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• Conduct preliminary data collection focussed on developing a map of team and
task processes in HQ. Data generated from the objective observations will be fed
into a behaviour systems model of HQ operation. Ultimately, this will allow
predictions of changes in behaviour/performance that result from changes to the
system input.
3. Collecting Observational Data in the Field
3.1 Overview
As was mentioned in the Introduction, it is necessary to have objective observational
measures, subjective measures, and outcome measures in order to generate an
adequate picture of C2 operation. To date, a large amount of effort has been spent
generating reliable methods of collecting subjective data. For example, the NASA
Task Load Index (TLX) is used as a standard way of assessing subjective workload,
and structured interview techniques are used as a systematic way of collecting data
on a subject’s view of task and team characteristics. Additionally, war-game
simulations generally have outcomes that can be correlated with other performance
measures. In contrast, there has been a low emphasis on behavioural measures. This
is largely because of the difficulties involved in the collection of the basic behavioural
data from a field setting. The labour intensive nature of the work, combined with the
need for an experienced observer has tended to dissuade researchers from
attempting to collect this information. As was discussed, though, it is impossible to
generate a complete picture of C2 operation without objective behavioural data.
Consequently, the current section aims to provide clear guidelines on formal
methods of collecting such data in the field.
It should be noted that the following reflects the authors’ experiences in
observational data collection, as well as an aggregation of concepts from the
published literature (Altman, 1974; Bakeman, 1978; Crockett, 1996; Dunbar, 1976;
Hinde, 1973; Hollenbeck, 1978; Lehner, 1979; Martin & Bateson, 1993; Noldus, 1991).
Thus, it is difficult to provide an exact reference for specific aspects. Instead, the
reader is referred to these papers as a source of information on field research
DSTO-TR-1034
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techniques. In addition, Appendix A provides a Glossary of standard field research
terminology.
3.2 Formulate the Problem
One of the most important aspects of collecting data in a field setting is formulating
the problem. Under no circumstances should the project attempt to observe
everything. This is one of the most common errors made by inexperienced observers,
and tends to lead to ill-defined observations that risk lapsing into the chaotic. A
general problem we may seek to solve concerns identifying the behavioural
indicators of cognitive functioning, and assessing whether they are correlated with
other measures. A more specific problem may be to ask what tasks the Operations
Cell of a Bde HQ perform, and how the individuals communicate the information
necessary to fulfil their roles.
3.3 Identify the Critical Variables
If it is relevant, it is also important to identify the dependent and independent
variables. It must be noted that in some case, the aim of the observations may be to
build a topographic map of existing C2 behaviours, such as teamwork, that can be
used to assist in guiding future system design. If this is the case, then the issue of
dependent and independent is not applicable. If the goal is to examine the effect of a
system such as BCSS on C2 team processes, the dependent variables will include
communication, cognitive and physical workload, and frustration. These are
behavioural variables. The independent variable in this case will tend to be the
various components of BCSS. Other possible independent variables include
communication architecture and team structure. It is important to notice that the
independent and dependent variables are interchangeable. In a field setting, clear-cut
variable boundaries tend not to exist, with distinctions hovering between the
arbitrary and the outright fuzzy.
3.4 When to Collect Data
Another area of observational research that needs to be clearly defined is when the
observations should occur. This can only be determined through preliminary
observations. However, when it comes to a military exercise, it is usually necessary
to attend for the full duration (using sampling techniques to collect the data). Only
observing for peak activity periods will act as a cue to the subjects, and will bias the
data (particularly if a behaviour taxonomy is the aim). In real world activities,
observation will largely be opportunistic. Ideally, it would consist of at least three
full days of observation spread across one week. While this time frame is somewhat
　
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