Abstract
Worked-out examples have been shown to increase learning gains over problem solving alone. These increases are even greater in novices and those who are learning algorithmic topics, such as those in Computer Science. We have integrated this strategy into our Intelligent Tutoring System and evaluated it on undergraduate students learning the linked list data structure. Although promising, we have identified behavioral differences between high and low gainers - spending less time on an example, and prematurely quitting them led to greater learning.
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