Showing automatically generated students' conceptual models to students and teachers

被引：1

作者：

Pérez-Marín D. ^{[1
]}

Pascual-Nieto I. ^{[2
]}

机构：

[1] Department of Computing Languages and Systems i Department, Universidad Rey Juan Carlos, 28933, Móstoles, Madrid, Tulipán s/n street

[2] Computer Science Department, Universidad Autónoma de Madrid, 28049, Madrid, Francisco Tomás y Valiente street

来源：

International Journal of Artificial Intelligence in Education | 2010年 / 20卷 / 01期

关键词：

e-assessment; e-learning; free-text scoring; Open student models;

D O I：

10.3233/JAI-2010-0002

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A student conceptual model can be defined as a set of interconnected concepts associated with an estimation value that indicates how well these concepts are used by the students. It can model just one student or a group of students, and can be represented as a concept map, conceptual diagram or one of several other knowledge representation formats. Some e-assessment systems that automatically evaluate free-text students' answers have recently been extended to include the possibility of automatically generating students' conceptual models. The research reported in this paper focuses on studying the effects of showing these automatically generated models to students and teachers. The e-assessment system used was the Will Tools suite with a group of Engineering students during a semester at the Universidad Autónoma of Madrid. © 2010 - IOS Press and the authors.

引用

页码：47 / 72

页数：25

共 27 条

[1]

Aguilar G., Kaijiri K., Design overview of an adaptive computer-based assessment system, Interactive Educational Multimedia, 14, pp. 116-130, (2007)

[2]

Ausubel D.P., Novak J.D., Hanesian H., Educational Psychology: A Cognitive View, (1978)

[3]

Birenbaum M., Tatsuoka K., Gutvirtz Y., Effects of response format on diagnostic assessment of scholastic achievement, Applied Psychological Measurement, 16, 4, pp. 353-363, (1992)

[4]

Brusilovsky P., Schwarz E., Weber G., ELM-ART: An intelligent tutoring system on World Wide Web, Proceedings of the International Conference on Intelligent Tutoring Systems, pp. 261-269, (1996)

[5]

Bull S., Brna P., Pain H., Extending the scope of the student model, User Modeling and User-Adapted Interaction, 5, pp. 45-65, (1995)

[6]

Bull S., Pain H., Did I say what I think I said, and do you agree with me?: Inspecting and questioning the student model, Proceedings of the World Conference on Artificial Intelligence in Education, pp. 501-508, (1995)

[7]

Bull S., Brna P., What does Susan know that Paul doesn't? (and vice versa): Contributing to each other's student model, Proceedings of the Artificial Intelligence of Education Conference, pp. 568-570, (1997)

[8]

Bull S., Nghiem T., Helping learners to understand themselves with a learner model open to students, peers and instructors, Proceedings of the Workshop on Individual and Group Modelling Methods That Help Learners Understand Themselves at the International Conference on Intelligent Tutoring Systems, pp. 5-13, (2002)

[9]

Bull S., Kay J., Student models that invite the learner in: The SMILI: () open learner modelling framework, International Journal of Artificial Intelligence in Education, 17, 2, pp. 89-120, (2007)

[10]

Czarkowski M., Kay J., Potts S., Web framework for scrutable adaptation, Proceedings of the Workshop on Learner Modelling for Reflection at the International Conference on Artificial Intelligence in Education, pp. 11-18, (2005)

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