Introduction

Since the beginning of 2010, teachers in New Zealand have had the task of implementing learning programmes in technology that include a focus on the philosophy of technology. This is described through the Nature of Technology strand in the New Zealand Curriculum (NZC) (Ministry of Education 2007, p. 32). Therefore all teachers involved in year 1–10 technology programmes are expected to incorporate learning outcomes and report on student achievement using the Nature of Technology strand achievement objectives focused on the Characteristics of Technology (CoT) and the Characteristics of Technological Outcomes (CoTO) that have been developed for Leve1 1–8Footnote 1 of the NZC (see Ministry of Education 2007, pull out section for each achievement objective). Teachers providing technology programmes in the non-compulsory senior secondary sector will also be guided by these achievement objectives and will use the Nature of Technology achievement standards at Level 1, 2 and 3 of the New Zealand Qualifications Framework (NZQF)Footnote 2 to assess and credential student learning in the area of the philosophy of technology for qualification purposes. The technology achievement standards have been developed to align respectively to the Level 6, 7 and 8 technology achievement objectives and will be progressively implementedFootnote 3 for use to credential student learning towards a National Certificate of Educational Achievement (NCEA)Footnote 4 from 2011 onwards.

The inclusion of the philosophy of technology in technology learning programmes across the primary and secondary sector, and the subsequent progressive implementation of NZC aligned achievement standards in senior secondary sector, represents a significant level of change from the previous technology curriculum and achievement standards which focused primarily on technological practice (see Compton 2007; Compton and France 2007). In recognition of these changes, the New Zealand Ministry of Education funded a two and half year research project focused on the Technological Knowledge (TK) and Nature of Technology (NoT) strands. This project was the Technological Knowledge and Nature of Technology: Implications for teaching and learning (TKNoT: Imps) research project and ran from 2008 to June 2010. An overview of the theoretical and methodological basis for this project, illustration of coding methods, and the findings related to Stage One, are provided elsewhere (Compton and Compton 2009). In this paper we provide an overview of Stage Two of the TKNoT: Imps project as it related to the Nature of Technology focus, and present and discuss its key outcomes.

Stage two of the technological knowledge and nature of technology: implications for teaching and learning (TKNoT: Imps) research project

Overview

The TKNoT: Imps research employed a critical social science methodology with the aim of exploring how the componentsFootnote 5 of the TK and NoT strands progress from level 1–8 of the NZC (Ministry of Education 2007) and how teaching may support students to achieve such progressive understandings. While the levelled achievement objectives of the NZC (Ministry of Education 2007) provide overarching statements of progressive intent across all learning areas, they do not provide sufficient detail to guide teachers’ formative or summative assessment decisions. To address this Indicators of Progression have been developed for the learning area of technology in New Zealand. As discussed elsewhere (Compton and Harwood 2005), Indicators of Progression are research based descriptors developed to mediate between achievement objectives and classroom practice. By 2007 Indicators of Progression for Planning for Practice, Brief Development and Outcome Development and Evaluation had already been developed and were therefore available for teacher use to support the Technological Practice strand of the NZC (Ministry of Education 2007). While an initial draft of the Indicators of Progressions for the Technological Knowledge and Nature of Technology strands had been drafted to support the release of the NZC they were theoretically derived from the achievement objectives rather than based on classroom based research. Therefore Stage One of this research sought to validate and/or revise these descriptors as based on student portfolio data and teacher reflections on student understanding. An analysis of interview data from 81 students interviews focused Characteristics of Technology (CoT) and 55 student focused on Characteristics of Technological Outcomes (CoTO) served to test and refine the student indicators. This analysis, including illustrative examples of how this data was coded, has been reported elsewhere as part of the description and findings from Stage One of the research (see Compton and Compton 2009). As a result of Stage One, a revised set of draft Indicators of Progression were published in April 2009 for both components of the Nature of Technology strand.

Stage Two of the research ran from the beginning of March 2009 to the end of December 2009. A total of 32 teachers and 22 schools were involved in this of the research. The schools were geographically spread across New Zealand. Nine (28.1%) of the teachers were in Northland schools, six (18.75%) in Auckland, three (9.34%) in Waikato, six (18.75%) in Wellington, and eight (25%) in Canterbury. Sixteen teachers (50%) were from the primary sector (year 1–8), with the remaining 16 teachers (50%) being from the secondary sector (year 9–13).

This stage of the research was more interventionist in nature than the largely explorative Stage One and particularly focused on identifying and describing teaching practices that successfully provided opportunity for students to progress.

In this paper we report on the learning experiences teachers provided students when focusing on developing their philosophical understanding of technology as part of Stage Two. The teachers were asked to focus a significant percentage of their teaching on aspects related to either the CoT or CoTO component. We had noted during Stage One that in many cases the teachers assumed their students had a higher level of philosophical understanding than they did. This resulted in rendering the subsequent learning experiences they developed largely ineffective as they were pitched too high. Therefore we placed significant emphasis on developing diagnostic tools using the 2009 version of the CoT and CoTO student indicators to determine student prior understanding. This information was used to plan learning experiences tailored to consolidate, challenge and/or extend student understanding. The draft CoT and CoTO indicators were also used at the completion of the unit to ascertain if any shifts had occurred. Student data related to the CoT and CoTO components was collected through student portfolios/booklets, photographs, assessment tasks and teacher comments. The data collected during Stage Two was also analysed to further refine the 2009 version of the CoT and CoTO Indicators of Progression as part of the iterative process of their development.

The key outcomes related to the Nature of Technology strand from Stage Two of the research were:

  • The identification of common misconceptions of technology and partial understandings of technological outcomes that caused barriers to learning if not addressed;

  • the development of four case studies; and

  • the publication of further revised Indicators of Progression for each Nature of Technology components.

Each of these outcomes are presented and/or discussed below.

Misconceptions, alternative concepts and partial understandings

In Stage One of the TKNoT: Imps research, when students expressed ideasFootnote 6 about characteristics of technology and technological outcomes that were judged to be pre-level 1 they were categorised as ‘emergent’ or ‘0’.Footnote 7 Many of these ideas were again noted in the Stage Two data. However, during the analysis of the Stage Two data it became clear that these ideas across the five components of Technological Knowledge and the Nature of Technology strands were of different types and in some cases (misconceptions and alternative concepts) were not directly related or precursors to those ideas inherent in the level 1 student indicators for these components. We therefore decided to stop categorising these ideas as ‘emergent’, and instead identified them as misconceptions, alternative concepts or partial understandings. Misconceptions refer to those ideas that are incorrect and served as a barrier to student progress. Alternative concepts refer to ideas that are ‘correct’ in another context or discipline but not in technology, and when held, also served as a barrier to student progress. Partial understandings refer to ideas that are essentially correct but so small a part of the ‘big picture’ as to be unhelpful for students to progress. Table 1 presents a summary of the ideas students commonly hold about technology and technological outcomes, identifies them as misconceptions or partial understandings, explains probable reasons students hold these ideas, and discusses how easy or difficult teachers found them to address.

Table 1 Philosophical misconceptions and partial understandings
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Case studies of teaching components

Four case studies were developed from the work of six teachers as they taught aspects related to the Characteristics of Technology (CoT) or Characteristics of Technological Outcomes (CoTO). Extracts from the CoT case studies are provided in Tables 2 and 3. Extracts from the CoTO case studies are provided in Tables 4 and 5. These extracts have been selected to illustrate teaching strategies used and resulting student outcomes.

Table 2 Summary of case study one related to characteristics of technology (CoT)
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Table 3 Summary of case study two related to characteristics of technology (CoT)
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Table 4 Summary of case study three related to characteristics of technological outcomes (CoTO)
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Table 5 Summary of case study four related to characteristics of technological outcomes (CoTO)
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Publication of revised indicators of progression

The data provided in the Tables 2, 3, 4 and 5, alongside data collected from other students and teachers, was used to further refine the April 2009 CoT and CoTO Indicators of Progression as discussed below.

Revising the April 2009 version of the indicators of progression for characteristics of technology (CoT)

Both of the case studies summarised in Tables 2 and 3 provided evidence that verified the level 1 and 2 indicators, and most of the level 3 indicators, provided useful diagnostic and formative assessment tools to support student learning in terms of the related achievement objectives. However, in both cases the following indicator seemed too difficult for level 3.

  • explain that technological knowledge is evaluated in terms of how effective it is in supporting an outcome to function successfully (L3)

The first case study also raised issues with the following two level 4 indicators.

  • describe examples to illustrate how technological developments have expanded or have the potential to expand human possibilities and discuss the possible short and long term impacts of this (L4)

  • discuss examples of innovative technological development to illustrate the role of creative and critical thinking (L4).

Related to the first of these, the students had difficulty with the concept of ‘human possibilities’ suggesting the wording required changing to better communicate the intent. In terms of the second, students had difficulty ‘illustrating’ the role of creativity and critical thinking in supporting technological innovation as they could not identify what creativity and critical thinking in technology might look like.

The remaining indicator at level 4 regarding identifying and categorising knowledge and skills from inside and outside the discipline of technology seemed to cause no particular learning problems for students. This was also verified in the second case study.

The level 3 and 4 April 2009 student indicators for CoT were therefore modified as a result of these and similar findings from student data from other classes and subsequent discussions with teachers. The related student indicators were changed to read as follows:

  • identify that technological knowledge is knowledge that technologists agree is useful in ensuring a successful outcome (L3)

  • identify examples where technology has changed people’s sensory perception and/or physical abilities and discuss the potential short and long term impacts of these (L4)

  • identify examples of creative and critical thinking in technological practice (L4)

  • identify and categorise knowledge and skills from technology and other disciplines that have informed decisions in technological development and manufacture (L4)

Revising the April 2009 version of the indicators of progression for characteristics of technological outcomes (CoTO)

Both of the case studies summarised in Tables 4 and 5 provided evidence that verified the level 1 indicators provided useful diagnostic and formative assessment tools to support student learning in terms of the related achievement objective. However the teachers experiences with using the level 2 indicators suggested the indicators themselves, and the related teacher guidance, should more clearly communicate the importance of linking the physical and functional nature of technological outcomes—whether they be described as technological products or systems.

Both of the case studies also showed the link between physical and functional nature and the outcome’s fitness for purpose was difficult for students, and understanding related to this could be better developed by breaking this down into smaller ideas and introducing them across more than one level.

The level 2, 3 and 4 April 2009 student indicators for CoTO were therefore modified as a result of these and similar findings from student data from other classes and subsequent discussions with teachers.

The student indicators were changed to read as follows:

  • identify a technological product and describe relationships between the physical and functional attributes (L2)

  • identify a technological system and describe relationships between the physical and functional attributes (L2)

  • explain why a technological outcome could be called a ‘good’ or ‘bad’ design. (L3)

  • explain possible physical and functional attributes for a technological outcome when provided with intended user/s, a purpose, and relevant social, cultural and environmental details to work within. (L4)

The teacher guidance material for CoT and CoTo was extensively revised to provide more specific guidance, particularly in terms of ensuring students are provided with real examples of technological outcomes to explore and analyse and that new ideas are introduced across a range of contexts when developing foundational understandings and/or challenging misconceptions related to the Nature of Technology across levels 1–3.

All the research teachers were brought together to discuss their respective experiences of teaching the components of the Technological Knowledge and Nature of Technology strands. From this basis they were able to provide a classroom practice informed critique of the suggested refinements based on their usefulness as both planning and assessment tools. The refinements were also discussed with both in-service and pre-service technology teacher educators prior to their publication in October 2010. The revised version of the Indicators of Progression for the Nature of Technology are available at http://techlink.org.nz/curriculum-support/indicators/nature/index.htm.

Conclusion

The findings and outcomes related to the Nature of Technology strand from Stage Two of the TKNoT: Imps research allowed significant progress to be made in terms of providing research-informed guidance and support for the teaching of the philosophy of technology in New Zealand.

There was an overall shift in the level of student achievement related to both Characteristics of Technology (CoT) and Characteristics of Technological Outcomes (CoTO) between the Stage One and Stage Two data. In the interview data collected from Stage One, the majority of the 81 students showed understanding related to CoT at or pre level 1 (62 students or 76%). Only 16 students provided evidence of level 2 understanding (19.7%), two students showed partial level 3 understanding, and one student showed partial level 4 understanding. The majority of the 55 students showed understanding related to CoTO at or pre level 1 (32 students or 57.5%). Twenty one students provided evidence of level 2 understanding (38%), and two students showed partial level 3 understanding. This therefore meant the April 2009 student indicators for level 3 and above were tested against a very small and partial data set and due to this were published as draft discussion documents only.

In contrast, the Stage Two data set provided many examples related to both CoT and CoTO of students progressing from pre-level 1 to level 1, level 1–2 etc. and showed many older students working comfortably at levels 3 and 4 even after relatively minimal teaching. This allowed for greater confidence for both the CoT and CoTO indicators to be verified or changed as required. The resulting October 2010 Indicators of Progression were therefore published as support documents for teachers to use for planning and assessment purposes—that is no longer in draft form. However, it should still be noted that even in Stage Two, the majority of students did not progress beyond level 4 in either component. From teacher discussions we concluded that for CoTO this was an issue of time rather than teachers having difficulty in developing learning environments to progress their students further. However in relation to CoT, the teachers were less confident they could develop learning experiences to support student learning above level 4. Therefore as part of the final stage of the TKNoT: Imps research a pilot trial was set up to specifically explore deeper processing strategies to support the teaching of the CoT at level 4 and above. The findings from this trial will be reported on in a separate paper.

Many teachers kept a reflective journal during this stage of the research allowing us to gain deeper insight into the complexities of the learning environment they and their students were involved in, and the success or otherwise of their teaching practices. Teacher data, along with the material presented in Tables 2, 3, 4 and 5 was further analysed using the Model of Domain Learning (MDL) (Alexander 2003, 2006) to further explore the case studies in terms of factors that impact on effective teaching of technology. This will also be reported on in a subsequent paper.