This report is the fourth in a series considering career-readiness factors within existing high school assessments. The primary goal of this study was to provide a preliminary validation of the career-readiness features identified in prior reports by exploring how different participant groups with different levels of experience in the career/vocational world perform on a selection of test items with high numbers of careerreadiness features. Two exemplar careers, emergency medical technician (EMT) and web developer, were targeted for participation in this study. A total of 103 high school students, 111 community college students studying to become either EMTs or web developers, and 84 working EMTs or web developers participated in the study. A selection of ELA and math test items rated for career-readiness features were adapted into an 18-item test booklet. As expected, results indicated that workforce individuals scored significantly higher on the test than community college students, who in turn scored significantly higher on the test than high school students. These results suggest that having added experience in their field may lead to refining certain career-readiness skills found in high-school-level content-based assessments. Preparation for such assessments can help high school students prepare for college and/or a career, and inferences for both college and career readiness can be drawn from test performance.
The findings and opinions expressed in this report are those of the authors and do not necessarily reflect the positions or policies of Research for Action Inc. or the Bill and Melinda Gates Foundation. Kentucky has been a leader in the movement to more rigorous college and career ready standards to support their students' success in the 21st century. The first state to adopt new college and career ready standards (CCRS), termed the Kentucky Core Academic Standards, Kentucky and many of its districts have moved proactively and strategically to meet the challenge of more rigorous expectations and to facilitate educators and students' transition to the new demands. All students are to be on a trajectory to graduate high school, and should be prepared for college and career success. Basic skills have given way to goals for deeper learning, where students are expected to apply, reason with, communicate, and use their knowledge to solve complex problems. This brief summarizes early evidence on the success of two tools Kentucky districts have used to support their teachers' transition to these more demanding goals: Literacy Design Collaborative (LDC) and Math Design Collaborative (MDC). With support from the Bill and Melinda Gates Foundation, LDC and MDC tools have been designed and implemented to embody the key shifts in teaching and learning that the new standards demand. By implementing the tools, teachers then engage in new pedagogy and address relevant learning goals of the Kentucky Core Academic Standards. In the sections that follow, we provide a brief background on the two tools and our evaluation methodology. We then follow with findings for each intervention and conclude with implications of our findings across the two studies. We stress that our methods were rigorous and our findings positive, but still our study provides only an " early read " on LDC and MDC effectiveness. Our quasi-experimental design cannot separate the effects of LDC and MDC from other changes that may have been going on in the study districts and schools. Further, our study is based on a limited sample of schools and teachers in select subjects and grade levels who participated in the piloting of the tools. These included eighth grade social studies/history and science teachers and ninth grade Algebra 1 teachers who initiated their tool use during the 2010-11 or 2011-12 school years. Study results are based on data from the 2012-2013 school year. Full technical reports …
We present a logistic function of a monotonic polynomial with a lower asymptote, allowing additional flexibility beyond the three-parameter logistic model. We develop a maximum marginal likelihood based approach to estimate the item parameters. The new item response model is demonstrated on math assessment data from a state, and a computationally efficient strategy for choosing the order of the polynomial is demonstrated. Finally, our approach is tested through simulations and compared to response function estimation using smoothed isotonic regression. Results indicate that our approach can result in small gains in item response function recovery and latent trait estimation.
