Cluster like concepts in data reporting. This will bring clarity to reporting and help to provide rationale for your conclusions. Data and supporting rational should be reported in an order that runs from most important to least important. Additionally, data should be presented in a logical or sequential way so as to facilitate transition from one concept to another.
Match data appropriately with themes and other consistencies identified in the discussion so that a connection between data and stated themes is established. For instance, if reporting on the origin, frequency and nature of instructional and non-instructional interactions between a teacher and her students, the data should be reported separately in those two categories.
Convince the reader of the implications of the study's results. Convey enthusiasm and complete confidence in the findings and provide a defensible rationale for each insight discussed. Reference each subset of data and explain how that supports your conclusion.
Discuss the limitations or weakness of the research design, which may have impacted the results of the study. It is important that the researcher identifies any limitations that may have skewed the data. There may have been preexisting conditions that the research could not control, but that may have affected the results of the study. Additionally, there may have been some unexpected and or uncontrollable conditions that occurred during the study.
Discuss areas for future research that are related to the research topic and data set. Perhaps the research design was appropriate for the topic, but other considerations were ignored. For instance, if the research investigated the reaction of elementary school students to a new reading program, he might not have taken into account the gender balance of the research group. The data may have told a different story, leading to a different conclusion, if the research group was 75 percent male.