TY - GEN
T1 - iSTART-Early
T2 - 18th International Conference on Intelligent Tutoring Systems, ITS 2022
AU - Kendeou, Panayiota
AU - Orcutt, Ellen
AU - Arner, Tracy
AU - Li, Tong
AU - Balyan, Renu
AU - Butterfuss, Reese
AU - Watanabe, Micah
AU - McNamara, Danielle
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - In this paper, we present iSTART-Early, an intelligent tutoring system that provides automated instruction and practice on higher-order reading comprehension strategies to 3rd and 4th grade students. iSTART-Early provides personalized, interactive, game-based strategy instruction and practice on comprehension strategies (i.e., Ask It, Reword It, Find It, Explain It, and Summarize It) with grade-appropriate informational texts. Natural language processing (NLP) combined with automated speech recognition (ASR) and text-to-speech technologies enable immediate formative and summative feedback. A teacher interface allows teachers to assign texts and monitor students’ performance so that they can provide additional support and feedback when necessary, creating blended-learning opportunities. We describe the interface and the development of iSTART-Early, as well as our plans to examine the intelligent tutoring system for usability, feasibility and promise in improving reading comprehension strategies and outcomes for young readers.
AB - In this paper, we present iSTART-Early, an intelligent tutoring system that provides automated instruction and practice on higher-order reading comprehension strategies to 3rd and 4th grade students. iSTART-Early provides personalized, interactive, game-based strategy instruction and practice on comprehension strategies (i.e., Ask It, Reword It, Find It, Explain It, and Summarize It) with grade-appropriate informational texts. Natural language processing (NLP) combined with automated speech recognition (ASR) and text-to-speech technologies enable immediate formative and summative feedback. A teacher interface allows teachers to assign texts and monitor students’ performance so that they can provide additional support and feedback when necessary, creating blended-learning opportunities. We describe the interface and the development of iSTART-Early, as well as our plans to examine the intelligent tutoring system for usability, feasibility and promise in improving reading comprehension strategies and outcomes for young readers.
KW - ASR
KW - ITS
KW - Reading strategies
UR - http://www.scopus.com/inward/record.url?scp=85134174323&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134174323&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-09680-8_35
DO - 10.1007/978-3-031-09680-8_35
M3 - Conference contribution
AN - SCOPUS:85134174323
SN - 9783031096792
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 371
EP - 379
BT - Intelligent Tutoring Systems - 18th International Conference, ITS 2022, Proceedings
A2 - Crossley, Scott
A2 - Popescu, Elvira
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 29 June 2022 through 1 July 2022
ER -