Lecture 6 - Online Data Collection Flashcards
What are the main advantages of online data collection?
Convenience, larger sample sizes, faster data collection, and access to diverse demographics.
How did COVID-19 impact online research?
It increased reliance on online data collection methods, including video conferencing for qualitative research and broader participant pools.
How does online research address the replication crisis?
By allowing larger, more diverse, and replicable sample sizes with greater statistical power.
List key ethical considerations in online research.
Obtaining informed consent, pre-registering studies, maintaining participant confidentiality, and ensuring fair compensation.
Why are attention checks crucial in online surveys?
They ensure data quality by identifying inattentive participants.
What are the initial steps in designing an online study?
Define the population, choose the online method, create a clear and engaging layout, and conduct a pilot study.
Name two strengths of online research.
Accessibility to marginalized groups and reduced logistical burden for researchers.
What are common challenges in online research?
Response rates, maintaining data quality, digital inequalities, and ethical concerns.
Name a method to enhance data quality in online studies.
Using metadata to clean data and implementing specific demographic filters.
Why is piloting important in online research?
Piloting ensures instructions are clear, tasks are feasible, and surveys are engaging. It helps avoid wasting resources on low-quality data
Discuss the ethical challenges associated with online data collection.
Challenges include obtaining informed consent in a virtual environment, ensuring data confidentiality, fair compensation for participants, and addressing the blurring line between public and private online spaces
How to use Metadata to clean data.
Metadata refers to the supplementary information that is recorded during data collection, such as:
Time taken to complete the survey: If a participant finishes too quickly or too slowly, their data might be flagged as suspicious.
IP address or geolocation: Can identify duplicate submissions or ensure participants are from the intended geographical area.
Device and browser information: Helps detect unusual patterns (e.g., automated bots or participants using incompatible devices).
Completion status and progress tracking: Ensures participants completed all sections of the survey properly.
By analyzing metadata, researchers can:
Remove responses that show signs of low effort or inattentiveness.
Identify potential fraudulent responses, such as bots or repeat participants.
Exclude data from participants who did not meet the study’s criteria (e.g., taking significantly less time than expected).
