Journal article
The learning curve: Revisiting within-year linear growth assumptions
Important educational policy decisions, like whether to shorten or extend the school year, often assume that growth in achievement is linear through the school year.Ā This research examines this untested assumption using data from seven million students in kindergarten through 8th grade across the fall, winter, and spring of the 2016-17 school year.
By: Megan Kuhfeld, James Soland
Topics: Measurement & scaling, Growth modeling, Seasonal learning patterns & summer loss
In this study, we examine seasonal patterns of racial/ethnic achievement gaps in kindergarten through eighth grade using a national sample of over 2.5 million students.
By: Megan Kuhfeld, Dennis Condron, Doug Downey
Projecting the potential impact of COVID-19 school closures on academic achievement
This study provides a series of projections of COVID-19-related learning loss based on estimates from absenteeism literature and analyses of summer learning patterns of 5 million students.
By: Megan Kuhfeld, James Soland, Beth Tarasawa, Angela Johnson, Erik Ruzek, Jing Liu
Topics: COVID-19 & schools, Growth modeling, Seasonal learning patterns & summer loss
This study examined the benefits of pre-K through the end of kindergarten for children from low-income homes in a large and diverse county, and factors associated with a reduction in benefits during the kindergarten year.
By: Erik Ruzek, Arya Ansari, Robert Pianta, Jessica Whittaker, Virginia Vitiello
Topics: Early learning
Mind the kinder-gap: New data on childrenās math and reading skills as they enter kindergarten
Data on childrenās academic preparation at kindergarten entry tell a story of both declining achievement and shrinking gaps.
By: Christine Pitts, Megan Kuhfeld
Topics: Early learning, Equity
A huge portion of what we know about how humans develop, learn, behave, and interact is based on survey data. Although there is great deal of guidance on scaling and linking IRT-based large-scale educational assessment to facilitate the estimation of examinee growth, little of this expertise is brought to bear in the scaling of psychological and social-emotional constructs. Through a series of simulation and empirical studies, we produce scores in a single-cohort repeated measure design using sum scores as well as multiple IRT approaches and compare the recovery of growth estimates from longitudinal growth models using each set of scores.
By: Megan Kuhfeld, James Soland
Topics: Measurement & scaling, Growth modeling, Social-emotional learning
Using retest data to evaluate and improve effort-moderated scoring
This study investigated effortāmoderated (EāM) scoring, in which item responses classified as rapid guesses are identified and excluded from scoring, and its affect on score distortion from disengaged test taking.
By: Steven Wise, Megan Kuhfeld
Topics: Measurement & scaling, Innovations in reporting & assessment, School & test engagement