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Theoretical & Conceptual Framework

This chapter critically reviews the main theoretical issues which have been influential in the practice and the central concepts which developed.

Overview

The four concepts of design, learner, technology and education intersect to provide an overarching conceptual framework for the practice, which occurred in the intersection of all four.

conceptual and theoretical framework diagram

Figure 4: Conceptual framework for this thesis

The authors that surround the four concepts, shown in Figure 4, are the most significant theorists of those that have provided the author with insight, foundation and explanation for the design challenges experienced. Increasingly responsible rôles as a teacher, software developer, media designer, team leader and director, together with a natural proclivity to be reflective practitioner, broadened and deepened the author's understanding of the criteria for improving design quality in iterative design cycles, informed by these authors' theories.

Much of this understanding began as tacit in nature, but the need to lead design, prepare design guidance and collaborate with both technical and pedagogical  colleagues demanded explanation. Extensive opportunities to present at conferences and workshops, improved the explanations and created the need for a simplified and coherent framework, represented by three key analyses, which comprise the thesis set out in the Claim chapter:

The issues of design science, mental models, learning theories, teacher types and the symbiosis of technological and human evolution are the major themes discussed in the following sections.

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Design

The concept of design employed in the author's practice extended from the imaginative formation of learning resources, environments and systems to their development and evaluation and culminated in the innovation of courses and organisations for education.

Definitions

Design as a verb entails the process of imaginative formation of an entity. In the context of education, the entity, which may be  as simple as a text or as complex as an organisation, may provide a response to some or all the key questions to progress learning, from motivation to recognition ([A3] Millwood 2009, The Learner at the Centre). Design as a noun is concerned with the specification of such an entity. A more formal, nuanced and rich discussion can be found in Ralph and Wand (2009, 118), where they define Weltanschauung (worldviews) of design thus:

Weltanschauung (Worldview)

Description

Problem Solving

Design can be seen as an attempt to solve a known problem, a view characterized by the beliefs that a problem exists and is identifiable and that the success of a design is related to how well it solves the problem.

Problem Finding 

Design can be seen as an attempt to solve an unknown problem, implying that understanding the problem is part of the design process.

Epistemic 

Design can be seen as a learning process where actions that can lead to improvements to the current situation (in the eyes of stakeholders) are discovered.

Inspiration 

Design can be seen as a result of inspiration, i.e., in- stead of beginning with a problem, design begins with an inspiration of the form ‘wouldn’t it be great if....’

Growing

Design can be seen as growing an object, progressively improving its fit with its environment and purpose.

In their terms, my practice has been informed by each of these, as appropriate to different stages of the developmental process, but in particular Inspiration, deriving from the new opportunities that technology provided, tempered with Epistemic and Growing through engagement with teachers and learners.

The verb design in my practice is an iterative process of development, accompanied by trialling, feedback and evaluation to determine the focus for further improvement. The mutability of designs may be promoted by their expression in computer formats, which offer ready correction and change. With the advent of computer programs, many designs can be expressed in the computer language or information system directly, although not all such languages make such designs accessible. This is the domain of Learning Design (Koper 2006), where one possible benefit is that the design may become enacted through the computer to guide a student on a learning trajectory, but this is not territory which I have explored in any detail in my practice, preferring designs to provide infrastructure and tools for human decision making in a freer sense. I regard learning as less likely to succeed when too tightly prescribed and in its nature, more of a creative activity which benefits from openness in outcome rather than to be restricted to such sequences with too closely focussed learning outcomes.

In my practice the designed entities have all employed some element of computer technology to enhance learning. In my conception of design as a noun, it is a mutable specification:

a representation of teaching and learning practice documented in some notational format so that it can serve as a model or template adaptable by a teacher to suit his/her context
Agostinho (2006)

I would extend this definition so that a design may be that of an information resource, tool, activity, environment or educational organisation. I have learned and employed a wide range skills including composition of words, graphic design, desktop publishing, video editing and computer programming. I have tackled the design and making of computer programs, web sites, films, furniture, office spaces, online spaces and rooms to support education.

Design Science

Defined by Buckminster Fuller (1963), Design Science brought systematisation to the design process, and became understood as the scientific study of design (Gregory, 1966).

In the context of education, Mor explains it well:

A design science of education should be based on a linguistic framework which offers an intermediate level of systematisation, rising above anecdotes but remaining grounded in reality. Such a framework would allow us to capture the structure of educational situations, the challenges they engender, as well as the means of addressing them, in forms which should empower learners and teachers to control their practice as much as it allows researchers to inspect it scientifically.

(Mor 2010, 14)

I would extend this view and suggest that a design science of education might also encourage creativity in the attempt to transform education for the better, and argue that the analytical perspectives I present in the section Claim form part of a 'linguistic framework' to support such creativity.

Complexity and iteration in design

Educational designs I have engaged with have been complex and iterative, and in a research context could be considered as design studies as described by Shavelson et al:

Design studies have been characterized, with varying emphasis depending on the study, as iterative, process focused, interventionist, collaborative, multileveled, utility oriented, and theory driven.
(Shavelson et al. 2003, 26)

The iterative view of design (the verb) is not opposed to a design process base on architectural/engineering specification, where well known and predictive calculations can be made to find the exact dimensions and materials to create a building or bridge. Instead, the iterative view recognises the unpredictability of the design of education where people, their diversity, complexity and culture are part of the design space, not simply users of an end product. It is not enough to design a computer program which performs to specification, tests correctly and is viewed as satisfactory - in education such software is subject to the richness of human discourse, re-interpretation and creativity. In the process of iterative design, such issues can be explored and the design improved with the evidence gathered to make the most effective educational outcome in a dynamic context.

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Learner

The concept of learner in my work has been particularly concerned with the developmental fulfilment of the learner at all stages in a lifelong venture, that is learning for intrinsic reasons, as well as preparation for work, culture and citizenship.

Introduction

This section focusses on the learner perspective that informs my practice. The learner in my practice has been central to improving the design of materials and courses which aim to support the development of learners' knowledge.

Learner's Knowledge

Knowledge is a term that is naturally confused in definition, between the kind of knowledge which individuals have in their head in order to think, perform and make decisions, and that which is shared in speaking, writing and other media and used by society to coordinate meaning and action. I prefer to consider the first as primary, and analyse it below by dividing it into facts, skills, mental models, strategies and attitudes, all of which are of course intimately connected. The secondary, externalised or articulated knowledge, is not normally functional independent of human interpretation, but is essentially information, which in some cases can be formally expressed in code and is then capable of computer processing.

Facts

In my view 'facts' are the simplest form of knowledge that enable the learner to respond to simple questions of definition. In logical terms, they represent connections between two or more atomic concepts, for example 7 times 8 is 56 connects 7, 8 and 56. Such facts are interconnected with others, such as 56 divided by 8 is 7 and thus can become metal models. They are important in that they empower higher order knowledge, but becoming less vital as we are increasingly supported by technology in the form of calculators, online dictionaries and searchable information. Performance is shown by recall or recognition of sounds, acts, definitions or simple relationships.

Skills

Skills are the standard, well-established procedures to be carried out by the learner when applicable situations are recognised. Performance is demonstrated by carrying out the procedure in front of others or by recording steps in the process.

Mental Models

Mental models are complex and dynamic relationships which can be employed to explain and predict more complex issues and may be based on networks of facts and skills.

My design practice has developed with the fundamental assumption that mental models (Craik 1943Johnson-Laird 1983) are the basis of an individual's knowledge. Facts and skills could be argued to be the simplest mental models, but I prefer to identify them separately and as building blocks.

My belief in the importance of mental models to educational design is based on Donald Norman's view:

In interacting with the environment, with others and with the artefacts of technology, people form internal mental models of themselves and of the things with which they are interacting. These models provide predictive and explanatory power for understanding the interaction.
(Norman 1983a, 7)

I contend that mental models enable explanation, prediction and thus decision-making and action in a much wider sphere than Norman's focus on the interaction with technology. Nevertheless, it is in the practice of developing better user-interfaces in educational software that my journey as a practitioner started.  I found that by extending the concept of mental model to embrace a wide variety of modalities (sensory modes such as sound, vision, touch) and genre (expressive modes, such as narrative, diagram, play or poem), it could provide a basis for understanding learners' knowledge in all its guises.

I accept the constructivist view, that knowledge is created in the mind of the learner by their own mental activity in response to experience and information (Kolb 1984). In my view, at the heart of this is the establishment and improvement of mental models.

Mental models are not only faulty (as they continue to develop through refinement), but also unconscious in the sense that they may be unknown and even their nature unknowable to the person employing them. Nevertheless they may provide effective capability and thus form the basis of tacit knowledge (Polyani 1966).

Observing mental models

I do not believe that it is fruitful, especially for the design practitioner, to spend too long identifying mental models' structural properties nor attempting to use mental models as a basis for formal prediction or explanation. In my view, the biological representation and processing of mental models, in both the network and dynamics of the neural connections in the brain or the phenomenology of the mind, is simply too complex, diverse and subtle. To add further futility (or utility if this is seen instead as a teaching strategy), the act of discovering mental models, through dialogue with learners, can change the mental model itself. (Rogers et al. 1992).

Further research in this area may be ultimately successful, but is a diversion in terms of my design practice. Clarity about the neural structure of the brain may indicate useful design issues, but often on a different level than that of thinking and learning. I suggest we can only objectively deduce the strengths and limitations of mental models by observing and analysing  human behaviours, verbal utterances and written or graphic articulations - expressions. This inability to more directly observe mental models does not lead me to reject mentalism, the study of mental perception and thought processes, as Skinner might (Hill 1984, 63-87).

Introspection and self-report

Instead, in my design practice I have favoured a more subjective lens for examining mental models through introspection (Kind 2005), the self examination of thoughts and imagination which can support our understanding. This kind of self-report is, I believe, no more or less useful than any other evidence we gain from human behaviour, and clearly needs to be handled with care. Nevertheless, table 3 lists some examples of mental models and distinguishes between mental models (learner's knowledge) and externalised conceptual models (information).

Table 3: Examples of Mental models

Mental modelDescription

Visualisation of a number line

In my own experience, I am aware that I imagine a timeline of numbers when comparing numerical values, which I suggest has grown organically as I have developed numerical understanding. The numbers 1 to 10 are arranged in a semi-circle with a slightly tighter bend after 5. Another sharp bend between 10 and 12 leads to a gentle spiral from there until 30 after which an even more gentle curve leads to 100. After 100 a final line, almost straight, leads to 1000 and beyond. Other numerical contexts such as temperature, time and calendar dates, offer other shapes to the line and with significance perceived at key points by bends - 32 degrees Fahrenheit, 100 degrees centigrade, 0 degrees Kelvin, breakfast, tea-time, midnight,  December 31st/January 1st, the centuries....

These mental models help me to estimate values and relate numerical symbols to real-world phenomena and decision making. If I attempt to draw this model on paper, as a conceptual model, it soon fails, since the mental perception often defies three-dimensional space, showing and revealing features dynamically as needed.

Arithmetical facts, e.g. 7 x 8 = 56, 56 ÷ 8 = 7 and
56 ÷ 7 = 8

These three number facts are combined as part of a bigger mental model for me - someone who was successful at memorising multiplication tables from an early age. An external representation would be in the form of a concept map relating the three numbers 7, 8 and 56 as nodes with directional arcs labelled with the relevant mathematical operations. The full model takes in all the factors up to 12 - in my day you learnt up to the 12 times table - and some other exceptional numbers beyond. A relationship with other number facts ( 70 x 80 = 5600) where other rules and patterns extend the basic multiplication table. I have no idea how this material is actually formulated in my mental model, it is recalled unconsciously, but I believe it is both parsimonious and effective for me because of its cross connections. The mental model helps me both predict and explain arithmetical results, estimate calculations and solve numerical problems.

Externalised conceptual models which are often drawn include number squares, but the graphics do not make clear all the patterns and connections held in a complete mental model.

The effect of flattery

This complex mental model helps with other people's reaction to my behaviour. Through it I can predict how well received a comment about someone's performance, appearance or feelings might be, and thus choose my words carefully to achieve the effect I desire. It can go wrong and has often lead to doubt about my ability to make these judgements. It can be effective in forecasting behaviour or just as often, dissecting the reasons for upset. It is symptomatic of autism that this kind of modelling is poor.

Externalised conceptual models for this can be found as narrative in literature, plays or films.

Catching and throwing a ball

The capacity to predict where a ball will be, and at what time, after being thrown by a distant person is good example of unconscious, and quite likely unknowable, mental model. Its converse and, I suggest, closely related mental model is that of throwing a ball to arrive at a particular place at a particular time.

Externalised conceptual models for this capability are rare and these capabilities often remain tacit knowledge.

The Bohr model of the atom

Unlike the previous example, which was primarily about prediction, this is a mental model primarily for chemical explanation. It is a picture of orbiting electrons imagined as moons around an 'earth' which represents the atomic nucleus of protons and neutrons. It can be extended to imagine more complex orbital patterns and rules for the number of electrons at each level. Limited predictions can then be made to imagine new elements and chemical bonds between atoms. This articulation does not mean that this is exactly how the mental model is formed in the mind, but the gravitational and geometrical parallels to actual atomic forces provide a visual and visceral way to know about atomic particles, although incomplete and a fiction!

An externalised conceptual model in the form of a diagram (or animated film) can be drawn - this can become a shared articulation helping to develop and align each individual's mental model.

How do I get to the station?

On many occasions, I have travelled from a railway station to a conference venue. My ability to return to the station is based on the mental model built on the journey, which in my case is considerably richer than a turn-by-turn account of street corners. The model is used to make decisions and affords flexibility, rather than simply followed by inverting the turns made on arrival.

Its representation as an externalised conceptual model might be a map, but this only captures part of a more complex 3D visualisation and relationship with a body-centred decision making procedure.

These examples are important to me in my practice because they differentiate between the idea of mental model and that of externalised conceptual model. The latter is a shared articulation of knowledge, often in oral, written or diagrammatic form (including a map) which tries to capture the essence of mental models so as to communicate knowledge.

Problem solving strategies

This form of knowledge is the basis of analysis and creativity and may involve the application of mental models. I argue that the key capabilities are those of recognition, open-mindedness, backtracking and re-formulation. My own work in this area resulted in a published paper to identify the steps that the learner would need to undertake to formulate computer models (Millwood and Stevens 1990), based on the experience gained in formulating the Modus project to design modelling software:

  • identifying a purpose;
  • having concern for presentation and communication;
  • constructing an interactive simulation;
  • picturing the end-product;
  • dentifying elements;
  • characterising elements;
  • identifying relationships and
  • characterising relationships.

Attitudes to learning

Learning attitudes are often the 'soft' and unrecognised aspects of knowledge in the learner, and not tested directly through summative assessment. I would argue that attitudes to be developed include determination, motivation, love of subject and a concern for quality and detail. Successful learners may also be patient, optimistic and persevering (Seligman 1998). A substantial development in my thinking in relation to attitudes to learning, inspired by collaboration with Stephen Heppell, was the concept of delight. The challenge to script and present a Teacher's TV programme, Happiest Days? (Millwood 2006), was the starting point for my own delight framework An Analysis of Delight (Millwood 2008) based on John Heron's work (Heron 1992), which I designed to explain and justify design choices in technology-enhanced education. This framework is outlined in the Methodology section on Values driving the research.

Summary

This view of the learner and the range of types of their knowledge helps me as a designer to identify how technology enhanced educational innovations can support learning and offer a critical framework within which improvement to designs can be made based on a static understanding of what is to be learned  - the curriculum. But the dynamic processes of learning, as described by learning theorists in the next section - The Challenge of Learning Theory, provide such a rich and diverse picture, that to be pragmatic in my design practice I began to seek a simple model that provided sufficent detail to inspire and justify design decisions.

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    The challenge of Learning Theory

    For the designer, understanding the learner through learning theories can lead to a rich, diverse and contested quagmire, where the differences between concept, theory and paradigm are not well explained nor observed. This section sets out that complexity in order to understand the motivation to construct a simple model.

    Learning Theory.png

    Figure 5: Learning Theory

    This concept diagram (Figure 5) and notes below are taken from the work I undertook to complete an overview of learning theory for the EU-funded HoTEL project in 2013, intended to help technology enhanced learning innovators untrained in educational theory to make better sense of theory in order to improve their designs and the impact of their innovations.

    "Learning theory has been a contested scientific field for most of its history, with conflicting contributions from many scientific disciplines, practice and policy positions. With the continuing and disruptive influence of technology on information, knowledge and practice in all sectors of society it is no wonder that innovators, drawn to the interactive potential that computers bring to learning, are challenged by the theoretical basis for their innovations.

    Formal education is also a high stakes, culturally & institutionally conservative activity, which serves more than one societal purpose, including:
    • learner development and fulfilment;
    • child care;
    • preparation for citizenship, parenthood and retirement;
    • preparation for work;
    • selection for jobs.
    Even in the higher, informal and professional sectors of education, complexity of education is matched by complexity of learning outcomes which may include:
    • skills development;
    • knowledge acquisition;
    • improvement in strategic, analytic and creative capacities;
    • attainment of competence;
    • establishment of attitudes and values.
    Each of these societal purposes and these learning outcomes demand different approaches and understandings for the theorist and may develop at varying rates or found to be diverse in relation to context, location and culture."
    Millwood (2013)

    In these circumstances, I as a designer have had to create a theoretical position which draws from the best, yet can provide a more straightforward basis for design decision-making - this position is set out in the Claim

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    Technology

    Technology as an augmentation of human performance has been central to my design practice - for creativity, communication and content. I have been a strong advocate of Owers' ideas (2001) regarding the evolutionary symbiosis of technology and humankind, which provides a context for justifying educational design with technology.

    Technology in education is often positioned as its servant, a tool to help achieve pedagogic ends already determined without technology. Although there is merit to be driven by educational needs when employing any resource, this position can be questioned in the light of technology's relationship with humankind more generally. As Stan Owers pointed out in his PhD study:

    The literature research confirmed that technology is as old as humankind. The foundations of technology resides in our imaginative capabilities as toolmakers. Humankind has always used tools, and recently technologies, as extensions of itself. Tools and technological evolution have been constant companions to the evolution of humankind.
    (Owers 2001, abstract)

    Owers' point of view, that technology extends humankind and has been a constant companion in evolution, suggest that we look for extension to education through technology, not simple service to education. Educational software has the capacity to support new pedagogies, and this has been recognised since the 1970's as evident in the analysis offered by McDonald et al, as tabulated by me in table 6 (Millwood 1987), to identify the computer's potential contribution through three paradigms: instructional, revelatory and conjectural.

    Table 6: Educational Paradigms for Computer Assisted Learning

    INSTRUCTIONAL

    REVELATORY

    CONJECTURAL

    Key concept:

    Mastery of content.

    Articulation and manipulation of ideas and hypothesis-testing.

    Discovery, intuition, getting a 'feel' for ideas in the field etc.

    Curriculum emphasis:

    Subject matter as the object of learning.

    Understanding, 'active' knowledge.

    The student as the subject of education.

    Educational means:

    Rationalisation of instruction, especially in terms of sequencing presentation and feedback reinforcement.

    Manipulation of student inputs, finding metaphors and model building.

    Provison of opportunities for discovery and vicarious experience.

    Role of computer:

    Presentation of content, task prescription, student motivation through fast feedback.

    Manipulable space/field/'scratch pad'/language, for creating or articulating models, programs, plans or conceptual structures.

    Simulation or information handling.

    Assumptions:

    Conventional body of subject matter with articulated structure; articulated hierarchy of tasks, behaviouristic learning theory.

    Problem-oriented theory of knowledge, general cognitive theory.

    (hidden) model of significant concepts and knowledge structure; theory of learning by discovery.

    Idealisation / Caricature:

    At best, the computer is seen as a patient tutor; at worst it is seen as a page turner.

    At best, the computer is seen as a tool or educational medium (in the sense of milieu, not communications medium); at worst, as an expensive toy.

    At best, the computer is seen as creating a rich learning environment; at worst, it makes a 'black box' of the significant learnings.

    McDonald et al also propose a fourth paradigm, the emancipatory paradigm, in which the key concept is the reduction of inauthentic labour, but this does not occur in isolation to the three paradigms initially defined, since each reduces such labour to some extent.

    This analysis was hugely influential in the 1980s, often cited by students exploring the possibilities of technology, but as time passed and new capabilities of the technology available were developed, I found the need to clarify the potential contribution made by technology in learning as set out in the next section.

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    Education

    The concept of education is here concerned with the aims, objectives & values, the organisations, processes & culture of the instruments & institutions that society has formulated to address the its needs to educate lifelong learners. The ideas of Hargreaves concerning the interpersonal, Deming regarding the pursuit of quality and the cybernetics systems theory from Beer and Ashby have been influential.

    Teacher and Learner

    In the early years of my design practice, I focussed on learning in the microcosm of the individual learner. Even within this context, my attention was on the use of the computer rather than the wider process of education signified by the classroom. When first registering for PhD in 1986, I was invited to produce a qualifying essay (Millwood 1987) which I based on teacher types identified by Hargeaves (1975).

    Table 7: Hargreaves' teacher types

    This diversity of aims, objectives and values devised by Hargreaves was new for me, not only as a perspective on education but in how the design of technology enhancements might take account of the context of use and indeed support the aims of such de-schoolers as Illich (1970) and Holt (1976). In my essay (Millwood 1987) I made a connection between the paradigms for computer assisted learning and Hargreave's teacher types that helped me understand why teachers might propose designs in different ways according to the predominant teacher type in their practice.

    Educational quality and improvement

    In producing the CD-ROM for the 'Business of Quality' ( [C6] The Renaissance Project ), an interactive multimedia account of Deming's theories for improvement in manufacturing and business (Deming 1982), I learnt about the notion of quality and how it can be monitored. What came as a revelation was the idea that customers should be delighted, not simply satisfied in order to succeed in competition with other companies. I found these ideas transformative in my own thinking about educational institutions and their improvement, and connected to the social sciences notion of an action research approach with the plan–do–check–adjust cycle. It gave foundation to my later work to design education organisations to be profoundly learner centred ( [C11] TeacherNet UK[C18] Ultraversity Project ).

    Educational community and variety

    The development of educational organisations online presented many new challenges to the designer, and tacitly these were solved by encouraging online learning community to develop where peers expected to learn from each other as well as from content, experts or tutors. This thinking became clearer when contrasting the [C18] Ultraversity Project and the [C20] Inter-Disciplinary Inquiry-Based Learning (IDIBL) project. The first was considered highly successful and the second struggled to make headway. By applying the concept of 'variety' in the context of Cybernetics (Beer 1985Ashby 1956), it was clear that the successful design benefitted from the absorption of variety in student states by inviting them to build relationships of mutual respect and support with each other. This meant that the facilitation team, tasked with leading the community, were able to manage the variety that remained without being swamped with diverse questions and problems (Millwood and Powell 2011).

    Educational design

    In my practice, applying the ideas of design to education was initially tacit in nature, but later influenced by the explicit principles developed by theorists such as Gagné (1985). These are based on an analysis of instructional events (and corresponding cognitive processes):

    1. gaining attention (reception)
    2. informing learners of the objective (expectancy)
    3. stimulating recall of prior learning (retrieval)
    4. presenting the stimulus (selective perception)
    5. providing learning guidance (semantic encoding)
    6. eliciting performance (responding)
    7. providing feedback (reinforcement)
    8. assessing performance (retrieval)
    9. enhancing retention and transfer (generalization).

    But these events are focussed on what the teacher should do, with the assumption of a Hargreaves 'lion tamer' or 'entertainer' style. It also focusses on the lesson, rather than the complete scope of educational experience for the learner. This led me to analyse education from the perspective of the learner, which is the subject of the Claim.

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    “Thus, the task is not so much to see what no one yet has seen, but to think what nobody yet has thought about that which everybody sees.”
    ― Arthur Schopenhauer