Text Complexity versus Task Complexity: Item Difficulty Modeling for Reading Items
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| Title: | Text Complexity versus Task Complexity: Item Difficulty Modeling for Reading Items |
|---|---|
| Language: | English |
| Authors: | M. Christina Schneider, Jing Chen, Jeremy Heneger |
| Source: | Practical Assessment, Research & Evaluation. 2026 31(1). |
| Availability: | University of Massachusetts Amherst Libraries. 154 Hicks Way, Amherst, MA 01003. e-mail: pare@umass.edu; Web site: https://openpublishing.library.umass.edu/pare/ |
| Peer Reviewed: | Y |
| Page Count: | 17 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Test Items, Reading Comprehension, Difficulty Level, Instructional Program Divisions, Reading Achievement, Predictor Variables, Summative Evaluation, Readability |
| Assessment and Survey Identifiers: | Flesch Kincaid Grade Level Formula, Lexile Scale of Reading |
| ISSN: | 1531-7714 |
| Abstract: | This study investigates item features to aid in improving understanding of what makes items that measure reading comprehension easy or difficult. In this item difficulty modeling (IDM) study, item and passage features were included as predictors that represented text-task interactions and stimulus demands. The passage-level features included two common quantitative metrics of text complexity: the Lexile Framework® for Reading and Flesch-Kincaid. Passage word count, item type, Depth of Knowledge (DOK), and item to Range Achievement-Level Descriptor (RALD) match were held constant across conditions. Two IDM models were examined; one included passage-level text complexity features and not grade level, and the other included grade level and not passage level text complexity features. We found that quantitative metrics of text complexity added 3% to the IDM compared to when grade was substituted for those features. Text-task interactions as represented by RALDs and DOK levels were found to provide unique and significant information to the IDM model as did item type and particular standard topics. Implications for RALD construction and additional research related to RALDs for reading are discussed. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1507968 |
| Database: | ERIC |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=EJ1507968 Name: ERIC Full Text Category: fullText Text: Full Text from ERIC |
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| Header | DbId: eric DbLabel: ERIC An: EJ1507968 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Text Complexity versus Task Complexity: Item Difficulty Modeling for Reading Items – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22M%2E+Christina+Schneider%22">M. Christina Schneider</searchLink><br /><searchLink fieldCode="AR" term="%22Jing+Chen%22">Jing Chen</searchLink><br /><searchLink fieldCode="AR" term="%22Jeremy+Heneger%22">Jeremy Heneger</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Practical+Assessment%2C+Research+%26+Evaluation%22"><i>Practical Assessment, Research & Evaluation</i></searchLink>. 2026 31(1). – Name: Avail Label: Availability Group: Avail Data: University of Massachusetts Amherst Libraries. 154 Hicks Way, Amherst, MA 01003. e-mail: pare@umass.edu; Web site: https://openpublishing.library.umass.edu/pare/ – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 17 – Name: DatePubCY Label: Publication Date Group: Date Data: 2026 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Test+Items%22">Test Items</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Comprehension%22">Reading Comprehension</searchLink><br /><searchLink fieldCode="DE" term="%22Difficulty+Level%22">Difficulty Level</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Program+Divisions%22">Instructional Program Divisions</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Achievement%22">Reading Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Summative+Evaluation%22">Summative Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Readability%22">Readability</searchLink> – Name: SubjectThesaurus Label: Assessment and Survey Identifiers Group: Su Data: <searchLink fieldCode="SU" term="%22Flesch+Kincaid+Grade+Level+Formula%22">Flesch Kincaid Grade Level Formula</searchLink><br /><searchLink fieldCode="SU" term="%22Lexile+Scale+of+Reading%22">Lexile Scale of Reading</searchLink> – Name: ISSN Label: ISSN Group: ISSN Data: 1531-7714 – Name: Abstract Label: Abstract Group: Ab Data: This study investigates item features to aid in improving understanding of what makes items that measure reading comprehension easy or difficult. In this item difficulty modeling (IDM) study, item and passage features were included as predictors that represented text-task interactions and stimulus demands. The passage-level features included two common quantitative metrics of text complexity: the Lexile Framework® for Reading and Flesch-Kincaid. Passage word count, item type, Depth of Knowledge (DOK), and item to Range Achievement-Level Descriptor (RALD) match were held constant across conditions. Two IDM models were examined; one included passage-level text complexity features and not grade level, and the other included grade level and not passage level text complexity features. We found that quantitative metrics of text complexity added 3% to the IDM compared to when grade was substituted for those features. Text-task interactions as represented by RALDs and DOK levels were found to provide unique and significant information to the IDM model as did item type and particular standard topics. Implications for RALD construction and additional research related to RALDs for reading are discussed. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2026 – Name: AN Label: Accession Number Group: ID Data: EJ1507968 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1507968 |
| RecordInfo | BibRecord: BibEntity: Languages: – Text: English PhysicalDescription: Pagination: PageCount: 17 Subjects: – SubjectFull: Test Items Type: general – SubjectFull: Reading Comprehension Type: general – SubjectFull: Difficulty Level Type: general – SubjectFull: Instructional Program Divisions Type: general – SubjectFull: Reading Achievement Type: general – SubjectFull: Predictor Variables Type: general – SubjectFull: Summative Evaluation Type: general – SubjectFull: Readability Type: general – SubjectFull: Flesch Kincaid Grade Level Formula Type: general – SubjectFull: Lexile Scale of Reading Type: general Titles: – TitleFull: Text Complexity versus Task Complexity: Item Difficulty Modeling for Reading Items Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: M. Christina Schneider – PersonEntity: Name: NameFull: Jing Chen – PersonEntity: Name: NameFull: Jeremy Heneger IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2026 Identifiers: – Type: issn-electronic Value: 1531-7714 Numbering: – Type: volume Value: 31 – Type: issue Value: 1 Titles: – TitleFull: Practical Assessment, Research & Evaluation Type: main |
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