Perceived organizational structure for teacher liking: the role of peers’ perceptions of teacher liking in teacher–student relationship quality,motivation, and achievement

Previous research has identified the role of perceived peer hierarchies, or organizational structures, in affecting students’ adjustment to school (Lease et al. 2003, Journal of Early Adolescence, 23, 194–217). The purpose of this study was to examine whether middle school classrooms can be described in terms of the perceived status individual students hold for who will and will not be ‘liked’ by the teacher. Specifically we examined: (1) Do students share a mutually agreed on representation, a perceived organizational structure, for describing relative status with their teacher? (2) Are teachers perceived as systematically favoring girls or boys? (3) Are peers’ perceptions of teacher liking associated with individual students’ social and academic motivation and relationship quality with teachers? (4) Are students identified by peers as ‘not liked’ at risk for long-term teacher rejection and underachievement? And, (5) What are the underlying criteria students use to judge teacher likeability? Data for this study were drawn from peer ratings from 516 (262 boys, 254 girls) middle school students in 20 classrooms. Findings indicate multidimensional scaling techniques can be used to map the ‘teacher-liking space,’ accounting for  > 90% of the variability in peers’ ratings of teacher likeability. Additionally, findings indicate perceived status in the teacher-liking space has consequences for students’ achievement and teacher relationship quality.     

Dissimilarity cumulation theory and subjective metrics

We present a new mathematical notion, dissimilarity function, and based on it, a radical extension of Fechnerian Scaling, a theory dealing with the computation of subjective distances from pairwise discrimination probabilities. The new theory is applicable to all possible stimulus spaces subject to the following two assumptions: (A) that discrimination probabilities satisfy the Regular Minimality law and (B) that the canonical psychometric increments of the first and second kind are dissimilarity functions. A dissimilarity function Dab for pairs of stimuli in a canonical representation is defined by the following properties: (1) a≠b?Dab>0; (2) Daa=0; (3) If and , then ; and (4) for any sequence {a_nX_nb_n}_n∈N, where X_n is a chain of stimuli, Da_nX_nb_n→0?Da_nb_n→0. The expression DaXb refers to the dissimilarity value cumulated along successive links of the chain aXb. The subjective (Fechnerian) distance between a and b is defined as the infimum of DaXb+DbYa across all possible chains X and Y inserted between a and b.     

Identifying similarities in cognitive subtest functional requirements: An empirical approach

In the cognitive test interpretation literature, a Rational/Intuitive, Indirect Empirical, or Combined approach is typically used to construct conceptual taxonomies of the functional (behavioral) similarities between subtests. To address shortcomings of these approaches, the functional requirements for 49 subtests from six individually administered scales of cognitive ability (WISC-IV, WPPSI-III, SB-V, WJ-III, CAS, and UNIT) were typed on index cards. Forty-eight (48) in-service and/or pre-service school psychologists were asked to sort the cards into two, three, five, or eight functionally similar piles. A multidimensional scaling analysis was performed on a 49 × 49 matrix of similarity scores collapsed across all 48 subjects. Three dimensions were extracted from the data: Reproduction of Stimuli Sequences versus Picture Viewing (Dimension 1), Timed Speed versus Untimed Power (Dimension 2), and Verbal versus Performance (Dimension 3). A hierarchical clustering procedure was then applied to the matrix data, and results were compared to previous categorization schemes identified in the test interpretation literature.     

Goodness-of-Fit Assessment in Multidimensional Scaling and Unfolding

Judging goodness of fit in multidimensional scaling requires a comprehensive set of diagnostic tools instead of relying on stress rules of thumb. This article elaborates on corresponding strategies and gives practical guidelines for researchers to obtain a clear picture of the goodness of fit of a solution. Special emphasis will be placed on the use of permutation tests. The second part of the article focuses on goodness-of-fit assessment of an important variant of multidimensional scaling called unfolding, which can be applied to a broad range of psychological data settings. Two real-life data sets are presented in order to walk the reader through the entire set of diagnostic measures, tests, and plots. R code is provided as supplementary information that makes the whole goodness-of-fit assessment workflow, as presented in this article, fully reproducible.     

“Delayed Response” as Tested by three Methods and its Relation to Other Learning Situations

The so-called “nervous habits” of 198 students were assessed by time-sampling 22 movement categories. Concentration of manipulatory behavior in the head and hand areas suggested that the stimulation generated by these activities is of some importance. Compared to men, women showed less facial manipulation and less leg and foot movement, but compensated, particularly by more nail-biting and manicure. Category scores did not have significant linear correlations with either Extraversion or Neuroticism scores on the Eysenck Personality Inventory (EPI). This may be due to idiosyncrasies in movement patterns.     

Advancement of Criminal Profiling Methods in Faceted Multidimensional Analysis

The current study seeks to advance the faceted multidimensional scaling (termed FMDS) procedure used in much of the investigative psychology research. To this end, recent research on street robbery by Goodwill and colleagues will be utilised to illustrate the effectiveness of a facet scale method for offender profiling. Four FMDS themes of street robbery (Con, Blitz, Confrontation and Snatch) were revealed by the crossing of two underlying axial facets: the offenders' level of violence and interaction with the victim. The facet scale method, utilising offenders' axial facet scores, was compared to previous count, proportional and centroid classification methods in the prediction of offender criminal histories. Utilising logistic regression and receiver operating characteristic analyses, the axial facet scale method was found to significantly outperform the qualitatively based dominant theme classification methods that typically employ angular and radial facets for FMDS interpretation. Implications for the use of axial facet scales within FMDS analysis for offender profiling research are discussed. Copyright © 2012 John Wiley & Sons, Ltd.     

Measuring Schwartz's values in childhood: Multidimensional scaling across instruments and cultures

The Picture-Based Value Survey for Children (PBVS-C; Döring et al., 2010) assesses children's values through self-report and thereby depicts Schwartz's theory of universal human values at an early age. Despite evidence on the PBVS-C's structural validity, there remains an open question: Does the PBVS-C measure the same values as does Schwartz's Portrait Values Questionnaire (PVQ; Schwartz et al., 2001), an established assessment instrument for adult and adolescent respondents? To answer this question about the PBVS-C's validity, Polish (N = 167) and German (N = 119) children's values were measured with both instruments. The multitrait–multimethod correlation matrix (Campbell & Fiske, 1959) of value items from both instruments was analysed with multidimensional scaling (MDS), as proposed by Borg and Groenen (1997). Our structural expectations for the MDS output about the distinctiveness (1) of Schwartz's higher order value types (i.e., traits) and (2) of the two assessment methods (PBVS-C and PVQ) were confirmed in both samples.     

中国员工基于组织自尊的内容探析：概念构图法的应用

基于对26名来自不同组织、有不同职业背景员工的深度采访,本文运用定性和定量相结合的分析方法——概念构图法,实证探索了中国员工基于组织的自尊（OBSE）的内容。本研究发现,中国员工自尊包括五个维度：基于工作单位的自尊、基于工作绩效的自尊、基于工作角色的自尊,基于领导的自尊和基于下属和同事的自尊。本文通过对OBSE的实证分析详细介绍了概念构图法的过程和应用,为如何对新概念、新现象进行探索性研究提供了参考。     

Investigating Separate and Concurrent Approaches for Item Parameter Drift in 3PL Item Response Theory Equating

This study examines separate and concurrent approaches to combine the detection of item parameter drift (IPD) and the estimation of scale transformation coefficients in the context of the common item nonequivalent groups design with the three-parameter item response theory equating. The study uses real and synthetic data sets to compare the two approaches based on IPD flagging rates, type I error and power rates, and recovery of scale transformation coefficients. Results indicate that the two approaches render similar outcomes with stable anchor sets. However, they can produce dissimilar results with unstable anchor sets because of differences in the performance of their IPD components. Further, the findings of this study caution about working backward from equated cut scores to motivate the selection of an anchor set.     

A tutorial on how to do a Mokken scale analysis on your test and questionnaire data

Over the past decade, Mokken scale analysis (MSA) has rapidly grown in popularity among researchers from many different research areas. This tutorial provides researchers with a set of techniques and a procedure for their application, such that the construction of scales that have superior measurement properties is further optimized, taking full advantage of the properties of MSA. First, we define the conceptual context of MSA, discuss the two item response theory (IRT) models that constitute the basis of MSA, and discuss how these models differ from other IRT models. Second, we discuss dos and don'ts for MSA; the don'ts include misunderstandings we have frequently encountered with researchers in our three decades of experience with real‐data MSA. Third, we discuss a methodology for MSA on real data that consist of a sample of persons who have provided scores on a set of items that, depending on the composition of the item set, constitute the basis for one or more scales, and we use the methodology to analyse an example real‐data set.