AI Assist: Data Collection

SoTL Research Foundations: Data Collection

AI Assist

Artificial intelligence (AI) can greatly assist SoTL researchers in various aspects of data collection. For obtaining necessary permissions, AI can help draft research proposals by providing templates and suggesting best practices based on previous successful submissions. AI chatbots can guide researchers through the IRB application process, offering tips on addressing common ethical concerns and ensuring all required information is included.

When planning data collection, AI tools can analyze the research prospectus and provide feedback on its comprehensiveness and clarity. AI can also help identify the most appropriate data collection methods and instruments by comparing the research objectives with existing SoTL studies. For example, an AI tool could suggest using a specific student engagement survey validated in similar studies.

In recruiting participants, AI can aid in developing recruitment materials, such as emails or LMS announcements. AI can offer different written options based on the intended audience to ensure higher participation rates.

When retrieving data from secondary sources, AI can streamline the process by quickly extracting relevant data from large datasets, ensuring accuracy and completeness. This can be helpful with sentiment analysis or other text-based machine-learning tasks.

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SoTL Helper (AI - POE external): https://poe.com/SoTLCIRTBOT49

Site Authorization: https://research.gcu.edu/integrity/site

Research Consultation: https://cirt.gcu.edu/research/support/consultation

THINK: https://cirt.gcu.edu/research/support/clubs

IRB: https://research.gcu.edu/irb

SoTL Steps: Collect Data: https://cirt.gcu.edu/blogs/sotl-news/sotl-step-3-collect-the-data

RR: Collect in Qualitative Descriptive: https://cirt.gcu.edu/resources/students/features_of_qualitative_descriptive_studies/data

RR: Collect in Mixed Methods: https://cirt.gcu.edu/research/develop/research_ready/mixed_methods/4

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Related Resources

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