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SeongYeup Kim

Biographic Data

ID5971685
NAMESeongYeup Kim
GIVEN NAMESSeongYeup
FAMILY NAMEKim
SIGNATUREKIM S
AFFILIATIONSPennsylvania State University
ORCID0000-0002-3703-8243
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
AUTHOR COUNT4
EDITOR COUNT0
FIRST PUBLICATION YEAR2026
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Evaluating the consistency between human raters and three AI systems on the scoring of argumentative essays

    Open Access•SeongYeup Kim, Matthew T McCrudden•ARTICLE•Assessing Writing•2026

  • Prompting strategies with generative AI during learning from multiple sources

    Open Access•SeongYeup Kim, Matthew T McCrudden•ARTICLE•Learning and Instruction•2026

  • Measuring strategic knowledge in multiple text reading

    Open Access•SeongYeup Kim, Pui-Wa Lei•ARTICLE•Contemporary Educational Psychology•2026

    We developed and validated the MTSKI to measure knowledge of multiple-text reading strategies. • IRT analyses supported the MTSKI’s reliability and unidimensional structure. • Integrative strategy items were more informative at higher proficiency levels. • MTSKI predicted intra- and inter-textual comprehension beyond control variables. • MTSKI advances research and instruction in strategic multiple-text reading. Although effective strategy use is…

  • Developing and Validating an Instrument for Assessing Secondary Students' Self‐Efficacy for Online Reading

    Open Access•SeongYeup Kim, Yongjun Lee et al.•ARTICLE•Reading Research Quarterly•2026•References: 59

    This study develops and validates the Self‐Efficacy for Online Reading Questionnaire (SEORQ), a process‐grounded instrument designed to assess secondary students' self‐efficacy for enacting the core demands of online reading. We generated items from established models of online reading and multiple‐source comprehension and refined them through expert review and content validity analyses, yielding an initial pool of 40 items. We administered the q…

No prominent works on this page.

  • Evaluating the consistency between human raters and three AI systems on the scoring of argumentative essays

    Open Access•SeongYeup Kim, Matthew T McCrudden•ARTICLE•Assessing Writing•2026

  • Prompting strategies with generative AI during learning from multiple sources

    Open Access•SeongYeup Kim, Matthew T McCrudden•ARTICLE•Learning and Instruction•2026

  • Measuring strategic knowledge in multiple text reading

    Open Access•SeongYeup Kim, Pui-Wa Lei•ARTICLE•Contemporary Educational Psychology•2026

    We developed and validated the MTSKI to measure knowledge of multiple-text reading strategies. • IRT analyses supported the MTSKI’s reliability and unidimensional structure. • Integrative strategy items were more informative at higher proficiency levels. • MTSKI predicted intra- and inter-textual comprehension beyond control variables. • MTSKI advances research and instruction in strategic multiple-text reading. Although effective strategy use is…

  • Developing and Validating an Instrument for Assessing Secondary Students' Self‐Efficacy for Online Reading

    Open Access•SeongYeup Kim, Yongjun Lee et al.•ARTICLE•Reading Research Quarterly•2026•References: 59

    This study develops and validates the Self‐Efficacy for Online Reading Questionnaire (SEORQ), a process‐grounded instrument designed to assess secondary students' self‐efficacy for enacting the core demands of online reading. We generated items from established models of online reading and multiple‐source comprehension and refined them through expert review and content validity analyses, yielding an initial pool of 40 items. We administered the q…

Educational Strategies and Epistemologies (3 works) · Artificial Intelligence in Healthcare and Education (2 works) · Metacognition (2 works) · Reading comprehension (2 works) · Argumentative (1 work) · Comprehension (1 work) · Confirmatory factor analysis (1 work) · Convergent validity (1 work) · Conversation (1 work) · Discriminant validity (1 work)

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