SARA Reading Components Tests, RISE Forms: Technical Adequacy and Test Design, 3rd Edition

Sabatini, John; Weeks, Jonathan; O’Reilly, Tenaha; Bruce, Kelly; Steinberg, Jonathan; Chao, Szu-Fu

doi:10.1002/ets2.12269

Cited by 27 publications

(25 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is a confirmation of the internal validity of the algorithm. Evidence of external validity was also confirmed in analyses of learning gains on comprehension skills that were measured by independent psychometric tests ( Woodcock et al, 2007 ; Foorman et al, 2017 ; Sabatini et al, 2019 ). Learning gains on these tests were predicted by the accuracy rate of engaged question-answer observations in AutoTutor but not the disengaged observations.…”

Section: Discussion and Summarymentioning

confidence: 89%

“…As an independent evaluation, learning gains were analyzed on subsets of the 252 students who took three standardized tests of comprehension before and after the larger CSAL AutoTutor intervention that included AutoTutor-ARC lessons. Of the 252 participants, 205 took both pre- and post-test of the Woodcock Johnson III Passage Comprehension subtest ( Woodcock et al, 2007 ); 143 took Reading Assessment for Prescriptive Instructional Data (RAPID) Passage Comprehension subtest develop by Lexia Learning ( Foorman et al, 2017 ) and 142 took Reading Inventory and Scholastic Evaluation (RISE) battery developed by ETS ( Sabatini et al, 2019 ). Fang et al reported that the learning gains in Woodcock Johnson and RAPID tests were highest for conscientious readers, lowest for struggling readers, with higher performing readers and under-engaged readers in between (Fang et al, submitted).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Automated Disengagement Tracking Within an Intelligent Tutoring System

Ying

Shi

et al. 2021

Front. Artif. Intell.

Self Cite

View full text Add to dashboard Cite

This paper describes a new automated disengagement tracking system (DTS) that detects learners’ maladaptive behaviors, e.g. mind-wandering and impetuous responding, in an intelligent tutoring system (ITS), called AutoTutor. AutoTutor is a conversation-based intelligent tutoring system designed to help adult literacy learners improve their reading comprehension skills. Learners interact with two computer agents in natural language in 30 lessons focusing on word knowledge, sentence processing, text comprehension, and digital literacy. Each lesson has one to three dozen questions to assess and enhance learning. DTS automatically retrieves and aggregates a learner's response accuracies and time on the first three to five questions in a lesson, as a baseline performance for the lesson when they are presumably engaged, and then detects disengagement by observing if the learner's following performance significantly deviates from the baseline. DTS is computed with an unsupervised learning method and thus does not rely on any self-reports of disengagement. We analyzed the response time and accuracy of 252 adult literacy learners who completed lessons in AutoTutor. Our results show that items that the detector identified as the learner being disengaged had a performance accuracy of 18.5%, in contrast to 71.8% for engaged items. Moreover, the three post-test reading comprehension scores from Woodcock Johnson III, RISE, and RAPID had a significant association with the accuracy of engaged items, but not disengaged items.

show abstract

Section: Discussion and Summarymentioning

confidence: 89%

Section: Methodsmentioning

confidence: 99%

Automated Disengagement Tracking Within an Intelligent Tutoring System

Ying

Shi

et al. 2021

Front. Artif. Intell.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The real data were obtained from a web‐administered assessment of the Reading Inventory and Scholastic Evaluation (RISE; Sabatini et al., 2019). The RISE is a measure of six foundational reading skills.…”

Section: Relationship Of Mirt and Locally Dependent Irtmentioning

confidence: 99%

Using a Projection IRT Method for Vertical Scaling When Construct Shift Is Present

Strachan

Cho

Kim

et al. 2020

J Educational Measurement

View full text Add to dashboard Cite

In vertical scaling, results of tests from several different grade levels are placed on a common scale. Most vertical scaling methodologies rely heavily on the assumption that the construct being measured is unidimensional. In many testing situations, however, such an assumption could be problematic. For instance, the construct measured at one grade level may differ from that measured in another grade (e.g., construct shift). On the other hand, dimensions that involve low‐level skills are usually mastered by almost all students as they progress to higher grades. These types of changes in the multidimensional structure, within and across grades, create challenges for developing a vertical scale. In this article, we propose the use of projective IRT (PIRT) as a potential solution to the problem. Assuming that a test measures a primary dimension of substantive interest as well as some peripheral dimensions, the idea underlying PIRT is to integrate out the secondary dimensions such that the model provides both item parameters and ability estimates for the primary dimension. A simulation study was conducted to evaluate the effectiveness of the PIRT as a method for vertical scaling. An example using empirical data from a measure of foundational reading skills is also presented.

show abstract

“…While only one month of treatment did result in small gains for certain component literacy skills, lengthier interventions would likely have led to greater treatment outcomes. Finally, the current standardized assessments of morphology (e.g., Foorman, Petscher & Bishop, 2012;Sabatini, O'Reilly, Halderman & Bruce, 2014;Sabatini, Bruce, Steinberg & Weeks, 2015) were not available at the time of the study.…”

Section: Limitationsmentioning

confidence: 99%

Linking Root Words and Derived Forms for Adult Struggling Readers:A Pilot Study

Gray¹

2019

ALE JOURNAL

View full text Add to dashboard Cite

Ninety million adults in the United Stated have low literacy skills according to the National Research Council (2012). Given the number of people directly affected, and the associated costs to public health and employment, there is a serious lack of rigorous research studying interventions for adult struggling readers (Greenberg, 2008; Kruidener, 2002; Tighe & Schatschneider, 2016). Adults seeking alternative high school credentials like the General Education Development (GED) diploma, and those in Adult Basic Education (ABE) programs have a wide range of reading skill deficits (Perin, Flugman & Spiegal, 2006; Greenberg, Ehri & Perin, 1997). Surprisingly, despite promising results of morphological instruction with both children and adults, there is little evidence that adult literacy studies are taking advantage of the potential of teaching morphemes, including prefixes, root words and suffixes (Alamprese,

show abstract

SARA Reading Components Tests, RISE Forms: Technical Adequacy and Test Design, 3rd Edition

Cited by 27 publications

References 70 publications

Automated Disengagement Tracking Within an Intelligent Tutoring System

Automated Disengagement Tracking Within an Intelligent Tutoring System

Using a Projection IRT Method for Vertical Scaling When Construct Shift Is Present

Linking Root Words and Derived Forms for Adult Struggling Readers:A Pilot Study

Contact Info

Product

Resources

About