Why we need to change how we design courses.

There are many courses out there that do a great job of teaching manual, dexterity and physical capabilities. From bricklaying, hairdressing, to gas-fitting, there are course that are focussed around manual processes. However, there are huge numbers of graduates from tertiary programmes that cannot perform duties required of employers on day-one simply because they have not learnt how to do something. Their learning may have been told ‘why’, and even ‘what’ is expected, but it has not enabled them to perfect the skills associated with the ‘how’.

It remains remarkable to me that so many course and programme specification documents, replete with (sometimes well-formed) learning outcomes, have NO psychomotor outcomes. There are few courses that could not be improved by including an assessed outcome associated with using a tool or technology.

To prove the point I asked colleagues informally before Christmas whether they could think of a course where there was NO tool or technology use in play. Without further prompting, most agreed that Excel skills, SPSS, CAD tools, even library databases all required a degree of incremental competence but that these had not been in any way ‘taught’, let alone assessed, within their courses. One provocateur suggested that their course required only the ability to write and reflect. It took little effort to unpick this given that writing in this context requires a word-processing package, formatting, style sheets, spell-checking and in-text-citations, all of which are assumed graduates skills. This colleague stood their ground, suggesting that they were not employed to teach those skills; that was someone else’s responsibility.

This may be at the root of the challenge. Thirty years ago (when many of our current educational leadership graduated) your three to seven years spent at University was a valuable time spent in proximity to the sources of privileged knowledge, the esteemed Professor or the library. You had a whole life after graduation to develop the rounded skills associated with being whatever your chosen lifetime employment might be. That is simply no longer the case. The ‘academy’ no longer contains the privilege knowledge. We have democratised the information sources. Even those who embark on a lifelong vocation will find the landscape around them continuously changing.

Access to the LinkedIn Learning resources, and the cornucopia of free web resources, has allowed some institutions to negate whatever obligations for manual, dexterity and physical skills development they might feel towards their students. Some course weave these external resources into the learner’s experience, others totally abdicate responsibility and deem it part of the independent learning required of learners.

One reason for this lack of attention paid to the acquisition of psychomotor skills is because it is thought harder to assess someone’s psychomotor skill set that it is to test their knowledge, and by extension their intellectual or cognitive skills. If I can’t meaningfully assess it, I’ll just avoid teaching it. It is also a function of the ‘curse of knowledge’, given that faculty have acquired their psychomotor skills in a particular technology or tool over an extended period of time and they have failed to either document that learning or indeed to reflect on it.

There are some well designed courses out there. I hope you designed or teach on one. But there is still a significant deficit in the in-course provision of support for the acquisition of psychomotor skills associated with tools and technologies in a range of disciplines. We need to design courses across ALL disciplines that are rooted in the skills that graduates require to handle the uncertain information, technology, and socio-cultural environments they face. This means designing courses first around psychomotor skills, interpersonal and affective skills, then meta-cognitive and cognitive skills. Then, and only then, should we worry about the factual knowledge element. We need programme and course designers to be designing with different priorities if we want to make learning appropriate for the contemporary learner.

Photo by Markus Spiske on Unsplash

Blended by us or differentiated by learners: the future of courseware design

Ten years ago, in 2011, I wrote a blog entitled ‘there’s no such things as blended learning’, which essentially suggested that all learning experiences are blended to some extent, making the term irrelevant.

Since then, the boundaries between contexts, technologies and experiences have become even more blurred. Yet rather than discarding the blended terminology, there is simply a profusion of new terms, hybrid and hyflex, being the current vogue. Oh, and ‘flipped’, which is presented to the ill-informed as something new and radical. The problem is these terms are driven by us, as institutions, to define the nature of our course offering, rather than being conceptualised as the learner experiences them.

I am comfortable using the term ‘blend’, alongside ‘mix’, ‘selection’, ‘options’ and many synonyms when talking about courseware designed for a specific delivery context. The context of the learner is key. Any contemporary learner journey is going to involve a ‘smorgasbord’ of learning material, voices to be exposed to, individuals to share reflections with, and physical, social and cultural contexts in which learning is occurring. I can’t imagine a context in which a learner only learns through one communication mode, be it a lecture or workshop.

Learning can, and should, be as ‘flexible’ as possible. Informed by the principles of Universal Design for Learning, learning should be malleable enough by the learner to suit their evolving needs and context. Learners should be able to discard elements of the learning journey, take shortcuts rather than revisit existing learning if they choose. Equally, they should be able to explore around the edges of the path designed for them; to go ‘off-piste’ if you like.

Good learning design and good teaching encourage the learner to re-contextualise newly gained knowledge and experience in the light of previous learning. Given that each individual’s context is unique, it is essential that learners should blend their own learning experience. Learners should be enabled to make-meaning for themselves. Good teachers know this.

In practice, the terms blended, hybrid and hyflex, are really being used by institutions to define the nature of their ‘product’, rather than the nature of the learning experience. Institutions choose to package what they sell under different labels, it’s a marketing pitch, “now with added webinars” or “now with extra VLE resources available”. Some senior managers have assumed the opportunities for off-campus communication engagement in the internet era represent a new alternative pedagogy. In reality, the ‘alternative’ pedagogies have always been there. There have always been skilled faculty who reached beyond the lecture or seminar room and engaged learners in their own context. Designing courses that are suitable for open navigation is counter-intuitive for most institutions. The focus has been on designing a learning pathway, not pathways. It’s easier for institutions that way.

What has changed since 2011 is the range of communication technologies available for learners to choose, or not choose, to interact with content, experiences and each other. Courseware in my view can, and should, be designed with open navigation, open pathways, so a learner can choose how they want to arrive at a preconceived set of outcomes. We can provide an optimal route to success for the less adventurous, but choice empowers. Essentially, learners can differentiate their journey from others based on their context and personal needs. Hey, why don’t we use the term ‘differentiated learning’… although that sounds familiar. Wonder if anyone has used that term before? Forgive my sarcasm, but I do wonder whether we need to find new language to describe the aspirations for our courseware as it is experienced by learners.

If we acknowledge that everything is to some extent blended, then what term would encourage courses to be designed to enable learning journeys suitable for personalisation by the learner. Differentiated learning is the best I’ve got.

Photo credit: Photo by Elena Mozhvilo on Unsplash

What are the four key skills required of learning designers or instructional designers?

Let’s talk about the skills required of learning designers, or instructional designers. 

Context makes all the difference. Learning design in a face-to-face University context looks very different from an online instructional designer working in a government department or commercial enterprise.

Roles using generic job titles can differ significantly. There are learning designers who guide academics in their practice (in the way ‘educational developers’ do), and others who interpret how-to notes into a short visually rich interactive screen based experience (more like a UX ‘user experience’ designer). And all points in between.

Job descriptions can be fairly meaningless.

Knowing the needs of the organisation is the best place to start. Knowing the difference between designing a series of courses as part of a University programme that is going to amount to 3,600 hours of student learning differs greatly from taking a manual and putting it into an e-learning unit that takes an hour to work through.

The nature of the organisation also determines the degree of autonomy and responsibility the designer is likely to be given. Turning a manual into e-learning may require no content knowledge at all. Just convert what’s there and you’re good. A course as part of a formal qualification either requires the designer to have some foundation in the discipline or the ability to research, corroborate, validate and extract knowledge,  and establish how best to ‘teach’ that. 

The only commonality across these roles and contexts is the ability to see things through learner’s eyes, whoever that learner is. 

That means empathy is the first key skill.

In the contexts in which I have worked in the last 25 years, the ability to overcome the ‘Curse of Knowledge’, the inability to remember what it means to be a beginner in any area of learning has been key. That means that for me, it has never been about building a team of discipline specialists. It has meant looking to build course teams that include those who possess knowledge and practical experience, and those who act as the ‘first learners’. These first learners, as designers, need to ask the simple questions, the ‘dumb’ questions, to make sure that the level at which we pitch the learning is appropriate.

This may seem obvious to you, but it’s remarkable how many designers are intimidated by specialist knowledge. Faced with a Subject Matter Expert (SME) who is ‘cursed with knowledge’ and who cannot express learning intentions at the appropriate level, a good designer has to cajole, persuade and chorale the learning from the SME.

This means that the ability to listen and ask questions as though a ‘first learner’ is the second key skill.

Designing learning that works within a specific context, say a three hour face-to-face workshop, is unlikely to work in an online form without modification. This means designers need to combine their skills of empathy and listening, of understanding the institutional purpose and the perceptions of the learner, and adapt courseware accordingly.

In the last 18 months many organisations have been forced to learn this lesson the hard way. Faced with the challenge of sustaining learning under pandemic conditions, most have made a reasonable effort of getting it right. Those that held to their core values and listened to the needs of their students and teachers have done better than those that reached for process and systems driven approaches.

A good classroom teacher, with practice, can adapt their delivery from workshop to seminar, from lecture to discussion fora, when timetabling assigns them a different teaching space, learning designers need to adapt the ‘tools’ they use to suit the learning need. Digital tools come and go, upgrades can change the way tools behave significantly. A designer who is an expert at using Rise 360 may move into a role where that tool is not available, or they may use H5P like a pro only to find that their organisation prohibits its use on their platform. A good designer looks past the tool (or space) and can identify the essence of the learning experience and make it engaging.

Being adaptable to the means of communication and associated toolset is the third key skill.

You notice that there is nothing about intellectual skills or the ability to use any particular tool. I am making an assumption that you have at least a bare minimum of digital-literacy, that you have used more than one tool, and that you know what appropriate use looks like in a given context. I am also making the assumption that you are intellectually capable of some level of judgement and analysis. 

Most importantly, I am going to assume that you are, because you have read to the end of this post, sufficiently self-reflective to consider what your skill set is, and what it should or could be. That’s a great start. 

Being a reflective practitioner is the fourth key skill. Arguably, the most important one!

If you are thinking about building a career as a learning designer, of whichever guise, these are the four key foundational skills: being empathic, a listener, adaptable, and reflective.

 

 

Photo by Halacious on Unsplash

Overview of the 8-Stage Learning Design Framework (11’48”)

This an introduction to a new resource being shared on this website, the 8-Stage Learning Design Framework, or 8-SLDF for short. The framework provides a supportive step by step process to enable faculty and course designers to develop robust and well-aligned programmes or modules. Publication of the 8-SLDF is in preparation so only brief explanations are provided but resources will be shared over time with associated commentaries. These blog posts will find a permanent home on the research pages of this site too.

Graphical representation of the * Stage Learning Design Framework
8-SLDF (©2016)
O: Overview

I believe that the best way of ensuring that students and faculty can both engage in a meaningful, positive and fruitful learning collaboration is by designing courses well.

By well, I mean that courses that are constructively aligned, relevant to the real-world experience of students, engaging and transparent. Courses must also be cultural and socially aware. Students need to know why they are being asked to perform learning tasks and we should always have an answer. Knowing ‘why’ an activity matters because it is the first step in any individual’s self-reflective process, their metacognition and the development of their personal epistemologies (Atkisnon, 2014). We also need to know ‘why’ because doing anything for the sake of it is clearly wasteful of our time and energy. We as faculty are valuable players in the relationship between our students, the discipline, our institution and the wider world. Being good at what we do makes a difference. Designing courses that enable us to be better at what we do simply makes sense.

The 8-Stage Learning Design Framework has had a long gestation. It has its foundations built through my educational development practice around the work done by John Biggs on constructive alignment (2007) and the SOLO taxonomy (1982). I then incorporated work by Anderson and Krathwohl’s reworking of Bloom’s cognitive domain taxonomy (2001) alongside others domain development, including the original Bloom project’s articulation of the affective domain (1956), Dave’s psychomotor domain (1967), and my own interpretations of Metacognitive and Interpersonal domains.

The issue of the effective materials design was inspired by the Open and Distance learning world (pre-digital), particularly by Derek Rowntree (1994) and Fred Lockwood (1994), on my collaborations with Kevin Burden around the DiAL-e Framework (2009) and my own scholarship around the SOLE Model (2011). More recently I have drawn inspiration from the work of James Dalziel and Gráinne Conole (2016), and Diana Laurillard (2012), in their learning design conceptualisations, particularly as it relates to learning activities.

The result is I believe a comprehensive, flexible and adaptable learning design framework not just for activities but for entire courses, module and programmes. It is an appropriate framework regardless of the discipline, level, context or mode of learning. It is a framework for any adult, formal, learning context.

See the research pages to follow this resource development

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.

Atkinson, S. P. (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.

Atkinson, S. P. (2014). Rethinking personal tutoring systems: the need to build on a foundation of epistemological beliefs. London: BPP University College.

Atkinson, S. P. (2015). Graduate Competencies, Employability and Educational Taxonomies: Critique of Intended Learning Outcomes. Practice and Evidence of the Scholarship of Teaching and Learning in Higher Education10(2), 154–177.

Biggs, J., & Collis, K. F. (1982). Evaluating the Quality of Learning: Structure of the Observed Learning Outcome Taxonomy. New York: Academic Press Inc.

Biggs, J., & Tang, C. (2007). Teaching for Quality Learning at University: What the Student does (3rd ed.). Buckingham. GB: Open University Press.

Burden, K., & Atkinson, S. P. (2009). Personalising teaching and learning with digital resources: DiAL-e Framework case studies. In J. O’Donoghue (Ed.), Technology Supported Environment for Personalised Learning: Methods and Case Studies (pp. 91–108). Hershey, PA: IGI Global.

Conole, G. (2016). Theoretical underpinnings of learning design. In J. Dalziel (Ed.), Learning design: conceptualizing a framework for teaching and learning online (pp. 42–62). New York: Routledge

Dave, R. H. (1967). Psychomotor domain. Presented at the International Conference of Educational Testing, Berlin.

Krathwohl, D. R., Bloom, B. S., & Masia, B. B. (1956). Taxonomy of Educational Objectives, Handbook II: Affective Domain. New York; David McKay Company, Inc.

Laurillard, D. (2012). Teaching as a Design Science (1 edition). New York: Routledge.

Lockwood, F. (Ed.). (1994). Materials Production in Open and Distance Learning. London: SAGE Publications Inc.

Rowntree, D. (1994). Preparing Materials for Open, Distance and Flexible Learning: An Action Guide for Teachers and Trainers. London: Routledge.

Four contractual agreements to make with your students about feedback (3’30”)

There are social conventions, unwritten rules, around feedback in a formal education setting. Most students associate feedback as coming from the voice of authority in the form of red marks on a written script! It is important to redefine feedback for university and professional learners.

In this short overview video (3’30”) Simon outlines four ‘contractual’ arrangements all faculty should establish at the outset of their course or module with respect to feedback for learning.

These are
1) ensuring that students know WHERE feedback is coming from
2) WHEN to expect feedback
3) WHAT you mean by feedback
4) WHAT to DO with the feedback when it’s received.

  1. Feedback is undoubtedly expected from the tutor or instructor but there are numerous feedback channels available to students if only they are conscious of them. These include feedback from their peers but most important from self-assessment and learning activities designed in class.
  2. Knowing where feedback is coming from as part of the learning process relieves the pressure on the tutor and in effect makes feedback a constant ‘loop’, knowing what to look out for and possibly having students document the feedback they receive supports their metacognitive development.
  3. Being clear with students as to what you regard as feedback is an effective way of ensuring that students take ownership of their own learning. My own personal definition is extremely broad, from the feedback one receives in terms of follow-up comments for anything shared in an online environment to the nods and vocal agreement shared in class to things you say. These are all feedback. Knowing that also encourages participation!
  4. Suggesting to students what they do with feedback will depend a little bit on the nature of the course and the formal assessment processes. Students naturally enough don’t do things for the sake of it so it has to be of discernable benefit to them. If there is some form of portfolio based coursework assessment you could ask for an annotated ‘diary’ on feedback received through the course. If its a course with strong professional interpersonal outcomes (like nursing or teaching for example) you might ask students to identify their favourite and least favourite piece of feedback they experienced during the course, with a commentary on how it affected their subsequent actions.

What’s important is to recognise that there are social conventions around feedback in a formal education setting, normally associated with red marks on a written script! It is important to redefine feedback for university and professional learners.

Simon Paul Atkinson (PFHEA)
https://www.sijen.com
SIJEN: Consultancy for International Higher Education

Using Learning Design to Unleash the Power of Learning Analytics

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Atkinson, S.P. (2015). Using Learning Design to Unleash the Power of Learning Analytics. In T. Reiners, B.R. von Konsky, D. Gibson, V. Chang, L. Irving, & K. Clarke (Eds.), Globally connected, digitally enabled. Proceedings ascilite 2015 in Perth (pp. 358-364 / CP:6-CP:10).


 

A very enjoyable presentation made this week at ascilite 2015 in Perth, Australia. Wonderful to engage with this vibrant and hospitable community. Amongst some fascinating presentations exploring the theoretical and information management dimension of learning analytics and academic analytics, my very foundational work on constructively aligned curricula and transparency in design was I believe welcomed.

I said in my paper that I believed “New learning technologies require designers and faculty to take a fresh approach to the design of the learner experience. Adaptive learning, and responsive and predicative learning systems, are emerging with advances in learning analytics. This process of collecting, measuring, analysing and reporting data has the intention of optimising the student learning experience itself and/or the environment in which the experience of learning occurs… it is suggested here that no matter how sophisticated the learning analytics platforms, algorithms and user interfaces may become, it is the fundamentals of the learning design, exercised by individual learning designers and faculty, that will ensure that technology solutions will deliver significant and sustainable benefits. This paper argues that effective learning analytics is contingent on well structured and effectively mapped learning designs.

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Enhancements to the SOLE Tookit – now version 3.5

I have no idea what the protocol is for naming versions of things. I imagine, like me, someone has an idea of what the stages are going to look like, when a truly fresh new is going to happen. For me I have a sense that version 4.0 of the SOLE Toolkit will incorporate what I am currently learning about assessment and ‘badges’, self-certification and team marking. But for now I’m not there yet and am building on what I have learnt about student digital literacies so I will settle for Version 3.5.

This version of the SOLE Toolkit 3.5.1, remains a completely free, unprotected and macro-free Excel workbook with rich functionality to serve the learning designer. In version 3.0 I added more opportunities for the student to use the toolkit as an advanced organiser offering ways to record their engagement with their learning. It also added in some ability to sequence learning so that students could plan better their learning although I maintained this was guidance only and should allow students to determine their own pathways for learning.

Version 3.5 has two significant enhancements. Firstly, it introduces a new dimension, providing a rich visualization of the learning spaces and tools that students are to engage with in their learning. This provides an alternative, fine-grain, view of the students modes of engagement in their learning. It permits the designer to plan not only for a balance of learning engagement but also a balance of environments and tools. This should allow designers to identify where ‘tool-boredom’ or ‘tool-weariness’ is possibly a danger to learner motivation and to ensure that a range of tools and environments allow students to develop based on their own learning preferences.

Secondly, it allows for a greater degree of estimation of staff workload, part of the original purpose of the SOLE Model and Toolkit project back in 2009. This faculty-time calculations in design and facilitating are based on the learning spaces and tools to be used. This function allows programme designers and administrators, as well as designers themselves, to calculate the amount of time they are likely to need to design materials and facilitate learning around those materials.

I invite you to explore the SOLE Toolkit on the dedicated website for the project and would welcome any comments of feedback you might have.

Rich visualizations and costing in SOLE 3.5

As promised this version of the SOLE Toolkit, 3.5, remain a free, unprotected and macro-free Excel workbook with rich functionality to serve the learning designer. Version 3.5 has two significant enhancements.

Rich visualization of the learning spaces and tools: that students are to engage with in their learning. This provides an alternative, fine-grain, view of the students modes of engagement in their learning.

Faculty-time calculations in design and facilitating: based on the learning spaces and tools to be used

As promised this version of the SOLE Toolkit, 3.5, remain a free, unprotected and macro-free Excel workbook with rich functionality to serve the learning designer. Version 3.5 has two significant enhancements.

Rich visualization of the learning spaces and tools: that students are to engage with in their learning. This provides an alternative, fine-grain, view of the students modes of engagement in their learning. It permits the designer to plan not only for a balance of learning engagement but also a balance of environments and tools. This should allow designers to identify where ‘tool-boredom’ or ‘tool-weariness’ is possibly a danger to learner motivation and to ensure that a range of tools and environments allow students to develop based on their own learning preferences.

Faculty-time calculations in design and facilitating: based on the learning spaces and tools to be used there is now a function to allow programme designers and administrators, as well as designers themselves, to calculate the amount of time they are likely to need to design materials and facilitate learning around those materials.

This builds on newly designed functionality release in September 2014 in version 3 of the toolkit, namely;

  • Predicated Workload – the amount of time the designer anticipates students will spend is on activities charted.
  • Sequencing activities – the ability to suggest the order in which activities should be tackled. It remains an open approach and so the numbering system (letters, Roman, multiple instances of the same item) is open. It is considered important in the SOLE Model that students should take responsibility for the learning process as so the sequence should  be suggestive or advised.
  • Completion Record – a column has been added to allow students to record whether an activity has been completed alongside indicating the amount of time was actually spent on any given activity.
  • Objectives Met Record – an area is included to allow students to indicate that they believe they have met the objectives for each individual topic/week.

At its core the toolkit serves to implement a model of learning based on the SOLE Model itself and it is worth reminding yourself how the model is designed to work.

Further Details:

Here are two short videos that detail the significant enhancement made in Version 3.5 of the Tookit.

Visualisation of Learning spaces

Calculating Faculty-Time in Design and Facilitation

Why ‘learning analytics’ is like a sewer

Back in the late northern hemisphere summer of 2013 I drafted a background paper on the differences between Educational Data Mining, Academic Analytics and Learning Analytics. Entitled ‘Adaptive Learning and Learning Analytics: a new design paradigm‘, It was intended to ‘get everyone on the same page‘ as many people at my University, from very different roles, responsibilities and perspectives, had something to say about ‘analytics’. Unfortunately for me I then had nearly a years absence through ill-health and I came back to an equally obfuscated landscape of debate and deliberation. So I opted to finish the paper.

I don’t claim to be an expert on learning analytics, but I do know something about learning design, about teaching on-line and about adapting learning delivery and contexts to suit different individual needs. The paper outlines some of the social implications of big data collection. It looks to find useful definitions for the various fields of enquiry concerned with collecting and making something useful with learner data to enrich the learning process. It then suggest some of the challenges that such data collection involves (decontextualisation and privacy) and the opportunity it represents (self-directed learning and the SOLE Model). Finally it explores the impact of learning analytics on learning design and suggests why we need to re-examine the granularity of our learning designs.

I conclude;

Learning Analytics Cover“The influences on the learner that lay beyond the control of the learning provider, employer or indeed the individual themselves, are extremely diverse. Behaviours in social media may not be reflected in work contexts, and patterns of learning in one discipline or field of experience may not be effective in another. The only possible solution to the fragmentation and intricacy of our identities is to have more, and more interconnected, data and that poses a significant problem.

Privacy issues are likely to provide a natural break on the innovation of learning analytics. Individuals may not feel that there is sufficient value to them personally to reveal significant information about themselves to data collectors outside the immediate learning experience and that information may simply be inadequate to make effective adaptive decisions. Indeed, the value of the personal data associated with the learning analytics platforms emerging may soon see a two tier pricing arrangement whereby a student pays a lower fee if they engage fully in the data gathering process, providing the learning provider with social and personal data, as well as their learning activity, and higher fees for those that wish to opt-out of the ‘data immersion’.

However sophisticated the learning analytics platforms, algorithms and user interfaces become in the next few years, it is the fundamentals of the learning design process which will ensure that learning providers do not need to ‘re-tool’ every 12 months as technology advances and that the optimum benefit for the learner is achieved. Much of the current commercial effort, informed by ‘big data’ and ‘every-click-counts’ models of Internet application development, is largely devoid of any educational understanding. There are rich veins of academic traditional and practice in anthropology, sociology and psychology, in particular, that can usefully inform enquiries into discourse analysis, social network analysis, motivation, empathy and sentiment study, predictive modelling and visualisation and engagement and adaptive uses of semantic content (Siemens, 2012). It is the scholarship and research informed learning design itself, grounded in meaningful pedagogical and andragogical theories of learning that will ensure that technology solutions deliver significant and sustainable benefits.

To consciously misparaphrase American satirist Tom Lehrer, learning analytics and adaptive learning platforms are “like sewers, you only get out of them, what you put into them’.”

Download the paper here.

Siemens, G. (2012). Learning analytics: envisioning a research discipline and a domain of practice. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (pp. 4–8). New York, NY, USA: ACM. doi:10.1145/2330601.2330605

Visualisation of Educational Taxonomies

Sharing a paper today on the visualisation of educational taxonomies. I have finally got around to putting into a paper some of the blog postings, discussion, tweets and ruminations of recent years on educational taxonomies. I am always struck in talking to US educators (and faculty training teachers in particular) of the very direct use made of Bloom’s original 1956 educational taxonomy for the cognitive domain. They seem oblivious however to other work that might sit
(conceptually) alongside Bloom is a way to support their practice.

Taxonomy Circles ATKINSON AUG13

In New Zealand, whilst at Massey, I got into some fascinating discussions with education staff about the blurring of the affective and cognitive domains, significant in cross-cultural education, and this led me to look for effective representations of domains. I came across an unattributed circular representation that made instant sense to me, and set about mapping other domains in the same way. In the process I found not only a tool that supported and reinforced the conceptual framework represented by Constructive Alignment, but also a visualising that supported engagement with educational technologies and assessment tools. I hope this brief account is of use to people and am, as always, very open to feedback and comment.

I’m very grateful to those colleagues across the globe who have expressed interest in using these visual representations and hope to be able to share some applicable data with everyone in due course.

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