevents the ‘curse of knowledge’ from infiltrating delivery. Chunking the delivery of content by interleaving testing/retrieval and using multi-modal learning segments (discussions, formative assessment, group work) increases attention and prevents mind wandering, both of which inevitably improve the opportunity to process new learning. Providing mastery paths as corrective feedback also consolidates understanding.
Formative assessment via discussions and group learning should serve to strengthen understanding, but teacher presence and timely feedback is critical to ensure students remain on track in the novice stage. Peer assessment, inquiry and co-creation of curriculum are also incumbent to the learning continuum and require explicit training to validate them being used as learning pedagogies. The processes for getting the best out of summative assessment should also be explicitly practised.
Designing learning spaces in such a way promotes accessibility. Exceeding minimum requirements for an LMS should be the default practice in ensuring the student user experience is optimised to improve learning outcomes. Reflecting on the design of learning sequences by engaging in SELTS and communities of practice can help to inform future practice.
What it all means
It is certain that I have missed things that you may feel are important for this journey, and I would love for you to comment and let me know your thoughts. What I have really wanted to do however is to present a range of knowledge that I believe equips the learning designer with a great deal of confidence to be able to support the design of a high quality educational experience.
I’m Paul Moss. I’m a learning designer at The University of Adelaide. I’m on Twitter too