Data Validity and Reliability

Module 3, Part 1: Research Design

Triangulation

Action research commonly employs triangulation as a strategy to establish validity and reliability.

Triangulation involves collecting and analyzing various forms of data to address research questions, mitigating gaps that might arise from relying on a single data source. This approach facilitates corroboration by examining independent pieces of evidence that converge on the same conclusion.

Diagram of triangulation between observing behaviors, conducting surveys, and polling software analytics.

For instance, in a study on enhancing student engagement through online polling in large classrooms, researchers might observe behaviours, conduct surveys, and analyze polling software analytics. Analyzing these diverse data sets individually and collectively ensures alignment, enhancing the credibility of conclusions.

Triangulation, although traditionally involving three data sources, can include more for greater research study reliability. However, researchers must be mindful of increased time and potential complexity in data analysis associated with incorporating multiple data sources, balancing the benefits with practical considerations.

Triangulation Matrix Example

A Triangulation Matrix can be used to determine what sources of data can be used. The table below identifies three different types of data (Artifact, Observation, and Inquiry).

Research Question Artifacts Observational Data Inquiry Data
How can the use of online polling increase student engagement in large classes? Analytics from polling software Field notes – record body language during class to see if there are differences when polling is used Attitude Scale that asks students about the use of online polling

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Action Research Handbook Copyright © by Dr. Zabedia Nazim and Dr. Sowmya Venkat-Kishore is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.

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