This study investigated the direct and indirect relationships between participating in a learning community, student engagement, and self-reported learning outcomes. Using a sample of 241 freshmen at a single urban research university who took the College Student Experiences Questionnaire, the results indicate that after controlling for demographic characteristics and entering composite ACT score, the relationship between learning community participation and learning outcomes are mediated by students' levels of engagement. Learning community participation was not directly related to educational gains but was indirectly related to educational gains through student engagement. Student engagement in turn was strongly related to educational gains.

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The present study was designed to extend research on supplementing social skills training (SST) with a Tootling intervention to enhance student performance of social skills in authentic social contexts. The Tootling intervention included an interdependent group contingency with randomly selected criteria, which involved the after-school class receiving rewards contingent upon students reporting classmates' performance of prosocial behaviors as they participated in a typical school activity. First, reinforcement was delivered contingent upon peer reports of classmates' giving compliments. In subsequent phases, peer reports of classmates providing encouragement and saying thank you were added to the contingency, but each day students did not know which of these behaviors was selected as the criterion for reinforcement. Results from our multiple baseline across behaviors design provided three demonstrations of a treatment effect. When peer reports of each social skill were added to the contingency, the targeted social behavior increased. Discussion focuses on supplementing SST with Tootling interventions to enhance student performance of prosocial behaviors outside the SST context. Impact and ImplicationsElementary students often monitor and report their classmates' antisocial behavior-they tattle. We taught students' prosocial behaviors (complimenting and encouraging peers and saying thank you) and reinforced them for tootling or reporting when classmates engaged in these prosocial behaviors. After the Tootling intervention was applied to each behavior, students increased their performance of these behaviors as they played.

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.

Pascarella (J Coll Stud Dev 47:508-520, 2006) has called for an increase in use of longitudinal data with pretest-posttest design when studying effects on college students. However, such designs that use multiple measures to document change are vulnerable to an important threat to internal validity, regression to the mean. Herein, we discuss a brief history of regression to the mean and illustrate a straightforward procedure to make adjustments to initial pretest scores for regression to the mean effects utilizing a method developed by Roberts (in: G. Echternacht (Guest ed.) New directions for testing and measurement, 1980). Analyses are shown with both unadjusted and adjusted pretest scores, illustrating dramatic differences in conclusions about whether students change across time.Keywords Regression to the mean Á Pre-test/post-test design Á Methodology Á Longitudinal data Á College students Á Change Higher education researchers have been aided in their study of college and university faculty and students by longitudinal data, and the models that have guided most of the recent research on the effects of college on students are longitudinal in nature (Smart et al. 2000). Moreover, longitudinal studies have provided college and university administrators with a plethora of support in making data based decisions related to policies and practices applied to individual institutions. Pascarella (2006) has even called for an increase in use of longitudinal data with pretest-posttest design when studying effects on college students. While longitudinal data can be beneficial to scholars and administrators alike, it can also be very difficult to conduct, very time-consuming, and costly.

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To construct and validate a scale of emotional intelligence (EI) for the medical field, n = 80 resident physicians responded to a 69-item self-report measure during the pilot phase of development of the Scale of Emotional Functioning: Medicine (SEF:MED). Based on multiple-phase item and structural analyses, a final 36-item version was created based on data from n = 321 respondent residents. Initially exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) supported the expected three-factor solution as did additional CFA from a second sample of n = 113 participants. Internal consistency reliabilities obtained from the original n = 321 residents for the three SEF:MED subscales of Interpersonal Skills (IS), Emotional Awareness (EA), and Emotional Management (EM) were 0.81, 0.82, and 0.84, respectively. Alphas for the second CFA data set were 0.89, 0.87, and 0.88 for IS, EM, and EA, respectively. In addition, the SEF:MED was validated by comparing it to related measures (i.e., the Profile of Emotional Competence (PEC) and the Maslach Burnout Inventory-Human Services Survey for Medical Personnel [MBI-HSS (MP)]); Correlation coefficients between the Total EI composite on the SEF:MED and the PEC global scales ranged from r = 0.64 to 0.68. Finally, correlation coefficients from the Total EI composite on the SEF:MED significantly related to the MBI-HSS (MP) Emotional Exhaustion (EE), Depersonalization (DP), and Personal Accomplishment (PA) scales (r = −0.50, −0.44, and 0.52, respectively). The SEF:MED may provide useful data to physicians and other medical professionals as they consider their own well-being and how it may affect care of their patients.

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