Tuesday, April 29, 2025
2:00 - 4:00 PM (PST) at Berkeley Way West 1212 and via Zoom
Open to GSE faculty, students, and community.
Request a zoom link from convenors@bear.berkeley.edu
About the Session:
Reading fluency, signaling automaticity in word recognition (Hiebert, 2024), is widely recognized as a strong
predictor of reading competence. Research has shown that simple measures of oral reading rate correlate
more strongly with reading comprehension performance than silent reading (Fuchs, 1988), leading to the
widespread adoption of ORF assessments as a key tool for identifying struggling readers for placement in
tiered instruction (Stanovich, 1991, Fuchs et. al., 1988, 2001; Hasbrouck & Tindal, 2011; Hiebert, 2024).
Despite its popularity, ORF’s summative indicators at the passage level, namely the number and % of words
read correctly in a minute – do not offer word-level insights, which are critical for designing effective
instructional texts and interventions that build on existing students’ knowledge. In this talk, we share
preliminary findings from a secondary-data analysis of untimed word-reading performance in connected text by
650 second-graders from the Computerized Oral Reading Evaluation (CORE) project (Nese & Kamata, 2021).
Specifically, we used the Rasch model and explanatory item response models (EIRMs, De Boeck & Wilson,
2004) to (1) estimate word difficulty, and (2) examine word-features, such as position in text, frequency,
concreteness, vowel-patterns in the first syllable, that influence the difficulty to derive critical information for
designing effective instructional texts and interventions that build on students’ existing knowledge.
About the Author:
Yukie Toyama (Ph.D., University of California, Berkeley) is currently a research specialist at the BEAR center.
Her research focuses on the use of learning progressions and explanatory item response models to advance
understanding about student learning in literacy and STEM fields.
Freddy Hiebert (Ph.D., University of Wisconsin) is an educational researcher whose work addresses literacy
learning among at-risk youth in American classrooms. Currently, she is the CEO and president of TextProject,
Inc., a not-for-profit that is dedicated to bringing beginning and struggling readers to high levels of literacy
through a variety of strategies and tools, particularly through using science and social studies texts, used for
reading instruction.
Qing Cai is a doctoral student in the Social Research Methodology cluster at Berkeley School of Education. As
a passionate researcher and reading advocate, her work focuses on bi-literacy, measurement and assessment
of reading.
Robin Irey (Ph.D., University of California, Berkeley) is an education research specialist working on
literacy-related projects at both University of California, San Francisco and Stanford University. Her research
interests are informed by her previous experience as a special education classroom teacher and include early
reading acquisition, reading intervention, metalinguistic underpinnings of reading, cognitive processes of
reading, morphological awareness, and assessment.