Psychology

Information processing theory deals with how people receive, store, integrate, retrieve, and use information. The present course uses theoretical and empirical perspectives on human cognition, perception, and the experimental methods to study cognition and perception. Eleven basic topics of cognitive science/psychology are discussed using a Problem Based Learning format. The topics studied in the course are amongst others: the history of the study of the human mind as information processing machine, schema’s, scripts, plans, and frames, knowledge representation, top down and bottom up processing, semantic networks and spreading of activation, and intelligence and individual differences. This course assumes prerequisite knowledge from Introduction to Psychology or Artificial Intelligence.

This course provides a study of the behavior patterns, attitudes, interests, values, beliefs, conflicts and other cultural aspects of human groups in different social situations. It focuses on the historical context of the development of social psychology and also examines key concepts at both the micro and macro scales of group dynamics: behavior, attitude, role development, and the psychological condition of both an individual and a group. The course also considers the problems and challenges of contemporary social psychology.

This course cultivates, through theoretical study, the necessary skills for working in child welfare. It covers fundamental concepts and values, history, policies, organizations, services and skills required in the field of child welfare. The course also provides the foundational knowledge of child and youth development, critical perspectives for analyzing child and youth related social problems, and the understanding of key issues related to child welfare policy and programs. It uses a comparative framework to evaluate the current state of major child and youth development problems and the policies and programs aimed to address them.

This course presents some basic techniques for the analysis of the uncertainty inherent in statistical information, with the goal of providing a correct evaluation and communication of risk. Basic notions of elementary probability theory and of Bayesian probability are introduced and discussed, and their application is illustrated in problems connected with the medical and psychological practice, also within the framework of recent Italian legislation on informed consent which imposes to all health care professionals a correct risk assessment and the adequate communication of it to patients. The course discusses topics including uncertainty in statistical information; problems related to the evaluation of risk and communication of risk; real-world examples; Bayesian inferences through the use of probabilities and by means of natural frequencies; suitability of the natural frequencies for a more intuitive and direct insight in both risk estimation and in a transparent representation of risk; examples focusing on the correct judgement of the probabilistic predictive value of medical diagnostic tests, and aiming at avoiding misleading risk information; cases related to the ongoing Covid-19 public-health emergency; evaluation of the effect of interventions, including relative risk and absolute risk, and relative and absolute risk reduction (or increase); and number needed to treat or to harm.