Research Techniques for Experimental Data Collection

According to Mertens (2008), there are many methods for data collection. These include observation, experiments and archival and follow-up studies. Observation is used to detect changes in a controlled experiment to isolate the effect of a single factor. The effects would be recorded so that the results can be “built on”. Scientific theories are based upon controlled and repeatable experimental protocols. This allows for the recording of accurate data from solid testable evidence (Mertens, 2008). Conducting experiments gives a clearly defined path to follow in a quest for ongoing improvements. Referring to historic experimental data and archived results from similar products, tested and recorded at the thermal testing laboratory, will create comparison data and may eliminate the need for excessive amounts of experiments. Follow-up studies can be used to collect and evaluate the long-term experimental outcomes. This will help to obtain generalized knowledge about the product and enable developed faults to be “ironed out”.

Defining the experimental unit will help to achieve the detailing of the data collection format. This is the purpose of the research and is the analysis unit within the experiment that is used to collect data. For example, in this research context, the unit will be soap insulation. Once defined, the sources of variability must be identified within the experimental conditions. Trying to improve the precision of the results, in order to investigate the research hypothesis, is the objective. Inconclusive results can occur if the following variables are not sufficiently defined (Mertons, 2008). Fig.3.12, shown on the following page, demonstrates the relationship between the four main variables and the research question.

Figure 3.12: Experimental Data Collection

3.5.1 Types of Variables

1. Background Variables

These are both identifiable and measurable but are uncontrollable (Vollmer, 2013). They will have a negligible bearing on the outcome of the experiments undertaken. If background variables are applied to an analysis, a superior estimation of the primary variables may be the result. This is because the variation sources that have been supplied by the control variants have been taken away. The different fats and oils are background variables. The fats all contribute to the soap manufacturing process, but will create soap of differing qualities and texture.

2. Constant Variables

Constant variables can be measured and controlled but will remain constant throughout the continuance of the research (Vollmer, 2013). This action will increase the result’s validity by halting or reducing external variation sources and stopping them from “clouding” the data. Soap aeration is a constant variable. Aeration is a key requirement for soap insulation to perform. The size of the air pockets or bubbles is irrelevant in a constant variable context, as any size bubble will allow the soap insulation to perform, although to differing degrees of thermal performance.

3. Uncontrollable Variables

These are variables that refuse to be manipulated and are difficult to measure (Vollmer, 2013). Errors occur in data because of the influential effects of these uncontrollable variables, which affect the evaluations of the background and primary variables. Planned experimental design should control or eliminate uncontrollable variables. This will increase the reliability of, and heighten confidence in the end result. In the ensuing experiments, the controlled variables is the strengthening measures adopted for the accepted soap body. The uncontrolled variable is how the product performs under strength testing. This performance is unknown before the results are revealed and so the strength of the soap is beyond the researcher’s control. This is one example. Uncontrollable variables are present in the waterproofing, vermin repelling and fire proofing of the insulation product.

4. Primary Variables

Primary (independent) variablesare the usual sources of variations in the responsive reaction (Vollmer, 2013). For example, the values that can be changed in a given model or equation. These primary variables contain the design and treatment structures and provide the "input" which is modified by the model to change the "output." The research question asks if soap can be used as an alternative to petroleum in thermal insulation. The independent variable is the composition of the soap within the experiments. This is controlled by the experimenting researcher. The values that result from the independent variables are called the dependant variables. The actual experiment is a situation in which the researcher attempts to make unbiased and impartial observations in the experimental situation (Johnson & Christenson, 2007). As the experiments progress, samples will be manufactured, tested and remanufactured in a cyclic process of improvement (Fig. 3.13 shown on the following page). This evolution of an idea should incorporate the testing of the hypothesis or null hypothesis (no difference existing between the control and experimental group) for the variables being compared.

Figure 3.13: Testing & Manufacturing Process Loop

3.5.2 Research Process Design

The research process is based on the cycles of soap sampling and experimental testing. This process will identify the preliminary stages before the thermal laboratory testing and the stages during the thermal laboratory testing.

Preliminary Testing: Different types of fats and oils (including waste engine oil) will be used in the soap manufacture. This identifies a soap body that is the most receptive to aeration and strengthening procedures. At this stage the soap can aerated with different products and by using different aeration techniques to make the soap lightweight and thermally efficient. Strengthening the soap body will take place at this stage to create a soap body that can withstand accidental knocks without breaking. A protective casing will need to be fitted to the outside of the soap body for protection. At this stage the soap casing will made from plastic sheet.

Laboratory Testing: The samples taken forward for laboratory testing had aeration voids of differing sizes. This will identify the optimum size of air void to give the most favourable thermal conductivity and thermal resistance results. Different casings will be tried for the protective casing.

Improvement Testing: The insulation samples will treated to make them moisture, vermin and UV resistant. The casing will also be made fire retardant.

Manufacture of test samples Observation Recording of data Comparison of results for improvement and evolution of improved test samples

3.5.3 Research Techniques for Data Analysis

Sequential hypothesis testing is the use of a sequence of experiments, whereby the design of each stage depends on the results of previous experiments, including the possible decision to call a halt to the experimenting (Fukunaga, 2013). The soap insulation experimentation is organised along this process. In order that the process runs smoothly, explicit knowledge of prior research must be observed. Alongside this, the know-how of interpreting and recording basic statistics and observations, expertise of constructing databases, alongside knowledge of the implications of the experimental research should be considered (St. Pierre, 2004).

To analyse the data for research techniques, the causal analysis strategy will be employed. This strategy searches for the cause or causes of particular events. A causal factor is a variable which may cause changes in another variable. In a similar way but to a lesser extent, correlational analysis may also be employed. In correlational research, variables are not influenced, but only measured in order to look for relations (correlations) between sets of variables (McNabb, 2008). This will be important for the control test samples.