| Conati, C., & VanLehn, K. (1999) Teaching meta-cognitive skills: implementation and evaluation of a tutoring system to guide self-explanation while learning from examples. in proceedings of International Conference on Artificial Intelligence in Education, |
....self explanation, which is the process of generating explanations and justifications to oneself when studying an example. Studies have shown that students who self explain learn more. Moreover, when students are prompted to self explain, most students will do so and thus increase their learning [Cona99]. Therefore, it is highly desirable for ITSs to encourage self explanation. The original implementation of SQL Tutor provides no explicit support for its users to compare their solutions with the hints offered by the system, and justify them. 3.2 Expected benefits of introducing an agent 16 3.2 ....
Conati Cristina and VanLehn Kurt. Teaching meta-cognitive skills: implementation and evaluation of a tutoring system to guide self-explanation while learning from examples. Artificial intelligence in Education.S.P.LajoieandM. Vivet (Eds). IOS Press, pp. 297-304, 1999
....create the final output to the user. DISCUSSION AND FUTURE WORK Critiquing is an effective mechanism for improving human behavior, especially that of near expert users. The critiquing method introduced here encourages reflexive problem solving and challenges the user to create self explanations [1] for perceived expectation failures. A critiquing system can also reduce the gulf of evaluation [6] the effort required to interpret the feedback provided by a system. Expert critiquing systems have had a large impact where there is a good source of expert knowledge and where complex ....
Conati, C. and VanLehn. Teaching meta-cognitive skills: implementation and evaluation of a tutoring system to guide self-explanation while learning from examples. In Proceedings of AIED'99: the 9 th World Conference on Artificial Intelligence and Education, Le Man, France, 1999.
....still unclear and under investigation. Since the SE Coach is built on existing hypotheses about the features that make self explanation effective for learning, an accurate evaluation of its effectiveness may allow us to shed light on the validity of the hypotheses and possibly suggest new ones. In [6], we presented initial results of a formal evaluation that we performed to test the usability and effectiveness of the system. These results indicated that the SE Coach s interface is easy to use and generally effective in stimulating self explanation. They also provided initial support on the ....
....1) In order to read the text or graphics hidden under a box, the student must move the mouse pointer over it. The fact that not all the example parts are visible at once helps students focus attention and reflect on individual example parts, and allows the SE Coach to track student s attention [6]. The second level of scaffolding is provided by explicit prompts to selfexplain. These prompts go from a generic reminder to self explain, that appears when a student uncovers an example part, to more specific prompts for self explanations that have been shown to correlate with learning in the ....
[Article contains additional citation context not shown here]
Conati, C., & VanLehn, K. (1999). Teaching meta-cognitive skills: implementation and evaluation of a tutoring system to guide self-explanation while learning from examples. In Proc. of AIED'99, 9 th World Conference of Artificial Intelligence and Education, Le Mans, France.
.... needs (Chi in press) How can a computer tutor decide what further self explanations can be more beneficial for those students that do not spontaneously selfexplain When and how should the tutor elicit these selfexplanations from students that are naturally reluctant to self explain In (Conati 1999) we have proposed solutions to these challenges, including: 1. An interface that monitors student s attention through a masking mechanism that requires the student to explicitly move the mouse over an example part in order to uncover and view it. Pilot studies have revealed that the masking ....
....that provides tutoring for self explanation within Andes, a tutoring system for Newtonian physics that supports students during both example studying and problem solving. An empirical evaluation of the SE Coach has confirmed the usability and effectiveness of the SE Coach interface (Conati and VanLehn 1999) and has provided statistical evidence that the tutorial interventions suggested by the probabilistic student model increase students learning (Conati 1999) Toward more adaptive support to effectively learn from examples. Although our previous work formalizes some of the crucial processes ....
[Article contains additional citation context not shown here]
Conati, C. and K. VanLehn (1999). Teaching metacognitive skills: implementation and evaluation of an tutoring system to guide self-explanation while learning from examples. AIED'99, 9th World Conference of Artificial Intelligence and Education, Le Mans, France.
No context found.
Conati, C., & VanLehn, K. (1999) Teaching meta-cognitive skills: implementation and evaluation of a tutoring system to guide self-explanation while learning from examples. in proceedings of International Conference on Artificial Intelligence in Education,
No context found.
Conati, C., and K. VanLehn, 1999. Teaching Meta-Cognitive Skills: Implementation and Evaluation of a Tutoring System to Guide Self-Explanation While Learning from Examples. In Artificial Intelligence in Education, Proceedings of AIED-99, edited by S. P. Lajoie and M. Vivet, 297-304. Amsterdam: IOS Press.
No context found.
C. Conati and K. VanLehn. Teaching meta-cognitive skills: Implementation and evaluation of a tutoring system to guide self-explanation while learning from examples. In S.P. Lajoie and M. Vivet, editors, Artificial Intelligence in Education, pages 297--304. IOS Press, 1999.
No context found.
C. Conati and K. VanLehn. Teaching meta-cognitive skills: Implementation and evaluation of a tutoring system to guide self-explanation while learning from examples. In S.P. Lajoie and M. Vivet, editors, Artificial Intelligence in Education, pages 297--304. IOS Press, 1999.
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