Students watch short videos and answer a short quiz about the lecture before coming to class. During class, I start by answering students' questions and work through some examples, and then students work on group activities related to the concepts discussed in the lecture.
Students work on a semester-long, team-based, realistic (uses real datasets or solves a real-world problem) project designed to challenge them 1) to apply concepts taught in class on a domain of their choice and 2) to learn how to communicate with their teammates, and 3) to learn new skills that are not taught in class.
ONLINE ASSESSMENTS FOR DATABASE PROGRAMMING ASSIGNMENTS
I developed a sophisticated external grading infrastructure to enable online and auto-graded assignments for three database systems (MySQL, MongoDB, and Neo4J). Online auto-graded assessments provided students with immediate feedback and an excellent opportunity to learn at their own pace.
Auto-generated questions help our students learn and practice non-coding database concepts. We developed sophisticated assessments covering core concepts related to database, including storage and indexing, transaction management, and query processing and optimization. These questions also help instructors spend less time developing questions, freeing more time to focus on other essential aspects of the course, such interacting with students.
We have developed AI-Based system that determines trends in students' database programming in real-time. This system produces intuitive categories of student solutions to database programming assignments, allowing instructors to address a variety of student approaches and thus create a more responsive classroom.
As part of a SIIP funded research project, we developed the infrastructure needed for Prairielearn to support group assessments. This new functionality allowed instructors to offer online collaborative assignments and collect data about teams' collaborations and work habits.