Education demands data. This isn’t just about lively debate; it requires educators to act as educational researchers, asking clear questions, designing robust data collection methods, and analyzing findings to draw reasonable conclusions. At the heart of this process lies the critical twin pillars of ethical data gathering and rigorous data validation. Only through these can we establish the “facts” necessary to transform raw data into information, knowledge, and ultimately, wisdom, thereby truly advancing educational practice.
Ethical Data Gathering: Respecting Every Participant
The responsibility of an educational researcher begins with an unwavering commitment to ethics. Whether conducting large-scale academic studies or localized action research to improve school practice, researchers must respect the subjects, the process, and the community. This professional duty translates into concrete actions:
Protecting subjects: Researchers must not endanger the physical or emotional health of subjects. Steps must be taken to ensure the privacy of subjects and to preserve their right to withdraw from the study without penalty. It’s crucial to remember that rewarding subjects for participating poses a threat to data validity and must be avoided.
Purposeful data collection: Ethical research necessitates gathering only the necessary data. This is vital because every piece of data collected from a population can influence subsequent data and subjects’ perceptions, potentially distorting future findings.
Oversight and review: For large-scale research, proposals are submitted to an institutional review board (IRB), which rigorously vets methods to ensure ethical conduct and data necessity before any collection begins. While action researchers in local settings may not have access to an IRB, they are well-advised to seek review from knowledgeable outsiders to ensure their methods are appropriate and ethical. Furthermore, evaluative research, highly relevant to progressive discourse, must be of relevance to the community and conducted in an efficacious manner to provide valid data.
Validating Data: Transforming Observations into Established Facts
Once data is ethically gathered, its utility for progressive discourse hinges on its quality and validation. For conclusions to move beyond tentative observations and become established facts, educators must meticulously assess research quality.
Different problems require different data and, consequently, different methods.
Quantitative methods gather numeric data, analyzed statistically to describe populations or test hypotheses89. This includes using descriptive statistics (like means) to compare group performance or inferential statistics to establish correlations9. Tools include questionnaires, surveys, checklists, inventories, and scales.
Qualitative methods gather narrative data, which are interpreted to elucidate hypotheses8. They are particularly suited for “wicked problems” where understanding participants’ perspectives and experiences is key. The language subjects use is a rich source of data, and methods like interviews (individual and group), observation protocols, and document analysis are common. Qualitative data is often presented as themes or in case studies.
Assessing the quality of research varies based on the methodology:
For quantitative research, professionals consider:
- Internal validity: Identifying a real effect, not an extraneous one.
- External validity: The ability to observe the effect in other populations.
- Reliability: The ability for other researchers to observe the effect using different tools.
- Objectivity: Ensuring unbiased research conduct.
For qualitative research, quality is assessed using terms like:
- Credibility: Thoroughly describing phenomena.
- Transferability: Observations can be made in other populations.
- Dependability: Thoroughly describing methods.
- Confirmability: Replacing objectivity with a focus on confirming findings.
Regardless of the methods used, researchers seek to confirm their observations through triangulation. If the same conclusion can be reached by three different measures and methods, the hypothesis gains strong support. In the context of progressive discourse, if at least three threads of evidence support a clarification or improvement of a conceptual artifact, it can legitimately become the fact upon which future discourse is built. Just as academic researchers seek multiple data sources, facts supporting decisions in progressive discourse also demand multiple sources of evidence.
By embracing these rigorous ethical and validation practices, educational researchers empower progressive discourse to move beyond speculation, grounding improvements in curriculum and instruction in robust, verifiable facts.