Student Engagement at a Large Suburban Community College: Gender and Race Differences

Previous research shows that there are individual differences in academic achievement associated with gender and race. Research also suggests that student engagement is an important determinant of student outcomes/achievement. The present study explored student engagement at an extra-large community college. It specifically investigated possible individual differences in student engagement and explored how it maps on to student achievement. As predicted, the results indicate that there are gender and race differences in student engagement—females show greater engagement than males, and African-American students show greater engagement than students of other races. The results are discussed in the context of student achievement as indicated by students’ self-reported GPAs.     

Peer Coaching of At-Risk Students in a Remedial Mathematics Course

Remedial mathematics at the college level has evidenced strikingly low retention and passing rates. It has been shown that at least 25% of the variation in student performance is explained by students’ affective variables such as attitudes, study skills, and mathematics anxiety. This study endeavored to address affective variables by: (a) incorporating the teaching of study skills into an elementary algebra course; and (b) identifying at-risk students and assigning these students “coaches,” who functioned both as tutors and counselors, providing regular personalized assistance. The results showed that the attrition rate was significantly lower in the treatment groups, and the overall passing rate for coached students was significantly higher.     

Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling

A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or simple hypotheses about these coefficients. The proposed method is illustrated with a numerical example.     

Examining Measure Correlations With Incomplete Data Sets

A 2-stage procedure for estimation and testing of observed measure correlations in the presence of missing data is discussed. The approach uses maximum likelihood for estimation and the false discovery rate concept for correlation testing. The method can be used in initial exploration-oriented empirical studies with missing data, where it is of interest to estimate manifest variable interrelationship indexes and test hypotheses about their population values. The procedure is applicable also with violations of the underlying missing at random assumption, via inclusion of auxiliary variables. The outlined approach is illustrated with data from an aging research study.     

How invariant and accurate are domain ratings in writing assessment?

The use of evidence to guide policy and practice in education (Cooper, Levin, & Campbell, 2009) has included an increased emphasis on constructed-response items, such as essays and portfolios. Because assessments that go beyond selected-response items and incorporate constructed-response items are rater-mediated (Engelhard, 2002, Engelhard, 2013), it is necessary to develop evidence-based indices of quality for the rating processes used to evaluate student performances. This study proposes a set of criteria for evaluating the quality of ratings based on the concepts of measurement invariance and accuracy within the context of a large-scale writing assessment. Two measurement models are used to explore indices of quality for raters and ratings: the first model provides evidence for the invariance of ratings, and the second model provides evidence for rater accuracy. Rating quality is examined within four writing domains from an analytic rubric. Further, this study explores the alignment between indices of rating quality based on these invariance and accuracy models within each of the four domains of writing. Major findings suggest that rating quality varies across analytic rubric domains, and that there is some correspondence between indices of rating quality based on the invariance and accuracy models. Implications for research and practice are discussed.     

RAN Components and Reading Development From Grade 3 to Grade 5: What Underlies Their Relationship?

We examined (a) how rapid automatized naming (RAN) components—articulation time and pause time—predict reading accuracy and reading fluency in Grades 4 and 5, and (b) what cognitive-processing skills (phonological processing, orthographic processing, or speed of processing) mediate the RAN–reading relationship. Sixty children were followed from Grade 3 to Grade 5 and were administered RAN (Letters and Digits), phonological processing, lexical and sublexical orthographic processing, speed of processing, reading accuracy, and fluency tasks. Pause time was highly correlated with reading fluency and shared more of its predictive variance with lexical orthographic processing and speed of processing than with phonological processing. Articulation time also predicted reading fluency, and its contribution was mostly independent from other cognitive-processing skills. Implications for the relationship between RAN and reading are discussed.     

Rapid Naming Components and Their Relationship With Phonological Awareness,Orthographic Knowledge,Speed of Processing,and Different Reading Outcomes

This study examines (a) how rapid automatized naming (RAN) speed components—articulation time and pause time—predict reading accuracy and reading fluency in Grades 2 and 3, and (b) how RAN components are related to measures of phonological awareness, orthographic knowledge, and speed of processing. Forty-eight children were administered RAN tasks in Grades 1, 2, and 3. Results indicated that pause time was highly correlated with both reading accuracy and reading fluency measures and shared more of its predictive variance with orthographic knowledge than with phonological awareness or speed of processing. In contrast, articulation time was only weakly correlated with the reading measures and was rather independent from any processing skill at any point of measurement.     

Do Poor Readers Feel Angry,Sad, and Unpopular?

We investigated whether being poorly skilled in reading contributes to children's reported feelings of anger, distractibility, anxiety, sadness, loneliness, and social isolation. Data were analyzed from a longitudinal subsample of children (N?=?3,308) participating in the Early Childhood Longitudinal Study–Kindergarten Cohort. Multilevel logistic regression analyses indicated that poor readers in third grade were about twice as likely to consider themselves as angry, distractible, sad, lonely, and unpopular in fifth grade as those who had not been poor readers in third grade. Being poorly skilled in mathematics increased children's risk of feeling sad or lonely but not of feeling angry, distractible, or unpopular. The results provide additional empirical evidence that reading failure contributes to generalized socioemotional maladjustment in young children.