At Stanford, we recently placed three computer science courses online, using a similar format. Remarkably, in the first four weeks, 300,000 students registered for these courses, with millions of video views and hundreds of thousands of submitted assignments.
What can we learn from these successes? First, we see that video content is engaging to students — many of whom grew up on YouTube — and easy for instructors to produce.
Second, presenting content in short, bite-size chunks, rather than monolithic hourlong lectures, is better suited to students’ attention spans, and provides the flexibility to tailor instruction to individual students. Those with less preparation can dwell longer on background material without feeling uncomfortable about how they might be perceived by classmates or the instructor.
Conversely, students with an aptitude for the topic can move ahead rapidly, avoiding boredom and disengagement. In short, everyone has access to a personalized experience that resembles individual tutoring.
Watching passively is not enough. Engagement through exercises and assessments is a critical component of learning. These exercises are designed not just to evaluate the student’s learning, but also, more important, to enhance understanding by prompting recall and placing ideas in context.
Moreover, testing allows students to move ahead when they master a concept, rather than when they have spent a stipulated amount of time staring at the teacher who is explaining it.
For many types of questions, we now have methods to automatically assess students’ work, allowing them to practice while receiving instant feedback about their performance. With some effort in technology development, our ability to check answers for many types of questions will get closer and closer to that of human graders.
Asking questions of the professors The course will offer a forum in which you can pose your questions directly to the instructors. You can also see the questions of other students in this class and vote on them. The instructors will answer the top-voted questions. So for your question to make it to the top of the list, you will have to ask a question that appeals to many other students. Discussions There will also be a general discussion forum, in which you can discuss questions and interact with other students. You are not allowed to post solutions to active homework assignment and exams here, but you are allowed to discuss the material covered in class; and you can of course pose questions. Once the answers to a homework assignment have been posted you are free to discuss them, as well as sharing any code you may have written. Video Lessons Video lectures are the primary method for communicating content in this class. They are posted weekly, and are composed of many small chunks of 1 to 15 minutes in length. Professors Thrun and Norvig will cover key concepts of AI in these lectures. Lectures will be posted weekly for each topic, and you can view lectures at your own pace once they have been posted until the end of the course. Quizzes There will be online quizzes as well, which enable you to demonstrate your knowledge of the AI topics you just learned about. If you get a question wrong, no problem. Quizzes don't count towards your score. But you may find that you will be asked to watch specific videos that discuss certain mistakes you may have made. Homework assignments These are just like quizzes, but now your submission counts towards the score. Homework assignments will be available all week, and you must complete all the questions during the week they are available; otherwise they count for 0. We plan for a total of 8 homework assignments, of which your two lowest scores will not be counted towards your score. The remaining 6 assignments taken together