This post is part of the continuing mini-series on RQ–RH–D–M across fields. Its purpose is to provide a compact, practical toolkit showing how research questions, research hypotheses or working propositions, data, and methodology can be aligned in one specific discipline.

Biology is especially well suited for this exercise because it encompasses molecular processes organisms, populations, ecosystems, behavior, adaptation and experimental manipulation. It also naturally supports quantitative, qualitative and mixed methods designs, especially when biological measurement, field observation, laboratory evidence and interpretive inquiry about practice or ecological meaning need to be connected.

In biology, empirical studies are often grounded in frameworks such as evolutionary theory, ecological theory, systems biology, developmental biology, cell and molecular regulatory models, life-history theory, allometric theory and, in educational contexts, biology education frameworks such as conceptual change or active learning. These frameworks generate questions and hypotheses about mechanism, variation, adaptation, growth, interaction, regulation or learning and the relevant constructs are operationalized through biological measurements, laboratory indicators, observational data, genetic or molecular markers, physiological signals, growth parameters or structured learning measures.

Note: The entries in the Methodology are intentionally general and indicative. They are meant to illustrate plausible methodological directions, not to exhaust the full range of possible methods, model variants or analytic choices available to the researcher. Researchers are not expected to apply all of the methodological tools listed in column Methodology in a single study. The entries are intended to indicate suitable methodological options or families of approaches from which the researcher selects those that best fit the research question, hypothesis, data, and design.