Sleepy Mice Case Study: Implementation and Assessment.

Area of Science:

• Neuroscience
• Educational Technology
• Data Science Education

Background:

• Case studies are effective pedagogical tools for applying course content to real-world scenarios.
• Engaging students with authentic scientific datasets enhances learning outcomes.
• Sleep is a relevant and relatable topic for undergraduate students.

Purpose of the Study:

• To develop and evaluate the Sleepy Mice Case Study, integrating RStudio and a high-throughput sleep dataset.
• To assess the case study's impact on student learning objectives and confidence in neuroscience and data processing.
• To provide implementation best practices for educators utilizing the case study.

Main Methods:

• The Sleepy Mice Case Study was implemented in synchronous and asynchronous Introductory Neuroscience, Biopsychology, and Human Anatomy and Physiology courses.
• Students completed a series of assignments, including homework, in-class activities, and a take-home application.
• The case study utilized the Allen Institute for Brain Science's open-access high-throughput sleep dataset on mice.

Main Results:

• The case study demonstrated success through significant gains in student scores and confidence related to learning objectives.
• Most students reported positive engagement and enjoyment in learning about sleep deprivation.
• The case study proved versatile, applicable to various courses and teaching modalities.

Conclusions:

• The Sleepy Mice Case Study is a valuable and effective tool for teaching neuroscience content and data processing skills.
• Its flexible design allows for integration into diverse educational settings and student learning needs.
• Further implementation is encouraged to leverage its potential in science education.