Development of the Counseling Center Assessment of Psychological Symptoms-62 (CCAPS-62)

Few instruments have been designed specifically to address the needs of college counseling centers. This article reviews existing instruments and presents 4 studies that describe the development and psychometric properties of a new instrument, the Counseling Center Assessment of Psychological Symptoms-62 (CCAPS-62). Study 1 describes the initial item development, factor analysis, and preliminary scale development steps. Study 2 describes the results of exploratory and confirmatory factor analyses using data from more than 22,000 clients pooled via a national practice-research network of counseling centers. Studies 3 and 4 provide preliminary evidence of subscales' convergent validity and retest reliability. Results from these 4 studies provide support for the instrument's factor structure, construct validity, and subscale reliabilities for both the total sample and subgroups. Clinical and methodological issues pertaining to the future development of the CCAPS are discussed in the context of a national practice-research network of college counseling centers.     

CTTITEM: SAS macro and SPSS syntax for classical item analysis

This article describes the functions of a SAS macro and an SPSS syntax that produce common statistics for conventional item analysis including Cronbach’s alpha, item difficulty index (p-value or item mean), and item discrimination indices (D-index, point biserial and biserial correlations for dichotomous items and item-total correlation for polytomous items). These programs represent an improvement over the existing SAS and SPSS item analysis routines in terms of completeness and user-friendliness. To promote routine evaluations of item qualities in instrument development of any scale, the programs are available at no charge for interested users. The program codes along with a brief user’s manual that contains instructions and examples are downloadable from suen.ed.psu.edu/~pwlei/plei.htm.     

Confirmatory factor analysis of the Early Arithmetic,Reading, and Learning Indicators (EARLI)

Despite growing interest in early intervention, there are few measures available to monitor the progress of early academic skills in preschoolers. The Early Arithmetic, Reading, and Learning Indicators (EARLI; DiPerna, Morgan, & Lei, 2007) were developed as brief assessments of critical early literacy and numeracy skills. The purpose of the current study was to examine the factor structure of the EARLI probes via confirmatory factor analysis (CFA) in a sample of Head Start preschoolers (N = 289). A two-factor model with correlated error terms and a bifactor model provided comparable fit to the data, although there were some structural problems with the latter model. The utility of the bifactor model for explaining the structure of early academic skills as well as the utility of the EARLI probes as measures of literacy and numeracy skills in preschool are discussed.     

Effect of Quality Characteristics of Peer Raters on Rating Errors in Peer Assessment

Little research has been done on the effects of peer raters’ quality characteristics on peer rating qualities. This study aims to address this gap and investigate the effects of key variables related to peer raters’ qualities, including content knowledge, previous rating experience, training on rating tasks, and rating motivation. In an experiment where training and motivation interventions were manipulated, 24 classes with 838 high school students were randomly assigned to study conditions. Inter-rater error, intra-rater error and criterion error indices for peer ratings on four selected essays were analyzed using hierarchical linear models. Results indicated that peer raters’ content knowledge, previous rating experience, and rating motivation were associated with rating errors. This study also found some significant interactions between peer raters’ quality characteristics. Implications for in-person and online peer assessments as well as future directions are discussed.