Lately, I’ve been thinking about sequencing instruction. Various theorists promote sequencing in terms of:
- Moving content from simple to complex
- Moving content forward based on prerequisites
- Meeting goals of learners by advancing goals as content advances
- Linear content presentation (behavioural)
- Adaptive sequencing based on learner needs
As I’ve discussed previously, so much of our learning design is rooted in approaches that may no longer provide value to learners. Most learning is content-focused, with the underlying assumption stating that our ability to navigate content is what generates learning. What if exposure to content isn’t learning? What if content isn’t even required in the learning process? Inquisition and dialogue are the core traits of learning in complex environments, largely replacing content (due to the fact that content is changing rapidly).
In this environment of chaos and shifting core elements (note the changing fields of media, music, and news), what we know (usually thought of as possession of content-based knowledge) is replaced with how we continue to stay current and informed. We often think of this learning process as isolated based on the learner learning a new concept or idea. It’s valuable, however, to see learning as a whole – when one element changes it creates a ripple effect on others. A network image is more completely explains what happens when things change quickly (and at their core). As a node in a network is updated, it creates a ripple effect that alters the network itself – but not the other nodes in the network (this is the concept “connected specialization” – one node advances (hopefully) and impacts the health of the network…but still allows all additional network nodes autonomy to function as they desire).
What does this have to do with instructional sequencing? If instruction is more than content, and learning is about increased development of health within a network as a whole, then sequencing needs to include interaction, dialogue, and network-related functions (i.e. creating a network, growing a network (adding new nodes like content resources, newcomers, masters, correlative/complimentary nodes, etc.). Sequencing in this model still allows designers to incorporate some of the approaches listed above (e.g. simple to complex, linear). While the methodology may be similar, the process of sequencing is extended to include a rich array of non-content based items. Giving learners control to explore the network, interact with nodes of interest, and then continue on in fostering their own network may replace much of the designer’s design process. Learning motivation is not exclusively a function of learner goals…instead (in a network model), motivation is also driven by contextual changes, reactionary to growth or nodes within the network as a whole.