Learning Problem Solving Heuristics from Worked Examples
نویسندگان
چکیده
Much human learning of mathematics takes place from worked examples, yet this is a subject that has not received much study in Cognitive Science. A major problem is to ensure that a model can learn in a general way, and not be limited to a small subset of mathematics, such as Calculus. This paper describes a computational model of how students learn problem solving heuristics. The model is implemented as the computer program HAL (Heuristic Applier/ Learner), and is an extension of the Mathematics Understander system (MU).
منابع مشابه
Examples and Tutored Problems: Adaptive Support Using Assistance Scores
Research shows that for novices learning from worked examples is superior to unsupported problem solving. Additionally, several studies have shown that learning from examples results in faster learning in comparison to supported problem solving in Intelligent Tutoring Systems. In a previous study, we have shown that alternating worked examples and problem solving was superior to using just one ...
متن کاملThe role of worked-examples in schema acquisition: Implications and preliminary findings
Research has shown that worked-examples play an important role in learning and problem solving and are crucial to cognitive skill acquisition. We propose to extend previous work on example-based learning systems with regard to the instructional design of the examples themselves. This can be done by drawing on current developments in Cognitive Load Theory. We aim to explore the roles that worked...
متن کاملWhy Tutored Problem Solving May be Better Than Example Study: Theoretical Implications from a Simulated-Student Study
Is learning by solving problems better than learning from worked-out examples? Using a machine-learning program that learns cognitive skills from examples or by being taught, we have conducted a study to compare three learning strategies: learning by solving problems with feedback and hints from a tutor, learning by generalizing worked-out examples exhaustively, and learning by generalizing wor...
متن کاملImproved teaching–learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems
Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having ‘g’ operations is performed on ‘g’ operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem...
متن کاملAdaptive Support versus Alternating Worked Examples and Tutored Problems: Which Leads to Better Learning?
Learning from worked examples has been shown to be superior to unsupported problem solving when first learning in a new domain. Several studies have found that learning from examples results in faster learning in comparison to tutored problem solving in Intelligent Tutoring Systems. We present a study that compares a fixed sequence of alternating worked examples and tutored problem solving with...
متن کامل