Intended learning outcomes By the end of the lecture & through appropriate reading you should be able to: Discuss differences between the Positivist & Interpretivist approaches to research Discuss the strengths & weaknesses of the Positivist & Interpretivist approaches to research Understand how both quantitative and qualitative testing fit in with these approaches.
Scientific thinking is ‘knowing, but with uncertainty’ ‘To the believer no proof is necessary, to the non-believer none is sufficient ’
Positivism & Interpretivism : Viewing the world through tinted lenses Positivism Interpretivism
Positivism & Interpretivism Two broad, but contrasting approaches to the nature of knowledge. Both have differing implications on: Types of research questions asked Subsequent methodology adopted Nature of the data collected The analysis and interpretation of such data
Positivism Only true knowledge is that which is scientific Generalisable laws of nature/natural science Objective measurements Discover laws from facts Careful research designs show causal relationships E.g. X causes Y
Characteristics of Positivist approach Control Control one variable and assess its influence on another E.g. The presence of crowd on shooting performance. Researcher can control crowd size Researcher can measure crowd size & performance Researcher can draw inferences from the data
Characteristics of Positivist approach Replication In order to explain a phenomenon the same results would need to occur if the experiment was repeated E.g. Larger crowd = decreased performance Hypothesis Testing This approach involves the creation and systematic testing of a hypothesis
Task 1 As a group take five minutes to identify the strengths and weaknesses of a positivist approach. Strengths: Inferences are possible Clear cut interpretation Straightforward planning Precision, control & objectivity Weaknesses Doesn’t allow for perceptions, beliefs, opinions, attitudes, emotions etc. Can we confirm hypotheses? Can we produce an objective truth?
Interpretivism Non-numerical measures (over simplify?) Meanings, values, explanations, perceptions etc. ‘Facts’ are what they mean to people Reality it multiple (different for everybody) Describe a school sports day you were involved in Reality is socially constructed in interactions They seem interested in ... so I’ll ...
Characteristics of Interpretivism Attempts to study of phenomena in it’s natural environment. Accept there are many interpretations of reality These interpretations are part of scientific knowledge Search for understanding rather than truth Coping with reoccurring injury
Task 2 As a group take five minutes to identify the strengths and weaknesses of an interpretivist approach. Strengths Insiders perspective Weaknesses Difficulties in legitimising research (?) Less generalisable (?) Longer time-scale
Quantitative & Qualitative research Refers to the characteristics of data collected by the researcher rather than the underlying philosophy of the nature of knowledge.
Quantitative Research Quantitative Research is the systematic investigation of quantitative properties and phenomena and their relationships. The objective of quantitative research is to develop and employ mathematical models, theories and/or hypothesis pertaining to natural phenomena. The process of measurement is central to quantitative research because it provides the fundamental connection between empirical observation and mathematical expression of quantitative relationships.
Quantitative Research Take objective measures and place a numerical value on them Positivists observe behaviours, and objectively measure and analyse them. Often, but not always numerical
Qualitative Research Qualitative Research is often adopted by sociologists and educators. It involves observation of data in a natural setting. Data is analysed and interpreted using description, narratives, quotes, charts and tables
Qualitative research Aims to capture meaning or qualities that are not quantifiable. Uses non numerical data Often collected over a period of time Issue of ‘how many’ is not relevant Is a rare experience any less significant than a common one – or may it be more meaningful?
Methods of data collection Quantitative Qualitative Experimental data Hypotheses Laboratory testing Fieldwork Archive work Others? Naturalistic data Research question/s Semi-structured interviewing Focus groups Diaries Participant observation Others ?
Mixed method protocols Here you may choose to combine both quantitative and qualitative approaches. There are two main ways in which to do this: One may facilitate the other –quantitative research may identify the existence of a phenomenon that qualitative research may explore. Both approaches investigate the same phenomenon; quantitative approaches used to simple numerical data from a large sample, whereas qualitative methods collect detailed data from a smaller sample
Mixed methods: a consideration Is there sufficient time to carry out multiple or mixed methods study? Often these methods are take longer to collect and require more money!
Summary Positivist: Quantitative What, where, when, how many? Predetermined design Establishes causality Confirms theory Interpretivism : Qualitative Why, how? Flexible design Explains causality Develops theory