This is a video of a Research Centre for Digital Education seminar from 2nd March that went ahead virtually due to #snowmageddon. The seminar was from Peter Rich from Brigham Young University on computational thinking as a new literacy that enhances the application of the skills of collaboration, communication, critical thinking and communication that are demanded by employers.
The seminar addresses the issue of balancing content or subject knowledge based education and skills for employability from graduates. This balance being reflected in expectations from employers that seek the content knowledge and abilities (albeit situated content knowledge to do a specific job in a specific organisation) along with personal qualities and inter-personal skills. Many of the non-content skills and attributes can be found in the University of Edinburgh’s Graduate Attributes and the HEAs view of employability. This seminar looks to the P21 Partnership for 21st Century Learning and their framework for 21st century learning. This framework differs from graduate attribute schemes by aiming to be generic where graduate attributes are supposedly distinct to, for example, the particular attributes of a graduate from the University of Edinburgh.
These schemes all present higher education as an instrument to enhance individual and collective employability within competitive labour markets.
The emphasis in the presentation points towards collaboration across disciplines – so cognitive diversity should as important as skills diversity – and towards T-shaped people. This relates to the importance Peter places on the combination of critical thinking and creativity skills especially in responding to wicked problems.
The presentation gives on overview of the standard arguments for compulsory study of computing and/ coding but extends this to computational thinking. Computational thinking is summarised as the way computer scientists will approach and resolve problems using technology involving breaking down problems to identify patterns, creating algorithms and automating processes and analysing data. So it is a type of problem solving applicable across many disciplines and occupations. I particularly liked the way that Peter talks of problems as stories: what’s the context, the setting, the (sub) problems in the story, the players, etc. in the story. Also, I was really interested in the findings on the effect of studying computational thinking and coding on students’ personal resilience and understanding of failure as being points for learning – to push through failure to continue to challenge themselves and to continue to learn.
So why are the 5Cs of collaboration, communication, critical thinking, communication and computational thinking insufficient? Peter powerfully argues for compassion as a lens for teaching the 5Cs as without compassion the 5Cs can be used as much for nefarious as beneficial ends. The stories of the ideas using the 5Cs with compassion such as Safe Wander and the fun theory were great with very strong stories.
For the education implications of this, one question later on was on including compassion in curricula. Peter pointed to the affective domain of Bloom’s taxonomy and various examples of formulating learning outcome statement for that domain – an example from Warwick University is here.
The seminar’s emphasis on computational thinking as problem-solving rather than on the specific skills of learning to code in a particular language, is crucial here i think in terms of the relevance to employability and transferability of the attributes and skills developed through education.