A cognitive tutor is a particular kind of intelligent tutoring system that utilizes a cognitive model to provide feedback to students as they are working through problems. This feedback will immediately inform students of the correctness, or incorrectness, of their actions in the tutor interface; however, cognitive tutors also have the ability to provide context-sensitive hints and instruction to guide students towards reasonable next steps.

Introduction

The name of Cognitive Tutor now usually refers to a particular type of intelligent tutoring system produced by Carnegie Learning for high school mathematics based on John Anderson's ACT-R theory of human cognition. However, cognitive tutors were originally developed to test ACT-R theory for research purposes since the early 1980s and they are developed also for other areas and subjects such as computer programming and science. Model tracing and knowledge tracing are essentially used to monitor students' learning progress, guide students to correct path to problem solving, and provide feedback.

The Institute of Education Sciences published several reports regarding the effectiveness of Carnegie Cognitive Tutor. A 2013 report concluded that Carnegie Learning Curricula and Cognitive Tutor was found to have mixed effects on mathematics achievement for high school students. The report identified 27 studies that investigate the effectiveness of Cognitive Tutor, and the conclusion is based on 6 studies that meet What Works Clearinghouse standards. Among the 6 studies included, 5 of them show intermediate to significant positive effect, while 1 study shows statistically significant negative effect. Another report published by Institute of Education Sciences in 2009 found that Cognitive Tutor Algebra I to have potentially positive effects on math achievement based on only 1 study out of 14 studies that meets What Works Clearinghouse standards. It should be understood that What Works Clearinghouse standards call for relatively large numbers of participants, true random assignments to groups, and for a control group receiving either no treatment or a different treatment. Such experimental conditions are difficult to meet in schools, and thus only a small percentage of studies in education meet the standards of this clearinghouse, even though they may still be of value.

Theoretical foundations

Four-component architecture

Intelligent tutoring systems (ITS) have a four-component architecture: a domain model, a student model, a tutoring model and an interface component.

The domain model contains the rules, concepts, and knowledge related to the domain to be learned. It helps to evaluate students' performance and detect students' errors by setting a standard of domain expertise.

The student model, the central component of an ITS, is expected to contain knowledge about the students: their cognitive and affective states, and their progress as they learn. The function of the student model is threefold: to gather data from and about the learner, to represent the learner's knowledge and learning process, and to perform diagnostics of a student's knowledge and select optimal pedagogical strategies.

The tutoring model uses the data gained from the domain model and student model to make decisions about tutoring strategies such as whether or not to intervene, or when and how to intervene. Functions of the tutoring model include instruction delivery and content planning.

The interface component reflects the decisions made by the tutoring model in different forms such as Socratic dialogs, feedback and hints. Students interact with the tutor through the learning interface, also known as communication. The interface provides domain knowledge elements. A tutoring system adopting a cognitive model is called a cognitive tutor.

A cognitive model is an expert system that generates a multitude of solutions to the problems presented to students. The cognitive model is used to trace each student's solution through complex alternative solution paths, enabling the tutor to provide step-by-step feedback and advice, and to maintain a targeted model of the student's knowledge based on student performance.

Cognitive Tutors

Cognitive Tutors provide step-by-step guidance as a learner develops a complex problem-solving skill through practice. Typically, cognitive tutors provide such forms of support as: (a) a problem-solving environment that is designed rich and "thinking visible"; (b) step-by-step feedback on student performance; (c) feedback messages specific to errors; (d) context-specific next-step hints at student's request, and (e) individualized problem selection.

Both cognitive model and two underlying algorithms, model tracing and knowledge tracing, are used to monitor the student's learning. In model tracing, the cognitive tutor uses the cognitive model in complex problems to follow the student's individual path and provide prompt accuracy feedback and context-specific advice. In knowledge tracing, the cognitive tutor uses a Bayesian Knowledge Tracing method of evaluating the student's knowledge and uses this student model to select appropriate problems for each student.

Application and utilization

The first real world applications of cognitive tutors were in the 1980s and involved a geometry proof tutor used by high school students and a LISP programming tutor used by college students in a mini course in introductory programming course at Carnegie Mellon University.

One of the first organizations to develop a system for use within the school system was the PACT Center at Carnegie Mellon University. Their aim was to "...develop systems that provide individualized assistance to students as they work on challenging real-world problems in complex domains such as computer programming, algebra and geometry". and their Algebra course was designated one of five exemplary curricula for K-12 mathematics educated by the US Department of Education. Further, in 2005, Carnegie Learning released Bridge to Algebra, a product intended for middle schools that was piloted in over 100 schools.

Cognitive tutoring software is continuing to be used. According to a Business Insider Report article, Ken Koedinger, a professor of human-computer interaction and psychology at Carnegie Mellon University, describes how teachers can integrate cognitive tutoring software into the classroom. He suggests that teachers use it in a computer lab environment or during classes. Cognitive tutors can understand the many ways that a student might answer a problem, and then assist the student at the exact time that the help is required. Further, the cognitive tutor can customize exercises specific to the student's needs.

The focus of Cognitive Tutor development has been the design of the software to teach specific production rules and not on the development of curricular content. Despite many years of trials, improvements, and a potential to advance learning objectives, the creators continue to rely primarily on outside sources for curricular direction.

Practicality dictates that designers must choose from a discrete set of methods to teach and support learners. Limited choices of methods, prompts and hints may be effective in supporting some learners but may conflict with the methods already in use by others.

See also

  • Educational psychology

References

  • Pittsburgh Advanced Cognitive Tutor Center, of Carnegie Mellon University, which researches cognitive tutors
  • Product page for Cognitive Tutor at Carnegie Learning
  • Evaluation of Cognitive Tutor Algebra I Program in Miami-Dade County Public Schools
  • Overview of evaluations of Cognitive Tutor
  • Cognitive Tutors: The End of Boredom and Confusion?, Survey article (2018)