Glossary of Key Terms –
Audience effects: this is how a passive audience can influence someone’s performance on a task. For instance, during an observation, the presence of the researchers may influence the behaviour of the subjects.
Contextual description: a detailed account of contextual factors that may influence the interpretation and analysis of the data. Examples of contextual information would focus on such factors as the environment in which the observation took place and the characteristics of the participants. For example, relevant considerations in Rosenhan’s study on psychiatric hospitals could include details such as the physical layout of the psychiatric wards (e.g. bars on windows, Doctor’s office sealed and locked, etc.)
Covert Observation: when the participants are not aware that they are being studied.
Credibility: The extent to which the results and conclusions of a qualitative research study can be confirmed as accurate and truthful. (credible = how readily something can be believed). It is similar to validity in quantitative research.
Data saturation: the point where no new information is found within the data being analysed.
Data: Facts and statistics collected for reference and/or analysis.
Descriptive data: this means recording only what actually happens, such as actions and words.
Disclosure: is revealing information to someone. In observations, it refers to a kind of informed consent and debriefing.
Ecological validity: Increasing the accuracy of the data gathered by collecting it in a natural environment.
Evaluative data: making notes about judgments on the behaviour being observed.
Hawthorne Effect: is when participants change their behaviour based on their understanding of what is being studied.
Inductive Content Analysis (ICA): the process of drawing conclusions based on recurring themes in the data.
Inductive: drawing conclusions from what you observe. In this context, it means drawing conclusions regarding individual’s experiences of phenomena based on data collected during observations.
Inferential data: making notes on what the behaviours observed might mean (making inferences is like “reading between the lines”).
Inter-observer reliability: Having more than one observer gathering data to increase the validity of the data gathered.
Naturalistic Observation: when the observation happens in a natural environment.
Non-participant Observation: when the observer (i.e. the researcher) is isolated from the situation being studied.
Objectivity: remaining free from bias during the observation.
Observation method: The design of the observation. i.e. whether it is covert, non-participant, etc.
Overt Observation: when the participants are aware that they are being studied.
Participant expectations (reactivity): How the participants attitudes towards the research context can affect their behaviour, and thus the data gathered.
Participant Observation: when the observer (i.e. the researcher) is taking part in the situation being studied.
Personal reflexivity: Reflecting on the ways in which the personal qualities of the researcher may influence the research process.
Phenomenology: The study of individuals’ experiences of phenomena (e.g. events, situations, belonging to groups, etc.)
Phenomenon: a situation that is observed to have happened, especially one whose cause or explanation is in question. In qualitative research, phenomena (plural of phenomenon) refers generally to the event or situation that an individual has experienced. Examples of phenomena in qualitative research include the use of social media, being a single parent, living in impoverished conditions, being homeless, drug addiction, etc.
Qualitative data: Information that needs describing in sentence form. They are qualities, which are more subjective.
Qualitative research: a research method that gathers qualitative data through the use of such methods as observations and interviews. It often involves describing behaviour and experiences of phenomena, as opposed to finding causes of behaviour or establishing cause-and-effect relationships.
Quantitative data: Information in the form of numbers and figures that have pre-determined and set values. They are quantities.
Quantitative research: a research method that aims at collecting objective data and establishing a cause and effect relationship between variables and behaviour.
Raw theme: an initial point or idea that is stated in the data.
Reflexivity: The process of a researcher being aware of all the possible ways in which they can influence the research process and so they reflect and think about this in order to minimize the chances that their bias will interfere with the research. It is the importance that researchers are aware that because the data is qualitative in nature, they have the potential to bias the results at many points within the research. Being aware of this will hopefully reduce the impact of researcher bias on the research.
Representative sample: a group of participants that are selected because their results will have a high probability of being able to be generalized to a wider group. (Qualitative research is less interested in generalizability than quantitative research).
Researcher Bias: the inaccuracy of data recording by researchers because of their personal biases. This is why triangulation and reflexivity are important.
Researcher Bias: when a researcher’s own views, beliefs or opinions influence the research method. They may influence the research at any stage, such as design, data gathering or analysis.
Researcher bias: when the researcher’s own opinions or views interfere with the data gathering or analysis stages of the research.
Researcher Triangulation: in the observation context, this means that more than one researcher will conduct the thematic analysis in order to increase the validity of the results.
Researcher triangulation: to reduce the possibility of bias, it is often useful to have more than one researcher conducting the observation. This is researcher triangulation.
Retrospective consent: this involves obtaining consent from participants after the observation has occurred.
Semi-structured observations: The observer has loose guidelines on what data to gather.
Spot light anxiety: an increased feeling of nervousness when put on the spot to perform a task. This will affect the performance of the task.
Spotlight effect: This is the tendency for people to overestimate how much attention others are focusing on them. This could lead to anxiety, which may influence the behaviour of research participants.
Structured observation: The researcher has strict guidelines on what data to gather.
Subordinate theme: a narrower example of a theme that fits within a broader superordinate theme.
Superordinate theme: a larger category of themes.
Thematic analysis: the breaking down of the data to uncover the recurring themes within the research so conclusions can be drawn.
Triangulation: Using more than one method or researcher to collect and/or analyse the data. Again, this is to increase the credibility of the research by reducing researcher bias.
Type of data: the types of notes that the observers are making; descriptive, inferential or evaluative.
Unstructured observation: The researcher gathers data on any and all behaviours observed.