Analytic Strategies
Some of the analytic strategies or principles underlying the use of a general inductive approach
are described below.
1. Data analysis is guided by the evaluation objectives, which identify domains and topics to be investigated.
The analysis is carried out through multiple readings and interpretations of the raw data,
the inductive component. Although the findings are influenced by the evaluation objectives or
questions outlined by the researcher, the findings arise directly from the analysis of the raw data,
not from a priori expectations or models. The evaluation objectives provide a focus or domain of
relevance for conducting the analysis, not a set of expectations about specific findings.
2. The primary mode of analysis is the development of categories from the raw data into a model or
framework. This model contains key themes and processes identified and constructed by the evaluator
during the coding process.
3. The findings result from multiple interpretations made from the raw data by the evaluators who
code the data. Inevitably, the findings are shaped by the assumptions and experiences of the evaluators
conducting the study and carrying out the data analyses. For the findings to be usable, the evaluator
must make decisions about what is more important and less important in the data.
4. Different evaluators may produce findings that are not identical and that have nonoverlapping
components.
5. The trustworthiness of findings derived from inductive analysis can be assessed using similar techniques
to those that are used with other types of qualitative analysis (e.g., Lincoln&Guba, 1985).
It is worth noting that evaluation projects often have specific objectives that guide data collection
and analysis. Some common objectives are to identify what isworking well in a program
and what needs improving. In outcome evaluations, there may be particular interest in collecting
qualitative data to identify any unplanned outcomes. Although specific objectives or evaluation
questions undoubtedly constrain the range of possible interpretations and outcomes from
an inductive analysis by focusing attention on specific aspects of the data, the approach is unlike
deductive investigations in which a specific hypothesis, theory, or model is being tested.