Introduction : "Individual tutoring is perhaps the first instructional method. It dates back
at least to Socrates and the Socratic method. Although one-to-one tutoring by expert human tutors has been shown to be much more effective than typical oneto-
many classroom instruction (Bloom, 1984), it has not been economical to provide every child with an individual tutor. Lectures and books became pervasive in education to spread knowledge at lower cost. However, increasing
capabilities of computer hardware and software have been creating new opportunities to bring one-to-one tutoring to more students. Furthermore, computer technology provides an opportunity to systematically incorporate
advances in learning science into the classroom, to test associated principles of
learning, and best adapt them to the needs of students and teachers." read more... > see the resource
Introduction : "Carnegie Learning’s Cognitive Tutor programs give students the opportunity to receive individualized
attention, maximizing the amount of time spent actively learning and mastering fundamental sets of knowledge skills.
Cognitive Tutor programs are an innovative application of technology, applied content curriculum and cognitive science. An important component of the program is software that is intelligent. That is, it monitors the status of the
student’s knowledge on a moment-by-moment basis and tailors course material, based on these continual assessments." read more... > see the resource
This paper review the 10-year history of tutor development based on the ACT theory (Anderson, 1983,1993). We developed production system
models in ACT ofhow students solved problems in LISP, geometry, and algebra. Computer tutors were developed around these cognitive models.
Construction ofthese tutors was guided by a set of eight principles loosely based on the ACT theory. Early evaluations of these tutors usually but not always showed significant achievement gains. Best-case evaluations showed that students could achieve at least the same level of proficiency as conventional instruction in one third the time. Empirical studies showed that students were learning skills in production-rule units and that the best tutorial interaction style was one in which the tutor provides immediate feedback, consisting of short and directed error messages. The tutors appear to work better if they present themselves to students as nonhuman tools to assist learning rather than as emulations of human tutors. Students working
with these tutors display transfer to other environments to the degree that they can map the tutor environment into the test environment. These experiences have coalesced into a new system for developing and deploying tutors. This system involves first selecting a problem-solving interface, then constructing a curriculum under the guidance of a domain expert, then designing a cognitive model for solving problems in that environment,
then building instruction around the productions in that model, and finally deploying the tutor in the classroom. New tutors are being built in this system to achieve the NCTM standards for high school mathematics in an urban setting. read more... > see the resource
Now available in paper, The Architecture of Cognition is a classic work that remains relevant to theory and research in cognitive science. The new version of Anderson's theory of cognitive architecture -- Adaptive Control of Thought (ACT*) -- is a theory of the basic principles of operation built into the cognitive system and is the main focus of the book. read more... > see the resource
Rule-based cognitive models serve many roles in intelligent tutoring systems (ITS) development. They help understand student thinking and problem solving, help guide many aspects of the design of a tutor, and can
function as the “smarts” of a system. Cognitive Tutors using rule-based cognitive models have been proven to be successful in improving student learning in a range of learning domain. The chapter focuses on key practical
aspects of model development for this type of tutors and describes two models in significant detail. First, a simple rule-based model built for fraction addition, created with the Cognitive Tutor Authoring Tools, illustrates the importance of a model’s flexibility and its cognitive fidelity. It also illustrates the modeltracing algorithm in greater detail than many previous publications. Second, a
rule-based model used in the Geometry Cognitive Tutor illustrates how ease of
engineering is a second important concern shaping a model used in a large-scale
tutor. Although cognitive fidelity and ease of engineering are sometimes at
odds, overall the model used in the Geometry Cognitive Tutor meets both concerns to a significant degree. On-going work in educational data mining may lead to novel techniques for improving the cognitive fidelity of models and thereby the effectiveness of tutors. read more... > see the resource
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