Chris Piech is a professor of computer science who studies how computers can help students learn. In comparing human- and computer-aided education, he says humans are great one-on-one, but AI is more consistent at grading and feedback. He and colleagues have created several generative AI grading apps to take advantage of these relative strengths, as he tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.
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Chapters:
(00:00:00) Introduction
Host Russ Altmans introduces guest Chris Piech, a professor of computer science at Stanford University.
(00:01:50) Defining Coding and Its Challenges
What coding entails for beginners and the challenges associated with learning to code.
(00:03:37) Enhancing Learning with Computers
How computers and AI can be used to make learning more enjoyable and effective.
(00:05:12) Human Connection in Education
The significance of teacher-student relationships and how recent learners can be effective teachers.
(00:07:02) AI and Coding Education
The impact of AI on professional coding and how it can enhance the learning experience for new coders.
(00:08:48) Joy of Programming
The creative joy of programming and how AI tools can elevate the creation process.
(00:11:57) Comparing Human and AI Tutors
Results from experiments comparing the effectiveness of human and AI tutors.
(00:14:43) Fair and Effective Assessment
Challenges and strategies for fair and effective computational assessment of students' work.
(00:16:42) Addressing Bias and Fairness in Grading
Demographic fairness in grading algorithms and the potential biases in different subjects.
(00:20:52) Interactive and Unstructured Feedback
Using AI to provide feedback on unstructured and interactive student work, like games and apps.
(00:25:30) Expanding Beyond Academic Tests
Application of AI in non-academic assessments, such as medical tests, to improve accuracy and efficiency.
(00:27:42) Generative Grading
Introduction to generative grading, where AI generates potential misconceptions to help with grading and feedback.
(00:31:37) Conclusion
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