Teach with Case Studies: Enhancing Data Science and Statistics Education
The power of case studies
In the ever-evolving landscape of data science and statistics education, case studies have emerged as a powerful pedagogical tool. At zyBooks, we recognize the value of real-world applications in fostering a deeper understanding of complex concepts. Our case studies, available in three key zyBooks—Data Science Foundations, Machine Learning, and Statistics for Decision Making—serve as a bridge between theoretical knowledge and practical application. Data Science Foundations has 12-14 case studies, Machine Learning has 13 case studies, and Statistics for Decision Making has 6 case studies.
Data science is such a new field that the pedagogy isn’t yet etched in granite. Instructors often shift into this subject from other disciplines, like I did, and have to figure it out on their own (again, like I did). I joined zyBooks to help solve this problem, and create the data science textbook I wish I had back at school.
Although the discipline is still evolving, through my own experience, research and talking with instructors across the country, I’ve evolved the following set of best practices that are invaluable in helping students master this subject – best practices you can put into action in your own classroom right away.
Real-world applications in Data Science Foundations
In our Data Science Foundations (DSF) zyBook, the “Customer Churn” case study exemplifies how companies predict customer turnover based on a customer’s profile and spending habits. This case study not only introduces students to the concept of customer churn but also demonstrates the practical application of data analysis techniques in a business context. By analyzing real-world data, students learn to identify patterns and make data-driven decisions, reinforcing the importance of data science in today’s business environment¹.
Deep learning in Machine Learning
The Machine Learning (ML) zyBook features the “Classifying Product Reviews Using RNNs” case study, which delves into the use of deep learning methods to categorize text samples, such as product reviews. This case study provides students with hands-on experience in implementing recurrent neural networks (RNNs) to solve real-world problems. By working through this case study, students gain a practical understanding of how deep learning models can be applied to natural language processing tasks, enhancing their ability to tackle complex data science challenges¹.
Statistical Analysis in Statistics for Decision Making
In the Statistics for Decision Making (SDM) zyBook, the “Activity Levels for Parents and Children” case study explores the correlation and regression techniques to describe how parents’ exercise habits influence their children’s activity levels. This case study illustrates the application of statistical methods and highlights the importance of data-driven insights in public health and behavioral studies. By engaging with this case study, students learn to apply statistical analysis to real-world scenarios, fostering a deeper appreciation for the role of statistics in decision-making processes².
Integrating case studies in the classroom
Case studies in zyBooks are designed to serve as a foundation for in-class discussions or as inspiration for semester-long projects. By presenting students with real-world problems, these case studies encourage critical thinking and collaborative learning. Professors can use these case studies to facilitate engaging discussions, allowing students to explore different perspectives and develop their problem-solving skills. Case studies also provide students with a model for class projects or writing about data and complex methods.
Moreover, case studies reinforce the data analysis lifecycle as a process rather than a mere collection of models or algorithms. By working through these case studies, students gain a holistic understanding of the data analysis process, from data collection and cleaning to analysis and interpretation. This comprehensive approach ensures that students are well-equipped to apply their knowledge in real-world settings, preparing them for successful data science and statistics careers.
Review these Related Resources
Open Case Studies: Statistics and Data Science Education through Real-World Applications – https://arxiv.org/pdfpdf2301.05298
Data Science – https://www.zybooks.com/data_science
Integrating Learning Sciences in STEM – https://www.zybooks.com/integrating-learning-sciences-in-stem-the-zybooks-model/
Conclusion
At zyBooks, we are committed to providing high-quality educational resources that bridge the gap between theory and practice. Our case studies in Data Science Foundations, Machine Learning, and Statistics for Decision Making exemplify this commitment by offering students practical, real-world applications of the concepts they learn. Integrating these case studies into your curriculum can enhance your students’ learning experience and prepare them for the challenges of the data-driven world.
