1,721,033 research outputs found
Measuring students'assessemnts on university course quality using mixed-effects models
No full textIn this work a generalized Item Response Model has been considered in order
to analyze students’ perceived quality of university course. The approach allows the
author to pursue several tasks in the estimation of item and person parameters. Namely:
(i) it allows to jointly model students’ answers to the whole set of indicator items; (ii)
it considers the dimensionality of the items composing the test by explicitly specifying
more than one latent trait; (iii) it evaluates the effect of significant characteristics on students’
perception of the latent traits; (iv) it takes into account the ‘intra-cluster’ variability
which affect ratings at course level. Moreover, by moving from the posterior estimates at
individual and course level, it has been possible to make pairwise comparisons between
courses and students on the bases of their levels of perceived quality
Assessing the effectiveness of a sthocastic regression imputation method for ordered categorical data
Full text linkThe main aim of this paper is to describe a workable method based on stochastic regression and multiple imputation analysis (MISR) to recover for missingness in surveys where multi-item Likert-type scale are used to measure a latent attribute (namely, the quality of university teaching). A simulation analysis has been carried out and results have been compared in terms of bias and efficiency with other missing data handling methods, specifically: Complete Cases Analysis (CCA) and Multiple Imputation by Chained Equations (MICE). The authors provide also functions (implemented in R language) to apply the procedure to a matrix of ordered categorical items. Functions described allow: (i) to simulate missing data at random and completely at random; (ii) to replicate the simulation study presented in this work in order to assess the accuracy in distribution and in estimation of a multiple imputation procedure
Quality of life among university students in Cagliari. A synthetic indicator
Full text linkThis article reports findings from a survey addressed to measure
university students’ quality of life in Cagliari. The aim to build up a synthetic
indicator of students’ ‘quality of life at the university’ has been pursued by
adopting an ad hoc modeling approach to scale ordered items (Item Response
Models) which belongs to the family of the Generalized Linear and non Linear
Mixed Models . The sensibility of the results has been deeply analyzed
by setting up several models with different characteristics. A comparison
study with other scaling methods has been made
A further proposal to multiple impute missing categorical values using Latent Class Analysis
No full textThe evaluation of university teaching. An imputation procedure to recover for messingness
No full text
Pointing Out Homogeneous Classes of Students Moving from Assessments of Management of Their Degree Schemes
No full textBuilding up adjusted indicators of students' evaluation of university courses using generalized item response models
No full textThis article advances a proposal for building up adjusted composite indicators of the quality of university courses from students' assessments. The flexible framework of Generalized Item Response Models is adopted here for controlling the sources of heterogeneity in the data structure that make evaluations across courses not directly comparable. Specifically, it allows us to: jointly model students' ratings to the set of items which define the quality of university courses; explicitly consider the dimensionality of the items composing the evaluation form; evaluate and remove the effect of potential confounding factors which may affect students' evaluation; model the intra-cluster variability at course level. The approach simultaneously deals with: (i) multilevel data structure; (ii) multidimensional latent trait; (iii) personal explanatory latent regression models. The paper pays attention to the potential of such a flexible approach in the analysis of students evaluation of university courses in order to explore both how the quality of the different aspects (teaching, management, etc.) is perceived by students and how to make meaningful comparisons across them on the basis of adjusted indicators
Assessing divergences in mathematics and reading achievement in Italian Primary Schools: a proposal of adjusted indicators of School effectiveness
No full textThis research aims to reach four main objectives by identifying plausible factors influencing Italian fifth grade pupils’ achievement in mathematics and reading: (1) to assess the relationships between pupils’ performances and their socio-cultural characteristics; (2) to suggest value-added measures of the contribution that schools give to pupils’ achievement; (3) to advance a system of indicators in order to detect schools characterized by distinctive performances; (4) to summarize main evidences at different geographical levels. Nationwide pupils’ scores in mathematics and reading tests have been jointly summarized using Item Response Theory models. A Multilevel Bivariate Regression model with heteroscedastic random terms at school-level has been adopted to single out the factors which seem to account for the greatest variability in pupils’ achievement as well as to jointly model the unobserved heterogeneity among geographical areas. A system of school value-added measures is proposed to make comparative assessments at national and at sub-national levels
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