TPC Journal V8, Issue 1 - FULL ISSUE

The Professional Counselor | Volume 8, Issue 1 25 Based on the results of the factor analysis, the researchers used results from a one-parameter Rasch analysis to reduce the number of items on the RIS. Classical Testing Homogeneity was explored by computing Kuder-Richardson 20 (KR 20 ) alphas. Across all 68 items the internal consistency was strong (.92). Concurrent validity (i.e., construct validity) was examined by looking at correlations between the RIS and the RSES. The overall correlation between the RIS and the RSES was .66 ( p < .001). Item Response Analysis Item response theory brought about a new perspective on scale development (Embretson & Reise, 2000) in that it promoted scale refinement even at the initial stages of testing. Item response theory allows for shorter tests that can actually be more reliable when items are well-composed (Embretson & Reise, 2000). The RIS initially included 68 items. Through Rasch analyses, the scale was reduced to 21 items (items numbered 3, 4, 9, 10, 12, 13, 16, 18, 19, 24, 26, 34, 39, 41, 42, 43, 44, 46, 47, 49, 61). The final 21 items were selected for their dispersion across location on theta in order to widely capture the constructs. The polychoric correlation matrix for the 21 items was then subjected to a principal components analysis yielding an initial eigenvalue of 11.72. The next eigenvalue was 1.97, which clearly identified the crook of the elbow. Further, Cronbach’s alpha for these 21 items was .90. Taken together, these results suggest that the 21-item RIS measures a single factor. This conclusion was further tested by fitting the items to a two-parameter Rasch model (AIC = 3183.1). Slopes were constrained to unity (1.95), and item location estimates are presented in Table 1. Bayesian a posteriori scores also were estimated and strongly correlated with classical scores (i.e., tallies of the number of positive responses [ r = .95, p < .0001]). Discussion This scale represents a move from subjective to a more objective assessment of RI. In the future, the scale may be used with other student and non-student populations to better establish its psychometric properties, generalizability, and refinement. Although this study sampled undergraduate students, this scale may be well-suited to use with counseling graduate students and practitioners because items were developed based on a qualitative study with master’s-level counseling students and practicing counselors (Jorgensen & Duncan, 2015a). Additionally, this scale offers another method for assessing student learning and changes that take place for both students and professionals. As indicated by Holden et al. (1999), it is important to assess learning in multiple ways. Traditional methods may have focused on measuring outcomes that reflect a performance-based, rather than a mastery-based, learning orientation. Performance-based learning has been defined as wanting to learn in order to receive external validation such as a grade (Bruning, Schraw, Norby, & Ronning, 2004). Mastery learning has been defined as wanting to learn for personal benefit and with the goal of applying information to reach a more developed personal and professional identity (Bruning et al., 2004). Based on what is known about mastery learning (Bruning et al., 2004), students with this type of learning orientation experience identity changes that may be best captured through assessing changes in thoughts, attitudes, and beliefs. The RIS was designed to measure constructs that capture internal