Stairstepper

An adaptive remedial iSTART module

Cecile A. Perret, Amy Johnson, Kathryn S. McCarthy, Tricia A. Guerrero, Jianmin Dai, Danielle McNamara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper introduces StairStepper, a new addition to Interactive Strategy Training for Active Reading and Thinking (iSTART), an intelligent tutoring system (ITS) that provides adaptive self-explanation training and practice. Whereas iSTART focuses on improving comprehension at levels geared toward answering challenging questions associated with complex texts, StairStepper focuses on improving learners’ performance when reading grade-level expository texts. StairStepper is designed as a scaffolded practice activity wherein text difficulty level and task are adapted according to learners’ performance. This offers a unique module that provides reading comprehension tutoring through a combination of self-explanation practice and answering of multiple-choice questions representative of those found in standardized tests.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings
PublisherSpringer Verlag
Pages557-560
Number of pages4
Volume10331 LNAI
ISBN (Print)9783319614243
DOIs
StatePublished - 2017
Event18th International Conference on Artificial Intelligence in Education, AIED 2017 - Wuhan, China
Duration: Jun 28 2017Jul 1 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10331 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th International Conference on Artificial Intelligence in Education, AIED 2017
CountryChina
CityWuhan
Period6/28/177/1/17

Fingerprint

Intelligent systems
Module
Intelligent Tutoring Systems
Question Answering
Strategy
Training
Text

Keywords

  • Game-based learning
  • Intelligent tutoring systems
  • Reading assessment
  • Reading comprehension
  • Strategy based learning
  • System adaptivity

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Perret, C. A., Johnson, A., McCarthy, K. S., Guerrero, T. A., Dai, J., & McNamara, D. (2017). Stairstepper: An adaptive remedial iSTART module. In Artificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings (Vol. 10331 LNAI, pp. 557-560). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10331 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-61425-0_63

Stairstepper : An adaptive remedial iSTART module. / Perret, Cecile A.; Johnson, Amy; McCarthy, Kathryn S.; Guerrero, Tricia A.; Dai, Jianmin; McNamara, Danielle.

Artificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings. Vol. 10331 LNAI Springer Verlag, 2017. p. 557-560 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10331 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Perret, CA, Johnson, A, McCarthy, KS, Guerrero, TA, Dai, J & McNamara, D 2017, Stairstepper: An adaptive remedial iSTART module. in Artificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings. vol. 10331 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10331 LNAI, Springer Verlag, pp. 557-560, 18th International Conference on Artificial Intelligence in Education, AIED 2017, Wuhan, China, 6/28/17. https://doi.org/10.1007/978-3-319-61425-0_63
Perret CA, Johnson A, McCarthy KS, Guerrero TA, Dai J, McNamara D. Stairstepper: An adaptive remedial iSTART module. In Artificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings. Vol. 10331 LNAI. Springer Verlag. 2017. p. 557-560. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-61425-0_63
Perret, Cecile A. ; Johnson, Amy ; McCarthy, Kathryn S. ; Guerrero, Tricia A. ; Dai, Jianmin ; McNamara, Danielle. / Stairstepper : An adaptive remedial iSTART module. Artificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings. Vol. 10331 LNAI Springer Verlag, 2017. pp. 557-560 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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