Running out of Time: Leveraging Process Data to Identify Students Who May Benefit from Extended Time
Saved in:
| Title: | Running out of Time: Leveraging Process Data to Identify Students Who May Benefit from Extended Time |
|---|---|
| Language: | English |
| Authors: | Burhan Ogut (ORCID |
| Source: | International Electronic Journal of Elementary Education. 2025 17(2):253-266. |
| Availability: | International Electronic Journal of Elementary Education. T&K Akademic Rosendalsvein 45, Oslo 1166, Norway. e-mail: iejee@iejee.com; Web site: https://www.iejee.com/index.php/IEJEE/index |
| Peer Reviewed: | Y |
| Page Count: | 14 |
| Publication Date: | 2025 |
| Sponsoring Agency: | Institute of Education Sciences (ED) |
| Contract Number: | R324P210002 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Identification, Testing Accommodations, National Competency Tests, Equal Education, Students with Disabilities, Time Factors (Learning), Computer Assisted Testing, Student Evaluation, Timed Tests |
| Assessment and Survey Identifiers: | National Assessment of Educational Progress |
| ISSN: | 1307-9298 |
| Abstract: | This study explored the effectiveness of extended time (ET) accommodations in the 2017 NAEP Grade 8 Mathematics assessment to enhance educational equity. Analyzing NAEP process data through an XGBoost model, we examined if early interactions with assessment items could predict students' likelihood of requiring ET by identifying those who received a timeout message. The findings revealed that 72% of students with disabilities (SWDs) granted ET did not use it fully, while about 24% of students lacking ET were still actively engaged when timed out, indicating a considerable unmet need for ET. The model demonstrated high accuracy and recall in predicting the necessity for ET based on early test behaviors, with minimal influence from background variables such as eligibility for free lunch, English Language Learner (ELL) status, and disability status. These results underscore the potential of utilizing early assessment behaviors as reliable predictors for ET needs, advocating for the integration of predictive models into digital testing systems. Such an approach could enable real-time analysis and adjustments, thereby promoting a fairer assessment process where all students have the opportunity to fully demonstrate their knowledge. |
| Abstractor: | As Provided |
| IES Funded: | Yes |
| Entry Date: | 2025 |
| Accession Number: | EJ1468386 |
| Database: | ERIC |
| Abstract: | This study explored the effectiveness of extended time (ET) accommodations in the 2017 NAEP Grade 8 Mathematics assessment to enhance educational equity. Analyzing NAEP process data through an XGBoost model, we examined if early interactions with assessment items could predict students' likelihood of requiring ET by identifying those who received a timeout message. The findings revealed that 72% of students with disabilities (SWDs) granted ET did not use it fully, while about 24% of students lacking ET were still actively engaged when timed out, indicating a considerable unmet need for ET. The model demonstrated high accuracy and recall in predicting the necessity for ET based on early test behaviors, with minimal influence from background variables such as eligibility for free lunch, English Language Learner (ELL) status, and disability status. These results underscore the potential of utilizing early assessment behaviors as reliable predictors for ET needs, advocating for the integration of predictive models into digital testing systems. Such an approach could enable real-time analysis and adjustments, thereby promoting a fairer assessment process where all students have the opportunity to fully demonstrate their knowledge. |
|---|---|
| ISSN: | 1307-9298 |
