What do we mean by pedagogy? (Part 3) Thinking about curriculum

Curriculum is a large and complex area for study and reflection. It is the vision of education made concrete, but as such, Schiro (2013) argues that this leads to conflicting visions about what curriculum should contain or focus upon. I would argue that if curriculum is merely characterised as a list of knowledge (and possibly skills), then it has become a poor representation of a very complex set of ideas and processes. Definitions and classifications of ‘curriculum’ are numerous, but as Stenhouse (1975:1) comments,

‘Definitions of the word curriculum do not solve curricular problems; but they do suggest perspectives from which to view them.’

Curriculum can be seen as a prescribed list of knowledge and indeed there has been a resurgence in characterising curriculum in this way in some jurisdictions and in some phases of education. However, a list of content can atrophy the notion of curriculum to being that of an ‘epistemic shopping list’. This then endangers the distilling out of any notion of curriculum as action or as vehicle for agency. This may still be possible – in the right hands – but may just as easily become a prescriptive list of ‘stuff to get through’, especially if linked to narrow conceptualisations of assessment. It also makes the links between curriculum, teaching, assessment and learning potentially far weaker.

In constructing a curriculum at masters level, a consideration of the wider educational context is crucial. A report by the Quality Assurance Agency for Higher Education (QAAHE, 2013), What is mastersness? gives a strong indication of some of the core features of masters level study. They characterise the main ‘facets of mastersness’ as (for an explanation of how I understand the link between knowledge, understanding, concepts and skills see here):

  • Complexity: emergent understanding by the students of the provisionality of knowledge, and the interplay and integration of knowledge, skills and application with an allied mastering of conceptual complexity. Due to the nature of masters level study there should also be an emerging ability to deal with the complexity of the learning process involved in study at this level.
  • Abstraction: the emerging ability to extract knowledge and meaning from study to use in synthesising new meanings in new and applied contexts.
  • Depth: emerging use of knowledge in new contexts and in new ways, based on development of more in-depth and interdisciplinary knowledge and understanding. This also relates to an increasing capacity to reflect on knowledge and understanding in new contexts.
  • Research: the development and emergence of greater skills and capacity in research and enquiry. This includes a wider knowledge and understanding of research perspectives and methodologies beyond the narrow confines of disciplinary or undergraduate approaches, greater autonomy in initiating research foci/agendas and maturing of the resultant methodological approaches, and carrying out more critical and in-depth analyses and interpretations.
  • Autonomy: the core of this feature of masters level study is the need for learner responsibility in their own learning. This includes ability to self-organise, to identify and conceptualise problems and to locate and acquire/abstract knowledge to consider and engage with those problems.
  • Unpredictability: the understanding that knowledge is often provisional and linked to real world problems which are often complex and ‘messy’. Therefore, students need to learn to use knowledge creativity and critically to deal with real-world unpredictability.
  • Professionalism: reflection on and emergence of ethical attitudes, values and behaviour as part of professional development. Also, this is crucial in relation to the process of research itself.

These facets are important in considering the shape and approach of a curriculum at masters level, and are also central to the link between curriculum and teaching, learning and assessment. What the report makes clear is that the emphasis across the facets will contrast between different disciplines, courses, and indeed between individual students as the diversity of prior learning and experiences as students enter masters level means that they will all be on personal and often very different trajectories, even if following the same course.

As I’ve suggested in a previous post, many of the features outlined above are in keeping with the notion of an emergent curriculum (Osberg and Biesta, 2008). By providing some structure and knowledge input as the basis for individual exploration and discovery, students can begin to shape their learning and studies in ways which suit them and which also begins to aid the emergence of autonomy, research, unpredictability etc. This also moves the notion of curriculum far beyond a list of things to be learned (which often, ultimately reduce to knowledge transfer), and one which encompasses much wider educational goals.

In this characterisation curriculum becomes indivisible with teaching, learning and assessment as it includes not only consideration of what is to be taught, but also how and why. Therefore, any conceptualisation of teaching which lacks reference to curriculum is risking an impoverished understanding and discussion of how they relate as emergent and interpenetrating concepts. As suggested in an earlier post, consideration of assessment is likewise tied to these discussions. To separate out is to unravel a complex framework of ideas which have little meaning apart.

References

Quality Assurance Agency for Higher Education (2013) What is mastersness? Discussion Paper. Retrieved from: http://www.enhancementthemes.ac.uk/docs/report/what-is-mastersness.pdf [Last accessed 5/7/15]

Osberg, D. &Biesta, G. (2008) ‘the emergent curriculum: navigating complex course between unguided learning and planned enculturation.’ Journal of Curriculum Studies, 40(3): 313-328.

Schiro, M.S. (2013) Curriculum Theory: Conflicting Visions and Enduring Concerns. Thousand Oaks, CA: Sage.

Stenhouse, L. (1975) An Introduction to Curriculum Research and Development. London: Heinemann.

Teaching Research methods – Some initial reflections

On March 20th, we finally finished teaching a research methods module which is a core element of our MA International Education (MAIE) course. As I outlined in this blog last autumn (here, here and here), I have been working with a colleague in the School of Education to develop a new approach to our research methods course.

Having finished the course and the data collection we have captured from a parallel research project of our own on the module, it feels like a good time to consider some initial reflections about our work. This is obviously an initial perception, we need to spend many months analysing the very rich dataset we have collected. Any reflections can’t be taken as a detailed and accurate account. However, several issues seem to have emerged across the module:

1) Thinking about threshold concepts. As we began to develop a curriculum framework we discussed possible threshold concepts in research methods as a basis for instructional design. In a past post, I listed threshold concepts identified by Kiley and Wisher (2010). They saw the threshold concepts relating to research methods as being:

  • argument
  • theory
  • frameworks
  • knowledge creation
  • analysis
  • paradigm

We started from this point, but through discussion emphasised the following concepts as being both central to understanding research methods and also having the potential to be transformatory. Consequently, our list of threshold concepts became:

  • criticality
  • theory
  • methodology
  • ethics
  • analysis
  • epistemology/ontology

In the event, we spent less time on theory as a concept than we had expected, but all of the other concepts became a major part of the course. In student interviews criticality was seen as central to developing an ability to read research and from this to writing well considered and careful texts. Methodology and analysis were also seen as being important for assessing papers as well as being central to a critical and deep understanding of how to carry out research. One student reflected that previously she had read the ‘start and end’ of papers to engage with the main messages; now she first engages with the ‘middle’ to assess the degree to which the research could be used or trusted. Ontology and epistemology were the most difficult concepts to tackle and at the end of the module I would argue that some are still in liminal space in this respect. Some students reflected that at undergraduate level the nature of reality and knowledge, as well as paradigms, were assumed and hence never discussed. As an interdisciplinary pursuit education needs to engage in these debates as researchers from many different traditions meet at this particular crossroads and there is therefore a level of philosophical complexity. Methodology, analysis and ethics were all equally important in aiding students to gain a deeper and holistic understanding on which to base their expanding knowledge and practical experience.

One additional concept which we had not included in our original list but which I would be minded to include having completed the module is that of ‘sampling’. Some struggle with this and yet good understanding often acted as a basis for logical, well considered and critical bridges between methodology and data collection tools. Where sampling was not well understood this bridge was less, if at all, secure and logical explanation of research design began to default to general description and a lack of criticality.

2) Importance of language. We have started to see the research methods module more and more as a language course. This is not only the result of developing a course which predominantly attracts international students, although this is obviously important. We have a number of English speaking students and yet they often commented on the difficulty of engaging with the language. Research methods language is conceptually rich and difficult; we are teaching this language and regardless of student origin, we need to ensure that students understand the language and the concepts underlying it.

3) Research methods as an applied activity. In our planning, we also developed a pedagogic model which sees conceptualisation, knowledge and application as equally important, and intertwined.

understanding elements of learning for a master's RM programme

At the end of the module I feel this is a very useful framework and has aided in developing a critical approach to the module. Conceptualisation is vital as a basis for constructing and developing knowledge. However, where these began to really make sense for students was when they actually enacted their ideas. The application of research methods started from day one of the course and revolved around two practical exercises. Firstly, students acted in pairs to consider the characteristics of good interviewing before developing a set of group research questions based on a research problem given to them by ourselves. From the research questions they discussed and agreed interview questions before splitting into pairs to complete their interviews. Once complete, the pairs then transcribed and encoded their data. This process shadowed their work in face-to-face sessions and therefore their emerging understanding of the module. The final exercise focused on comparing codes across the group to identify re-occurring themes as well as outliers.

Students then moved on to complete a module assignment which asked them to develop an area for research, develop research questions from this, before creating a research design which was then piloted. Subsequent to the pilot, students were then asked to reflect on their experience and how they would change their research design as a prelude to developing their dissertation work.

This proved very challenging, but also, according to some of the students, allowed them to consider how far their understanding of research methods developed.

I am currently discussing the potential for a new master’s degree focusing on praxis-based approaches to education. Having developed our work on research methods I fully intend to embed an emergent element of research methods across all modules of the programme, leading towards a specialist research methods module. Research methods needs to be engaged with over a period of time and within different contexts to give a wide critical and experiential basis for discussion and theoretical understanding.


These are some of the basic reflections from the course, but as I said above, these are only initial and need to be considered in far more detail as we begin to engage with the very large amount of data we have collected from this course. In my next post, I will continue my reflection, by considering the process of researching this module and the utility of considering the learning environment as being a complex adaptive system.

Designing a complex curriculum-reflections on knowledge, understanding, concepts and skills

If we are to develop an emergentist curriculum, as suggested in the last post, we need to make room for the emergence of meaning within the seminar room. But in defining a process of meaning making as emergent we cannot have ready-made goals, other than perhaps a loose field of interest within which we construct our work (i.e. the link between coherence and freedom in Davis and Sumara’s (2006) conditions for emergence). One critique that might be made of this approach is that it could lead to a form of ‘radical relativism’ with individuals following any direction they feel is warranted and ending up with very little to show for their endeavour. However, this is to fundamentally misunderstand an emergentist agenda. The coherence element as a foundation for for emergence ensures limits to the field of interest, but within this admits freedom. In addition, by questioning the meaning which individuals develop, as suggested by Osberg and Biesta (2008), the teacher is required to use information and knowledge to challenge thinking and understandings through a mixture of appropriate pedagogic strategies. Thus the goals of the curriculum might not be set closely, but this does not mean knowledge is not sought. I see knowledge as central to the emergence of meaning, but how that knowledge is understood and how it also emerges in the individual needs consideration.

Knowledge is central to any curriculum. But if this is the case then knowledge itself needs defining. The definition of knowledge at one level can be very simple, being the facts, information, and skills acquired through experience or education. However, this hides a very complex area of debate as the search for a definition of knowledge is a central strand of philosophical study and over millennia, has not managed to create a definitive statement which all can agree on, and which stands the test of philosophical scrutiny. The definition of knowledge is also made even more complex by the debate as to the degree to which it stands apart from, or acts an overarching term for, the notions of ‘concepts’, ‘understanding’, and ‘skills’. Each of these terms can be taken as a subset of knowledge (as a concept!). However, how they relate is again a contested area.

Van Camp (2014: 97) sees understanding is a type of knowledge, but nevertheless feels it important to distinguish it as an explicit idea, as he states,

‘To a large extent, much of the aversion to giving understanding any philosophical prominence comes from conflating concepts simply because of linguistic poverty.’

There is a debate over whether understanding is a form of knowledge or something different, and definitions of understanding themselves vary. For example, Kvanvig (2003:192) states

understanding requires the grasping of explanatory and other coherence-making relationships in a large and comprehensive body of information. One can know many unrelated pieces of information, but understanding is achieved only when informational items are pieced together by the subject in question.’

Likewise, Zagzabski (2001: 241) defines understanding as

‘involves seeing the relation of parts to other parts and perhaps even the relation of part to a whole.’

Both of these definitions see understanding as more than basic knowledge. It is characterised by a qualitatively different aspect, the development of a structure within knowledge which is relational. Van Camp (2014) suggests that this view of understanding is, therefore, incremental, and an individual can have more or less understanding depending on the degree to which relational connections have been made. He then goes on to argue that understanding is central to our development of causation,

On my account of understanding, information is better understood if it fits into that network of knowledge, and in tension with fundamental causal beliefs if it does not. So, while causation is not necessary for understanding in principle (other types of explanation, such as unification, can make connections in our knowledge), as a fundamental-perhaps native-worldview, phenomena which are not fitted to a causal framework remain conspicuously outside a comprehensive body of information, and thus not fully understood.’

Therefore, whilst understanding might be a form of knowledge, I would argue that it makes sense to retain it as differentiated from knowledge as a concept as it emphasises the explicit purpose of denoting the links and developing network of knowledge which we gain as we learn.

A simple diagrammatic way of showing this is

KandU1

Concepts are likewise difficult to define. At a very simple level concepts can be defined as mental representations of classes of things (Murphy, 2004) inside the head. Mead and Gray (2010) develop this simple definition by considering how concepts might be understood within the wider context of ‘threshold concepts’. They consider the form and role of concepts within disciplines, emphasising the difference between private and public conceptions (or mental representations). They differentiate between the concepts we have inside our own heads, which are prone to change, and those which are shared (disciplinary) and which tend to be much more stable as change here requires negotiation and debate. They see concepts is providing the ‘underlying logic’ (p.99) used to develop and structure knowledge. Perkins (2006) in his discussion of troublesome knowledge uses Foucault’s notion of ‘episteme’ (any historical period’s way of configuring knowledge), referring to ‘a system of ideas or way of understanding that allows us to establish knowledge.’ (p.41-2). Concept is therefore positioned as a logical framework or system which allows us to structure knowledge in a way that supports and promotes understanding. Concepts by this definition become the foundation on which we structure and make sense of knowledge and understanding. As such I argue that they should also be the basis for building curricula. To add to the diagrammatic structure given above, concepts can be seen as underpinning knowledge and understanding.

KandU2

Finally, there is the issue of skills. Skills again can be defined as knowledge – procedural knowledge, which is the knowledge exercised in the performance of a task. What is important here, regardless of the term used is the idea of application. Skills/procedural knowledge is concerned with the performance of something, be it driving a car (rather than just knowing how a car works), or being able to successfully search for information; procedural knowledge is therefore of a different form of knowledge when compared to declarative knowledge (knowledge about something).

In developing and enacting an emergent curriculum, I will define ‘knowledge’ as equating to declarative knowledge, which is made increasingly useful by the relational growth of understanding. How these nodes and relationships are given a structure occurs through the underpinning power of disciplinary concepts which provide the overarching logical framework for disciplinary knowledge and understanding. Finally, given that I have retained the term knowledge to refer to declarative knowledge, I use the term ‘skill’ rather than procedural knowledge to refer to the application of knowledge, understanding and concepts. Therefore, in developing the terms of an emergentist curriculum, the following conceptual diagram becomes a useful structure for thinking about the detail in developing such an approach.

KandU3

In the next post, I will consider some of the practical ramifications of defining these processes in the way presented here, and how they interact with notions of curriculum and assessment to give a coherent approach to programme development.

References

Davis, B. & Sumara, D. (2006) Complexity and Education: Inquiries into Learning, Teaching, and Research. New York: Routledge.

Kvanvig, J. (2003) The value of knowledge and the pursuit of understanding. Cambridge: Cambridge University Press.

Mead, J. & Gray, S. (2010) ‘Contexts for Threshold Concepts (1) A conceptual Structure for Localizing Candidates.’ In J.H.F. Meyer, R. Land and C. Baillie (eds.) Threshold Concepts and Transformational Learning. pp. 97-113.Rotterdam: Sense Publishers.

Murphy, G. (2004) The Big Book of Concepts. London: The MIT Press.

Osberg, D. &Biesta, G. (2008) ‘the emergent curriculum: navigating complex course between unguided learning and planned enculturation.’ Journal of Curriculum Studies, 40(3): 313-328.

Perkins, D. (2006) ‘Constructivism and troublesome knowledge.‘ in J. Meyer and R. Land (eds.) Overcoming barriers to student understanding: Threshold concepts and troublesome knowledge. Pp. 33-47. Abingdon: Routledge.

Van Camp, W. (2014) ‘Explaining understanding (or understanding explanation).’ European Journal of Philosophy of Science, 4(1): 95-114.

Zagzebski, L. (2001) ‘Recovering understanding’ in M. Steup (ed.) Knowledge, truth and duty, pp.235-251. Oxford: Oxford University Press.

Designing a complex curriculum – Building the foundations for an emergent curriculum

In the last post in this series, I outlined some thoughts on the idea of an emergent pedagogy and in particular the work of Davis and Sumara (2006) in setting out the conditions for emergence, namely,

  • decentralised control and neighbour interactions: learning is developed in the interaction between the personal and social. Individual and collective interests should be mutually supportive rather than inherently competitive and it is the interaction between neighbours which allows for the development and emergence of new ideas and perspectives. However, to allow the development of rich neighbour interactions, it is essential that learning is not controlled from a single point; any learning-based group must be given a level of decentralised capability.
  • internal diversity and redundancy: systems need to be able to react in different ways to different situations to ensure a diversity of insights to aid innovative solutions to problems. However, for such diversity to be present there needs to be a level of duplication within the system, such as shared responsibility and interests. It is this duplication which allows for easy interaction within the system and for elements to compensate for inadequacies which reside there.
  • Freedom and coherence: within any system there must be potential for the exploration of possibilities resulting in the opportunity for personal agency and the diversity identified above. However, whilst this inclusion of freedom is central to the emergence of learning, complex systems are not chaotic and require a level of coherence to orientate the activity of the actors within the system. Coherence imposes a loose framework within which individuals are able to operate freely whilst creating frameworks for coherence.

To understand the basis for these elements, I want to develop a wider notion of an ‘emergent curriculum’ as a foundation for their application. The idea of an emergent curriculum has already been suggested by Osberg and Biesta (2008), who provide a potential philosophical foundation for such an approach. They begin from the idea that our knowledge emerges as we ‘participate in the world’ (p.313). If this is so, should this also be the way we consider learning within the classroom?

It is suggested that teaching has become increasingly viewed as an activity which needs to be structured around explicit goals and outcomes. Curriculum then becomes the framework by which predetermined goals are (or are not) met. An important aspect of this view of curriculum is that the meeting of specific outcomes is suggestive of a predetermined and restricted form of enculturation. From an emergent perspective, this can become highly problematic as,

‘if we hold the meaning as emergent, and we insist on a strict interpretation of emergence (i.e. what emerges is more than the sum of its parts and therefore not predictable from the ground it emerges from) then the idea that educators can (or should) control the meanings that emerged in the classroom become problematic. In other words, the notion of emergent meaning is incompatible with the aims of education, traditionally conceived. Emergent meaning-if it exists-is incompatible with the idea of education as planned enculturation.’ (Osberg and Biesta, 2008: 315)

This suggests that an emergent curriculum requires both the opportunity for meaning to merge through the act of pedagogy, but also that we support the emergence of uniqueness in each student. This, however, then suggests that the curriculum cannot be seen as a restrictive, ‘one size fits all’ structure which attempts to limit the emergence of meaning. Hence,

the first thing to notice about the curriculum as a ‘space of emergence’ is that it is not a space of common ground. Because human subjectivity emerges only when one acts with others who were different (Arendt, 1958; Biesta, 2006: 33-54), this means education only takes place where ‘otherness’ – being with others who are different from us – creates such a space. In this sense it is the plurality of the ‘space of emergence’ that educates, not the teacher (Biesta 2006: 13-32),’ (Osberg and Biesta, 2008: 324)

Hence, plurality is key. We need to move away from reducing the difference between the teacher and students as the ‘space of emergence’ suggests the need for difference. We need to ensure that students meet and encounter difference which then leads to a greater opportunity for the development of unique characters in understanding rather than a convergence. Many curriculum are designed to eradicate difference, but by encouraging and supporting difference, the frustration and difficulties which result lead to the spaces where real education occurs. This means that the curriculum approach which is fostered requires highly skilled teachers to help constantly challenge, and unsettle. As Osberg and Biesta (Osberg and Biesta, 2008: 326) state,

‘with the logic of emergence it becomes possible to understand educational responsibility as continuously complicating the scene, thereby making it possible for those being educated to continue to emerge as singular beings. Educational responsibility is about continuously reopening subjectivity, unsettling closures, and unpicking ‘destinations’.’

This gives the teacher a huge responsibility as it suggests a middle course between unguided, discovery learning and a model of knowledge transmission, whilst also understanding the ethical imperative of aiding individuals to finding greater understanding and uniqueness within a space of emergence. For an international masters course on innovation and reform it also provides an interesting basis for working to allow students to find meaning and understanding through an emergent process. With this as a philosophical foundation, in more practical terms, I see the conditions for emergence set out by Davis and Sumara (2006), outlined again at the start of this post as a useful framework for realising this ‘space of emergence’. In a future post, I will add to this consideration of the emergence of the subject, by exploring how it can be positively entwined with the emergence of concepts, understanding and knowledge.

References

Arendt, H. (1958) The Human Condition. Chicago: University of Chicago press.

Biesta, G. (2006) Beyond Learning: Democratic Education for a Human Future. Boulder CO: Paradigm Pulishers.

Davis, B. & Sumara, D. (2006) Complexity and Education: Inquiries into Learning, Teaching, and Research. New York: Routledge.

Osberg, D. &Biesta, G. (2008) ‘the emergent curriculum: navigating complex course between unguided learning and planned enculturation.’ Journal of Curriculum Studies, 40(3): 313-328.

Reflecting on a new Research Methods course – Some initial musings

Since September, we have been running the research methods course the planning for which was outlined in this blog earlier in the year. The ideas which I set out below are first impressions – we haven’t started to analyse the large dataset we’ve already accrued over this first term. That will be a long, if enjoyable, job!!

Working on an MA in International Education is both rewarding and also extremely thought-provoking. The groups with whom we engage are very diverse in just about every way possible; the stereotypical view that ‘academics’ don’t know anything about teaching seems somewhat wide of the mark when working with international groups. They are wonderful, and developing ideas with such groups are some of the most positive, difficult and enjoyable teaching experiences I have ever had.

What follows is a series of initial musings because any systematic understanding of our experiences thus far are a long way ahead of us due to the large scale process of in-depth data analysis which we will need to undertake once our project finishes at the end of the academic year. This post can only hope to give initial impressions and reflections on some apparently important elements of an emergent and very different pedagogy which we are developing as we gain insights from the course and the students.

International groups are often very diverse, and the group with whom we are working this year is no different. We have students from China, Japan, Saudi Arabia, the USA, Kurdistan, Turkey, Kazakhstan, Nigeria and the UK. This leads to a wide spectrum of language ability, but students are also coming straight from undergraduate degrees, including Chinese literature to Chemistry, others have trained as teachers and taught in schools, and some have Masters degrees in other subjects. Consequently, the diversity of prior knowledge and understanding of both education and of research methods is huge. However, educational research has some interesting characteristics which are different to many single discipline approaches to research, and together with a rich conceptual language has led us to consider a number of ideas and approaches, some of which are outlined below as a series of short reflections rather than a single synthesised narrative.

Language is a central element in helping a diverse international group engage with, and understand, research methods. This area of study has a rich conceptual character with an equally rich and at times abstract language associated with it. To begin to gain a working understanding of research methods requires students to begin to have confidence in their use of terminology, and the ways in which that terminology links to important concepts. Interestingly, this means that a research methods language is not only new to those for whom English is an additional language, but also for native speakers. At the end of each session we have been asking students to identify terms which they still have trouble understanding, which then become the basis for developing an online glossary and subsequent quizzes at the start of following sessions. In interviews, both native and non-native speakers have suggested that a conscious consideration of language has helped them to develop their conceptualisation of research methods in the early part of the course. Conscious consideration of vocabulary is useful to everyone.

The development of a blended approach to learning also appears to have had a very positive impact. The use of a flipped classroom approach together with pre-reading has been important for the learning of students. A number of individuals have reflected on the importance of narrated PowerPoints which they watch before a face-to-face session. They can pause, rewind, and watch a video several times if they wish, allowing them to understand both language and concepts in their own time which they can then utilise more fully within the sessions. Likewise, use of pre-reading with focused activities has allowed students to further define and embellish their basic understanding of an area as well is providing them with concrete case studies and examples of research approaches. These papers can then be used to exemplify concepts in face-to-face sessions, concepts which might otherwise remain very abstract and difficult to understand. This approach means that a large part of face-to-face sessions becomes focused on paired and group work which allows for debate and extension of ideas which they have already come across. This is particularly important in helping students to develop active and authentic use of language.

In this first term we have focused on the philosophical and theoretical foundation for research methods, covering principles of what defines research as well as basic introductions to ontology, epistemology and paradigms. These have then formed the basis for a consideration of methodology and ethics. In addition to these core ideas we have spent a day exploring approaches to critical reading, and one developing frameworks for critical writing. Anecdotal experience of research methods courses is that these issues can become separated foci which rarely crossover one to the other leading to atomised and incomplete understanding. We have attempted to constantly revisit ideas as we move forward, leading to a strong narrative within the module. Critical reading has been discussed as a process of ensuring that the understanding of research methods underpins a critical reading of literature within their other, content focused modules. Therefore, having introduced ontology, epistemology and paradigms, these concepts have been used as a way of understanding different approaches to research covered in pre-readings. Then having focused on other issues within a critical writing day we came back to ontology etc through a consideration of methodology and ethics, leading to a degree of interleaving. This also allowed us to develop an understanding of the need to create a clear philosophical and practical narrative within the development of research projects. For example, given a project title, the outlining of context should lead to research questions and from here ontological and paradigmatic foundations. These principles should then act as the basis for appropriate methodologies and methods as well is outlining ethical considerations. By revisiting these concepts and vocabulary on a number of occasions and within a number of worked examples and contexts there is evidence that students’ confidence and understanding has started to develop well.

The last reflection which has been of interest in this first period has been the use of summary concept maps at the end of each face-to-face session. As a final activity each day students have been asked to reflect upon what they believe have been their main areas of learning and then to relate these to each other. Given that it might be possible to create a concept map which gives the appearance of a well-developed level of understanding without that understanding being present, we have also asked students to create five minute recorded narrations explaining the form of their concept maps. They then send a photograph of the concept map with recordings to us so that we can understand any misconceptions or holes in understanding which might be apparent. Students who have been interviewed towards the end of term believe that this activity has helped them gain a clearer understanding of their own level of learning within sessions and has also helped them to revisit terminology and concepts in a structured way. Their inclusion within our pedagogic framework has been both useful and popular.

Reflecting on what we have learned during this first term from this revised approach to research methods, central to our thinking has been the ways in which we build linguistic and conceptual understanding to help form coherent and strong narratives concerning the foundations for understanding research methods. Linking this to varied pedagogy which includes more transmissive approaches linked to more independent, project-based and group-led work, we have started to develop a very enriched approach, one which a ‘methodology of glimpses’ appears to have helped uncover.

Designing a Complex Curriculum – The Case of Innovation and Reform 3 – emergent pedagogy and learning.

In my last post I outlined some of the main characteristics of complexity, and in particular, of complex adaptive systems (CAS). Hardman (2011) stresses that it is not a sustainable position to assert that something is a CAS without any particular evidence other than an impression of complexity. In the case of higher education pedagogy and contexts is seems reasonable to suggest that a characterisation as a CAS does work. Why? The argument here is based on the underlying characteristics of post-graduate pedagogic contexts. Taking Cilliers’ (1998) notion of a CAS the table below outlines an argument for seeing pedagogy in post-graduate study as indeed complex.

CAS element Reflection
  1. A large number of elements with many interactions
By considering the number of students, the technology they use and the multitude of spaces inhabited together with tutors and resources, it becomes clear that there are a large number of elements within a postgraduate seminar group. Any attempt to observe a seminar session demonstrates a large number of interactions which also extend spatially and temporally beyond the face-to-face ‘event’ as students continue to engage with learning in different ways and in different locations, both pre-and post-session.
  1. Non-linear interactions
The interactions which occur during the process of learning are not predictable and ‘linear’. Discussion and learning will not follow a strictly predetermined form or path. Different interactional media will occur both between participants and between them and the various resources, media and spaces they use. As a consequence, for any given individual, elements of work which are expected to have a ‘core’ role in learning may actually have little impact, whilst a brief informal chat may be crucial in opening up the understanding of the concept or area of knowledge. As such, the process of learning needs to be seen as non-linear.
  1. Interactions leading to feedback loops
As the students attempt to engage and learn there may be the emergence of positive and/or negative feedback loops. Discussion, for example, may lead a student to begin to make connections between elements of a sub-topic, and even between topics, leading to a positive feedback loop which brings rapid development of understanding as a consequence of synthetic insight. Alternatively, a resource or activity may actually confuse a student leading to a more general questioning of their understanding of the topic, in turn generating anxiety and a lack of learning. Predicting such fluctuations in the learning process are often not possible to predict bringing a level of uncertainty to the learning process.
  1. Interactions with the environment, making the identification of system boundaries difficult
The fluidity of student use of space within a typical postgraduate course leads to difficulties in deciding the unique characteristics and boundaries of particular systems. Due to the often intertwined nature of systems the nature and permeability of boundaries between each of them and the environment become blurred and hard to detect with any certainty. For example, in any given week, a student may engage with academic learning in a number of spaces, such as libraries, cafes, lecture theatres, seminar rooms and study-bedrooms within which they may make greater or lesser use of technology, reference to physical materials and/or discussion and completion of given planned activities. How a system within such fluid contexts is identified and characterised within this network of processes and where the environment begins is difficult to determine. In addition systems may be flexible both spatially and temporally as a result of this interplay of elements.
  1. Open to interactions with the environment
As suggested in the point above, the multisite nature of learning spaces and the flexibility in content development in postgraduate learning leads to constant interaction with the ‘environment’.
  1. System far from equilibrium, needing constant energy flow
As a system, teaching and learning requires constant energy input. In this case energy can be characterised as taking the form of information. If this energy flow is suppressed, or does not exist in the system, it would begin to break down, stagnating as a result of a lack of constant information input for use in learning. Energy can be found from within the system and in interaction with the environment but must be present as a flow to maintain the open nature of the system.
  1. Importance of history and past processes on the form of the present
The history of the system is important as past processes such as prior teaching activities, prior learning and experiences of individuals and the use of resources, etc, all play a part in informing and producing the current system, sometimes in unexpected and surprising ways.
  1. Each element acting only on local information rather than information of the whole system
The elements of the system, and particularly people, predominantly act on local information rather than through an understanding of the whole system at any point in time.

If learning and teaching systems are accepted as demonstrating the characteristics of a CAS, certain processes and features will be present. Firstly, the history of the system provides a foundation for the emergent form of the system. Reflection, experience, etc informs the learning and innovation of the present. A simple example of this is the impact that the differential prior learning of students has on interaction within the present and from here to the emergence of new knowledge, skills and conceptual understanding within and beyond the seminar room.

Secondly, Biesta (2010) considers the nature of complexity reduction within learning and teaching contexts which in simple terms is the differential impact of the imposition of various structures on the pedagogic process. For example, the imposition of a given curriculum or pedagogic approach within a formalised teaching and learning context is an example of the reduction of complexity as coherence becomes dominant over freedom, leading to a diminishing of emergence. Alternatively, an approach where students are left to make individual decisions concerning these important features may lead to freedom over coherence, which in its own right might be detrimental to learning. Consequentially, the degree of complexity reduction for any given context needs to be considered carefully so as to maximise the emergence of student learning. Sullivan (2010) considers the idea of emergent learning in relation to three small scale case studies and emphasises that the level of complexity within each context was dependent upon the degree to which the teacher controlled or encouraged independent approaches to learning.

Where complexity reduction is excessive. It may have a negative impact as there is a tendency to simplify through an exclusive focus on ‘knowledge’ and the use of single pedagogic approaches regardless of appropriacy to stated intentions, etc. However, complexity reduction can also be positive as all postgraduate courses require some form of structure, the use of supporting online materials which focus on stated aims, questioning frameworks and timetabled sessions. However, these are only positive if they do not destroy the complexity, instead making energy transfer into the system structured and efficient. In this way single agents may be aided in moving away from potential chaos (i.e. a surfeit of unstructured information) and into more productive states of engagement. Such teaching and learning becomes centred to a degree on creating environments and systems which allow enough flexibility to steer away from stagnation whilst not allowing for unstructured, overwhelming and therefore chaotic exposure to information.

Within post-graduate contexts, teaching and learning occur across a number of spaces, both formal and informal but also in individual and group situations, and within virtual, physical, personal, social and academic spaces. With such a variety of contexts and free access to large volumes of information descent into chaos is a distinct possibility. As the interactions occur within the system emergence can arise under certain circumstances. Emergence leads to features which are more than the sum total of elements and processes leading to their creation. Davis and Samarra (2006) argue that such emergence occurs as a result of the interaction of three tensional dyads:

  • decentralised control and neighbour interactions: learning is developed in the interaction between the personal and social. Individual and collective interests should be mutually supportive rather than inherently competitive and it is the interaction between neighbours which allows for the development and emergence of new ideas and perspectives. However, to allow the development of rich neighbour interactions, it is essential that learning is not controlled from a single point; any learning-based group must be given a level of decentralised capability.
  • internal diversity and redundancy: systems need to be able to react in different ways to different situations to ensure a diversity of insights to aid innovative solutions to problems. However, for such diversity to be present there needs to be a level of duplication within the system, such as shared responsibility and interests. It is this duplication which allows for easy interaction within the system and for elements to compensate for inadequacies which reside there.
  • Freedom and coherence: within any system there must be potential for the exploration of possibilities resulting in the opportunity for personal agency and the diversity identified above. However, whilst this inclusion of freedom is central to the emergence of learning, complex systems are not chaotic and require a level of coherence to orientate the activity of the actors within the system. Coherence imposes a loose framework within which individuals are able to operate freely whilst creating frameworks for coherence.

It is the holding of these various tensions within a relatively stable field which allows for the development of an emergent pedagogy and learning. In addition, this set of processes leads to the need for the use of a mixed approach to pedagogy. More transmissive approaches may well be the most appropriate when setting the basic foundation for study. By ensuring that targeted, focused information is given to students in the first instance(i.e. the temporary imposition of more acute complexity reduction) students are exposed to information in a coherent way, but the introduction of greater interaction and diversity within the pedagogic system allows for an emergent pedagogy in the longer run. However, to constantly reduce to a transmissive level potentially leads to the ossifying of the system, with the boundary between environment and system becoming impermeable leading to a closed system and ultimately decay. Therefore, more discovery, enquiry and collaborative-based approaches are needed. The above discussion leads to a preliminary schematic of a complex adaptive learning system which provides a conceptual model for enabling the development of a complexity led curriculum model.

complex learning and teaching contexts

References

Biesta, G. (2010) ‘Five Theses on Complexity Reduction and its Politics.’ in D. Osberg & G. Biesta (eds.) Complexity Theory and the Politics of Education.  Rotterdam: Sense Publishers. pp.5-13.

Cilliers, P. (1998) Complexity and Postmodernism: understanding complex systems. London: Routledge.

Davis, B. & Sumara, D. (2006) Complexity and Education: Inquiries into Learning, Teaching, and Research. New York: Routledge.

Hardman, M. A. (2011) ‘Is Complexity Theory Useful in Describing Classroom Learning?’ in B. Hudson, & M.A. Meinert (eds.) Beyond Fragmentation: Didactics, Learning and Teaching in Europe. Opladen and Farmington Hills: Verlag Barbara Budrich.

Sullivan, J.P. (2010) Emergent Learning: The Power of Complex Adaptive Systems in the Classroom. Saarbrücken: Lambert Academic Publishing

Designing a Complex Curriculum – The Case of Innovation and Reform 2 – a possible complexity

‘Sense making is often about creating a whole out of fragments.’ Burns (2007:2)

This post sets out some of the basic conceptual foundations of complexity as a basis for considering its use in education in the next post in this series. Over the past 30 to 40 years complexity science has developed rapidly from its origins in physics, chemistry, biology and cybernetics to offer new insights within the social sciences. The use of a complexity lens within social contexts has started to create a different way of seeing the social world as well as suggesting new approaches to researching it. Defining complexity itself is difficult as there is no single, unified theory. As Cilliers (2010: vii) argues,

‘….there is a growing realisation that there is no single coherent ‘complexity theory’ which will unlock the secrets of the world in any clear and final way. Instead, we are beginning to understand more about exactly why complex things are so difficult to understand. We really have no choice but to acknowledge that we have to take complexity seriously, even if it does not guarantee perfect solutions.’

To demonstrate some of the different perspectives which have grown from a consideration of complexity, some of the contrasting approaches and typologies are given here. Morin (2008) distinguishes between:

  • restricted complexity – complexity as an emergent product between simple agents. Such a view allows for rules-based, agentic modelling (i.e. modelling of the parts to give a sense of the whole), which is ultimately reductionist in character, i.e. leads to the idea that by modelling the parts, even though difficult, we can gain an understanding of the whole system;
  • general complexity – within this definition the system of interest is not merely the sum of the parts/agents as when they interact they give rise to new properties which are themselves emergent and which resist modelling. Indeed Morin suggests that this shows that we are limited in our understanding of complex systems regardless of the approach we use, that we must accept this, and search for a new language in describing and explaining such systems.

Richardson and Cilliers (2001) alternatively classify complexity through three contrasting approaches to study:

  • hard complexity – computational modelling and quantitative approaches, generally used within the sciences;
  • soft complexity – employed in the social sciences and often seen as offering a ‘metaphor’;
  • complexity thinking – an approach which focuses on the lack of full understanding of systems. This inherently partial perspective is due to multiple factors operating across a number of scales. However, by focusing on emergence (the way systems develop through numerous interactions) as a central process, coherent change can be discerned and studied.

Whilst Cilliers (2010) rightly points to the breadth of approaches to complexity, calling into question the idea of a single ‘theory’, Byrne and Callaghan (2014;8) argue that we should see complexity less as a traditional theory and more as a ‘framework for understanding’, based on the notion that ‘much of the world and most of the social world consists of complex systems…if we want to understand it we have to understand it in those terms.’. They quote Castellani and Hafferty (2009:34) to differentiate a traditional theory from a frame of understanding:

‘social complexity theory is more a conceptual framework than a traditional theory. Traditional theories, particularly scientific ones, try to explain things. They provide concepts and causal connections (particularly when mathematicised) that offer insight into some social phenomenon….. Scientific frameworks, in contrast, are less interested in explanation. They provide researchers effective ways to organise the world; logical structures to arrange their topics of study; scaffolds to assemble the models they construct. When using a scientific framework ‘theoretical explanation’ is something the researcher creates, not the other way round.’

Complexity is explained on an ontological basis starting from a foundation of seeing much of social reality as complex (as opposed to either simple/linear or random).

Taken ontologically, complexity rests on a number of basic concepts.

non-linearity: non-linear systems are those in which cause and effect relationships are disproportionate, i.e. small causes may have very large impacts and vice versa. There are different forms of non-linearity, including ‘threshold effects’, where a system might act in a linear and predictable way until it hits a certain threshold beyond which it acts in the non-linear manner, commonly referred to as a ‘bifurcation point’, and ‘general deterministic chaos’ where very small variations in initial conditions give very different outputs (the so-called ‘Butterfly effect’). What non-linearity stresses is an inability to accurately model or predict a complex system. Where mathematical modelling is used to explain and characterise such systems, it makes use of ‘qualitative methods’ which generate approximate descriptions as it is not possible to create exact and accurate simulations of complex, non-linear systems. This is not to suggest that quantitative approaches to complexity have no utility, they do. However, they are best used in mixed methods approaches with qualitative approaches.

Emergence: non-linear systems have the potential to create new properties from the interactions of the multitude of elements within them, properties which are not predictable given the known starting-points within the system. Deacon (2007) argues that three ‘levels’ of emergence exist.

  1. First order emergence is characterised by an aggregate of elements to give a ‘simple’ higher-order property which occurs through statistically or stochastically determined behaviours. It is the relationships between the lower-order elements/properties which give rise to the higher-order properties, a relationship referred to as ‘supervenience’. This form of emergence is perhaps most closely aligned to Morin’s (2008) definition of restricted complexity.
  2. Second order emergence introduces the impact of time on the processes involved. First-order emergence may retain self-similarity in the relationships over time. Second-order emergence shows change and development of both ‘micro and macro-properties over time.’ (Deacon, 2007:99). This means that prior states in the system become irreversibly replaced and superseded by new states/system characteristics.
  3. Third order emergence has an evolutionary character. Here, there can be amplification of global influences on parts which can lead to recursive amplification (positive feedback) or degradation (negative feedback) across all scales of the system. Hence, initial complex states can become amplifiable initial conditions for later states.

Therefore, the basis for understanding emergence is the interplay of many properties over time and across scales which can lead to new, unpredictable states and properties.

Far from equilibrium systems: Systems can exist in a number of states. Those in equilibrium tend to be isolated with no exchange of energy with the environment beyond. In many cases the lack of interaction with the wider environment leads to decay and death. Much more common are systems which are close to equilibrium, called ‘closed’ systems where there is limited interaction with the environment beyond. Here, any move away from equilibrium tends to lead to damping effects to bring it back towards the near equilibrium state. In other words closed systems tend to be driven by negative feedback loops. Finally, there are ‘open’ systems of which most human systems are examples. These can be impacted by negative feedback but may also be impacted by positive feedback which can move the system further away from equilibrium. It is the introduction of elements from beyond the system which keep these systems in a state of flux and disequilibrium. One specific type of open system is the ‘adaptive’ system, commonly referred to in complexity theory as a Complex Adaptive System. Here, change is in part the result of experience with constant exchange of information between the system and the wider environment. Such systems have a number of features, the most important of which are discussed by Cilliers (1998) who identifies them as characterised by:

  1. a large number of elements with many interactions;
  2. interactions which are non-linear, i.e. large-scale causes can have small-scale impacts and vice versa;
  3. interactions which lead to feedback loops, both negative and positive;
  4. an ‘open’ system, having interactions with elements in external environments beyond the immediate system;
  5. elements which interact with their environment making the identification of boundaries difficult;
  6. a system which is far from equilibrium and therefore needs a constant energy flow for it to operate;
  7. the importance of history, past processes playing a role in forming the present, often unpredictably;
  8. each element only acting on local information rather than information from the whole system.

Cilliers (1998: 13) goes on to argue that such systems are so complex that any total representation of them would have to be as large as the system itself – a practical impossibility;

‘In building representations of open systems, we are forced to leave things out, and since the effects of these omissions are nonlinear, we cannot predict their magnitude.’

Consequently, Richardson et al (2007) refer to CASs as ‘incompressible’, and argue that to understand them, at last in part, we need to use different perspectives to build ever richer, if incomplete, models of the system we are interested in. To some, this might be an excuse not to bother; why research something we cannot understand in its entirety? For others, there is the temptation to use experimental approaches which isolate single variables and assume they operate in the same way in a complex context. But in both cases, the complexity of the system is lost and in many experimental approaches interactive processes are assumed to have little, or no, impact.

Final thoughts

The characterisation and understanding of complexity, particularly in social research, is still very much in its infancy. We have to accept that there is no single, accepted body of theory which is unchallenged, but whilst these restrictions exist, the basic building blocks and ontological underpinning of complexity as a ‘framework for understanding’ seem to me to be worth pursuing. Methodologically, complexity accepts that research will never ‘see’ an ultimately reality (however, I accept the epistemological perspective of ‘complex realism’ developed and advocated by Reed and Harvey (1992 and 1996) and Byrne and Callaghan (2014)). As Richardson and Tait (2010: 92-93) state,

‘Just because a complex system is incompressible it does not follow that there are (incomplete) representations of the system that cannot be useful – otherwise how would we have knowledge of anything, however limited? Incompressibility is not an excuse for not bothering.’

 

References

Burns, D. (2007) Systemic Action Research: A strategy for whole system change. Bristol: Policy Press

Byrne, D. & Callaghan, G. (2014) Complexity Theory and the Social Sciences: The state of the art. Abingdon: Routledge.

Castellani, B. & Hafferty, F. (2009) Sociology and Complexity Science. Berlin: Springer.

Cilliers, P. (1998) Complexity and Postmodernism: understanding complex systems. London: Routledge

Cilliers, P. (2010) ‘Acknowledging Complexity: A Forward.’ In D. Osberg & G. Biesta (eds) Complexity Theory and the Politics of Education. Rotterdam: Sense Publishers. vii-viii

Deacon, T.W. (2007) ‘Three Levels of Emergent Phenomena.’ In N. Murphy & W.R. Stoeger (eds) Evolution and Emergence: Systems, Organisms, Persons. Oxford: Oxford University Press. 88-110

Morin, E. (2008) On Complexity. Cresskill, NJ: Hampton Press.

Reed, M. & Harvey, D.L. (1992) ‘The New Science and the Old: Complexity and Realism in the Social Sciences.’ Journal for the Theory of Social Behaviour, 22, 356-79.

Reed, M. & Harvey, D.L. (1996) ‘Social Science as the Study of Complex Systems.’ In L.D. Kiel & E. Elliott (eds) Chaos Theory in the Social Sciences. Ann Arbor: University of Michigan Press. 295-324.

Richardson, K. A., & Cilliers, P. (2001). What is complexity science? A view from different directions. Emergence, 3, 5–22.

Richardson, K.A.; Cilliers, P. & Lissack, M. (2007) ‘Complexity Science: A ‘Gray’ Science for the ‘Stuff in Between’ in Thinking Complexity: Complexity and Philosophy volume 1, Cilliers, P. (ed.). Mansfield, USA: ISCE Publishing, 25-35. (an original version of the paper can be found at http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.94.7038&rep=rep1&type=pdf)

Richardson, K.A. & Tait, A. (2010) ‘The Death of the Expert?’ E:CO, 12(2), 87-97.