Relationships and connections

tekijä: Tanja Tuulikki Välisalo Viimeisin muutos tiistai 09. maaliskuuta 2010, 11.22

 

circle_aimsaimsExploring BackgroundTemporal ProcessesRelationships and ConnectionsCause and EffectModels and TheoriesPredicting the FutureCritical Views and ChangeCaseCategories, Classes and TypesExperiencesBelieves, Opinions and AttitudesConstruction of MeaningsInterpretationPhenomena

 

Humanistic research often aims to present and explore relationships between phenomena or meanings. The aims of the research can be based on observations, which show connections or relationships of meanings between phenomena. The research can also aim at exploring the intensity of relationships and meanings. The presentation of connections and relationships is unsuitable for a clear analysis of causality.

 

Strategies

Research aiming to present the connections and relationships between meanings or phenomena by examining concrete materials such as text documents, audio recorded interviews, images and objects, can be defined as empirical research. In order to explore connections and relationships, you can use either a quantitative research strategy  of numeric variables or a qualitative research strategy. A qualitative approach focuses on how meanings are interrelated: an object, concept or action may produce specific meanings for other objects, concepts or actions. Phenomena are related to each other, but this is not understood or explained in terms of causal relations.

Research into connections and relationships can be based on several strategies:

Longitudinal research enables you to explore relationships and their qualities over a long period of time.

Cross-sectional research enables you to conduct a broad exploration of connections and relationships in different areas of culture and society at a certain point in time.

Historical research enables you to conduct a qualitative study.

Experimental research enables you to examine connections between variables.

 

Data Collection

You can study connections between phenomena and the relationships between meanings through different types of data collected by a variety of methods. You can use either data collected for previous research by another researcher (existing concrete materials) or collect / produce your own data during the research process. You can use a variety of research strategies: Population research is suitable when the quantity of available data on a phenomenon is small. Sampling is suitable when the quantity of available data on a phenomenon is too large for you to analyse all of it. Random sampling enables you to select a small element without bias. Purposive sampling (goal-directed sampling) enables you to select samples that match the aim of the study. For example, archival texts and documents are typical in historical research and are usually available in large quantities. While the majority may be relevant to your research, you can regulate which documents you want to analyse.

You may collect data for research on connections between phenomena and relationships between meanings from archives or through a follow-up study. Data can also be collected through an experiment or a survey.

 

Data Analysis

Both quantitative analysis and qualitative analysis methods are suitable for analysing connections between phenomena and relationships between meanings:

Correlation analysis is a form of quantitative analysis.

Hermeneutic analysis is a form of qualitative analysis.

Close reading of data is a form of qualitative analysis, enabling a deep understanding of the relations between meanings obtained through the analysis.

Thematic analysis is a form of qualitative analysis.

Typification is a form of qualitative analysis.

There are also, in different academic fields, various discipline-specific methods which enable analysis of the connections and relationships changes.  

 

Philosophy of Science

Quantitative analysis methods in the humanities are based on interpretivism. Views, which emphasize interpretation in the formation of meanings and subjectivity in meaning-making processes, obey the idea of relativism.

Quantitative analysis methods are based on positivism, which stresses the production of knowledge through exact measurements and use of numeric variables. Views emphasising the exactness and correctness of measured knowledge are based on realism, which views knowledge as objective.

Hermeneutic analysis modes are based on hermeneutics.

Close reading methods are based on hermeneutics

Research examples aiming to present connections between phenomena or relationships between meanings are available in:

Sulkunen, Sari, 2007. Text Authenticity in International Reading Literacy Assessment. Focusing on PISA 2000. Jyväskylä: University of Jyväskylä. (pdf)

Nieminen, Lea, 2007. A Complex Case. A Morphosyntatic Approach to Complexity in Early Child Language. Jyväskylä: University of Jyväskylä. (pdf)