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College admissions leaders increasingly desire to incorporate non-cognitive factors like grit into admissions decisions. Consequently, we examined the validity of the Short Grit Scale (Grit-S) using data collected on undergraduates attending 38 colleges. Using confirmatory factor analysis (CFA), we found that Grit-S does not possess adequate model fit; however, a modified version of the scale does possess this property. Using multi-group CFA, we also found that Grit-S is relatively invariant across multiple demographic groups. Next, we examined the concurrent validity of grit with students' engagement, perceived gains, time spent studying, and grades.These results confirmed previous research that most of the predictive power of grit is contained in its perseverance of effort, not consistency of interest, dimension.

Findings from national studies along with more frequent calls from those who employ college graduates suggest an urgent need for colleges and universities to increase opportunities for students to develop quantitative reasoning (QR) skills. To address this issue, the current study examines the relationship between the frequency of QR activities during college and student and institutional characteristics, as well as whether students at institutions with an emphasis on QR (at least one QR course requirement for all students) report more QR activity. Results show that gender, race-ethnicity, major, full-time status, first-generation status, age, institutional enrollment size, and institutional control are related to the frequency of QR activities. Findings also suggest that such activities are indeed more common among institutions that emphasize QR.

Colleges and universities in the United States are being challenged to assess student outcomes and the quality of programs and services (McPherson and Shulenburger, 2006; Commission on the Future of Higher Education, 2006). One of the more widely used sources of evidence is student engagement as measured by a cluster of student engagement surveys administered by the Center for Postsecondary Research at Indiana University. They include the National Survey of Student Engagement (NSSE) and its companion projects: the Beginning College Survey of Student Engagement, Faculty Survey of Student Engagement, and Law School Survey of Student Engagement. The University of Texas-Austin hosts the two-year variation of the NSSE, the Community College Survey of Student Engagement.With more than thirteen hundred colleges and universities using NSSE, many institutional researchers may benefit from guidance about how to understand and use these data. This chapter shares practical tips and recommendations for the analysis and interpretation of NSSE data. We divided the chapter into three parts. The first offers six overarching tips and recommendations for working with student engagement data. We then discuss considerations for the analysis of multiple years of student engagement data. Finally, we describe how effect sizes can be used and interpreted to make student engagement results more meaningful. 35 3 NEW DIRECTIONS FOR INSTITUTIONAL RESEARCH, no. 141, Spring 2009

The popularity of online student surveys has been associated with greater item nonresponse. This chapter presents research aimed at exploring what factors might help minimize item nonresponse, such as altering online survey page length and using progress indicators.