Teacher Perspectives on Pedagogical Modelling And

Teacher perspectives on pedagogical modelling and

explaining in Design & Technology: a Q Methodology

Study

Matt McLain

Liverpool John Moores University

David Barlex

Educational Consultant

Dawne Bell

Edge Hill University

Alison Hardy

Nottingham Trent University

Abstract

The demonstration has been a long-standing signature pedagogy and teaching style in design and technology, its

precursors and practical education as a whole. However, the body of literature outlining the theory and practice of

teacher modelling and explanation within the 'field' is somewhat limited. As a practical and creative subject, with a

complex epistemology, engaging learning objectives from within the cognitive, affective and psychomotor domains, the

modelling of designing and making tools encompasses the interaction between thought and action. Therefore, the

authors assert that, the 'demonstration' in D&T is multifaceted and effective teachers adopt and adapt a range of skills

and values to scaffold learning. The aim of this study is to investigate the subjective values of practicing teachers towards

the demonstration of design and technology knowledge and skills. Q Methodology is used to compare and analyse the

responses of the participating teachers, to investigate shared ad contrasting values. A Q Set of statements, developed

and refined with D&T teacher educators, relating to modelling and explaining, representing the concourse of opinions

and perspectives. The sample is purposive, comprised of practicing teachers who are engaged with mentoring D&T Initial

Teacher Education (ITE) trainees. The findings will represent a snapshot of subjective values of practicing teachers, as part

of a wider, and developing, discourse on signature pedagogies in design and technology education.

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Introduction

"When education… fails to recognize that primary or initial subject matter always exists as

matter of an active doing, involving the use of the body and the handling of material, the

subject matter of instruction is isolated from the needs and purposes of the learner...

Recognition of the natural course of development, on the contrary, always sets out with

situations which involve learning byd'oint." (Dewey, 1916, p. 178)

We take from this that the demonstration is an essential first step in learning by doing. As a

practical and creative subject, the demonstration has been a staple of the design and technology

teachers’ repertoire for the past two to three decades since the introduction of the subject within the

National Curriculum for England in the 1990s (DFE, 2013; QCA, 2007; QCA, 2004; DfEE, 1999; DFE,

1995; NCC, 1990). This paper is an initial exploration of the pedagogy of demonstrations in design and

technology, as what the authors view as an under investigated area. The aim was to facilitate a dialogue

on effective pedagogy within the design and technology educator community, and as a pilot study in

which to begin to develop a framework for teaching and learning.

The demonstration is seen as important in science (Milne and Otieno, 2007) and physical

education (Mosston and Ashworth, 2002) building on the traditions of apprenticeship and craft education

of “demonstration, observation and constant practice” (Mason and Houghton in Sayer et al, 2002, p. 44).

And Petrina comments on the significance of demonstrations for technology education: “Demonstrations

are the single most effective method for technology teachers” (Petrina, 2007, p. 1).

Literature review

The demonstration: signature pedagogy for design & technology?

With this in mind, it is an anomaly to find a virtual absence written about the praxis (theory and

practice) of demonstrating in the subject. One might speculate that this may be because it is considered

to be such an elementary skill or it is considered such a tacit skill learnt in initial teacher training;

working alongside and mimicking experienced teachers in schools, colleges and universities in a diffuse

community of practice (Wenger in Illieris, 2009; Duguid, 2008; McLain, 2012; Lave and Wenger, 1991).

However, it may be that the act of demonstrating is a multifaceted skill, comprised of layers of

explanation, modelling and other established pedagogical techniques and from this perspective has

received little specific attention in literature. If true, the act of demonstration needs to be analysed to

reveal the complexity within the tacit skill view. If design and technology pedagogy is to stand distinct

from context-based, situated cognition, and identify theoretical, practical and portable, endogenous skills

shared and understood by the wider community of teachers, then conceptual frameworks and typologies

need to be discussed and debated (Sennett, 2009; Kimbell and Stables, 2007; Petrina, 2000).

Before we look at the elements the make an effective demonstration, it is appropriate to define

what we mean by ‘demonstration’. We begin with an assumption that a demonstration includes a

combination of teacher modelling, explanation and other pedagogical skills such as questioning, each of

which do not define demonstration, in themselves, but are pedagogical strategies that a teacher of design

and technology employs when demonstrating. The National Strategies Pedagogy and Practice, an

initiative to develop the teaching workforce within state schools in England in the mid-2000s, gave the

following definitions:

“Modelling is an active process, not merely the provision of an example. It involves the

teacher as the ‘expert’, demonstrating how to do something and making explicit the

thinking involved.” (DfES, 2004a, p. 3)

“Whether helping learners to acquire basic skills or a better understanding to solve

problems, or to engage in higher-order thinking such as evaluation, questions are crucial.”

(DfES, 2004b, p. 2)

“The purpose of explaining a process or procedure is to help pupils understand how things

happen or work. The emphasis is on sequence and connectives such as first, next, then and

finally are important. (DfES, 2004c, p. 3)

It is also important to note that the skills demonstrated in design and technology cover a wide

range of domains, from the manipulation of physical tools and materials (making), to virtual tools

(software, including computer-aided manufacture) and cognitive tools (design thinking and problem

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solving). Each of these skill domains has similar features as well as distinctive differences relating to the

learner, context, equipment and materials.

The planning of effective demonstrations

If the demonstration is, as we have suggested, a complex activity involving a range of skills, some

of which are conscious and deliberate, other that are subconscious, intuitive and automatic (Wood, Rust

and Horne, 2009; Race, 2007, pp. 17-20; McCormack, 1997; Luft, 1982), then it is essential that in the

design and technology education community we understand and name our practice. It is important, in

particular for training, newly and recently qualified teachers, to plan each demonstration, visualising and

rehearsing the key steps and processes. Where the pedagogical and practical skills are tacit and the

teacher is able to focus on learners and learning - somewhat analogous to driving a car – but to reflect on

practice and make and evidence-based improvements a degree of consciousness of practice is necessary

(Banks et al, 2004; Jay and Johnson, 2002).

The precise format and structure of each demonstration will differ according to the content and the

learners, as there is no one “universal sequence” but there are several common components (Figure 1;

Petrina, 2007, p. 14) where health and safety and safe working practices are embedded throughout the

process. These could also be synthesised into four elements, or 4Cs: coverage, context, content, and

conclusion (McLain, Bell and Pratt, 2013).

Figure 1. Common components of a demonstration (Petrina, 2007, p. 14)

1. Introduction (What will be demonstrated?)

2. Relevance (Why demonstrate this?) (Use Questions, Story, Description, etc.)

3. Use of application, instrument, machine, process, or tool (How to effectively and safely

do or use this?) (Actual execution of proposed process)

4. Conclusion (Recap-Summarize, What was covered-Where to go next?)

Visual communication in demonstrations

“First and foremost, the goal of a demonstration is to communicate and model how to do

something and how to talk about the task or technology at hand... The demonstrator must

demystify the tool or process, explaining what is to be accomplished, what knowledge is

applied and the roles of certain skills and senses.” (Petrina, 2007, p. 14)

It is commonly accepted that a significant proportion of human communication is non-verbal, and

for millennia mankind, and our hominid ancestors, have used symbols, signs and actions to

communicate (Engeström, 2009; Vygotsky, 1934/1986, 1978, cited in Tappan, 1997; Wertsch, 1985,

1991, cited in Tappan, 1997).

Visual processing, and interpretation, is sophisticated with the mind constructing and

reconstructing what we see into something that we can understand. That being said, individuals perceive

and understand in different ways from differing perspectives (physical and cognitive), so the effective

demonstrator should consider the important aspects of the activity that the observers need to see. To

quote Barlex and Carré (1985), “We do not see things as they are, we see them as we are” (p.4). A

maxim for effective visual communication might be: make sure that the learners can see what you can

see, where at all possible. There are several ways in which this can be achieved through arranging the

learning environment to using technology, such as the use of a video camera and screen. The complexity

and intricacy of the skills being demonstrated; as well as the novelty or familiarity of the activity to the

learners affect pedagogical choices. A simple approach to overcome an issue of visibility may be to

gather learners around as close as possible to the demonstration station as practicable. Two factors to

consider in opposition to this are: (a) the potential disruption of learners being in close quarters and (b)

the configuration of the teaching environment, including resources and equipment.

Verbal communication in demonstrations

“The necessity of a demonstration derives from the inadequacy of words [alone] to depict

technological processes.” (Petrina, 2007, p. 14; addition/emphasis ours)

With our adaption of Petrina’s statement to “… the inadequacy of words [alone]…” and the

demonstration treated as a complex and holistic interaction between the teacher and the learner, the use

of verbal communication can make or break a demonstration. When explaining a process, it is important

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that the critical stages or steps are identified and presented effectively using age-appropriate as well as

technical language. Pedagogical choices, made by the teacher, fall along an expansive-restrictive

continuum (Fuller and Unwin, 2003), when planning and differentiating explanations and questioning

strategies. In other words, the skillful teacher will tailor depth of knowledge and skill being demonstrated

to suit the learner, adjusting the balance and detail of modelling, explanation and questioning. In some

circumstances, for example with younger learners or with new concepts, the choice might be to adopt a

more restrictive and teacher led approach, with questions being used to gauge recall and understanding.

On the other hand, as learners become more independent and extend their knowledge and

understanding or when revisiting concepts, a more expansive approach might be adopted. For example,

questions may be used to prompt recall, probe understanding during the demonstration or encourage

speculation. As the learners become more skilful, the teacher may chose to use learner demonstrations or

narrations, or microteaching (Hattie, 2009, pp. 112-113). These approaches to the scaffolding of learning

involve the teacher making decisions to support and facilitate learners as they mentally construct an

understanding of the skills being demonstrated. Illustrating the complexity of choices that are

underpinned by the pedagogical knowledge and skill of the teacher, involving interplay between subject

and pedagogical knowledge.

Research method

The research question for this study was: What do teachers of design and technology believe to be

effective pedagogy when demonstrating skills and knowledge?

The overarching philosophical and conceptual framework for this investigation is pragmatic and

constructionist in the traditions of Dewey, Pierce and James (Watts and Stenner, 2012: 24-46). The

research paradigm is ontologically relativist, recognising the subjective nature of realities for individuals,

which are multiple (Guba, 1990, pp. 17-27; Guba, 1981, p. 77). As a Q Methodology study (Watts and

Stenner, 2012), the focus is on subjectivity (“mind-stuff”) and the individual in relation to the objectivity

of teaching and learning practice (“world-stuff”) (p. 29). In this aspect the intentions of the Q Method are

interpretive and qualitative, using Peirce’s “abduction”, where observation of facts are used “in pursuit of

an explanation and new insight” (p. 39).

Working within a social constructivist framework, the epistemological position adopted in this

paper is subjectivist, recognising the role of the researchers as a co-constructers of theory and knowledge

with the participants, or actors, in the study. However, the research perspective adopted is that human

beings’ perceptions of reality are socially and culturally constructed, but that this does not necessarily

mean that concepts such as truth and reality do not exist. Thus taking a pragmatic approach that does not

deny objective truth or reality, but acknowledges that we perceive and share conceptual constructs. As a

speculative ontology there are similarities with the critical realist ontological positions of post-positivist

or critical theory (Guba, 1990, p 20-25), although the pragmatic and working ontological position to

adopted in this study is that of relativism, in that the concern is with perception and experience or

realities (Guba, 1981, p. 77).

Figure 2. Q Sort distribution

Q Methodology originates from psychology research and “focuses on subjective or first person

viewpoints” (Watts and Stenner, 2012, p. 4). As such it does not purport to generate or confirm

generalizable concepts and principles. With its roots in pragmatism, it draws on inductive and abductive

reasoning with the support of mathematical modelling (factor analysis) to explore qualitative data

through quantitative methods. In Q Methodology the comparison focuses on the similarities and

differences between the participants, rather than their responses as is common within tradition factor

analysis. A series of statements, or Q Set, that represents the broad range of opinion or belief (concourse)

potentially held by the population that the sample is being drawn from. The participants then undertake a

Q Sort activity. This is typically a two stage process involving a pre-sort into three categories (essential,

desirable and optional, in this study), followed by the main sort where the Q Set statements are sorted into a

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forced-choice frequency distribution (Figure 2; p.16-17) ranging from most agree to most disagree (note: the

statements in this study were not designed to generate disagreement, so the ‘most disagree is relative).

The initial Q Set was developed through a focus group of six design and technology mentors,

working with initial teacher education trainees in the North West of England, and refined by the authors

through a teacher educator email discussion group. The list was divided into 10 categories to aid the

presentation and interpretation of the 62 statements (Appendix).

Seven teachers from a range of backgrounds and design and technology disciplines, and not part

of the focus group (above), completed the online Q Set. The stated design and technology specialisms of

each of the participants ranged from electronics and control (n=1), engineering (n=1), graphic design

(n=2), product design (n=2) and textiles and fashion (n=1); each having links with the initial teacher

education (ITE) institutions represented by the research team, as an ex-trainee and/or mentor for trainee

teachers. Five of the participants are currently involved with initial teacher training (ITT) with

management responsibilities that involve working both within and outside of their place of employment;

Participant 4 and 7 being Recently Qualified Teachers (RQTs).

The Q Sort for this study was conducted using an online questionnaire tool, QSortWare

(Pruneddu, 2014), to enable wider participation across institutions. The population for the study was

experienced teachers of design and technology engaged with the mentoring of ITE trainees and with links

to members of the institutions that the research team represent; with the sample being purposive (Guba,

1981). The factor analysis for data analysis was conducted using the PQMethod (Schmolck, 2014) software.

Findings and interpretation

As a study in the subjective beliefs, values and practice the small sample size does not pose a

problem (Watts and Stenner, 2012, p. 73), as the findings are not being used to infer generalizable

theoretical principles. Rather to explore existing practice with the view to refine the Q Set of 62

statements (Appendix) relating to modelling and explaining within the subject. Use with a larger sample

would then be appropriate and perhaps be able to be used to establish a recognised orthodoxy with

regard to demonstrations in design and technology.

Figure 3. Correlation matrix between Q Sorts (n=7)

1 2 3 4 5 6 7

1 100 44 25 20 -3 16 16

2 100 21 17 -1 11 42

3 100 17 0 12 24

4 100 6 8 28

5 100 -2 9

6 100 -3

7 100

The initial correlations between Q Sorts (Figure 3) from the PQMethod software (Schmolck, 2014)

indicate a superficial correlation between the participants ranging from 44 (Participants 1 and 2) to -1

(Participants 1 and 5), with Participant 5 showing the lowest correlation to the overall. This reinforces the

perception that the nature of teaching and learning is complex, with no ‘one size fits all’ approach.

Figure 4. Factor Matrix with X indicating defining sort (n=7)

Factor Loadings

Q Sorts Factor 1

Participant 1 0.65 X

Participant 2 0.58 X

Participant 3 0.40 X

Participant 4 0.38 X

Participant 5 0.03

Participant 6 0.16

Participant 7 0.64 X

Eigenvalues 1.51

Variance 21%

PQMethod was used to extract factors (Figure 4) and reduce the data, with the Eigenvalues (EV), or

Kaiser-Guttmann criterion, above 1.00 used to indicate the statistical strength (Watts and Stenner, 2012,

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p. 105). Watts and Stenner advise that Q Methodology researcher try to extract one factor for every 6 to 8

participants (p. 107). In this study, with only seven participants, two factors were extracted, but only the

EV for Factor 1 (1.51) indicating potential explanatory power (i.e. >1.00) and the presence of a single

common factor in the study – i.e. Factor 2 was discounted as insignificant.

The factors are the rankings of items (Q Set statements) in comparison to the participants, with the

items being treated as the sample rather than the participants. These factors are the building blocks of the