Developing perspectives on ‘the demonstration’ as a signature pedagogy in design and technology education

The term signature pedagogy was first used by Shulman (2005) to describe the “types of teaching that organise the fundamental ways in which future practitioners are educated” (p. 52). Originally developed from the study of professional preparation, Shulman identified three fundamental dimensions of professional work—thinking, performing and acting with integrity—that receive varying weight across the professions. A signature pedagogy has a ‘surface’ structure consisting of pedagogical activities, such as a demonstration or design and make in D&T. It also has a ‘deep’ structure that relates to bodies of knowledge and an ‘implicit’ structure comprised of the attitudes, values and dispositions. Despite the apparent distinctiveness of signature pedagogies between one discipline and another, Shulman points out that they may share common features; and the tried and tested principles identified as (domain specific) signature pedagogies may explain the effectiveness of these approaches over time. For example, the demonstration in D&T may share similar features to direct instruction in other subjects, such as science (Milne and Otieno 2007) and physical education (Mosston and Ashworth 2002), as well as general descriptions from educational psychology (Martin 2016).

In a small-scale pilot study of seven teachers, McLain (2017) identified a variety of views on demonstration, which drew on general (pedagogic) and subject-specific (didactic) teacher knowledge. In response to the research question regarding teachers’ beliefs about effective practice, the participants ranked competent subject knowledge as important—a commonly held view in education (e.g. DfE 2010, 2011; Shulman 1986)—underpinned by pedagogical knowledge and classroom management (McLain 2017).

The study correlated with Petrina’s (2007) common components of a demonstration; in particular to the relevance and application of practical knowledge, which rely on the specialist knowledge of the teacher. However, Hattie (2009) cautions that without empathy for learners and verbal ability, subject knowledge alone potential limits the effectiveness of teaching to a “level of basic competence” (pp. 113–114)—both of which were implied in participants’ responses in the pilot study. Therefore, it is important to see demonstration in a wider pedagogical context, requiring a complex interplay between subject and teacher knowledge—knowledge for teaching. The relationship and hierarchy of the teachers’ beliefs was represented graphically (Fig. 1), indicating a higher value placed on restrictive (teacher led and focused on the development of specific knowledge and practice) over expansive (learner led and open-end activity with multiple potential outcomes) approaches, based on Fuller and Unwin’s (2003) work on learning environments.

The restrictive–expansive framework, proposed by Fuller and Unwin, may be a useful tool for the D&T community to consider when considering the intentions of a particular demonstration—or, indeed, when selecting pedagogical approaches in general. For example, a restrictive demonstration might focus on specific procedures that must be correctly followed to achieve a successful outcome, which would tend to result in learners’ made outcomes appearing similar. Whereas, an expansive approach would provide stimulus for open-ended, design-oriented activity, leading to a range of outcomes. The responses to the pilot study indicated that participant views on demonstration favoured statements on the restrictive end of the continuum (i.e. competence with subject knowledge and skilful classroom management), rather than the expansive (i.e. consolidation of learning and facilitating of independence). Therefore, the demonstration alone may not be the most effective approach when the intention of teaching is to facilitate creativity and individual learner outcomes. Research from cognitive science, discussed below, supports the idea that direct instruction benefits some learners, particularly when learning new knowledge (Rowe 2006; Reynolds et al. 2014), whereas McLellan and Nicholl (2011) caution against restrictive approaches negatively influencing design thinking and creativity.

The popular taxonomy of educational objectives introduced by Bloom et al. (1956) identified three domains of learning: cognitive, affective and psychomotor. Bloom et al. initially defined the first, and most widely recognised, cognitive domain; updated by Andersen and Krathwohl (2001), who were part of the original research team. Krathwohl et al. (1964) later developed the affective domain, which focuses on values and aspects of emotional intelligence. However, the team involved with the original study chose not to define the psychomotor domain. In fact, Simpson quotes Bloom as having found “so little done about [the psychomotor domain]”, and “[did] not believe the development of a classification of these objectives would be very useful” at the time (Simpson 1972, p. 2, in Bloom et al. 1956, pp. 7–8). Simpson drew from expertise in practical subjects to describe a psychomotor domain (Table 1). The first four stages of Simpson’s domain (perception to mechanism), align well with the definition of the demonstration, as outlined above. Dave (1967) had described a similar progression of skill to Simpson up to the level of mastery, with Dave’s ‘naturalisation’ somewhat akin to Simpsons ‘complex overt response’ (Table 1).

Several other researchers have also sought to define the psychomotor domain (e.g. Harrow 1972) and redefine or update Blooms original work (Marranzo and Kendell 2007; Andersen and Krathwohl 2001). Marranzo and Kendell organise knowledge into three categories: information, mental procedures and psychomotor procedures, stating that all subject areas “can be described in terms of how much of these three types of knowledge” (p. 23) they are comprised of. They state that there is little specific psychomotor knowledge in geography, for example, whereas there is significant information and mental knowledge. Conversely, the D&T curriculum could be argued to have relatively limited information (conceptual knowledge) that is solely its own. In England, for example, the National Curriculum programme of study (DfE 2013) and the General Certificate of Secondary Education (GCSE) (DfE 2015) subject content both refer to the application of knowledge from other disciplines, including computing, mathematics and science. Commenting on knowledge in D&T, McCormick (1997) discusses the important and inextricable relationship between conceptual and procedural knowledge. Whilst “technology is geared to action” (p. 143), or the application of procedural knowledge, there is also an essential conceptual component. In other words, there may be distinct mental and psychomotor process in D&T activities, such as designing and making, the two work hand in hand. Marranzo and Kendell propose that mental and psychomotor procedures follow similar patterns. Thus questioning the appropriateness of treating cognitive and psychomotor learning as inhabiting separate domains. However, the cognitive domain developed by Bloom differs from Dave and Simpsons approach, which recognise the role of the learner in observation and imitation. Furthermore, language utilised in these psychomotor domains is knowledge for (and of) action (Kimbell 2018; Kimbell et al. 1996), the pedagogy of transformation (Morrison-Love 2017) and the value of experience in the curriculum (Biesta 2014).

Whilst there may be value in applying learning objectives from a cognitive domain in practical education, the psychomotor domains may also help D&T teachers to understand the demonstration, within a restrictive–expansive framework. For example, planning a demonstration aiming to develop novice learners’ manipulation of tools or guided responses should differ to one aimed at more experienced learners, where the practical knowledge is naturalised with complex responses (Table 1). Furthermore, Simpson’s adaption and origination require a pedagogical approach that expands rather than restricts learners’ options. An implication is that a more expansive demonstration should focus less on process and more on choices; and for a learner to make confident choices, they should be able to drawn on knowledge developed through prior experience. The following sections explore the theories of cognitive load and social learning, as they apply to the teacher and learners through direct instruction; and how this may apply to pedagogical choices in a restrictive–expansive framework and demonstration in D&T.

Cognitive load theory postulates that novice learners freely exploring “a highly complex environment may generate a heavy working memory load that is detrimental to learning” (Kirschner et al. 2006, p. 80). This being attributed to limited or underdeveloped mental schemas, which are the mental representations of concept constructed by the learner. Kirschner, Sweller and Clark state that direct instruction (DI) enables the teacher to structure and guide learners in a manner that aids recall, transfer, application and problem solving. The implication being that DI should precede more learner-centric methods, such as discovery learning (Mincu 2015; Rowe 2006). Furthermore, Mincu cites Reynolds et al. (2014) stating that constructivist approaches may be less appropriate learners who are younger, low-attaining or low socio-economic status. However, Reynolds et al. discuss this in the context of ‘structured teaching’ that emphasises knowledge and application, rather than DI, and refer to neither constructivism nor discovery learning, as implied by Mincu. DI is well supported by evidence from cognitive science (Kirschner et al. 2006; Rowe 2006) and shares similarities with demonstration as described by Petrina (2007). We will explore similarities later in this section.

Kirschner et al. are critical of what they describe as constructivist approaches, which they characterised with a number of more learner-centric approaches, including discovery learning; baldly stating “students learn so little from a constructivist approach” (2006, p. 79). However, they also adopt ideas more familiar in constructivist approaches, such as scaffolding (Wood et al. 1976). Rowe and Reynolds et al., adopt a less polarised critique, recognising the limitations of discovery learning and emphasising the benefits of DI for certain learners. Sternberg notes “extremes are not useful” (2009, p. xi) in the debate between constructivist and explicit instruction, and that both the teaching of facts and for creativity have their place. Therefore, the consideration of demonstration as either a ‘constructivist’ or ‘not constructivist’ pedagogical approach may be a somewhat redundant exercise. Considering pedagogical choices on restrictive–expansive framework, with DI tending towards the restrictive end of the continuum, the D&T teacher may adopt approaches without the fear of transgressing notional theoretical boundaries.

Effective guidance and examples, as promoted in DI, can avoid learners becoming frustrated or developing misconceptions when learning new concepts or processes. Hattie (2009) ranks DI amongst the most effective teaching approaches, acknowledging the tension with constructivist approaches; clarifying the distinction between “teacher led talking from the front” (p. 204) and DI, as described by Adams and Engelmann (1996).

In a nutshell: the teacher decides the learning intentions and success criteria, makes them transparent to the students, demonstrates them by modelling, evaluates if they understand what they have been told by checking for understanding, and re-telling them what they have told by tying it all together with closure. (Hattie 2009, p. 206)

The pedagogical process of modelling (and explaining), inferred by Hattie, is at the heart of direct instruction; as a planned and intentional activity, evaluated and revisited. In other words, DI is more than a teacher standing in front of the class, engaging in a one-way transfer of knowledge. Kirschner et al. favour DI for cognitive load reduction. However Martin (2016) draws on research from education psychology and adopts a more nuanced approach recognising that a range of approaches along a restrictive–expansive pedagogical continuum should be adopted for Load Reduction Instruction (LRI):

[LRI is] an umbrella term that encompasses instructional models such as direct instruction and explicit instruction – as well as some less structured approaches to instruction (e.g. guided discovery learning) – that seek to optimally manage the cognitive burden on students in order to enhance their learning and achievement. (Martin 2016, p. 5)

Bandura (1977) proposed that learning takes place within social context through observation, imitation and modelling. Social learning theory (SLT) bridges the gap between behavioural and cognitive theories of learning, making a distinction between an observer ‘acquiring’ and ‘performing’ a learnt behaviour, akin to Ryle’s (1949) ‘knowing that’ and ‘knowing how’. In D&T, teacher modelling utilises the social interactions between teacher and learner support increasing autonomy; with the intention that learners both know about (acquire) a process being demonstrated and are able to demonstrate (perform) that they know how to apply the knowledge. This is reflected in the aforementioned psychomotor domains, in Dave’s (1967) imitation to naturalisation and Simpson’s (1972) perception to complex overt response (Table 1); acknowledging the progression from the acquisition of knowledge through to action (performance). Therefore, demonstration that promotes learning and progress should be informed by an understanding of the learners and the learning intentions, in the context of a restrictive–expansive framework.

SLT describes four separate processes involved with observation learning: attention, retention, production and motivation. These are largely internal cognitive processes within the learner and the teacher’s role during and after demonstration is to recognise and accommodate these processes. SLT implies that when planning for and delivering instruction, the teacher must ensure that learners are supported and able to pay attention to the matter in hand, including being able to accurately observe with their interest being aroused. During and after instruction, consideration must be given to learners’ retention, their ability to understand and encode the information to memory, which can be support retrieval practice (Brown et al. 2014). The role of the teacher also includes supporting learners’ reproduction of observational learning with autonomy through structured teaching and feedback (Hattie 2009; Adams and Engelmann 1996). Both the quality of the instruction and subsequent activity learners perform, provide opportunities to motivate learners, and the role of the teacher is to balance internal and external incentives. Internal motivation becomes more important as learners engage with more learner-centred activity. Ultimately, the intention in D&T is motivation to act, typically in design and make activities, which are foundational to the subject (Kimbell et al. 1991).

McLain (2017) explored the implications of social constructivist theories and the role of the teacher as a ‘more knowledgeable other’ (Vygotsky 1978). Cognitive load theories of learning provide a counterargument, raising questions regarding the effectiveness of constructivist approaches (Kirschner et al. 2006). However, this is specifically directed at minimal instruction approaches, such as discovery learning. Others moderate the binary ‘direct instruction good, discovery learning bad’ view, suggesting that evidence indicates that it is more effective to begin with direct instruction and the use of a wide range of pedagogies is desirable (Mincu 2015; Hattie 2009; Rowe 2006). Bandura’s (1977) social learning theory goes some way to bridge the gap between the cognitive load (behaviourist) and the cognitive theories of learning, focusing on the role of observation by the learner; providing an insight into the early stages of a learner’s engagement with new knew knowledge. This aligns with Simpson’s (1972) perception and Dave’s (1967) imitation stages of the psychomotor domain, which rely the learner observing and imitating the teacher (expert). Thus focusing the teacher’s preparation on the learner and learning, alongside subject content knowledge. CLT and DI focus on the structuring of learning by a teacher, to combine subject knowledge with an understanding of how learners learn and the teacher’s ability to articulate said knowledge (i.e. break down and effectively present new or complex processes or ideas). This tripartite view of knowledge for teaching is ranked within the zone of desirable effects in Hattie’s meta-analysis of teacher knowledge (2009, pp. 113–115).

Therefore, the focus on ‘demonstration’ as a signature pedagogy in D&T is on the initial interactions between the learner (as a novice) and the teacher (as an expert); with the act of demonstration being a form of teacher modelling and explanation, concerned with developing new or more advanced practical knowledge. A comparison of Petrina’s (2007) four common components of demonstration with Hattie’s (2009) description of seven major steps involved in DI, reveals similar intentions and actions (Table 2). Furthermore, in the context of design and make activity, DI’s guided and independent practice are inferred in a D&T context, and Petrina clearly links demonstration with practice.

DI and Petrina’s components of demonstration also align with the cognitive apprenticeship framework developed by Collins et al. (1991), who present four dimensions that contribute to the learning environment: content, method, sequence and sociology (p. 12). This framework is more wide-ranging than both DI and demonstration, considering pedagogical method as part of curriculum design. Similar to the findings in McLain (2017; Figure 1), the content dimension considers domain knowledge (‘competence with subject knowledge’) and control strategies (‘effective classroom management’), as well as heuristic and learning strategies. The wider concerns with sequence and sociology focussing on the role of the teacher to plan for learning and progress to support and challenge all learners. The method dimension describes five elements, the first three of which (modelling, coaching and scaffolding) are considered the “core of cognitive apprenticeship” (p. 13), and strongly align with the both Hattie’s DI and Petrina’s demonstration frameworks. Collins, Brown and Holum describe the method dimension as “ways to promote the development of expertise…

The next two elements (reflection and reflection) focus on how learners process their understanding of expert technique, and the last (exploration) on autonomous application, which aligns with latter domains of psychomotor learning described above. In D&T, this is most often expressed through design and making activities.

An interim definition of ‘demonstration’ in D&T, for this study, is that it is a form of teacher modelling and explaining concerned with enabling learners to understand and apply with new knowledge (procedural) in and a practical context. Typically (although not exclusively) in a design and make context, where an ‘expert’ teacher visually and verbally prepares ‘novice’ learners to engage with practical activity. In addition to the procedural knowledge for learners to engage with D&T activity, effective demonstration should also consider aspects of the safe application, wider context and implications of the knowledge in question (Petrina 2007, p. 14). The sections below will outline the research methods and findings, exploring teacher educator perceptions on the nature of demonstration as a signature pedagogy; and what is considered to be effective practice when demonstrating skills and knowledge. A signature pedagogy being an approach to teaching and/or learning, characteristic (or commonly used) within particular discipline that influence how the subject is taught.

The 30 items from the Q-Set where there was consensus between both groups (Table 6) show similar results to the previous study (McLain 2017), with a strong core of statements that align with the competence of the teacher, with regard to D&T subject knowledge (Fig. 1). Alongside subject knowledge, the highest ranked items also emphasise that an effective demonstration relies on pedagogical knowledge (and skill), including the structuring and sequencing of learning (e.g. statement 17), promoting safe practice (e.g. statements 35 and 38), questioning for recall and reinforcement (e.g. statements 26 and 23) and addressing misconceptions (e.g. statement 21). Statements of this nature rank with a + 1 or above Q-Sort Value (Q-SV) for both groups, in the consensus statements (Table 6)—the Z Scores (Z-SCR) are the weighted average of the scores for participants’ responses in each group (factor). There was also a number of the middle to lower ranked items that relate to classroom management, including managing risk, whole class awareness and explicit expectations.

Similar to previous findings (McLain 2017), statements relating consolidation of learning and facilitation of learning were ranked on the negative (most disagree) end of the spectrum. Consolidation appears to rank higher, with a cluster of four statements relating to questioning in the mid-range. Items relating to the autonomy of the learner, such as identifying hazards and risks for themselves, fault finding and reflecting on values, appear lower down the rank order. However, a negative value does not necessarily imply a participant’s disagreement with a statement, rather a relative lower ranking compared to others in the context of the study.

The 32 items from the Q-Set where there was a lack of consensus between both groups (Table 7) shows a similar favouring of statement relating to teacher knowledge in the higher ranked items. However, there is less clustering of statements relating to the other areas. This may indicate that this set of statements may be useful for future studies, with potential to identify groups with more polarised views, and thus potentially groups (factors) with more distinct characteristics.

Two distinct groups of participants with similar trends in their responses emerge from the factor analysis. A summary of the data for each group is presented side-by-side, below, for comparison. Following a brief description of the composition of each group, the analysis of data is organised in five bands, based on their rank order:

Cross-references to statements are indicated in brackets, below, with the statement number 1–62 followed by the ranking within the group, + 6 to − 6. For example, (20:6) indicates the highest ranking for statement 20, “The teacher uses ICT to simulate or model process or products”, whereas (7:− 1) indicates a moderately low ranking for statement 7, “The teacher demonstrates skills and knowledge that learners will apply within the lesson”.

Group 1 was comprised of 6 teacher educators, 4 of whom were male and 2 female, with two identifying their main specialism as electronics and control, one as graphic design, one as textiles and fashion, and two did not identify a specialism.

Group 2 was comprised of 4 teacher educators, all of who were female, with 2 identifying their main specialism as product design, one as graphic design and one as textiles and fashion.

Group 1 appear to value a planned and structured demonstration, with the responses indicating a focus on the learning outcomes (5:5), identification of the main points or steps (17:5) and use of clear models or examples (13:5) of processes and procedures, underpinned by clear verbal explanations (11:6).

Group 2 also value a planned and structured learning experience, where the knowledge is broken down into its components parts (17:5), modelling and explaining a process in one demonstration (9:6), supported by ICT to stimulate or support understanding of a process or product (20:6). This group also highlight the use of other adults in the classroom to support learners (34:5), and ability to modify their tone in response to different groups and situations (49:5); ranking of statements with a learner focus at a higher level than Group 1. Hence, the more facilitative characterisation of this group.

Whilst Groups 1 and 2 appear to hold largely similar views (Table 8), the highest ranked items in the sort begin to suggest their overarching themes and characteristics. Both value planning and the role of the teacher to break down complex knowledge, whilst the focus of Group 1 appears to be on aspects relating to the transmission of content knowledge and teacher-centric approaches, whereas Group 2 focus on personalised and learner-centric approaches.

Continuing to focus on the higher ranked items (Table 9), a holistic focus emerges in Group 1, beginning with the teacher providing an overview of the skills or knowledge being demonstrated (1:4), in common with the other group, making links to learning and made clear through expectations of outcomes (60:4), what learners need to do (59:3) and the teachers role to enable them (62:3) to make progress. In contrast with the other group, Group 1 consider the didactics of breaking down more complex processes in separate, staged demonstrations (8:4), and the use of technical language and terminology (2:4) to be important, alongside demonstrating knowledge and skill in the context of the lesson in which it will be applied (7:2).

The common ground between Groups 1 and 2 are in relation to the importance of learning objectives (statement 4) and outcomes (statement 60), identification of hazards and risks (statement 35) and previewing content of a demonstration (statement 1). Similar themes also emerge through other statements, including preparation (statement 32), scanning and monitoring for learners’ safety (Group 1, 47:7; Group 2, 53:2). However, Group 1 identify pedagogical dimensions in the differentiation of approaches for the learners (10:3) and the use of questioning for recall (26:2) and probing understanding following a demonstration (58:2) and of concepts, process and procedures (27:2); highlighting an adaptive approach which is underpinned by teachers’ pedagogical and subject knowledge.

For Group 2, the wider considerations include clear expectations of learning and progress (1:4, 4:4, 3:2, and 60:2), including “…models/examples processes…” (13:2) and application of the knowledge being demonstrated, including modelling diagnostic processes (19:4) or peer support (55:3), application of knowledge in other contexts (40:4) and encouraging learners to speculate (50:3). In addition, they identify classroom management, through safe use of equipment (37:3), identifying and providing information about hazards and risks for learners (35:3 and 38:3), and whole class presence (48:3), awareness through visually scanning the room, during (45:2) and after (53:2) demonstrations, and moving “around the room to support learners” (60:2). This demonstrates a range of pedagogical and contextual knowledge in the planning and delivery.

For participants in Group 1, subject knowledge is also a feature of the mid-range responses (Table 10), including the addressing of misconceptions through planning (22:+ 1) and as they arise (21:+ 1). Consideration was also given to health and safety in their competent use of equipment (37:+ 1) and risk assessment (38:+ 1), including prompting learners to “identify hazards and risks for themselves” (36:0). Classroom management also underpins the pedagogic knowledge highlighted in the highest ranked responses, with whole class awareness through scanning and monitoring for engagement (46:0 and 45:− 1) and progress (53:0). Fundamental pedagogic skills of modifying tone for different situations (49:0) and moving around the room following demonstrations to support learners (56:0) contribute to the teacher’s presence in the classroom (48:− 1). A relate aspect of classroom management, which also links to planning and organisation is the use of support staff during, and after, the demonstration to support learners (34:− 1). A third aspect of the mid-range statements for this group is the teacher’s pedagogical knowledge, through questioning to probe prior knowledge (23:1 and 24:1) and encourage speculation (28:− 1), and exemplification of expectations (3:1 and 39:0), staged of a process (31:0) and final outcomes (30:0 and 61:− 1).

In Group 2, mid-range responses include, planning for teacher-led learning through preparation of the demonstration area (32:1), using examples of stages of a process (31:1) products/outcomes (30:1), learning resources (33:1, 29:0) and extension or enrichment activities for able learners (42:1). Delivery of teacher-led learning should also, make explicit to learners, what they will do, or be able to do (5:0), the next steps (18:0) and what they need to do to make progress (62:− 1, 59:− 1) following a demonstration. In addition, this group identify the use of questioning for recall (26:1), probing knowledge (23:1) and understanding (58:− 1). It may be noteworthy that questioning for knowledge appears to be given priority over understanding; and encouraging learner autonomy through learners identifying hazards and risks for themselves (36:0), peer demonstrations (43:0), attempting a task before the teacher intervenes (54:− 1), engaging in fault finding and quality control (44:− 1), and identifying alternative options (41:− 1). Teacher subject knowledge is ranked as moderately important, in teachers’ explanations (51:0) and modelling (7:− 1), targeting of personalised support (57:0), and addressing misconceptions as they arise in the lesson (21:− 1)—it should be noted that planning for misconceptions (22:− 2) was ranked below addressing them in context, indicating that there is an expectation of teachers identifying and address them within the lesson. An implication of this view is that teachers’ tacit subject knowledge may play an important role in learning, albeit not taking prime position.

Whilst statements with lower rankings (Table 11) do not indicate that the members of this group believe they are unimportant, they suggest that some categories of activity are relatively more important than others.

For Group 1, independent learning is ranked at lower end of the continuum, with less importance given to peer support (41:− 4) and demonstrations (43:− 2), encouragement to engage with fault-finding or quality control (44:− 2), consolidating learning through learner dialogue (50:− 3), probing learning from other subjects (25:− 3) and identifying alternative actions or choices (40:− 4 and 41:− 4). Less emphasis is also given to the activity of the teacher following the demonstration, to address misconceptions (57:− 2) or delaying teacher intervention until a learner has attempted a task (54:− 3)

Similar themes that emerge in Groups 1 and 2, including: wider or contextual dialogue around implications of decisions and/or actions, reflection on values, such as technology in society and the environment, and explaining with the aid of examples, analogies and/or similes, reference to application of knowledge outside of the classroom or other learning resources.

Themes that emerge from Group 2 include making links with cross-curricular themes/concepts (14:− 3). Other items in this category indicate that some activities may be viewed as relevant to specific situations, that arise with a demonstration, or lesson, such as addressing misconceptions (22:− 2), questions to probe prior knowledge and understanding from within D&T (24:− 3), other subjects (25:− 2) or to “encourage learners to speculate” (28:− 4); and the used of staged demonstrations for “more complex process” (8:− 4). Whilst scanning the room for learners progress (53:2) was viewed as important, scanning and monitoring for engagement (46:− 3) and safety (47:− 3) was less so, which may indicate that they are encompassed or subsumed by a teacher focus on progression.

In line with ranking of other statements relating to the use of learning resources, the teacher educators in Group 1 assign lower value (Table 12) to the use of visual resources (29:− 5) or ICT (20:− 6) to support demonstrations, and making links to wider knowledge (14:− 5) and diagnostic processes (19:− 5). Whilst an overview what is to be demonstrated is important (1:4), delivering this in one go is not (9:− 6).

For Group 2, the statements ranked in towards the bottom of the scale similar statements ranked in the top and middle of the range. However, this group rank questioning lower down the scale (cf. Table 11). As such, no clear themes emerge for discussion from these data.