SVF25 - STATISTICS AND TRAINING EVALUATION

courses

ID:

SVF25

Duration (hours):

48

CFU:

SSD:

STATISTICA

Located in:

CHIETI

Url:

Course Details:

ADVANCED EDUCATIONAL SCIENCES/CORSO GENERICO Year: 1

Year:

2025

Course Catalogue:

https://unich.coursecatalogue.cineca.it/af/2025?co...

Date/time interval

Secondo Semestre (01/03/2026 - 31/05/2026)

Course Objectives

The course aims to provide students with basic statistical tools for the analysis and evaluation of educational systems. The first part of the course will review fundamental concepts of descriptive statistics, useful for exploring, representing, and interpreting educational and social data. The second part will focus on the main statistical methods used in the evaluation of educational systems and learning outcomes, with particular attention to the use of measurement in educational contexts and psychometric approaches (Classical Test Theory and an introduction to Item Response Theory). Activities will be supported by practical exercises in Excel using real or simulated data, to develop operational skills in data analysis within pedagogical contexts.

Course Prerequisites

None

Teaching Methods

Lectures Practical exercises in Excel

Assessment Methods

The final exam will consist of an oral test; however, if the number of enrolled students exceeds 40, a written exam will be required.

Texts

Cicchitelli, G., D’Urso, P., & Minozzo, M. Statistica: principi e metodi, 4ª edizione (Ediz. MyLab, con aggiornamento online), Pearson, 2022. Supplementary materials will be provided during the course. All materials are also available online at: fad.unich.it. To access the online platform, please contact: annalina.sarra@unich.it

Univariate Descriptive Statistics • Types of variables and levels of measurement • Frequency tables and graphical representations • Measures of central tendency: mean, median, quartiles, mode • Measures of dispersion: range, standard deviation, variance, coefficient of variation Bivariate Descriptive Statistics • Contingency tables • Chi-square test for independence • Covariance, Pearson and Spearman correlation • Scatter plots • Analysis of linear dependence Foundations of Classical Test Theory (CTT) • Observed score, true score, and error score • Concept of reliability (split-half, test-retest, Cronbach's alpha) • Test validity • Item analysis: item difficulty and discrimination power Introduction to Item Response Theory (IRT) • Introduction to probabilistic models • Differences between CTT and IRT • Rasch model (1PL), 2PL, 3PL, and 4PL models • Item characteristic curves (ICCs) Excel Practical Lab • Complete analysis of a real dataset (educational or psychological) • Data preparation and cleaning • Descriptive data analysis

Course Language

Italian

More information

Lessons will be held in person, except as provided for in the University Guidelines regarding the provision of distance learning for conventional degree programs. All categories of students provided for by University regulations and agreements are entitled to access lessons via remote means.
To facilitate the participation of students enrolled in degree programs delivered in person at a University location different from the one where the lessons for this course are held, the start of teaching activities will respect the academic quarter-hour. These students will also be guaranteed access to lessons via remote means.

For information contact Prof.ssa Annalina Sarra : annalina.sarra@unich.it