This brief video (2’07”) is a reminder of the structural support that intense learning outcomes provide to the course design process. Having an understanding of the need to align course/module outcomes with programme outcomes, and to differentiate these reassessed outcomes from non-assessed topic/weekly level objectives is important. It is important because well-aligned learning outcomes provides scaffolding to all students’ learning.
These resources from 2013-2017 are being shared to support colleagues new to teaching online in the face of the COVID-19 pandemic. Consultancy for International Higher Education from Simon Paul Atkinson
I think being able to visualise things is important. Faculty and learning designers need to be able to see Intended Learning Outcomes (ILOs) take shape and mant find existing lists are uninspiring. It’s not uncommon for faculty and instructional designers to get tired and weary of ILOs; they can feel restrictive, repetitive, formulaic and sometimes obstructive. In previous posts I’ve tried to suggest that the bigger picture, the challenges of effective 21st century university level learning design, make them not only useful, but also essential. If you don’t agree, don’t bother reading. I’m not going to try and persuade you. If you think there’s some truth in the argument and you want to engage with ILOs to make your teaching more focussed, your students increasingly autonomous and your graduates equipped with meaningful evidence, then I hope I have something worthwhile sharing and will welcome your thoughts.
My argument is that a module (a substantial unit of a full years undergraduate study), and the programme of which is part, should have clearly articulated outcomes in four domains:
Knowledge and understanding – or the knowledge domain
Intellectual Skills – or the cognitive domain
Professional Skills – or the affective domain
Transferable Skills – or the psychomotor domain
I’m suggesting one SHOULD expect to see a different distribution of ILOs between the outcomes in these domains depending on the focus of the module and the level of study. One might expect to see a second year anthropology module on ‘theoretical perspectives’ emphasising cognitive outcomes and a module being studied alongside it on ‘research design and techniques’ emphasising affective and psychomotor outcomes. One might reasonably expect to see more foundational ‘knowledge and understanding’ outcomes in the first year of a programme of study, and more ‘cognitive’ outcomes at the end of the programme. The lack of this ‘designed articulation’ in many modules undermines their value to the student and ultimately to faculty.
The basic principle is that an outcome should be assessable. Lots of great stuff can happen in your teaching and students’ learning that DOESN’T need to be assessed. It can be articulated in the syllabus, it just isn’t a measured outcome. A student should be able, at the end of this course of study (module or programme), to evidence that they have attained the intended learning outcomes. This evidence has been assessed in some way and the student is then able to point to the ILOs amassed throughout their programme and say “I can demonstrate that I learnt to DO this”.
There has been a significant shift in the language we now use from the original work in the 1950s by Bloom and colleagues. The passively descriptive language of Bloom’s Taxonomy has become the active language of Anderson and Krathwohl (Anderson & Krathwohl, 2001). The taxonomies have moved from Evaluation to Evaluate, from Analysis to Analyse. This is significant in that the emphasis has moved away from describing what the focus of the teaching is supposed to be, to the demonstrable outcomes of the learning.
The illustration above consists of four visual ‘wheels’ that I have used to discuss learning outcomes with faculty in the context of module and programme design at Massey University in New Zealand and at the LSE and BPP University College in the United Kingdom. These visual representations were inspired by work done elsewhere, on the cognitive domain in particular. The first documented example of this circular representation I have been able to find is attributed to Barbara Clark in 2002, but a great many people have since represented Bloom’s original, and the revised, cognitive domain in this way.
The circular representation has the higher level terms at the centre, proto-verbs if you will, surrounded by a series of active verbs that articulate actions an individual might undertake to generate evidence, of their ability to represent to proto-verb. The circular visualisation also serves to create a more fluid representation of the stages, or divisions, in the proto-verbs. Rather than a strict ‘step-by-step’ representation where one advances ‘up’ the proto-verbs, one might consider this almost like the dial on an old telephone, in every case one starts at the ‘foundational’ and dials-up though the stages to the ‘highest’ level. Each level relies on the previous. It may be implicit that to analyse something, one will already have acquired a sense of its application, and that application is grounded on subject knowledge and understanding. So the circle is a useful way of visualising the interconnected nature of the process. Most importantly in my practice, it’s a great catalyst for debate.
The circular representations of the domains and associated taxonomies also serve to make learning designers aware of the language they use. Can a verb be used at different levels? Certainly. Why? Because context is everything. One might ‘identify’ different rock samples in a first year geology class as part of applying a given classification of rocks to samples, or one might identify a new species of insect as part of postgraduate research programme. The verb on its own does not always denote level. I talk about the structure of ILOs in a subsequent post.
More recent representations have created new complex forms that include the outer circle illustrated here. I’ve found these rather useful, in part because they often prove contentious. If the inner circle represents (in my versions) the proto-verbs within our chosen taxonomies, and the next circle represent that active verbs used to describe the Intended Learning Outcomes (ILO) AND the Learning and Teaching Activities (TLS), the outermost circle represents the evidence and assessment forms used to demonstrate that verb. Increasingly I’ve used this to identify educational technologies and get faculty thinking more broadly about how they can assess things online as well as in more traditional settings. The outermost circle will continue to evolve as our use of educational technologies evolves. In Constructive Alignment one might reasonably expect students’ learning activity to ‘rehearse’ the skills they are ultimately to evidence in assessment (Biggs & Collis, 1982; Boud & Falchikov, 2006) and the forms to enable that are becoming increasingly varied.
One of my favourite representations of the relationship between the knowledge dimension and the cognitive domain is from Rex Heer at Iowa State University’s Center for Excellence in Learning and Teaching (http://www.celt.iastate.edu/teaching/RevisedBlooms1.html accessed ). It’s an interactive model that articulates the relationship, as Anderson and Krathwohl saw it, rather well. My own interest, as we look to effective ILOs, is to separate out the knowledge dimension as a subject or knowledge domain and have faculty articulate this clearly for students, before reconnecting to the other domains. A process I’ll talk about subsequently.
Here are my four ‘working circles’ using adaptations of taxonomies from Anderson and Krathwohl (Knowledge and Understanding, and Cognitive), Krathwohl et al (Affective) and Dave (Psychomotor). I have adapted the Knowledge Dimension of Anderson and Krathwohl to do two things; to describe the dimension in terms of active verbs rather than as a definition of the nature of the knowledge itself, and I have incorporated a stage I believe is under represented in their articulation. I have added the ability to ‘ contextualise’ subject knowledge between the ability to specify it (Factual) and the ability to conceptualize (Conceptual). I have also rearticulated the original ‘Metacognitive’ as the ability to ‘Abstract‘. This will doubtless need further work. My intent is not to dismiss the valuable work already in evidence around the relationship between a knowledge dimension and the cognitive domain, rather it is to enable faculty, specifically when writing learning outcomes, to identify the subject, discipline or knowledge to be enabled in more meaningful ways.
These images are provided as JPG images. If you would like me to email the original PowerPoint slides (very low-tech!) so that you can edit, amend and enhance, I am happy to do so. I only ask that you enhance my practice by sharing your results with me.
I hope these provoke thought, reflection and comment. Feel free to use them with colleagues in discussion and let me know if there are enhancements you think would make them more useful to others.
Cognitive Domain – Intellectual Skills
Affective Domain – Professional and Personal Skills
Psychomotor Domain- Practical, Technical and Transferable Skills
Knowledge Domain – Subject and Discipline Knowledge
The next post will illustrate the usefulness of these visualisations in drafting Intended Learning Outcomes with some examples.
Anderson, L. W., & Krathwohl, D. R. (2001). A taxonomy for learning, teaching, and assessing : a revision of Bloom’s taxonomy of educational objectives. New York: Longman.
Biggs, J. B., & Collis, K. F. (1982). Evaluating the Quality of Learning: Structure of the Observed Learning Outcome Taxonomy. Academic Press Inc.
Boud, D., & Falchikov, N. (2006). Aligning assessment with long‐term learning. Assessment & Evaluation in Higher Education, 31(4), 399–413.
MOOCs, self generated OER based curricula, kite-marking schemes, and elaborate credit transfer schemes are a reality in increasingly complex higher education sector. Students often pursuing studies from within the world of work where physical mobility of employable precludes commitment to a single campus based programme over four years require well defined, constructively aligned, module designs. Clever module design means clever programme design, clever portfolios and successful institutions. Learning design is no longer just an issue for the Quality Office; the Strategy people are beginning to care too.
The vast majority of UK Universities now are able to produce detailed module and programme specifications for their teaching programmes. Specification templates usually detail the aims and objectives, resources, indicative scheme of work, staffing and mode of delivery. They also routinely use a template to generate the Intended Learning Outcomes (ILO) for the module or programme. Frequently divided into three or four sections covering, knowledge and understanding, intellectual skills (cognitive domain), professional and practical skills (affective domain) and general transferable skills (psychomotor skills), these templates are completed with varying degrees of comprehension as module validation panels will attest.
The logic is that to achieve a well-structured and constructively aligned curricula, the module team should determine what the ILOs for the module are to be (Biggs & Tang, 2007). What will the learner be able to do at the end of the module? Having determined the ILOs the team would then determine how they would enable the student to demonstrate achievement of the outcomes and draft an appropriate assessment strategy. Then, and only then, the module design team would look at what the student needed to be able to demonstrate and work out what was needed as input. Outcomes first, assessment second, teaching inputs third.
It’s not an easy thing to do. As teachers we’re passionate about our subjects, anxious to impart what we know is important, what ‘did it for us’, and at some point in this process many faculty will ‘go native’, reach for the seminal text (or the nearest thing to it, their own book), and start thinking about what the students need to know. This can of course produce fantastic learning experiences and there are a great many exciting modules drafted on the backs of envelopes without specification templates. They don’t make for effective records of achievement however.
Accreditation of prior accredited learning has always been a challenge. An effective template for module and programme design makes a significant difference. Students should be able to identify from their transcript exactly what it is they can evidence as intended learning outcomes. I would argue further that phases in learning and teaching activity should also have notable objectives that map directly to the ILOs (See the SOLE model described in Atkinson, 2011).
So how many intended learning outcomes, how many affective, how many cognitive, how many is too many? My next post will be my reasoning on that issue.
Atkinson, S. (2011). Developing faculty to integrate innovative learning in their practice with the SOLE model. In S. Ferris (Ed.), Teaching, Learning and the Net Generation: Concepts and Tools for Reaching Digital Learners. Hershey, PA: IGI Global.
Biggs, J., & Tang, C. (2007). Teaching for Quality Learning at University: What the Student does (3rd ed.). Buckingham. GB: Open University Press.
VERSION OF THIS POST FIRST APPEARED spatkinson.wordpress.com from May 13, 2010
The following brief video presentation was prepared for a Course Team workshop at Massey University NZ in May 2010 to introduce the SOLE Model.
The SOLE model is intended to be developmental, diagnostic, evaluative and descriptive. It is borne out of a desire to make the learning design process transparent to students, to encourage staff to share ‘patterns’ of learning with each other and to provide a basis for self-evaluation and development of specific learning designs. The model is not concerned with the design of specific learning activities but rather the appropriate balance between the different modes of student engagement anticipated.
The model does not prevent an academic scheduling four hours contact time a week and delivering a didactic lecture, but it would illuminate clearly that that was the approach being undertaken. Likewise, the model in and of itself does not prevent staff from reproducing an identical pattern of learning every week through a paper or course, but again, the models’ associated toolkit would make that process clear.
The SOLE model is not prescriptive and it is possible for teams to change and modify any aspect of the toolkit to suit their needs. The intention however is to provide staff with a model of effective practice such that one might be concerned about the quality of the student learning experience if the model illustrated a consistently ‘unbalanced’ approach.
One would anticipate that the visualisation generated by the toolkit would reflect a pattern of learning that differ from paper to paper, and from week to week. One could anticipate for example that in the first week of an undergraduate paper there would be significantly more ‘teacher-centeredness’ than in the twelfth week of a postgraduate paper. The visualisation will differ; the patterns can be expected to reflect different levels of engagement.
Centrality of Biggs Constructive Alignment
It is no coincidence that the model places the intended learning outcomes (ILO) at the centre. In each constructively aligned paper the pattern will be different because the learning outcomes, the assessment designed to illicit evidence of attainment and the patterns of teaching required to support that process will each be different. The SOLE model is precisely that, a model not a template. The model can, and should be adapted by staff to suit their particular approach to learning. It should reflect the nature both of their discipline, students existing context and the specific teaching environment.