iSTART-Early: Interactive Strategy Training for Early Readers
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| Title: | iSTART-Early: Interactive Strategy Training for Early Readers |
|---|---|
| Language: | English |
| Authors: | Panayiota Kendeou (ORCID |
| Source: | Grantee Submission. 2022. |
| Peer Reviewed: | Y |
| Page Count: | 10 |
| Publication Date: | 2022 |
| Sponsoring Agency: | Institute of Education Sciences (ED) |
| Contract Number: | R305A190050 |
| Document Type: | Speeches/Meeting Papers Reports - Descriptive |
| Education Level: | Early Childhood Education Elementary Education Grade 3 Primary Education Grade 4 Intermediate Grades |
| Descriptors: | Intelligent Tutoring Systems, Reading Instruction, Reading Comprehension, Reading Strategies, Grade 3, Grade 4, Elementary School Students, Individualized Instruction, Game Based Learning, Educational Technology |
| DOI: | 10.1007/978-3-031-09680-8_35 |
| Abstract: | 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. [This paper was published in: S. Crossley and E. Popescu, Eds., "ITS 2022, LNCS 13284," Springer Nature, 2022, pp.371-379.] |
| Abstractor: | As Provided |
| IES Funded: | Yes |
| Entry Date: | 2023 |
| Accession Number: | ED637291 |
| Database: | ERIC |
| Abstract: | 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. [This paper was published in: S. Crossley and E. Popescu, Eds., "ITS 2022, LNCS 13284," Springer Nature, 2022, pp.371-379.] |
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| DOI: | 10.1007/978-3-031-09680-8_35 |
