1,720,978 research outputs found
Impact of Emergency Online Classes on Students’ Motivation and Engagement in University During the Covid-19 Pandemic: A Study Case
No full textThe Covid-19 pandemic has had dramatic impact on many dimensions of living and studying conditions of
students at University. This paper analyses student satisfaction and motivation during the lockdown period
and try to understand whether different socio-economic and environmental conditions have influenced
needs and demands of students during the emergency online didactics. Drawing from the results of a
questionnaire administered to students enrolled in the University of Modena and Reggio Emilia, this
research is aimed at describing which factors, beyond the quality and the professionalism of the lecturers
and the quality of the education received, influence the satisfaction with the online learning experience and
impact on students’ motivations and perceived engagement. Moreover, the study investigates the
pandemic’s direct effects on gender differences and inequalities, analysing the obstacles affecting the self-
organization of study at home
Fuzzy methods and satisfaction indices
No full textThis chapter develops a framework that uses fuzzy set theory in order to measure customer satisfaction, starting from a survey with several questions. The basic concepts of the theory of the fuzzy numbers are briefly described. A criterion based on the sampling cumulative function, which assigns values to the membership function with reference to each quantitative, ordinal and binary variable, is suggested. Weighting and aggregation operators for the variables are considered. An application to ABC 2010 annual customer satisfaction survey data shows the usefulness of the fuzzy set approach: the gradual transition from very dissatisfied to really satisfied customers is captured by fuzzy composite indices. The comparison with the classical methods for the measurement of customer satisfaction highlights the advantages of the suggested criterion from both the theoretical and operational points of view
Robust estimation of regime switching models
No full textIt is well known that GM estimators for linear models are consistent and lead to a small loss of efficiency with respect to LS estimator. When they are extended to threshold models, which are piecewise linear models, the consistency of GM estimators is guaranteed only under certain choices of the objective function.In this paper we explore, in a simulation experiment, the loss of consistency of GMSETAR estimator under different objective functions, time series length, parameters combinations and type of contaminations. Finally the best robust estimator is appliedto study the dynamic of electricity prices where regime switching and high spikes are widely observed features
Advances in statistical models for data analysis
No full textThis edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy
Covid-19 e studenti UNIMORE: come l’emergenza cambia lo studio e l’esperienza universitaria
Full text linkIl rapporto di ricerca presenta i risultati della rilevazione online condotta dall'Università degli studi di Mo-dena e Reggio Emilia sulle condizioni di vita e di studio degli studenti nel periodo 8 aprile – 2 maggio 2020. Alla rilevazione on line ha risposto il 20% degli studenti: un tasso di partecipazione adeguato per cogliere alcune significative differenze tra corsi di studio. L'indagine ha come obiettivo quello di superare l'emergenza Covid-19 con maggiore consapevolezza, analizzando le condizioni di vita e di studio degli studenti e cercando gli strumenti più utili a una didattica inclusiva e a uno studio che contribuisca a dare a ogni studente la possibilità di procedere nel proprio percorso di studi e nel proprio percorso di vita nel migliore dei modi. Vengono presentati il questionario, gli strumenti di rilevazione e i risultati che emergono dall'analisi multivariata, sia per quel che riguarda le domande a risposte chiuse sia per le domande aperte, su cui sono state applicate tecniche di analisi testuale. Le diverse tecniche di analisi sono presentate per enfatizzare la specificità del dataset che presenta un differente livello di variabilità delle risposte nei diversi ambiti tematici. Il rapporto si conclude con una serie di considerazioni che offriamo alla comunità di Uni-more per supportare la discussione su quanto abbiamo appreso e continuiamo ad apprendere grazie alla voce degli studenti. È ormai chiaro che l'uscita dall'emergenza sarà un processo graduale. Il punto di vista degli studenti, che cogliamo da questa rilevazione, sarà davvero prezioso per progettare le attività didattiche e i servizi agli studenti del prossimo anno, per offrire una didattica di qualità che risponda alle diverse esigenze e ai diversi contesti di studio. Ulteriori sviluppi dell'analisi potranno riguardare altri approfondi-menti sulle specifiche modalità di didattica (a distanza e in presenza) e sulla valutazione delle condizioni di vita e di lavoro del personale docente e tecnico-amministrativo. L'idea di fondo è quella di leggere, attraverso la lente dell'emergenza Covid-19, le dimensioni essenziali per migliorare la qualità della didattica evidenziate dalla rilevazione empirica.The research report presents the results of the online survey conducted by the University of Modena and
Reggio Emilia on the living and study conditions of students in the period 8 April - 2 May 2020. The online
survey was answered by 20% of students: an adequate participation rate to capture some significant differences between courses of study. The aim of the survey is to overcome the Covid-19 emergency with greater
awareness, analysing the living and study conditions of the students and looking for the most useful tools
for inclusive teaching and study that contribute to giving each student the possibility to proceed in their
own study and life path in the best possible way. The questionnaire, the survey tools and the results that
emerge from the multivariate analysis are presented, both for the closed-answer questions and for the openended questions, on which textual analysis techniques have been applied. The different tools and methods
are presented to emphasize the specificity of the dataset, which presents a different level of variability of
the answers in the different thematic areas. The report concludes with a series of considerations that we
offer to the Unimore community to support the discussion on what we have learned and continue to learn
thanks to the voice of the students. It is now clear that the exit from the emergency will be a gradual process.
The students' point of view, which we gather from this survey, will be really valuable to plan next year's
educational activities and services for students, in order to offer a high quality teaching that responds to
different needs and study contexts. Further developments of the analysis may concern other in-depth studies
on specific teaching methods (distance and in-presence) and on the evaluation of the living and working
conditions of teaching and technical-administrative staff. The basic idea is to read, through the Covid-19
emergency lens, the essential dimensions to improve the quality of teaching highlighted by the empirical
surve
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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