Learning: Definition
The capacity… to acquire or develop new, memories, knowledge or skills based on experience
Knowledge To Action (KTA) Framework
The mindware tutorial for this session is for applying research knowledge to action – i.e. closing the know-do gap between generating evidence from various research methods and the application of knowledge gained to practice. This is sometimes called ‘knowledge translation’.Today’s information community expects us not only to have a specific knowledge base but also to be able to apply this knowledge to solve complex problems in an efficient way.
We will be using the Knowledge To Action Framework (Ian Graham, 2006). This mental model may be used on an individual level or at a more organizational level with multiple stakeholders. It is a widely cited model (ref), and was originally developed in the context of health care, helping end-users (policymakers, practitioners, and the patient-consumer-public) make efficient use of research knowledge that might otherwise remain locked away in journal publications.
The KTA model has two phases:
Phase 1: Knowledge Creation
This is a funnel with three phases. As knowledge moves through the funnel, it becomes more distilled and and useful. The needs of knowledge end-users are incorporated into each phase of knowledge creation.
Inquiry: Try to use journal scanning and alert services to keep track of new, relevant knowledge in the form of article abstracts (concise summaries of the research). You could try setting up a Feedly account for RSS blog/journal feeds and keyword alerts to help with this. I combine Feedly with research digest services that provide feeds summarizing research in the areas I am interested in. I use ScienceDaily: Mind & Brain News, BPS Research Digest, and Psychology Headlines, among others. You can also keep tabs on specific researchers or research labs that focus on the area you are interested in – as well as simply finding individual research articles at source.
Synthesis: Here we are looking for up-to-date systematic reviews of the research on the target topic. You can find these by using the keywords ‘review’ or ‘meta-analysis’. Reviews weigh up the whole field and draw conclusions based on all available evidence. It is this kind of information that applications should be based on, not individual research papers.
Tools & Products: Here we extract procedures, formulae, decision-making tools, etc that enable concrete implementation of the knowledge – in practice. For example, each of mindware models (like the KTA model!) covered in the HighIQPro tutorials is such a tool/product, with guidelines for their application.
The quality of the evidence here is critical. Research digests can be good filters for quality. If you are using source articles, ensure they are peer-reviewed, and associated with reputable research institutes (check if they are listed in the SSCI). Also, when scanning individual articles it is important not to over-generalize from them. One-off results always need replication – and ideally meta-analyses. As for possibilities and logic, remember that most research findings are interpreted in terms of theories – and that different theories may be available that can account for the data. The more you immerse yourself in research the more you will see different possibilities. For values we are looking at getting enough of a ‘feel’ for the literature to be able to judge what is important, and prioritizing what is needed for application.
Phase 2: Knowledge Application
Graham understood the action cycle as a dynamic process in which all phases in the cycle can influence one another and can also be influenced by the knowledge creation process. The cycle is not uni-directional, but helps structure our thinking about what to consider. This phase includes the much-needed implementation plans and practices designed for practical adoption of the knowledge.
Identify problem & select knowledge: This may involve evaluating the gap between the desired and actual practice and evaluating knowledge relevance. For instance, the gap between dietary habits, and a diet that promotes brain health, and evaluating which evidence based dietary practices can be implemented, drawing from the ‘Knowledge Creation’ phase.
Adapt knowledge to local context: Application of knowledge always involves calibration – tweeking and prioritization to fit the constraints and opportunities of your own actual situation. For instance, in applying dietary recommendations you may factor in your own dietary preferences or those of your family & friends. Perhaps your own physiology has distinct interactions.
Assess barriers to knowledge use: In our example, barriers may be that we have a limited budget or moving over to the ‘knowledge creation’ phase, we may not have the expertise (or time) to evaluate all claims adequately so trade-offs have to be made. It is also worth mentioning facilitators to knowledge here too (not in the original model). We may have access to a well-informed evidence-based nutritionist, for instance.
Select, tailor and implement interventions: The information above is used to develop and execute the plan and strategies to promote awareness and implement of the knowledge. This step may require education (information), training, or use of tools that facilitate decision-making. In our example, we are now looking at e.g. formulating a weekly meal plan – perhaps using an app to help us stick to it.
Monitor knowledge use: This step involves measuring outcomes and other relevant information – e.g. compliance level, budget, agreed on measures (may be subjective) of brain health. It is needed to determine the effectiveness of the strategies and plan so they can be adjusted / modified accordingly (see next step).
Evaluate outcomes: There comes a point where you’ll need to more deliberately evaluate the effectiveness of the knowledge tools/product in its applied context for the end-user, in order to decide on any needed changes. Has the knowledge made a difference? Have we narrowed the gap between evidence and actual practice?
Sustain knowledge use: Using strategies to maintain behavior/practice changes is critical to ensure that gains are not lost over time, or with changing circumstances. Maintenance strategies can be as simple as reminder systems, or more diverse tactics to build enduring, life-changing habits.
Double Loop Learning
As with all of these mindware models (‘mental model’ in the diagram here), the decisions that keep a model like the KTA framework active in your life should be based on periodic evaluation at a ‘meta’ level, after you’ve had ample opportunity to test the model out over time. The model may evolve into something better fit for purpose, or you may discard it entirely.
