In quantitative research, the data are in the form of “numbers” that are easy to summarize and submit to statistical analysis. Quantitative data are meant for generalization beyond the sample from which the data were drawn.

Qualitative data are gathered through direct interaction with participants—for example, through one-to-one or group interviews, or by observations in the field. The data consist of non-numeric data - for example, from transcripts or field notes. Data are open for interpretation. The term used is “rich data”, which means that they are rich in their description of the behaviours being observed. Because the data are rich, they are not easy to analyse, and there is no single way to approach analysis.

Qualitative data is descriptive in nature and describes "how". It is gathered by doing in-depth descriptions. Usually, people are studied in their own environment. For example, how does bullying affect school performance in children? How do IB students cope with stress?

The advantage is that statistical analysis can be applied and it can be determined to what extent the results may be due to chance. Quantitative research studies can also be more reliable since they can be replicated and the results can be easily compared. For example, to what extent does music assist in one's ability to learn a list of words? When this study is carried out, the average number of words in both conditions - that is, with and without music - can be compared.

Qualitative studies can be generalized, but only to a limited extent. The word often used by researchers is "transferability." In order to determine the level of transferability, the situation that is being studied must be described in detail so that the findings can potentially be applied to a similar situation. For example, if you are studying stress at our school you would not be able to generalize your findings to all schools, but only schools that are similar to ours. You would have to consider the size of the school, the level of economic and cultural diversity, that we run the IB program and the size of classrooms. The list could go on....

Unlike much quantitative experimental research, no IV is manipulated. However, sometimes the situation is manipulated to see how people will respond. So, in that sense the same ethical standards apply as in quantitative research. Very often qualitative research is long term and personal. The participants may develop a relationship with the researcher and disclose personal information. It is important that the anonymity of the participants is protected and that their trust is not violated. It is also important that the researcher not become too close to the participants and thus lose a sense of objectivity.

The most basic participant effect is called "reactivity." This is when the participants act differently than they usually would because they are aware that they are being studied. Another participant effect is the social desirability effect - this is where information is not disclosed if the participant fears being judged or seen in a negative light. Another effect is a conformity effect. This could happen in a focus group where participants behave in line with the other members of the group. Finally, another participant effect is expectancy effect, where the participant wants to help the researcher and thus gives information that is believed to be what the researcher is looking for. All of these effects may affect the study by distorting the data and providing data that is not credible - in other words, is not reflective of the actual opinions or behaviours of the participant.

When the researcher's own beliefs influence the research process. One way that this could be reduced is to train others to carry out the research who are not aware of the actual goals or expectations of the study. Another way is to have more than one researcher collect and/or analyse the data and compare the findings to see if the same interpretations are made. This can also be done by asking the participants whether they agree with the findings. Finally, the researcher can reflect on how their own biases may have influenced the study as part of the discussion of their findings.

Credibility is linked to the concept of validity. Are the findings and/or interpretations in line with the experience of the participants? This is also called "trustworthiness." So, if your interpretation of an interview with me says that I am very "anti-technology", this may not be true, but may be a misunderstanding of my tone, body language or word choice. It could also be a facet of an interview, ignoring other statements that may have shown a more balanced approach to technology. Credibility is important so that we can say that our findings do reflect the experiences of our participants and helps us to ensure an appropriate level of objectivity.

Credibility can be established through triangulation or through asking the participant to read the interpretations/results and say whether they agree with the researcher.

Triangulation is a "cross-checking" of data with the attempt of reaching the same conclusion by other means. One type is "method triangulation", where different methods are used to study the same behaviour. So, to determine how stress affects an individual, I may give them a questionnaire, carry out an observation and have a focus group. A second form of triangulation is researcher triangulation, where more than one researcher is carrying out an observation and the data can then be compared. Finally, there is theory triangulation, where a behaviour is studied by researchers of different theoretical backgrounds - for example, a biological, cognitive and sociocultural psychologist.

It is important to establish credibility. By using method triangulation and getting the same results, I can conclude that it was not simply my choice of method that led to the results. If more than one researcher comes to the same conclusion, then it is not just my own biases that led to the results.

There are two types of reflexivity. The first one is "personal." This is where the researcher reflects on how his or her own biases or personal experiences may have influenced their findings. This is important because it will help to reduce researcher bias. The second type of reflexivity is called "epistemological." This is when the researcher reflects on how they carried out the study and whether their choice of research method or procedure could have influenced the findings. This is important in order to establish the credibility of the findings.