Empirical Research can be defined as "research based on experimentation or observation (evidence)". Such research is conducted to test a hypothesis.
This article is a part of the guide:Discover 14 more articles on this topic
The word empirical means information gained by experience, observation, or experiment. The central theme in scientific method is that all evidence must be empirical which means it is based on evidence. In scientific method the word "empirical" refers to the use of working hypothesis that can be tested using observation and experiment.
Empirical data is produced by experiment and observation.
Objectives of the Scientific Research Process
- Capture contextual data and complexity
- Identify and learn from the collective experience of others from the field
- Identification, exploration, confirmation and advancing the theoretical concepts.
- Further improve educational design
Objectives of the Empirical Research
- Go beyond simply reporting observations
- Promote environment for improved understanding
- Combine extensive research with detailed case study
- Prove relevancy of theory by working in a real world environment (context)
Reasons for Using Empirical Research Methods
- Traditional or superstitional knowledge has been trusted for too long
- Empirical Research methods help integrating research and practice
- Educational process or Instructional science needs to progress
Advantages of Empirical Methods
- Understand and respond more appropriately to dynamics of situations
- Provide respect to contextual differences
- Help to build upon what is already known
- Provide opportunity to meet standards of professional research
In real case scenario, the collection of evidence to prove or counter any theory involves planned research designs in order to collect empirical data. Several types of designs have been suggested and used by researchers. Also accurate analysis of data using standard statistical methods remains critical in order to determine legitimacy of empirical research.
Various statistical formulas such uncertainty coefficient, regression, t-test, chi-square and different types of ANOVA (analysis of variance) have been extensively used to form logical and valid conclusion.
However, it is important to remember that any of these statistical formulas don't produce proof and can only support a hypothesis, reject it, or do neither.
Empirical cycle consists of following stages:
Observation involves collecting and organizing empirical facts to form hypothesis
Induction is the process of forming hypothesis
Deduct consequences with newly gained empirical data
Test the hypothesis with new empirical data
Perform evaluation of outcome of testing