Bloom’s Taxonomies

Most educators are familiar with Bloom’s (Cognitive) Taxonomy which is based on the following six-level structure:

 

blooms_taxonomy

 

Bloom believed that the ability to understand and apply knowledge was essential before advanced levels of development, such as analysis, synthesis and evaluation could be attained.

This model is very useful when planning learning objectives and aligning those objectives to differentiated assessment for learning strategies.

However, it is less well-known that Bloom also contributed to the development of taxonomies in all three learning domains; Cognitive (knowledge), Affective (attitude) and Psychomotor (skills).

Bloom devised his Affective Domain Taxonomy with Krathwhol and Masia in 1964. This particular theory advocates an approach for developing beliefs, mindsets, attitudes or behaviours. As per the others, the Affective Domain provides a framework for effective teaching, learning and assessment.

teaching-attitudes-pyramid

Bloom's Affective Domain
This five-stage model is based on the assumption that the learner is open to, and has a genuine willingness to change. It is perfectly reasonable to expect that some learners could oppose the tutor’s perspective of what is being taught if it is not compatible with the learner’s current beliefs.

It is important to grab the learners’ attention from the outset and create opportunities for them to share their feelings, and address any potential resistance to change.

Ideally, learning should also include links to experiences that develop attitudes and mindsets. In doing so, learners can develop social skills, personal relationships as well as their value systems.

As such, it is probably the most complicated of all three domains and requires more time for learning to be embedded than the others.

 

The Psychomotor Domain focuses on skills development, specifically the physical aspects of accomplishing a task.

Psychomotor-domain-of-learning-and-objectives

This model was finalised by Ravindrakumar Dave, who argued that learners must first observe, imitate skills, and then repeat them from memory before mastery can be achieved.

In order to maximise the learning opportunity, learners should be clear about what they will be able to do by the end of the session (outcomes). The tutor’s demonstration can take many forms, eg in person or using video, before allowing learners to do it for themselves.

Nowadays, the term ‘skill’ covers a multitude of attributes, which means that this Domain extends beyond the original traditionally intended manual and physical skills; tutors should therefore consider this Domain even if they think learning is adequately covered by the Cognitive and Affective Domains.

 

Further Reading
Bates, B., (2016) Learning Theories Simplified: Sage Publications Ltd.

 

 

Teaching and Learning Toolkit

I recently came across an interesting piece of research jointly conducted by The Sutton Trust and The Education Endowment Foundation (EEF). Originally carried out in 2011 with the premise of giving guidance to teachers and schools on how to utilise resources to raise achievement in disadvantaged learners, the researchers looked at 21 teaching and learning interventions, their cost-effectiveness and the impact on attainment.

The project was updated in 2015, and this time examined 34 teaching and learning interventions including collaborative learning (groupwork), digital technology, early years intervention, feedback, individualised instruction (differentiation), learning styles, mentoring, one to one tuition, parental involvement, peer tutoring, reducing class size, and social and emotional learning.

We all know that throwing money at a problem doesn’t necessarily resolve it, and the flip-side to that is not investing sufficient funds to make any material difference.

Cost estimations used in the Toolkit are based on the approximate cost of implementing an approach for a group of 25 learners. Where the approach does not require an additional resource, estimates are based on the cost of training or professional development which may be required. This data enables us to conduct our own cost-benefit analysis by comparing the cost estimations with the expected increase in average attainment.

Average impact is estimated in terms of the additional months’ progress you might expect learners to make as a result of an approach being used by an education provider, taking average learner progress over a year as a benchmark.

Having previously initiated a peer tutoring scheme in an FE college where it led to a significant improvement in retention and achievement, I was personally interested in the research findings regarding the impact of peer tutoring on attainment.

According to the research, implementing peer tutoring has an average impact of five months. This means that learners in a group where peer support is provided, will make on average five months more progress over the course of a year, compared to another group of learners who were performing at the same level at the start of the year. On a 12 month programme of study, like the apprenticeships we run, this is a significant outcome.

As with any research project, the results are contextual and therefore not automatically transferable, but they do provide practitioners with a useful basis on which to promote innovative teaching and learning strategies.

The Teaching and Learning Toolkit is a live resource and will continue to be updated.