Background Although generic skills development is a concern of educational policy and accreditation bodies, little is known about how engineering students perceive generic skills in relation to their motivation for learning such skills. The development of these skills is often done only through ad hoc approaches, without a well-structured curriculum design framework. Disagreement over the nuances and interpretations of generic skills across disciplines makes framework design even more challenging.Purpose/Hypothesis To investigate students' perceptions of generic skills on a disciplinary basis, this article reports the development and validation of the Generic Skills Perception Questionnaire designed for investigating engineering students' perceptions of their level of competency in these skills.Design/Method The questionnaire was administered to 1,241 first-year engineering students from three universities in Hong Kong. Most of the questionnaire was items asking students to rate their perceived level of competency in 38 generic skills. Exploratory and confirmatory factor analyses were performed to examine the psychometric properties of the instrument for providing evidence on reliability and validity.Results Exploratory factor analysis resulted in eight scales. Confirmatory factor analyses demonstrated that the correlated eight-factor model and higher-order factor model provided an acceptable fit with the data. Cronbach's alpha values indicated that the scales were reliable. ConclusionsThe questionnaire was reliable and valid. Findings from the questionnaire will help develop a conceptual framework facilitating the understanding of engineering students' generic skills development.

In item response theory (IRT) models, assessing model-data fit is an essential step in IRT calibration. While no general agreement has ever been reached on the best methods or approaches to use for detecting misfit, perhaps the more important comment based upon the research findings is that rarely does the research evaluate IRT misfit by focusing on the practical consequences of misfit. The study investigated the practical consequences of IRT model misfit in examining the equating performance and the classification of examinees into performance categories in a simulation study that mimics a typical large-scale statewide assessment program with mixed-format test data. The simulation study was implemented by varying three factors, including choice of IRT model, amount of growth/change of examinees’ abilities between two adjacent administration years, and choice of IRT scaling methods. Findings indicated that the extent of significant consequences of model misfit varied over the choice of model and IRT scaling methods. In comparison with mean/sigma (MS) and Stocking and Lord characteristic curve (SL) methods, separate calibration with linking and fixed common item parameter (FCIP) procedure was more sensitive to model misfit and more robust against various amounts of ability shifts between two adjacent administrations regardless of model fit. SL was generally the least sensitive to model misfit in recovering equating conversion and MS was the least robust against ability shifts in recovering the equating conversion when a substantial degree of misfit was present. The key messages from the study are that practical ways are available to study model fit, and, model fit or misfit can have consequences that should be considered when choosing an IRT model. Not only does the study address the consequences of IRT model misfit, but also it is our hope to help researchers and practitioners find practical ways to study model fit and to investigate the validity of particular IRT models for achieving a specified purpose, to assure that the successful use of the IRT models are realized, and to improve the applications of IRT models with educational and psychological test data.

BackgroundItem response theory (IRT) has been increasingly applied to patient-reported outcome (PRO) measures. The purpose of this study is to apply IRT to examine item properties (discrimination and severity of depressive symptoms), measurement precision and score comparability across five depression measures, which is the first study of its kind in the Chinese context.MethodsA clinical sample of 207 Hong Kong Chinese outpatients was recruited. Data analyses were performed including classical item analysis, IRT concurrent calibration and IRT true score equating. The IRT assumptions of unidimensionality and local independence were tested respectively using confirmatory factor analysis and chi-square statistics. The IRT linking assumptions of construct similarity, equity and subgroup invariance were also tested. The graded response model was applied to concurrently calibrate all five depression measures in a single IRT run, resulting in the item parameter estimates of these measures being placed onto a single common metric. IRT true score equating was implemented to perform the outcome score linking and construct score concordances so as to link scores from one measure to corresponding scores on another measure for direct comparability.ResultsFindings suggested that (a) symptoms on depressed mood, suicidality and feeling of worthlessness served as the strongest discriminating indicators, and symptoms concerning suicidality, changes in appetite, depressed mood, feeling of worthlessness and psychomotor agitation or retardation reflected high levels of severity in the clinical sample. (b) The five depression measures contributed to various degrees of measurement precision at varied levels of depression. (c) After outcome score linking was performed across the five measures, the cut-off scores led to either consistent or discrepant diagnoses for depression.ConclusionsThe study provides additional evidence regarding the psychometric properties and clinical utility of the five depression measures, offers methodological contributions to the appropriate use of IRT in PRO measures, and helps elucidate cultural variation in depressive symptomatology. The approach of concurrently calibrating and linking multiple PRO measures can be applied to the assessment of PROs other than the depression context.

Purpose In patient-reported outcome research that utilizes item response theory (IRT), using statistical significance tests to detect misfit is usually the focus of IRT model-data fit evaluations. However, such evaluations rarely address the impact/consequence of using misfitting items on the intended clinical applications. This study was designed to evaluate the impact of IRT item misfit on score estimates and severity classifications and to demonstrate a recommended process of model-fit evaluation. Methods Using secondary data sources collected from the Patient-Reported Outcome Measurement Information System (PROMIS) wave 1 testing phase, analyses were con ducted based on PROMIS depression (28 items; 782 cases) and pain interference (41 items; 845 cases) item banks. The identification of misfitting items was assessed using Orlando and Thissen’s summed-score item-fit statistics and graphical displays. The impact of misfit was evaluated according to the agreement of both IRT-derived T-scores and severity classifications between inclusion and exclusion of misfitting items. Results The examination of the presence and impact of misfit suggested that item misfit had a negligible impact on the T-score estimates and severity classifications with the general population sample in the PROMIS depression and pain interference item banks, implying that the impact of item misfit was insignificant. Conclusions Findings support the T-score estimates in the two item banks as robust against item misfit at both the group and individual levels and add confidence to the use of T-scores for severity diagnosis in the studied sample. Recommendations on approaches for identifying item misfit (statistical significance) and assessing the misfit impact (practical significance) are given.