Designing Activity Based Online Courses for Meaningful Learning
How to Achieve High-Quality Online Courses (Part 3)
Why learning happens through activity, not content consumption
High-quality online courses are defined less by how much content they contain and more by what learners are asked to do.
Yet many online modules still rely heavily on content delivery. Pages of text, long recorded lectures, and extensive reading lists often dominate the learning experience, with activities positioned as optional extras or as preparation for assessment. While content remains important, content alone does not result in learning.
At Learning Design Solutions, we design online courses around a simple but powerful principle: learning happens through activity. If quality is the goal, activity-based design is not an enhancement — it is foundational.
Learning as Activity, Not Content Consumption
Across learning theory and learning science, there is broad agreement that learning does not occur simply because information has been presented. Learning occurs through what learners do with that information.
Vygotsky (1978) conceptualised learning as an active, socially and cognitively mediated process rather than passive absorption. Biggs (1996) later formalised this idea through constructive alignment, arguing that learning outcomes are achieved through the activities students undertake, not through exposure to content alone.
This principle sits at the heart of how we design online courses. Content plays an enabling role, but learning is constructed through action — applying ideas, making judgements, testing understanding, and reflecting on experience.
Laurillard’s Conversational Framework (2012) reinforces this view by describing learning as involving multiple types of activity. Acquisition — reading or watching — is only one of several learning activity types. Practice, inquiry, discussion, collaboration, and reflection are all essential if learners are to develop deep and transferable understanding.
Using this framework helps ensure that online courses offer a purposeful mix of learning activity types, with content acquisition supporting — rather than dominating — the learning experience.
Designing Activities from Learning Outcomes
As discussed in Start With Outcomes: How Clear Intent Drives Quality (Part 1), learning outcomes define the purpose of a course. In high-quality design, they also define the learning activities.
At Learning Design Solutions, activities are designed directly from outcomes. Each activity exists for a clear pedagogic reason: to help learners practise, demonstrate, or develop the capabilities described in the outcomes. This ensures that learner effort is always purposeful and meaningful.
Designing this way helps ensure that:
activities are clearly aligned to learning outcomes and have an explicit pedagogic purpose
discussion tasks are structured to promote thinking, sense-making, and learning rather than participation alone
learning activities add value by preparing learners for assessment and professional practice, rather than duplicating assessment tasks
When learners understand how activities support their learning outcomes, engagement improves and cognitive effort is directed where it matters most.
Activity-Based Design and Cognitive Load
Activity-based learning must also be designed with cognitive load in mind. Well-designed activities support learning by structuring complexity carefully and focusing attention on key concepts.
Cognitive Load Theory highlights the limits of working memory and the importance of managing instructional complexity (Sweller, Ayres and Kalyuga, 2011). In practice, high-quality activities:
focus attention on a manageable number of ideas
provide clear instructions and expectations
build logically on prior learning
direct cognitive effort towards learning rather than navigation or interpretation
This connects directly to the issues discussed in Designing With Cognitive Load in Mind (Part 2). Activities should stretch learners intellectually while remaining within their capacity to engage meaningfully — particularly when learners are balancing study alongside other commitments.
Well-designed activities create productive effort: challenge that supports learning, confidence, and progression.
Scenario-Based and Practice-Based Learning
One of the most effective ways to design meaningful activity is through scenario-based and practice-based tasks.
These activities require learners to apply concepts in context — analysing situations, making decisions, or evaluating possible actions. This mirrors the kinds of thinking required in professional practice and supports deeper learning than recall-based tasks.
Importantly, scenario-based learning does not need to be complex or technology-heavy. Simple, well-framed scenarios can be highly effective when they are clearly aligned to learning outcomes and supported by appropriate guidance.
At Learning Design Solutions, we use scenarios as learning activities in their own right, not solely as assessment formats. They allow learners to rehearse thinking, test understanding, and build confidence before being formally assessed.
Activities as Preparation for Assessment and Practice
In a constructively aligned course, learning activities are not separate from assessment. They are deliberately designed to give students low-stakes opportunities to practise the skills and forms of thinking they will later be assessed on.
Activities support learners in developing confidence, testing their understanding, and gaining insight into how well they are performing against expectations — before marks are attached. This benefits both learning and assessment readiness.
In the courses we design, feedback is embedded into activities in several ways. Some activities provide immediate feedback, such as scenarios or case studies with model answers, exemplars, or guided responses. This allows learners to compare their thinking with expected approaches and refine their understanding in real time.
Other activities invite learners to share and compare their work with peers, often through structured discussion forums. Used in this way, discussion spaces become environments for reflection, comparison, and sense-making rather than simple participation.
Where workload models allow, learners may also receive formative feedback from tutors on draft work or practice tasks. While this depends on staff capacity, it can play an important role in supporting learner confidence and progression.
When planning and designing online courses, we also consider coherence and continuity across weeks. Activities are often scaffolded so that learners begin with simpler tasks and progress towards more complex applications over time. This approach draws on established principles of scaffolding, where support is gradually reduced as learner competence increases (Wood, Bruner and Ross, 1976).
In some courses, this takes the form of cumulative case studies, where learners revisit the same scenario with increasing depth and complexity. In others, particularly practical subjects, learners engage in progressively more challenging practice tasks, such as increasingly complex programming activities.
This structured progression helps learners see how weekly activities contribute to longer-term development, assessment readiness, and professional capability.
Designing with Appropriate Scope and Emphasis
A common misconception in online course design is that academic rigour is demonstrated through volume. In high-quality design, rigour is expressed through clarity, coherence, and purposeful challenge.
Effective courses make deliberate decisions about what to include and how learning time is used. Activities are given sufficient prominence and space to support learning, rather than being compressed between large blocks of content.
This approach supports sustained engagement and allows learners to invest their cognitive effort where it has the greatest impact.
The Role of AI in Supporting Activity-Based Design
AI can support activity-based design by helping learning designers generate, refine, and iterate on activity ideas — when guided by clear pedagogic intent.
At Learning Design Solutions, we use AI to:
suggest activity formats aligned to learning outcomes
draft scenario prompts that can be refined with subject matter experts
test whether activities are appropriately sequenced and scoped
support consistency across modules in large-scale programmes
AI supports efficiency and clarity, while professional judgement remains central to decisions about challenge, relevance, and authenticity.
What Meaningful Learning Feels Like
From the learner’s perspective, high-quality activity-based courses feel purposeful. Activities are clearly connected to outcomes, appropriately challenging, and relevant to real-world contexts.
Learners understand why they are being asked to engage, what they are developing, and how each task fits into the broader learning journey.
That experience is the result of intentional, outcome-led, activity-focused design.
What Comes Next
In the next post in this series, we’ll explore how assessment design builds on activity-based learning — and how assessment can reinforce quality rather than distort it.
High-quality online learning is not defined by how much content is delivered.
It is defined by how effectively learners are supported to think, apply, and learn.
Want to Talk About Quality in Your Courses?
If you are reviewing existing modules or planning new online programmes and want to strengthen quality through activity-based design, we’d be happy to talk.
References
Biggs, J. (1996) ‘Enhancing teaching through constructive alignment’, Higher Education, 32(3), pp. 347–364.
Laurillard, D. (2012) Teaching as a Design Science: Building Pedagogical Patterns for Learning and Technology. London: Routledge.
Sweller, J., Ayres, P. and Kalyuga, S. (2011) Cognitive Load Theory. New York: Springer.
Vygotsky, L.S. (1978) Mind in Society: The Development of Higher Psychological Processes. Cambridge, MA: Harvard University Press.
Wood, D., Bruner, J.S. and Ross, G. (1976) ‘The role of tutoring in problem solving’, Journal of Child Psychology and Psychiatry, 17(2), pp. 89–100.