Corsi XXXIX ciclo

Attività didattica programmata
Il corso di dottorato è strutturato in attività didattiche per acquisire le tecniche e le metodologie specifiche dell’indagine psicologica e biomedica e della gestione e analisi statistica dei dati psicologici e clinici. Il corso di dottorato prevede sei insegnamenti obbligatori (30 crediti), erogati in lingua inglese, ciascuno di 5 crediti (CFU): 4 corsi si svolgeranno nel primo anno e 2 nel secondo anno. Il programma didattico del primo anno comprenderà i seguenti insegnamenti (da 5 CFU ciascuno):

  • Experimental Research Methods Advancess
  • Course on ethics of research, responsible research and innovation and science communication (corso SAFD)
  • Frequentist and Bayesian methods in statistical inference
  • Behavioral Science Methods

Nel secondo, il programma include due corsi (ciascuno di 5 CFU)

  • Grant writing skills
  • Scientific paper writing skills

Ciascun dottorando dovrà acquisire nel corso della propria carriera, nell’ambito dei 30 CFU, almeno 6 CFU tramite la frequenza a corsi o attività volte all’acquisizione di competenze trasversali, di cui almeno 3 CFU tramite la frequenza di corsi offerti dalla Scuola di Alta Formazione Dottorale (SAFD) che saranno disponibili al seguente link: phd.unipv.it/corsi-trasversali-per-dottorandi

Programma dei corsi

Primo anno

  • Experimental Research Methods Advancess: This course will cover most of the basic inferential statistic tests both presented in the Frequentist as well as the Bayesian approaches. Hence, we will need first to revise some probability theories since different views of probability provide the basis for frequentist and Bayesian inferential statistics. We will then consider the conceptual basis of Frequentist statistics (i.e., what is its aim?), how it works and how it should be implemented. This will also be done for Bayesian analysis. After this, we will cover a series of statistical tests in frequentist and Bayesian form (Binomial test; Normal/t-test; Correlation; simple regression; Chi-square test; ANOVA). To support data analysis, we will use the software JASP.
  • Course on ethics of research, responsible research and innovation and science communication: Reaching ethics of research and Responsible Research and Innovation (RRI) at doctoral level in universities is mandatory in most of European countries. Science communication and dissemination is part of the duties of the researchers and is essential for the public involvement of citizenship in the process of decision making when science is involved in policies and norms. We set up an experimental interdisciplinary course in Ethics of Research, RRI and science communication for doctoral students at the University of Pavia since the academic year 2016-2017, following the model proposed by the EU Commission (undergraduate students are welcomed, but should apply by e-mail with a motivation letter and a short CV). The methodology includes frontal lessons, case discussions, participatory processes, and active involvement of the students in the development of each lesson. We want to foster interaction and participation. Simulation of ethics assessment and social impact assessment of research procedures, ethics evaluation and interaction with the general public will also take place to allow the students to develop practical skills in the field. The course will require some homework, like reading essays and papers. Our teaching goals for ethics of research and science communication fit into the following four general categories: knowledge, skills, attitude, and behaviors.
  • Frequentist and Bayesian methods in statistical inference: The course is aimed at providing the students with the basic practical skills for running both frequentist and Bayesian statistics, after a brief theoretical overview of the latter. The teacher will try to tackle the main issues met by researchers when analyzing data, both in exploratory and in confirmatory research. Examples will span from elementary statistical objects (t-test, ANOVA ,etc.) to more complex estimation procedures (simple linear regression, multiple regression, Mixed Linear Models, etc.). Basic (master-degree level) understanding of statistics is required in order to apply more complex concepts and analyses.
  • Behavioral Science Methods: The course will provide an historical framework concerning the Philosophy of Science and knowledge about the most relevant methodologies applied to different area of science.

Secondo anno:

  • Grant writing skills: The course aims to impart specific knowledge on how to write successful grant proposals. The course will be divided into a theoretical and a practical part. The most common grant proposal templates will be illustrated in the theoretical part, such as the ones for the ERC application or Ministerial grants (PRIN, Italian Ministry of Health). The most effective ways to fill in the different sections of the proposal will be illustrated. Particular attention will be paid to the division of funds required to calculate a coherent budget. In the practical part, writing exercises will be carried out. Students will choose a funding body for the simulation and learn how to write a project proposal from both a scientific and an economic point of view coherent with the funding agency call. Students will learn how to align the grant proposal with the requirements and objectives of the agency call. They will also learn how to write a grant proposal that is informative, effective and engaging.
  • Scientific paper writing skills: The course aims to provide knowledge on how to write successful scientific papers. The course will be divided into a theoretical and a practical part. The most common scientific journal templates will be illustrated in the theoretical part. The most effective ways to write the traditional scientific manuscript’s sections (Introduction, methodology, etc.) will be illustrated. Particular attention will be paid to the selection of the references and the principal sources available. In the practical part, writing exercises will be carried out. Students will choose topics for the simulation and learn how to write the article following the rules of the chosen journal. Students will also learn how to respond to the referees’ requirements.