Reframing data ethics in research methods education: a pathway to critical data literacy.

Area of Science:

• Higher Education Pedagogy
• Data Ethics
• Research Methods

Background:

• Existing data ethics training often focuses narrowly on informed consent.
• Higher education lacks a standardized framework for critical data literacy.
• Data science and research methods courses need to integrate ethical considerations more deeply.

Purpose of the Study:

• To develop a comprehensive ethical framework for critical data literacy.
• To guide the integration of data ethics into research methods and data science curricula.
• To foster a more nuanced understanding of ethical data practices in academia.

Main Methods:

• Systematic review of 250 research methods syllabi and 80 data science syllabi.
• Analysis of 12 existing data ethics frameworks from various sectors.
• Literature review encompassing data practices, research ethics, data ethics, and critical data literacy.

Main Results:

• Identified gaps in current data ethics education across disciplines.
• Developed a transversal ethical framework applicable across higher education.
• Demonstrated the need to address techno-centric environments and power hierarchies in data ethics.

Conclusions:

• Ethical training must evolve beyond informed consent to critical data literacy.
• An integrated ethical framework can empower educators to teach responsible data use.
• Fostering ethics as a method protects vulnerable populations and empowers communities through research.