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

–––––––––––––––––––––––––––– 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