Artificial Grammar Learning 2 (2020/2021)

Corso a esaurimento (attivi gli anni successivi al primo)

Codice insegnamento
cod wi: DT000011
Chiara Melloni
Chiara Melloni
Settore disciplinare
Lingua di erogazione
A.A. 20/21 dottorato dal 1-ott-2020 al 30-set-2021.

Orario lezioni

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Obiettivi formativi

This integrated PhD course intends to provide participants with updated knowledge of new research strategies concerning how language is acquired, implicit learning and Artificial Grammar Learning (AGL).
At the end of the course, participants will be endowed with some specific knowledge about:
a) new trends in language acquisition research
b) the role of AGL in assessing learning strategies in language acquisition, also with reference to special populations (dyslexic children) and bilinguals
c) the role of non-canonical grammars (Lindenmayer systems: ‘L-systems’) in assessing the interaction between sequential and hierarchical learning
d) the experimental methods and the forms of statistical analysis that can be applied in order to study the interaction between sequential and hierarchical parsing in children and adults


The course will consist in 16 hours of frontal teaching plus self-study by the participants.
In all its parts it will be the result of a strict cooperation among the 4 lecturers involved (Denis Delfitto, Diego Krivochen, Chiara Melloni, Maria Vender).
It will be organized in the following 4 parts:
Part 1: An introduction to the formal structure of grammars, L-systems and to some models of analysis of L-systems, including training and exercises in the formal theory of language (Lecturer: Diego Krivochen, 8 hours)
Part 2: A case-study in sequential and hierarchical learning across different populations: L-systems and Fibonacci grammar (Lecturers: Maria Vender, Chiara Melloni, Denis Delfitto, 8 hours)
Part 2 will be taught in 3 blocks:
Block 1: Strategies of language acquisition and methods of research in language acquisition (Lecturer: Chiara Melloni)
Block 2: Sequential and hierarchical learning across different populations: 4 experimental studies investigating implicit learning in some variants of Fibonacci grammar (Lecturer: Maria Vender)
Block 3: Statistically-based computation and strategies of hierarchical reconstruction (Lecturer: Denis Delfitto)

References: Reading instructions and proposals before the course and during the course

Modalità d'esame

Participants will be asked to read in advance some relevant literature.
During the course, some training and exercises will be proposed.
Interested participants can write a paper on some of the research issues addressed in the course.