Information Outlook, May 2003

Volume 7, Issue 5https://scholarworks.sjsu.edu/sla_io_2003/1004/thumbnail.jp

Effects of additions to independent silent reading on students’ reading proficiency, motivation, and behavior:Results of a meta-analysis

One often used approach to increase students' reading frequency is investing in independent silent reading (ISR) at schools: regularly scheduling time during which students read silently in books of their own choice. However, evidence for the impact of ISR is inconclusive and there appear to be important barriers to its effects on students' reading frequency, motivation, and proficiency: particularly struggling readers have difficulties choosing appropriate books, simply allotting time for reading does not guarantee that students read, ISR lacks accountability, and students are not always given the opportunity to interact about what they read. The aim of the current meta-analysis was to test whether additions to ISR that aim to overcome these barriers contribute to the effects of ISR on students' reading. Using outcomes of 51 effect studies covering 56 samples of students in primary and secondary education, we established a small but significant positive short-term intervention effect on overall reading proficiency (Cohen's d = 0.27). We additionally found that additions to ISR were particularly effective for students at risk of reading failure; for stronger readers, effects were absent. Finally, we found a negative effect of help or instruction by the teacher, which suggests that activities during reading might interfere with students' engagement with texts.</p

A Data Science Course for Undergraduates: Thinking with Data

Data science is an emerging interdisciplinary field that combines elements of mathematics, statistics, computer science, and knowledge in a particular application domain for the purpose of extracting meaningful information from the increasingly sophisticated array of data available in many settings. These data tend to be non-traditional, in the sense that they are often live, large, complex, and/or messy. A first course in statistics at the undergraduate level typically introduces students with a variety of techniques to analyze small, neat, and clean data sets. However, whether they pursue more formal training in statistics or not, many of these students will end up working with data that is considerably more complex, and will need facility with statistical computing techniques. More importantly, these students require a framework for thinking structurally about data. We describe an undergraduate course in a liberal arts environment that provides students with the tools necessary to apply data science. The course emphasizes modern, practical, and useful skills that cover the full data analysis spectrum, from asking an interesting question to acquiring, managing, manipulating, processing, querying, analyzing, and visualizing data, as well communicating findings in written, graphical, and oral forms.Comment: 21 pages total including supplementary material

Graduate Connections- April 2009

In This Issue: Click on links to navigate the newsletter Navigating Graduate School......1 Working with Your Supervisor Tips for Publishing How to Think and Act as a Writer Good Practices in Graduate Education......................................4 The Ethics of Authorship Essential Connections..................5 How Does Your Teaching Impact Undergraduates? Creating a Syllabus Teaching Tip .................................6 Helping Students Read Research Literature Professional Development...........8 Academic Job Search Timeline Is a Postdoc in Your Future? Launching Your Career Funding Opportunities...............11 Events..........................................13 Research Fair ITA Institute SPEAK Test TA Campus-wide Workshop Announcements..........................15 Calendar......................................16 Interactions.................................16 GSA News Readers’ Corner.........................17 Professors as Writer

University of Michigan Law School Faculty, 2011-2012

Biographies of the University of Michigan Law School faculty