Predicting Reading Comprehension from Constructed Responses: Explanatory Retrievals as Stealth Assessment

Kathryn S. McCarthy; Laura K. Allen; Scott R. Hinze

doi:10.1007/978-3-030-52240-7_36

Predicting Reading Comprehension from Constructed Responses: Explanatory Retrievals as Stealth Assessment

Kathryn S. McCarthy, Laura K. Allen, Scott R. Hinze

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

12 Scopus citations

Abstract

Open-ended constructed responses promote deeper processing of course materials. Further, evaluation of these explanations can yield important information about students’ cognition. This study examined how students’ constructed responses, generated at different points during learning, relate to their later comprehension outcomes. College students (N = 75) produced self-explanations during reading and explanatory retrievals after reading. The Constructed Response Assessment Tool (CRAT) was used to analyze these responses across multiple dimensions of language and relate these textual features to comprehension performance. Results indicate that the linguistic features of post-reading explanatory retrievals were more predictive of comprehension outcomes than self-explanations. Further, these models relied on different indices to predict performance.

Original language	English (US)
Title of host publication	Artificial Intelligence in Education - 21st International Conference, AIED 2020, Proceedings
Editors	Ig Ibert Bittencourt, Mutlu Cukurova, Rose Luckin, Kasia Muldner, Eva Millán
Publisher	Springer
Pages	197-202
Number of pages	6
ISBN (Print)	9783030522391
DOIs	https://doi.org/10.1007/978-3-030-52240-7_36
State	Published - 2020
Externally published	Yes
Event	21st International Conference on Artificial Intelligence in Education, AIED 2020 - Ifrane, Morocco Duration: Jul 6 2020 → Jul 10 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12164 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st International Conference on Artificial Intelligence in Education, AIED 2020
Country/Territory	Morocco
City	Ifrane
Period	7/6/20 → 7/10/20

Bibliographical note

Funding Information:
This research was made possible in part by grants from the Spencer Foundation (201900217) and the Institute for Education Sciences (R305A190063 and R305A180261). The views expressed are those of the authors and do not necessarily reflect the views of the funding agencies.

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

Natural language processing
Science learning
Stealth assessment

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Publisher link

10.1007/978-3-030-52240-7_36

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McCarthy, K. S., Allen, L. K., & Hinze, S. R. (2020). Predicting Reading Comprehension from Constructed Responses: Explanatory Retrievals as Stealth Assessment. In I. I. Bittencourt, M. Cukurova, R. Luckin, K. Muldner, & E. Millán (Eds.), Artificial Intelligence in Education - 21st International Conference, AIED 2020, Proceedings (pp. 197-202). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12164 LNAI). Springer. https://doi.org/10.1007/978-3-030-52240-7_36

Predicting Reading Comprehension from Constructed Responses: Explanatory Retrievals as Stealth Assessment. / McCarthy, Kathryn S.; Allen, Laura K.; Hinze, Scott R.
Artificial Intelligence in Education - 21st International Conference, AIED 2020, Proceedings. ed. / Ig Ibert Bittencourt; Mutlu Cukurova; Rose Luckin; Kasia Muldner; Eva Millán. Springer, 2020. p. 197-202 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12164 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

McCarthy, KS, Allen, LK & Hinze, SR 2020, Predicting Reading Comprehension from Constructed Responses: Explanatory Retrievals as Stealth Assessment. in II Bittencourt, M Cukurova, R Luckin, K Muldner & E Millán (eds), Artificial Intelligence in Education - 21st International Conference, AIED 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12164 LNAI, Springer, pp. 197-202, 21st International Conference on Artificial Intelligence in Education, AIED 2020, Ifrane, Morocco, 7/6/20. https://doi.org/10.1007/978-3-030-52240-7_36

McCarthy KS, Allen LK, Hinze SR. Predicting Reading Comprehension from Constructed Responses: Explanatory Retrievals as Stealth Assessment. In Bittencourt II, Cukurova M, Luckin R, Muldner K, Millán E, editors, Artificial Intelligence in Education - 21st International Conference, AIED 2020, Proceedings. Springer. 2020. p. 197-202. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-52240-7_36

McCarthy, Kathryn S. ; Allen, Laura K. ; Hinze, Scott R. / Predicting Reading Comprehension from Constructed Responses : Explanatory Retrievals as Stealth Assessment. Artificial Intelligence in Education - 21st International Conference, AIED 2020, Proceedings. editor / Ig Ibert Bittencourt ; Mutlu Cukurova ; Rose Luckin ; Kasia Muldner ; Eva Millán. Springer, 2020. pp. 197-202 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Predicting Reading Comprehension from Constructed Responses: Explanatory Retrievals as Stealth Assessment

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Publisher link

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