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Writing a methodology

The methods you use during your research are essential, especially if you want to ensure your research is accessible and available for people to replicate and verify your results. The type of methodology you use is essential as well, since it dictates what approach you might take throughout the experimental stage.

Section Title

Define Research Variables and Scope

Start by identifying and defining key variables to establish what you are measuring or observing. Specify your study’s scope, including the demographic, time frame, and any other relevant factors. For instance, if researching social behavior in digital spaces, clarify which platforms or user demographics you are focusing on.

Learn more about variables in the menu below:

Select Appropriate Research Methods

Choose methods that best fit your research objectives. Consider qualitative methods (interviews, observations) if the goal is to explore behavior or perceptions in depth, or quantitative methods (surveys, statistical analysis) if looking for patterns or correlations. A mixed-methods approach could also add depth, combining data types for a comprehensive analysis.

Plan for Data Analysis and collection

Detail your approach to analyzing data, whether through statistical software, coding for themes in qualitative data, or computational models. Mention specific techniques or frameworks (like regression analysis, thematic coding, or machine learning) that will help interpret your findings accurately.

you must also specify how you intend to collect the data in your research, and that requires a ton of background information to properly breakdown in your publication.

Address Potential Challenges

Identify possible obstacles and any limitations your study may encounter, such as sample size restrictions, data access, or uncontrollable variables. Prepare mitigation strategies to handle these issues and discuss how they may affect your results.

Methodology samples:

Here's a condensed version of a methodology written for one of our successful publications:

This study employs a structured methodology to design, simulate, and test an electrooculography (EOG) circuit interfaced with a microcontroller for digital signal acquisition. The EOG circuit is built around the TL072 op-amp, chosen for its high input impedance and low noise, essential for amplifying weak EOG signals (50 µV to 3500 µV). The initial preamplifier stage uses an instrumentation amplifier configuration, with a gain of 40,000 V/V to bring signals within the detectable range, producing output voltages between 5 mV and 350 mV for the filtering stages. A band-pass filter then refines the signal to retain only EOG-relevant frequencies (0.1 Hz to 30 Hz), while a second amplification stage (gain of 10,000 V/V) prepares the signal for the Arduino Uno’s ADC input. The Arduino, with a 10-bit ADC, samples at 256 Hz, providing real-time voltage data that correlates with eye movements, ultimately enabling precise angular displacement analysis.