Rapporto tecnico sugli esiti della prova nazionale nell'ambito dell'Esame di Stato al termine del primo ciclo anno 2007-2008. Analisi delle risposte al test di matematica e italiano: dalle proprietà delle domande alla valutazione degli studenti.

Il rapporto presenta i risultati dell'analisi statistiche effettuate sulle risposte date dagli studenti al'Esame di Stato della scuola secondaria di primo grado, classe terza, anno 2007-2008. I dati forniti dall'Invalsi riguardano le risposte fornite alle prove standardizzate di italiano e matematica

La Validazione Statistica di test standardizzati di profitto: principali aspetti di metodo e due casi di studio sulla valutazione degli apprendimenti nella scuola primaria

Il lavoro si propone di ripercorrere alcune metodologie generali di analisi dei test per la valutazione degli apprendimenti, discutendo i risultati ottenuti in due casi di studio riguardanti le prove preparate dal Servizio Nazionale di Valutazione (SNV) dell’INVALSI per la classe seconda della scuola primaria. In particolare, viene descritto il processo di analisi dei pre-test attraverso l’utilizzo congiunto degli indicatori derivanti dalla Classical Test Theory e dei modelli di Item Response Theory

TEACHING STATISTICS AT SECONDARY EDUCATION IN ITALY: SOME ISSUES ON LARGE SCALE STANDARDIZED TEST RESULTS

This paper focuses on recent issues in statistics learnin

Hyperactive Akt1 Signaling Increases Tumor Progression and DNA Repair in Embryonal Rhabdomyosarcoma RD Line and Confers Susceptibility to Glycolysis and Mevalonate Pathway Inhibitors

In pediatric rhabdomyosarcoma (RMS), elevated Akt signaling is associated with increased malignancy. Here, we report that expression of a constitutively active, myristoylated form of Akt1 (myrAkt1) in human RMS RD cells led to hyperactivation of the mammalian target of rapamycin (mTOR)/70-kDa ribosomal protein S6 kinase (p70S6K) pathway, resulting in the loss of both MyoD and myogenic capacity, and an increase of Ki67 expression due to high cell mitosis. MyrAkt1 signaling increased migratory and invasive cell traits, as detected by wound healing, zymography, and xenograft zebrafish assays, and promoted repair of DNA damage after radiotherapy and doxorubicin treatments, as revealed by nuclear detection of phosphorylated H2A histone family member X (γH2AX) through activation of DNA-dependent protein kinase (DNA-PK). Treatment with synthetic inhibitors of phosphatidylinositol-3-kinase (PI3K) and Akt was sufficient to completely revert the aggressive cell phenotype, while the mTOR inhibitor rapamycin failed to block cell dissemination. Furthermore, we found that pronounced Akt1 signaling increased the susceptibility to cell apoptosis after treatments with 2-deoxy-D-glucose (2-DG) and lovastatin, enzymatic inhibitors of hexokinase, and 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR), especially in combination with radiotherapy and doxorubicin. In conclusion, these data suggest that restriction of glucose metabolism and the mevalonate pathway, in combination with standard therapy, may increase therapy success in RMS tumors characterized by a dysregulated Akt signaling

The use of predicted values for item parameters in item response theory models: an application in intelligence tests

In testing, item response theory models are widely used in order to estimate item parameters and individual abilities. However, even unidimensional models require a considerable sample size so that all parameters can be estimated precisely. The introduction of empirical prior information about candidates and items might reduce the number of candidates needed for parameter estimation. Using data for IQ measurement, this work shows how empirical information about items can be used effectively for item calibration and in adaptive testing. First, we propose multivariate regression trees to predict the item parameters based on a set of covariates related to the item solving process. Afterwards, we compare the item parameter estimation when tree fitted values are included in the estimation or when they are ignored. Model estimation is fully Bayesian, and is conducted via Markov chain Monte Carlo methods. The results are two-fold: a) in item calibration, it is shown that the introduction of prior information is effective with short test lengths and small sample sizes, b) in adaptive testing, it is demonstrated that the use of the tree fitted values instead of the estimated parameters leads to a moderate increase in the test length, but provides a considerable saving of resources