Purpose: explain, gain insight and understanding of phenomena through intensive collection and study of narrative data

Approach: inductive, value-laden/subjective, holistic, process-oriented

Hypotheses: tentative, evolving, based on the particular study

Lit. Review: limited, does not always heavily influence a particular study

Setting: naturalistic, as much as possible

Sampling: for the purpose, not necessarily representative, for in-depth understanding

Measurement: narrative, ongoing

Design and Method: flexible, specified only generally;

Non-intervention, minimal disturbance, such as historical, ethnographic, or case studies

Data Collection: document collection, participant observation, informal interviews, field notes

Data Analysis: raw data is words/ ongoing, involves synthesis

Data Interpretation: tentative, reviewed on ongoing basis, speculative

• Think that social sciences cannot be well-studied with the same methods as natural or physical sciences
• Feel that human behavior is context-specific; therefore, behavior must be studied holistically, in situ, rather than being manipulated
• Employ an 'insider's' perspective; research tends to be personal and thereby more subjective.
• Do interviews, focus groups, field research, case studies, and conversational or content analysis.

• Qualitative research with more structure and less subjectivity
• Increased application of both strategies to the same study ("mixed methods")
• Evidence-based practice emphasized in more fields (nursing, social work, education, and others).

Purpose: explain, predict or control phenomena through focused collection and analysis of numberical data

Approach: deductive; tries to be value-free/has objectives/out-come oriented

Hypotheses: Specific, testable, and stated prior to study

Lit. Review: extensive, may significantly influence a particular study

Setting: controlled to the degree possible

Sampling: uses largest manageable random/randomized sample, to allow generalization of results to larger populations

Measurement: standardized, numerical, "at the end"

Design and Method: Strongly structured, specified in detail in advance;

Involves intervention, manipulation, and control groups; descriptive, correlational, experimental

Data Collection: via instruments, surveys, experiments, semi-structured formal interviews, tests, or questionnaires

Data Analysis: raw data is numbers; at end of study, usually statistical

Data Interpretation: formulated at end of study; stated as a degree of certainty

• Think that both natural and social sciences strive to explain phenomena with confirmable theories derived from testable assumptions
• Attempt to reduce social reality to variables, in the same way as with physical reality
• Try to tightly control the variable(s) in question to see how the others are influenced.
• Do experiments, have control groups, use blind or double-blind studies; use measures or instruments.

Adapted and expanded from a handout by Suzy Westenkirchner. Used with permission. Necia Parker-Gibson

See also Trochim, William M. The Research Methods Knowledge Base, 2nd Edition. Accessed from <http://www.socialresearchmethods.net/kb/> (version current as of October 20, 2006).on November 1, 2010.

Empirical Research: General Structure of Journal Articles

Handout by Esther Grassian

• Article Title

• Author(s) & Affiliation

• Abstract

• Introduction/History/Background

• Previous Research/Literature Review (related to this topic)

• Present Approach/ Objectives/Hypothesis/Model

• Methods/Study Design/Description of Statistical Analysis Methodology

• Results and Statistical Analysis

• Theoretical Implications/Discussion

• Conclusions (often includes areas which the authors believe merit further study)

• References

• Appendix

• Figures (may be at end of paper or interspersed throughout)

Adapted from:

Li, V. O. K. (1999) “Hints on Writing Technical Papers and Making   Presentations.” IEEE Transactions on Education. 42 (2):134-137.

E. Grassian 16 May 2003