### Metodologie e Tecnologie Didattiche per l'Informatica (PREFIT) (INF0193)

• Il corso mira a:

- Sviluppare capacità riflessive sulla disciplina, facendo emergere per confrontare le idee pregresse degli studenti sugli argomenti trattati.
• - Introdurre al pensiero computazionale e evidenziarne gli aspetti caratterizzanti
• - Far acquisire pratiche didattiche e di processi di insegnamento e apprendimento dell’Informatica sia con l'uso delle tecnologie digitali sia con tecniche di tipo csunplugged ovvero senza calcolatore con attività per i diversi livelli di scuola.

- Far praticare attivita di programmazione creativa e analisi di proprieta degli ambienti di programmazione che la favoriscono.

• - Trasmettere conoscenza delle principali metodologie per la costruzione di un curriculum di Informatica coerente con gli obiettivi fissati dalle indicazioni nazionali e dalle linee guida.
• - Sperimentare attività laboratoriali per lo sviluppo e la valutazione di competenze informatiche e riconoscimento della loro importanza.

### Performance Evaluation: Simulation and Modelling

Simulation is one of the most common techniques used for the evaluation of the performance and if the reliability of Discrete Event Dynamic Systems (DEDS) often modelled with Stochastic Processes. Discrete Event Simulation consists on the execution of a program which results in the production of a realization of a stochastic process driven by Monte-Carlo methods. Learning how to construct a simulator is the main objective of this course, together with the development of the techniques needed for the statistical analysis of the simulation output. To deeply understand the difficulty of writing an efficient simulator equipped with the output analysis components, students will be required to write a few simple simulators “from scratch” without using available tools and libraries.

Part I  (6 CFUs) Simulation and Operational Analysis – The first part of the course is devoted to the presentation and discussion of Discrete Event Simulation. Special attention is devoted to the measures that must be implemented to quantify the simulation results and to operational relations that may be derived among these measures useful to gain confidence on the correctness of the reliability of simulation outputs.

Part II (3 CFUs) Stochastic Processes and Markov Chains – The second part of the course introduces probability based analysis techniques that may be used to further improve the confidence on simulation results

At the end of the course the students will be able to perform the simulation of non-trivial Discrete Event Systems. The exercises and the final project will provide the students with the capability of writing the simulators using a general purpose programming language. Having developed the simulators “from scratch” will allow the students to understand the potentials and the limits of the Discrete Event Simulation technique, thus providing them with the capability of using professional simulators with competence

The course will be based on theoretical lessons as well as on the solution of class exercises. Computer implementations will be required as homework assignments. Personal training on assigned exercises is important for the success in this class.

The final examination will consist in the discussion of a project developed individually by te students used as the basis for asking questions on the theoretical aspects of the exercise. Students will not be required to be able to reproduce the derivations used  to obtain the results discussed during the course, but will have to know the definitions and the applications of the theory.

### Valutazione della didattica (Laurea Triennale in Informatica)

Questo corso, indirizzato agli studenti della Laurea Triennale in Informatica, contiene istruzioni e materiali utili per la compilazione dei questionari di valutazione della didattica.