essential-guide-to-qualitative-in-organizational-research

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–––––––––––––––––––––––––––– ACTION RESEARCH AND RESEARCH ACTION –––––––––– 355competence in the activities under investigation. This frequently leads the researcher to makevague suggestions for the possible meaning of the discovered statistical relationships. InAR/RA it is possible to make respondents into co-interpreters. 8 After all, researchers obtaindata from certain categories of people because they value the quality of their judgement andconsider them to have knowledge and experience in the area under study. However, whenit comes to interpreting the data, traditional research is content to leave these knowledgeablerespondents out of the picture. Co-interpretation produces important improvements in validity(consensual validity).Taking all this into account, I would argue that, on balance, AR/RA results have at leastas good a claim to scientific validity as traditional methods.Finally, within the limits of a short chapter, I want to describe two interrelated actionprojects: first, an AR project that drew on existing socio-technical theory, secondly, a RAproject that had to test new relationships for which no previous experience was available.ACTIVELY SAFEGUARDING THE ENVIRONMENT: AN AR/RA PROJECT ––––––––––––––––––––––––––Saving the environment became a major area for public discussion towards the end of thetwentieth century. The challenge now is to convert discussion and intentions into action. Oneway of approaching this problem is through the next generation of energy users: schoolchildren, whose attitudes and habits are not too rigid. An opportunity to work in this fieldoccurred when Essex County Council approached the Tavistock Institute to look at a problemthat they had with heating schools. Essex had been chosen by the European Union to test anew computer technology that could control the class room temperature of a large numberof schools from a single central location. Internal and external sensors were installed. Thecentral computer would start up the boilers of each school at a certain time of the morningdepending on the outside temperature surrounding that particular school. The computerwould then adjust the heating throughout the day based on internal sensors in each school.To maximize the use of technology, windows were bolted down and individual thermostatsremoved. The cost-benefit from this system was calculated to be considerable.During the first winter, the Architecture Department of Essex, which was in charge of thesystem, was faced with irate headmasters who threatened to close their school unless thecomputer was disconnected. Some classrooms were freezing while others were quite warm.This is how the project started. Interviews with a sample of teachers, heads of schools and thedepartment of architecture, led us to the conclusion that, on its own, the automatedtechnology was unable to take account of important contingencies. The computer could notaccommodate: weather patterns (changing prevailing winds), temperature differences forclassrooms facing north or south, the body heat generated from different numbers of pupilsin a given class, the number of windows in a classroom, the use of kitchen stoves in cookeryclasses and kilns in art rooms, and so on. From this diagnostic we concluded that this is a classiccase where socio-technology solutions could be applied without further research. Theautomated technology had to be jointly optimized with human intervention (Trist, 1993:580–98). Teachers and pupils had to obtain a greater measure of control. Thermostats werereinstated and windows unbolted (for variability of summer weather) to keep temperaturesat the government-recommended 19 degree level. The new joint optimized, computer/school, self-help design was popular; it balanced temperature variations and reduced energy
356 –––––––––– QUALITATIVE METHODS IN ORGANIZATION STUDIES ––––––––––––––––––consumption and cost (Heller, 2001b). 9 The important conclusion is the recognition that onlya short diagnostic, but no further research was necessary.The situation with the next project was different. No theoretical model and no researchexperience was available to guide us. The Energy Directorate of the European Unionsupported a project to discover whether schools could be a suitable conduit to reduce theemission of carbon dioxide (CO 2) in line with government policy and internationalagreements. We formulated our research objectives in two stages. The first was to create ActiveEnergy Awareness in pupils. Active Energy Awareness differs from awareness and favourableattitudes to saving energy, by being clearly associated with consistent changes in energy savingbehaviour. Secondly, we had to try and demonstrate that this changed energy behaviour couldbe related to significant savings of CO 2. New knowledge had to be obtained and tested.Oxford County Council collaborated in this project and facilitated our entry to ten secondaryschools. In line with the funding body’s requirement, we designated five schools operational andfive as controls. The diagnostic phase was similar to the Essex project and involved heads ofschools, teachers and discussion with groups of pupils. We explained, in non-technical terms,that unlike the Essex project, we were not now concerned with jointly optimizing technologyfor the comfort of school pupils. Instead, we wanted to jointly optimize technology for thecomfort of the population in general through CO 2reduction. 10 The diagnostic research led usto concentrate on lighting rather than heating and to use and amend the existing energy contentin syllabuses in science, technology and geography to unify and strengthen energy awareness.The mathematics syllabus was also used to allow students to carry out calculations that convertedenergy saving to CO 2emissions and to make graphs to plot progress.The method to motivate and inform pupils was Group Feedback Analysis (GFA) which willonly be described in outline (but, see Heller, 1969 and 1970). The method begins by creatingdissonance between what pupils know and what they should know about energy. This links upwith what is expected from their syllabuses in science, geography and technology. Later, regularfeedback is used to show what each class achieves and how their energy saving can be translatedinto reducing CO 2emission (this is part of the mathematics syllabus). Pupil energy monitors areappointed and asked to control lights in classes and corridors during breaks in the morning,afternoon, lunch and when lessons finish in the afternoon. With the permission of teachers, lightscan also be switched off in classes where additional light is not really necessary. The monitors keptrecords of the number of quarter hours they saved. Regular feedback of results createdconsiderable motivation. Everybody was astonished at the amount of electricity and CO 2thatcould easily be saved. Head teachers and governors were particularly interested to see thecalculations of cost saving, but teachers and pupils were much more motivated by translatingkilowatt hours of electricity into CO 2emission (Heller et al., 1997; Heller, 2001b). 11 Comparativegraphs were produced for each term and for each school, further increasing motivation.A considerable amount of knowledge and experience had accumulated in the two yearsof the RA project. The research experience was summarized in a multi-coloured booklet fordistribution to the European Union and Oxfordshire County Council. The difference inenergy saving behaviour between the control and operational schools was substantial. Teachersand pupils in the operational schools had progressed from a general interest in energy to activeenergy saving behaviour that was carefully documented in tables and graphs. Clear benefitsin terms of cost saving and reduction in CO 2emissions were achieved, although more in someschools than in others. Significant aspects of the RA project had been co-designed withteachers and influenced by boards of governors. Pupils as well as teachers helped to interpret
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ESSENTIAL GUIDE TO QUALITATIVE METH
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This book is dedicated to our child
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viii ---------- CONTENTS ----------
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Notes on ContributorsJohn Benington
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AcknowledgementsIt has been 10 year
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2 ---------- QUALITATIVE METHODS IN
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10 ---------- QUALITATIVE METHODS I
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4 ---- Life Histories -------------
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8 ---- The Twenty Statements Test -
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9 ---- Qualitative Research Diaries
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10 ---- Stories in Organizational R
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12 ---- Group Methods of Organizati
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15 ---- Critical Research and Analy
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20 ---- Grounded Theory in Organiza
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Quote Code in open coding Concept T
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Table 20.2 Examples of open coding,
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Table 20.3Collective stressors and
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21 ---- Using Templates in the Them
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Table 22.1Matrix 1: descriptive sum
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Table 22.1 cont1.1 Analysis by colu
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Table 22.2DebbieAndrewMatrix 2: con
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Table 22.2cont.Allan Petrol scam Wa
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23 ---- Preserving, Sharing and Reu
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