While it is common practice to incorporate tasks from Bloom’s Taxonomy lower order objectives into elearning, educators and learning professionals often have difficulty leveraging elearning to involve the model’s higher order tasks. This article will illustrate 4 scalable ways to help your elearners attain higher order cognitive objectives.
Bloom’s Taxonomy is used widely for classifying the different objectives that educators set for learners. Since Bloom’s lower order cognitive objectives (knowledge, comprehension, and application) are all fairly straightforward to do online, they make up the bulk of current online training tasks. However, it often surprises me how quickly Bloom’s higher order cognitive tasks get overlooked when developing online training. The one exception here is the use of branched scenarios, which are fantastic but can’t be forced into every training topic we need to cover as educators.
Bloom’s higher order cognitive skills (analyze, evaluate and create) are heavily focused on critical thinking. These, in order, ask learners to analyse situations based on their lower order knowledge, select and choose between presented options (listing and ordering with explanations) and propose new solutions or present a critical analysis of situation ideas.
Since most higher order tasks require feedback from a teacher, an instructor or a more knowledgeable other (MKO), this often gets a little tricky (but not impossible!) to facilitate and scale through elearning.
Many learning professionals avoid using elearning for these higher order tasks due to technological constraints, time or budget constraints, or simply because they just haven’t thought of some of the ways you can use elearning to achieve the higher order objectives. There are in fact, a few very effective ways to solve the problem of using elearning to capture higher order cognitive objectives.
Reach full Bloom through elearning
Solutions to the higher order objective challenge will involve some social participation, comparing against pre-prepared answers then rating confidence, or self-reflection, and doesn’t demand much in terms of instructor time and resources.
Here are 4 ways to create impactful, scalable elearning that will allow your elearners to bloom:
1. Compare and contrast answers
Users are given a question to answer in long-form. Rather than have someone mark it, they compare their answer against a pre-prepared answer, and then compare and contrast the two. Users rate their confidence afterwards – this reflective activity is useful for engagement and retention. Great for the analyze stage tasks.
2. Case studies
A bit more scaffolded than the option above. Have students read through a case study and then answer a series of questions. If it is a real-life case study then they can even evaluate choices, and once again check against a pre-prepared answer. The longer, step-by-step nature of case studies make them great for the evaluation stage tasks. This is a nice twist on standard branched scenarios that allows learners to stretch their critical thinking muscles.
3. Reflective journals
We all know people love to talk about themselves! Students are asked to personalize the answers to questions based on their own unique experiences and current work situations. These are great once students have progressed to the create stage tasks. Answers can stay personal, or they can choose to share if they want. At this stage, the act of writing and thinking about the questions is enough to help consolidate learning in adults.
4. Small projects submitted to a community
Higher order tasks can be given as small projects to be shared with the learning community upon completion. For example, elearners may be asked to come up with a new sales plan or to critique a customer service conversation. Once completed and submitted to the community, instructors can rely on a small group of super-users who emerge in most online communities to provide feedback. Fortunately these super-users are often MKOs, which removes the need for an instructor, lets trainers act as moderators, and let’s this type of task become scalable.
While these higher order tasks may not give us the raw quantitative data we’re used to seeing when we stick with lower order tasks, there is something to be said for letting our learners flex their muscles and start personalizing their responses and experiences with elearning. As long as we are providing feedback gates along the way, we should be able to incorporate higher order tasks and let our learners Bloom.
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