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Ministry of Education.
Kaua e rangiruatia te hāpai o te hoe; e kore tō tātou waka e ū ki uta

Summary and Research Finding: Stage Two

In the second stage of the research, intervention was more prevalent, and the refined April 2009 indicators of progression from Stage One were used extensively. The key focus of Stage Two was to explore pedagogical strategies developed specifically to progress student learning within the Technological Knowledge (TK )and Nature of Technology (NoT) strands. This stage of the research ran from the beginning of February 2009 to the end of December 2009.

The Ministry of Education guidance for 2009 was still to focus on Technological Practice for summative assessment and reporting purposes, so again most teachers integrated a learning focus from the technological knowledge or nature of technology strand into their learning programme for Technological Practice. Student data was collected primarily through student portfolios, photographs, and teacher comments. All data collected was used to further refine the indicators, and some data was used to develop case studies to illustrate particular pedagogical points and form the basis for a secondary analysis as discussed below.

Misconceptions, Alternative Conceptions and Partial Understandings

The misconceptions or partial understandings, which had been identified and categorised as "emergent" in Stage One and added to the indicators, were again noted in the Stage Two data. In the analysis of this data, however, it became clear that some of these "misconceptions" were actually alternative conceptions, and the partial understandings were usually a result of a lack of experience.

The points noted as partial understandings were usually resolved when students showed level 1 understandings, whereas those points that could be rightly called misconceptions or alternative conceptions, often remained with students even though they exhibited level 1, 2, or 3 understandings.

It was also noted that misconceptions or alternative conceptions in one component often caused considerable difficulty in shifting understandings in other components. The points referred to in Stage One as misconceptions or partial understandings were therefore removed as precursors to level 1 (that is, an "emergent" category in the indicators) and were reported separately as important points for teachers to be aware of and address when working with students across all components at all levels.

The Stage Two findings also provided greater insight into how easy or difficult these points were to address. The points representing misconceptions, alternative conceptions and partial understandings from Stage Two are provided in Table 7.

Table 7: Misconceptions, Alternative Conceptions and Partial Understandings

Points Related to Characteristics of Technology

  • Describes technology in terms of outcomes only and as either "good" or "bad".
  • The development of new outcomes seen as the result of people "playing around" and/or trial and error.
  • Any process that involves using technological tools, planning, and/or solving problems is seen as being technology - unable to differentiate technology from other human endeavours.
  • Technology seen as only new "things" often with a qualifier that they run off "power".
  • Changes in technology perceived as "just happening" – no recognition of "drivers" of technological development (such as new knowledge, skills, social or environmental needs, and so on).

These points all represent misconceptions of technology and were commonly noted across both Stage One and Stage Two findings and were common across all age groups. This is because they tend to reflect typical "public understandings" of technology and are therefore introduced early and constantly reinforced through everyday interactions with parents, friends, and so forth.

These misconceptions required extensive and explicit teaching to address. That is, they were often difficult to change and success in doing so relied on teachers continually probing for these ideas and challenging them across a range of contexts.

Points Related to Characteristics of Technological Outcomes

  • Cannot distinguish Technological Outcomes from other objects.
  • Describes a Technological Outcome solely in terms of what it is called.
  • Describes a Technological Outcome solely in terms of what it looks like such as shape, size, colour, and so on.
  • Describes a Technological Outcome solely in terms of what it does.

In contrast to the misconceptions related to Characteristics of Technology (CoT), the Characteristics of Technological Outcomes (CoTO) points were usually seen in younger students and were relatively easy to address. This is because all points reflect a basic lack in student knowledge and/or experience rather than reflecting a construction of "common" but inaccurate concepts from everyday interactions.

Success in addressing these points was achieved through providing students with the opportunity to interact with a range of Technological Outcomes and non-Technological Outcomes and undertaking scaffolded categorisation and description activities. This was significantly enhanced when teachers provided word banks to introduce new descriptive terms and allowed adequate time for students to discuss and employ these terms.

Points Related to Technological Modelling

  • Models identified as small replicas or people – for example, model trains or role models, fashion models.
  • Suggests that technologists use modelling but cannot explain what it is.

The first point is more like those related to CoT and was shown to be common across age groups. Rather than being a misconception, however, these represent alternative concepts of models which are often used in different everyday situations. The second point is a partial understanding tended to be caused from both a lack of knowledge and experience of technological modelling specifically and a confusion between other disciplines where modelling is employed in different ways and for different purposes.

To address these points, teachers were successful if they explicitly discussed the different meanings of "model" and modelling and provided multiple examples of technological modelling across a range of contexts in terms of its specific purpose (what design idea or outcome was it testing) and why it was useful in the decision making involved in the development of a Technological Outcome.

When teachers tried to discuss what a technological model is (as opposed to technological modelling), further misunderstandings or confusion arose. This was because the same model may be used in different ways – some of which may be technological and others may not (that is, they may be used to communicative or test a theory such as in science).

Points Related to Technological Products

  • Could not correctly identify materials.
  • Suggests materials that particular products might be made from but materials suggested are often not feasible.
  • Had no idea how materials were, or could, be manipulated.

These points are all partial understandings and were noted across a range of age groups when students were asked to explore unfamiliar products. However, they were relatively easily addressed by teachers through the provision of opportunities for students to undertake product analysis.

When opportunities were also provided to "play" and work with a range of different materials, tudents were able to begin to develop a more sophisticated generic knowledge of materials that was not so "product" bound.

Points Related to Technological Systems

  • Suggests a technological system is any series of steps or routines, including those undertaken by people – that is making a sandwich, getting dressed, and so on.
  • Identifies components that a particular system is made from but the components are not recognised as connected

The first point is a misconception that is directly linked to the CoTO lack of knowledge resulting in not recognising the difference between Technological Outcomes (both products and systems) and non-technological ones. In data related to CoTO, it was shown to be easier to categorise technological products than technological systems and therefore this misconception tended to remain with students across all age levels.

The second point showed a partial understanding demonstrating both a lack of knowledge and experience of exploring and analysing specific technological systems.

To address both these points teachers were successful if they explicitly discussed multiple examples of technological systems across a range of contexts and allowed students adequate time to explore in detail the connections between components and how these enabled the system as a whole to function and without additional human design input.

Case Study Analysis

Alexander's Model of Domain Learning (MDL) was used to analyse the strategies teachers used during Stage Two. Analysing the data in terms of processing strategies, interest and topic, and domain knowledge has provided interesting insights into pedagogical practices across all data and related to all components.

For example, the following list of learnings that have become clear from this analysis.

  • While most learning experiences allow for (and in some cases, expect) students to undertake both surface and deep processing strategies, many teachers do not explicitly teach processing strategies.
  • The use of surface level strategies appeared to be sufficient for developing domain knowledge prior to level 4.
  • In most cases, teachers focussed on both topic and domain knowledge. In some cases their focus on domain knowledge was during their diagnostic and/or summative assessment activities, rather than underpinning more substantive learning experiences.
  • Focusing on both topic and domain during learning experiences and formative interactions resulted in greater or more consolidated shifts in achievement than relying on topic alone to provide domain shifts.
  • When topic is dominant during learning experiences and the domain implications are not made explicit, shifts are reliant on students making links independently. This, in turn, relies on deep processing strategies. Yeat, at lower levels of topic and domain knowledge, this does not appear to occur.
  • Provision of situational interest is critical to acclimation stages of domain learning. Teachers should not expect individual interest to motivate student learning until they have sufficient topic and domain knowledge.
  • From competency or level 4 onwards, situational interest would often be supplemented with individual interest. This, alongside growing deep processing capability, should allow students to develop higher levels of domain and topic knowledge.

Pedagogical Content Knowledge

The development of Pedagogical Content Knowledge (PCK) for each component of the Nature and Knowledge strands was a major focus for Stage Two of this research. The case studies highlighted a number of features that supported effective teaching of particular components, as well as some features that appeared successful across all all components.

While PCK for technology (as opposed to PCK related to a particular component of technology) was not an explicit focus, analysing the teacher practice and student data showed clearly the importance of understanding each component as a separate focus for learning, as well as the importance of understanding how each component relates to the learning area as a whole. When teachers explicitly made these links, the learning within the component was enhanced and some evidence was also provided that an understanding in other components was consolidated.

The following points summarise the key features teachers exhibited when using pedagalogical strategies effectively as evidenced in case study examples across all components.

  • Teacher understanding of the component as a whole - including an overview of the way it progresses from level 1 to 8.
  • Teacher understanding of how topic knowledge relates to domain knowledge and vice versa in selected learning contexts.
  • Teacher knowledge of students – their prior understandings.
  • Teacher provision of situational interest.
  • Explicit focus on domain knowledge and the identification of associated learning as a recurring part of learning experiences.
  • Explicit focus on terminology and consistent use of this across a range of learning experiences.
  • Provision of multiple learning experiences over time to introduce, explore, and consolidate learning of focus ideas.
  • Scaffolding of topic knowledge into domain knowledge using a range of examples.
  • Consolidating domain knowledge by identifying examples within different contexts.

The remaining points are additional features we suggest would increase effectiveness as based on an analysis of examples in the case studies when student learning did not progress as planned.

  • Teacher knowledge of the specific nature of progression for the actual learning focus. That is, if a student is working at level 1 – what type of shift is being expected for them to move to level 2 (or further).
  • Recognition of critical links between the ideas within each component.
  • Recognition of critical links between ideas across components.
  • Teacher knowledge of students – their prior strategic processing capability and level of individual interest (alongside their prior understandings).
  • Matching of teaching strategy to both understandings of students (prior knowledge, strategic processing capability, level of individual interest) and the specific nature of progression being sought.
  • Explicit teaching of the strategic processing strategies students are expected to employ. This would include both surface and deep strategies and an understanding of the purpose and appropriateness of each.
  • Selection of teaching resources (including reference material, templates, examples, other) to ensure effective support of strategy and that learning opportunities are maximised.
  • Provision of opportunity to interact with "real" examples rather than symbolic representations of these. For example, when asking students to categorise objects, provide the object itself rather than pictures or text descriptions of the object, particularly at lower levels.

The case study findings, along with other data gathered throughout the year, informed the revision of the student indicators for each component and the teacher guidance associated with these.

The Indicators of Progression for all eight components within all three strands were therefore further revised and refined as based on the findings from Stage Two.


  1. For further information regarding this Model see Alexander, P. A. (2006). The path to competence: A lifespan developmental perspective on reading. Journal of Literacy Research, 37, 413-436.
  2. Topic knowledge is any specific knowledge required for students to succeed in particular contexts. For example, when creating a healthy food snack, nutritional knowledge would be key topic knowledge.
  3. Domain knowledge in technology is the generic knowledge and practices described in the eight components of technology.

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