Intelligent Tutor Feedback [85395 Final Paper]

In my sophomore spring (2020), I took the class Applications in Cognitive Science (85-395/795) with Dr. Roberta Klatzky, and in the term paper, we were asked to write about a cognitive science’s application in real life, summarize its theoretical foundations and evaluate the product.

Inspired by another graduate-level seminar course that I was taking that semester with Dr. Kenneth Koedinger, Human Learning and How to Optimize It (05-899), I wrote about Intelligent Tutoring Systems (ITS), and in particular its feedback functionality with regard to students’ behaviors.

In the final paper, Performance or Learning1? Feedback provided by cognitive tutors may change the outcome, my main idea is that

  1. immediate and corrective feedback work better for short retention interval, improves the speed of learning, and thus result in better performance, but it fails to support transfer learning;
  2. in contrast, delayed and elaborative feedback better support transfer and long-term retention, which describe greater learning versus performance gain.
  1. “performance” and “learning” mean different things in the educational literature.