The current practice at most institutions is to use a learning management system (Canvas, Blackboard, or Desire2learn) to deliver online content, and a separate proprietary homework grading program associated with a textbook (Pearson/ Mastering Physics , WileyPlus, or WebAssign) which typically cost the students over $250 per class. This additional cost is a burden to all students, but affects low socioeconomic status and first-generation college-going students disproportionately. The project will utilize well regarded open source textbooks coupled with interactive and engaging digital content to produce high quality teaching materials which can be widely distributed at low cost.
This project builds on a previously developed software platform to create a coherent learning delivery system that will feature, interactive content, embedded open source textbooks, problem sets with solutions, and algorithms to implement mastery-based adaptive learning. The project team, which includes faculty from the University of California, Irvine (UCI), Orange Coast College (OCC), and Golden West College (GWC), will use this system to build 4 new adaptive courses (3 physics and 1 chemistry) and add adaptive functionality to an engineering dynamics course. These courses will have innovative dynamic content and automatically graded problem sets with software tags that correspond to clearly defined learning goals. Used together with well-regarded open source textbooks, the interactive content and adaptive problems will have the potential to replace expensive commercial packages that are now in common use. Through these courses, the project will impact approximately 5400 students in each project year.
These online courses will be adaptive and based on a mastery of learning goals paradigm. Instead of exposing all students to the same content and problem sets, the courses will deliver individually tailored content that will guide students with a broad range of initial preparation to achieve mastery. This approach will level the playing field for students from diverse backgrounds and increase retention in STEM subjects. Modern computer technology will be utilized to grade more realistic complex symbolic problems. The instantaneous feedback that this provides will promote student learning and reduce the workload for instructors.
The learning delivery system developed through this project will also allow for the construction of a rich data set of student performance and behavior which will be used in education research. The software will record fine grain data including data on learner interactions with the system and the time spent on each piece of material. The data will be used to correlate performance with socioethnic factors, track performance and learning from one course to another, and provide feedback and nudges to improve study habits and time management.