applied experimental psychological sciences

Knowledge and understanding Students will acquire competencies in: Theories and methods in cognitive development The developmental cognitive neuroscience approach to the study of the human mind Developmental change from infancy to adolescence across a variety of cognitive domains Applying knowledge and understanding Students will acquire competencies in: Empirical questions, methods and limitations of research in cognitive development Evaluation of research outcomes and understanding of how empirical evidence and theories of cognitive development can inform each other Making judgment Students will gain the ability to independently integrate methodological and theoretical skills in the field of cognitive development and to apply them to critically judge previous studies and propose new research projects in the different sub-fields of cognitive development, taking into account the specific critical aspects of each research technique and various operational situations. Students will also gain the ability to reorganize the acquired knowledge to promote innovative and original solutions through judgment based on empirical data and a critical reading of the complexities inherent to cognitive development. This will be achieved through class discussions, group work and paper presentations. Communication skills Students will acquire communication skills that allow effective interaction with various professionals from different cultural and scientific backgrounds; through group presentations, students will learn how to propose innovative research projects in cognitive development and to communicate their results and conclusions to an audience of specialists and non-specialists in a clear, detailed, and scientifically grounded manner, using the specific lexicon of the discipline. Students will also learn how to coordinate during teamwork and collaborate effectively and competently in English. Learning skills The course will promote the acquisition of the ability to adopt new developments and innovations emerging from international scientific results in cognitive development, updating one's skills to the rapid evolution of the field. The course will also promote the use of specialized bibliographic resources to perform in-depth scientific reviews to critically judge current knowledge in cognitive development and capitalize on it to propose further advancements in the field (e.g., through the development of new scientific projects). This will be achieved by discussing the available digital instruments to perform bibliographic research and through class discussions.

Theoretical approaches to developmental change Behavioral (e.g., eye-tracking) and electrophysiological (e.g., EEG, ECG, EMG, skin conductance) research methods in cognitive development Development of attentional, perceptual and memory processes Development of physical objects and numerical knowledge Origins and development of the social brain The neuroconstructivist approach to the study of atypical development

The exam will consist of multiple choice questions and open-ended questions on the course topics (with optional oral examination). The questions are aimed at verifying the effective acquisition of both theoretical knowledge and research methods in the field of cognitive development. For the open-ended questions, the answers will be evaluated in terms of correctness, argumentative capacity, synthesis, and the ability to form links among the different areas of cognitive development. An optional activity will be offered for students attending lessons. This will consist in a presentation of a research article in the field of cognitive development (20% of the grade). The presentation will be evaluated in terms of knowledge of the background literature, the correctness and argumentative capacity to report the aim, methods and results, and the ability to link the findings of the paper to the contents of the course.

The bibliography will be provided at the beginning of the course and published in the course web-site.

Knowledge and understandingThis course provides a strong background in systems-level neuroscience and allows students to develop integrative research interests that cross domains. This knowledge will be based upon the most recent developments in the field, supported by relevant litterature and research examples. During the course, the critical thinking abilities of students will be supported through the discussion of research protocols in the field of cognitive neuroscience, to help them to understand the strength and weaknesses of different research methods and how to exploit them to improve our knowledge on the brain-cognition relationship through experimental actions. The laboratory will allow students to learn how to program basic experiments in cognitive neuroscience, also based upon the integration of their knowledge of psychological processes. Applying knowledge and understandingStudents will gain a thorough understanding of the intellectual issues that drive this rapidly growing field, as well as expertise in the major methods for research on higher brain function. Students will also learn to apply the acquired knowledge in designing and carrying out empirical studies in the field of cognitive neuroscience. In particular, they will learn how to design experiments in PsychoPy (www.psychopy.org), a program designed to facilitate the conception of any experiment that uses a computer as an interface between the subject and the experimenter. Making judgementStudents will gain the ability to independently integrate methodological and theoretical skills in the field of cognitive neuroscience and to apply them in different contexts, taking into account specific critical aspects of various operational situations. Students will also gain the ability to reorganize the acquired knowledge in order to promote innovative and original solutions through judgment based on empirical data and a critical reading of the complexities inherent to the field of cognitive neuroscience. Communication skillsStudents will acquire communication skills that allow an effective interaction with various types of professionals from different cultural and scientific backgrounds, both in the public and private sectors, to propose innovative research projects in cognitive neuroscience and communicate one's results and conclusions to an audience of specialists and non-specialists in a clear, detailed, and scientifically grounded manner, referring to specific disciplinary lexicons. Students will also learn how to coordinate and facilitate team work and collaborate effectively with other agents fluently and competently in English. Learning skillsThe course will promote the acquisition of the ability to adopt new developments and innovations emerging from international scientific results in cognitive neuroscience, updating one's skills to the rapid evolution of the field and making use of specialized bibliographic resources and various professional development initiatives. The course will also promote the ability to understand and apply in-depth scientific literature review in order to apply the most advanced knowledge and tools available in an original way.

• Basics and history of mind-brain investigations • Research methods in cognitive neuroscienceo Neurostimulation and neuromodulation (transcranial electrical stimulation and single pulse and repetitive transcranial magnetic stimulation)o Functional Magnetic resonance imaging • Cognition and the braino Neural bases of memory processeso Neural bases of attentiono Neural bases of consciousness • Laboratory: programming in PsychoPyo Creating experiments with “no-coding” in PsychoPy’s Builder interfaceo Running experiments online with PsychoPy’s Pavlovia platformo Coding in Psychopy

The exam will consist of a compulsory written part and an optional oral integration The written exam will consist of 30 multiple choice questions and 1 open question covering all the topics of the course.a. Multiple choice questions will be graded 1 if correct and 0 if incorrect.b. The open question will be evaluated 0-30 and will be averaged with the multiple choice results for the final grade. For those students who request it, or if the teacher considers it necessary, an oral interview can be arranged: the mark obtained in the oral test will be averaged with that obtained in the written test. The evaluation criteria are: the correctness of the answers, the ability to argue, synthesize, create links, and critically discuss the course topics. Knowldege of programming PsychoPy as imparted by the course will be assessed at the end of the laboratory practicum, by means of assigned problems such as implementing a new experiment. For those students who could not attend the PsychoPy Lab, an equivalent test will be integrated in the final course exam. Dissertation on a desired topic could be produced, and will integrate the final grade (0-3 points).

The reference textbook is: Principles of Cognitive Neuroscience.Dale Purves; Kevin S. LaBar; Michael L. Platt; Marty Woldorff; Roberto Cabeza; Scott A. HuettelPublisher: Sinauer AssociatesPrint ISBN: 9780878935734, 0878935738eText ISBN: 9781605354316, 1605354317 Further learning materials for the classes and laboratory will be indicated during the course and will be uploaded on the course web-site. This material should be studied in preparation for the exam.

Knowledge and understanding Students will develop• a deep understanding of cognitive concepts and theories by reviewing major research findings.• Knowledge and understanding of the experimental method: How the application of experimental method help in theoretical advances.• Knowledge of main real-world applications of research findings and how advances in basic reasearch can be relevant to everyday life. The laboratory will teach students basic programming abilities in Matlab. Applying knowledge and understanding Students will be able to• apply their understanding of main cognitive theories and concepts in order to design experiments related to everyday issues.• design a simple experiment and implement it in Matlab. Making judgmentStudents will gain the ability to independently integrate methodological and theoretical skills in the field of cognitive psychology to apply these skills to critically judge previous studies in order to propose new research projects in the field of applied cognitive psychology, that is reorganize and critically evaluate the previously acquired knowledge to promote new and original solutions. This will be achieved through class discussions on relevant recent findings, the use of the flipped-classroom strategy and group work. Communication skillsStudents will acquire communication skills that allow effective interaction; during flipped-classroms or through project presentations, students will learn how to present research projects and to communicate results and conclusions to an audience of specialists and non-specialists in a clear, detailed, and scientifically grounded manner, using the specific lexicon of the discipline. Students will also learn how to coordinate during teamwork and collaborate effectively and competently in English. Learning skillsThe course will promote the acquisition of the ability to adopt new developments and innovations emerging from international scientific results in cognitive psychology, updating one's skills to the rapid evolution of the field. The course will also promote the use of specialized bibliographic resources to perform in-depth scientific reviews to critically judge current knowledge and capitalize on it to propose further advancements in the field . This will be achieved by discussing the available digital instruments to perform bibliographic research and through class discussions.

Student will be exposed to advanced findings and research methodologies in the following topics: • Perception • Attention • Memory • Knowledge representation • Problem-solving • Reasoning and decision making

The exam will verify the level of mastery of the course contents with special attention to: • Theoretical references • The use of technical language • Methods and experimental procedures • Ability to elaborate course contents To better verify the achievements of the learning objectives the exam will be both written and oral. The written exam will consist of multiple-choice questions and open-ended questions on the course lecture topics. For the practial part the exam will be written consisting in multiple-choice and short-answers questions. The oral exam will consist in questions on the course topics and in the presentation and discussion up-to-date research articles on the course topics presented in class. For students attending the course, the examination could be partially or totally replaced by evalutarion of activities their participated to during term time (e.g research project or in class presentations).

M. W. Eysenck & D. Groome (Eds.) (2023) Cognitive Psychology Revisiting The Classic Studies. Sage. Lecture slides and additional material will be provided at the beginning of the course and made available on the course website.

Knowledge and understanding Students will acquire foundational knowledge of experimental paradigms using cognitive and behavioural measures They will understand how cognitive processes (e.g., intuition, deliberation) influence human behaviour. Applying knowledge and understanding Students will learn to apply theoretical concepts and experimental data to real life behaviors, like cooperation, altruism, and more. They will acquire practical skills in implementing psychological tasks and interpreting results in light of relevant theories. Making judgment Students will learn to assess experimental studies using cognitive and behavioral measures (e.g., RTs, Stroop task), recognizing methodological strengths and limitations. Students will develop the ability to design original studies, selecting appropriate tools to investigate social psychological constructs like cooperation and altruism. Communication Skills Students will practice communicating research findings clearly to both expert and non-expert audiences, using appropriate disciplinary language. Through group work, students will learn to present research ideas and collaborate effectively in English within teams. Learning Skills Students will learn how to search and critically review scientific literature to support the development of new research ideas. Students will develop the ability to stay updated on new tools and methods in cognitive and behavioral research.

How to define experimental variables: Behaviours, operationalizations, variables and confounds. How to define behavioral measures and paradigms to study human cognition. Experimental methods to manipulate cognitive processes (time constraints,ego depletion, cognitive load, two-response paradigm, conceptual inductions). Behavioral paradigms for the study of social behavior. The dual-process approach to human sociality. Meta-studies, mega-studies, crowdsourcing and online data collection: the use(fulness) of open science resources. Experimental design: Develop your own experiment.

The course will be assessed on a pass/fail basis only. There is no final exam; evaluation will be based on active participation and any assignments or activities carried out during the course. Specifically, students will be asked to implement, administer, and present (in the last class) preliminary results of a behavioral experiment (starting from one in-class example, students are asked to develop a novel experiment or reproduce an experiment from literature). The ability of students to appreciate the methodological value of an empirical study, implement a simple behavioral experiment, and inspect behavioral data will be assessed.

Capraro, V. (2024). The dual-process approach to human sociality: Meta-analytic evidence for a theory of internalized heuristics for self-preservation. Journal of Personality and Social Psychology.

Knowledge and understanding Methodological and epistemological foundations in cognitive modelling Development of computational models: techniques and approaches Methods for the validation and assessment of the models Applying knowledge and understanding Development of simple models in different domains of human cognition Application of toolkits to existing datasets Validation of computational models through behavioral data Critical analysis and interpretation of the model and its predictions Making judgments Choosing the most apt computational approach for a given question Activities: hands-on practice with a number of models from different computational traditions Communication skills Explaining inner workings and capabilities of computational models Activities: brief essays discussing outputs and predictions of different models Learning skills Exploring current developments in the field of computational psychology Activities: analysis of classical and contemporary reference papers, online apps and tutorials

Introduction to computational modelling and Artificial Intelligence Epistemological foundations of cognitive modeling Levels of description and representation Methods for developing models in different domains of cognition Tuning, setting, and interpreting parameters Training and validation of learning models Simulation of behavioral data Model evaluation: quantitative performance and theoretical criteria Example: implementing an exemplar-based model for categorization Example: implementing a model for the phonological loop Example: training models based on the Rescorla-Wagner equations Example: training and testing neural networks

The course will be assessed on a pass/fail basis only. There is no final exam; evaluation will be based on active participation and any assignments or activities carried out during the course.Attendance is mandatory for at least 70% of the course. Failure to meet this minimum attendance requirement will result in not passing the course. Individual assignments will require students to replicate the scripts developed in class, and to produce short essays concerning their views on cognitive modelling and AI. Moreover, further assignments will require the students to apply the practical knowledge acquired during the course. These will include modifying simple scripts, evaluating the impact of different parameters on model performances, testing model predictions against human-generated data, and comparing simulations from different models.

Reference materials: Lewandowsky, S., & Farrell, S. (2010). Computational modeling in cognition: Principles and practice. Sage Publications. Sun, R. (Ed.). (2008). The Cambridge handbook of computational psychology. Cambridge University Press.

Knowledge and understanding • Clinical psychological sciences: Methods and areas of investigation • Research designs for treatment evaluation • Experimental psychopathology: Investigating abnormal behavior, cognition, and emotion • Professional ethics for psychologists Applying knowledge and understanding • Understanding, analysis, and evaluation of research designs in clinical psychology • Identifying and analyzing the critical elements of research designs for treatment evaluation • Applying experimental paradigms for the investigation of abnormal behavior, cognition, and emotion • Applying the principles of professional ethics for psychologists Making judgementStudents will develop the ability to independently analyze and critically evaluate research designs used in clinical psychology, with particular focus on treatment evaluation and experimental psychopathology. They will be able to integrate methodological knowledge with ethical considerations and apply this to assess scientific papers, experimental paradigms, and empirical data. This competence will be fostered through critical discussions, group work, and individual assignments focused on treatment efficacy and research methods. Communication skillsStudents will acquire communication skills that enable them to effectively present complex scientific concepts related to clinical psychological research and experimental psychopathology. Through oral presentations, group discussions, and written assignments, students will learn to use appropriate technical language, engage in constructive academic dialogue, and communicate their ideas clearly to both specialist and broader academic audiences. Learning skillsThe course promotes autonomous and continuous learning by encouraging students to critically engage with current scientific literature, including international research articles and clinical materials. Students will develop strategies for effective bibliographic research and critical review, fostering the ability to update and deepen their knowledge in clinical psychological sciences and professional ethics, thus supporting lifelong learning and professional growth.

• Methodological and design considerations central to the scientific evaluation of treatment efficacy and effectiveness - Strengths and weaknesses of different treatment evaluation designs (recent developments in psychotherapy research will be used as examples) - Experimental psychopathology as a way to elucidate the processes underlying abnormal behavior. - Methodological approaches and paradigms employed in experimental psychopathology research. - The Experience Sampling Method (ESM) as a way to improve our understanding of how psychopathological symptoms unfold over time in everyday life. - Professional ethics for psychologists

The exam will verify the level of mastery of the course contents with special attention to: Methods and research designs for treatment evaluation; Methods and research designs in experimental psychopathology; Ability to elaborate course contents; Ability to analyze a scientific paper in the field of clinical psychology. Ability to apply professional ethics for psychologists. The exam will consist of multiple choice questions and open-ended questions on the course topics. The multiple-choice questions aim to ascertain the student's preparation; the open questions aim to evaluate the ability to think critically and create links between the acquired knowledge. For students willing to benefit from this opportunity, the examination could be replaced by activities to be held during term time. These will consist of: Mid-term assignment: Project work on development and presentation of a research project in clinical psychology (20% of final grade) End-term assignment: Critical analysis of a scientific paper (30% of final grade) consisting in an individual essay. End-term multiple choice test on course content (50% of final grade) More details will be provided during the course.

The bibliography will be provided at the beginning of the course and published in the course web-site.

Formare la figura professionale dell'analista dati tramite la metodologia informatica del machine learning.L'obiettivo viene perseguito; fornendo competenze di progettazione, sviluppo e documentazione di studi di machine learning, fornendo competenze su software open source professionale per l'estrazione della conoscenza a partire dai dati, stimolando e promuovendo il team working come metodo professionale di lavoro e collaborazione. Al termine del corso lo studente avrà maturato competenze e conoscenze tali da progettare, sviluppare,documentare e presentare uno studio di machine learning. (DdD 1, DdD 2).Inoltre, l'organizzazione della prova d'esame, tramite un progetto di gruppo da sviluppare e documentare, consentirà al candidato di sviluppare capacità critica (DdD 3), di comunicazione (DdD 4), mentre la disponibilià di materiale da leggere, suggerito dal docente consentirà al candidato di proseguire in modo autonomo lo studio e l'approfondimento della materia (DdD 5).

Esplorazione dei dati e Pre-Processing Tipi di dati ed attributi Esplorazione dei dati, grafica e tabellare Trattamento delle osservazioni mancanti Pre-processamento dei dati Classificazione Supervisionata Introduzione alla classificazione supervisionata Tecniche di classificazione supervisionata; reti neurali, classificatori Bayesiani, alberi di decisione, ... Misure di prestazione, procedure di valutazione e comparazione di classificatori Classi sbilanciate e problemi di classificazione non binaria Classificazione Non Supervisionata Introduzione alla classificazione non supervisionata Misure di prossimità per attributi continui, nominali, ordinali Algoritmi di clustering; k-means,algoritmi gerarchici, dbscan, opossum, ... Misure di prestazione, procedure di valutazione e comparazione delle soluzioni di clustering

La verifica prevede una prova di 4 ore durante la quale il/la candidato/a è chiamato/a a rispondere a 6 quiz (1 punto per ogni risposta corretta) e 1 domanda a riposta aperta (fino a 9 punti) (DdD 5). Inoltre, verrà assegnato un porblema di machine learning da risolvere. Nello specifcio verrà presentato un problema, fornito un dataset e si dovrà progettare e sviluppare un workflow KNIME (DdD 3, DdD 4) (ogni nodo del workflow andrà commentato utilizzando le funzionalità offerte dalla piattaforma KNIME, vengono assegnati massimo 10 punti), e si dovranno redigere delle slide secondo un template fornito dal docente (fino ad un massimo di 5 punti. Infine, dietro richiesta del/la candidato/a è possibile richiedere una prova orale che assegna un punteggio compreso tra -3 e +3 punti.Non sono previste prove in itinere. Il workflow e le slides verranno valutati in base ai seguenti criteri; Merito tecnico; accuratezza e correttezza del workflow (fino a 10 punti) Chiarezza espositiva e di comunicazione delle idee, includendo leggibilità e visione critica of the slides (fino a 5 punti)

Materiale audiovisivo, slides, dataset e workflow progettati e realizzati dai docenti del corso. https://www-users.cse.umn.edu/~kumar001/dmbook/index.phphttps://github.com/kerasking/book-1/blob/master/ML%20Machine%20Learning-A%20Probabilistic%20Perspective.pdf

Knowledge and understanding Learning different methods for survey research (including ambulatory assessment) and indirect measuresLearning about the scale construction process and psychometric issues when creating a measure Applying knowledge and understanding Identifying the best methods to measure different concepts in different domainsCreating surveys and indirect measures using specific software Making Judgements Understanding the quality and the shortcomings of psychological measurments methodsSeveral psychological measures are analyzed and their pros and cons are evaluatedGroups are formed to discuss pros and cons of measurement methodsPractical implementation issues are discussed and tested hands-on by students Communication skills Students present (in groups) their implementation of the various methods discussed in classStudents difend (in groups) their project and comment on other groups projects in class Learning skills Learning different methods for survey research (including ambulatory assessment) and indirect measuresLearning about the scale construction process and psychometric issues when creating a measureStudents develop their own survey or assessment project that allow them to apply these skills in their thesis or in their future workplace

Survey and vignette research: scale construction process, psychometric properties and quality, creating a survey using Qualtrics. Ecological Momentary Assessment method: construction process, psychometric properties and quality, creating a EMA survey using Qualtrics and an App and testing it.

The course will be assessed on a pass/fail basis only. There is no final exam; evaluation will be based on active participation and any assignments or activities carried out during the course. Students in small groups have to create a scale on a topic of their choice starting from the existing literature, then collect data, and examine the validity of the scale. The small groups have then to present their work orally with slides and each student has to provide an individual report on the work he/she/they produced within the group.

Mehl, M. R., & Conner, T. S. (2012) Handbook of Research Methods for studying life. Guilford Rudman, L. (2011). Implicit Measures for Social and Personality Psychology. Sage Furr, R. M. (2011). Scale construction and Psychometrics. Sage

Knowledge and UnderstandingThe course provides students with foundational and advanced knowledge in psychometrics and statistical methods in psychology, including measurement properties, hypothesis testing, regression, ANOVA, and factor analysis. Students also gain theoretical insights into data dimensionality and psychometric principles, as well as basic knowledge of a Bayesian vs. a Frequentist statistical approach. Applying Knowledge and UnderstandingStudents learn to apply statistical methods using real and simulated psychological data, including the selection and implementation of techniques appropriate to various research designs. Through laboratory sessions, students gain hands-on experience with R, whereas during lectures, they will be assigned exercises using Jamovi, allowing them to analyze data and interpret empirical results. Making JudgementsStudents develop critical thinking skills necessary to evaluate the adequacy of psychological measures, assess statistical assumptions, and select suitable analytic methods. They also learn to interpret findings in the context of psychological theories and empirical evidence. CommunicationThe course fosters the ability to clearly report and discuss statistical findings through open-ended assessment questions and laboratory reporting. Emphasis is placed on explaining complex analyses and results in understandable terms. Learning SkillsBy engaging with practical data analysis tasks, basic literature, and interactive lectures, students enhance their capacity for autonomous learning. The course supports the development of skills necessary for an independent application of statistical methods and software in future research or professional contexts.

Introduction to psychological measurement Direct and indirect measures Reliability and validity Statistical models and inferential statistics Multiple Regression ANOVA and General Linear Model Principal Component Analysis Confirmatory Factor Analysis Laboratory Basics of R statistical software and hands-on exercises with data.

The exam will verify the level of mastery of the course contents with special attention to: - Understanding the logic of the statistical analyses discussed in the course; - The ability to choose between different techniques based on the research design and aims; - Ability to execute the analyses with suggested software; - Ability to interpret and report the results of the statistical analyses discussed in the course. The exam will consist of multiple-choice questions and open-ended questions on the course topics. The multiple-choice questions aim to ascertain the student's preparation and knowledge of the topics. The open questions aim to evaluate the ability to think critically, create links between the acquired knowledge, and apply them concretely to analyze empirical data and discuss the results

Navarro DJ and Foxcroft DR (2025). Learning statistics with Jamovi: a tutorial for beginners in statistical analysis. https://www.openbookpublishers.com/books/10.11647/obp.0333; https://www.learnstatswithjamovi.com/. Additional readings and materials will be indicated during the lectures and in the laboratory sessions.

Knowledge and understanding• Knowing the functional and technical properties of the state-of-the-art techniques in Cognitive Neuroscience, with a specific focus on functional magnetic resonance imaging (fMRI)• Understanding the genesis and dynamics of brain signals and how they reflect mental functions Applying knowledge and understanding• Acquisition of the methodological knowledge required to (i) critically analyze studies applying state-of-the-art techniques in cognitive neuroscience, and (ii) design empirical studies in the field. Making judgmentStudents will gain the ability to independently integrate methodological and theoretical skills in the field of cognitive neuroscience and to apply them to critically judge previous studies and propose new research projects in the different sub-fields of cognitive neuroscience, taking into account the specific critical aspects of each research technique and various operational situations. Students will also gain the ability to reorganize the acquired knowledge to promote innovative and original solutions through judgment based on empirical data and a critical reading of the complexities inherent to cognitive neuroscience. This will be achieved through class discussions and group work. Communication skillsStudents will acquire communication skills that allow effective interaction with various professionals from different cultural and scientific backgrounds; through group presentations, students will learn how to propose innovative research projects in cognitive neuroscience and to communicate their results and conclusions to an audience of specialists and non-specialists in a clear, detailed, and scientifically grounded manner, using the specific lexicon of the discipline. Students will also learn how to coordinate during teamwork and collaborate effectively and competently in English. Learning skillsThe course will promote the acquisition of the ability to adopt new developments and innovations emerging from international scientific results in cognitive neuroscience, updating one's skills to the rapid evolution of the field. The course will also promote the use of specialized bibliographic resources to perform in-depth scientific reviews to critically judge current knowledge in cognitive neuroscience and capitalize on it to propose further advancements in the field (e.g., through the development of new scientific projects). This will be achieved by discussing the available digital instruments to perform bibliographic research and through class discussions.

Brief review: how the brain can be studied with cognitive neuroscience techniques. Brief review: how to design a cognitive neuroscience experiment from a methodological point of view. In-depth discussion of functional magnetic resonance imaging (fMRI): basic principles of functioning, critical discussion of some examples on how it can be applied in cognitive neuroscience studies (the case of Motor Cognition will be taken as an example), and hand-on exercises on data analysis. Practical activity: critical discussion of a research study applying fMRI to address a specific theoretical issue. Practical activity: development of a research project to address a specific theoretical issue by applying fMRI.

The course will be assessed on a pass/fail basis only. There is no final exam; evaluation will be based on active participation and any assignment or activity carried out during the course.Specifically, students learning will be assessed during data discussion, hands-on experience, and during the presentation of the research project, with questions pertaining issues addressed in class.

Learning material will be provided during the course.

Knowledge and understanding• Understand the role that cognitive processes play in how people perceive, interpret, and remember informationabout themselves, other people, and social groups.• Explain how cognitive biases affect social interactions.• Acquire basic competence in conducting social cognition research using Inquisit.• Develop skills in evaluating and synthesizing scientific sources to strengthen disciplinary knowledge. Applying knowledge and understanding• Analyze, evaluate, and integrate theory and research related to social cognition.• Apply theoretical models to real-world phenomena (e.g., stereotypes, decision making, group processes).• Identify and analyze with appropriate methodological skills the characteristics of different situations.• Use problem-solving strategies to transfer theory into practice. Making judgements• Exercise critical thinking by identifying strengths, limits, and implications of theories and empirical studies.• Reflect on own and others’ experiences through practical activities• Evaluate ethical and methodological challenges in programming experiments in social cognition. Communication skills• Improve oral communication and reasoning through class and small-group discussions.• Collaborate effectively with peers by presenting, discussing, and synthesizing course topics.• Communicate research findings clearly in both oral and written formats. Learning skills• Develop autonomy in study through independent literature search and critical source evaluation.• Strengthen self-regulation and metacognition by reflecting on personal learning strategies.• Build transferable skills (critical analysis, problem-solving, collaboration) to support lifelong learning.

• What is social cognition?• Automatic versus controlled processing• Dual-process models• Social categories and category structure• Mental representations• The Self in social cognition: Cultural differences• Attribution Theory• Impression formation of individuals and groups• Prejudice and Stereotyping• Programming social cognition experiments with Inquisit.

To verify the achievements of the learning objectives, the exam will be only oral, except for the assessment of the programming skills for social cognition experiments using the Inquisit software, which will take place as a practical task in the lab or as multiple-choice test for non-attending students The questions aim at ascertaining the effective acquisition of both theoretical knowledge and the ability to applythem to reality. The answers to all questions will be evaluated in terms of correctness of the answers, the argumentative capacity, synthesis, ability to form links among the different topics, and the ability to critically present the phenomena. Lab activities concerning the acquisition of basic skills in programming with Inquisit will be worth 25% of the finalgrade.

• Fiske, S.T. & Taylor, S. (2020). Social Cognition. From brain to Culture. 4?? edition. Sage Publication. Chapter1-3, 4 (from p.117), 5-8, 11-12, 15 (from p. 461)• Gawronski, B., & Creighton, L.A. (2013). Dual Process Theories. The Oxford Handbook of Social Cognition(Chap. 14).• Payne, B.K. (2012). Control, awareness, and other things we might learn to live without. Sage Handbook ofSocial Cognition (Chap. 2).• Payne et al. (2005). An Inkblot for Attitudes: Affect Misattribution as Implicit Measurement. Journal of Personalityand Social Psychology, 89 (3), 277–293. Additional material will be indicated during the course and will be uploaded on the course website.

Knowledge and understanding• Typical cognitive development: models, methods and instruments to assess cognitive development• Atypical cognitive development: etiological models explaining neurodevelopmental disorders• Experimental designs to study neurodevelopmental disorders• Technological approaches to assess and address neurodevelopmental disorders Applying knowledge and understanding• Understanding, analysis, and evaluation of research designs in cognitive developmental psychology• Identifying and analyzing the critical elements of research designs to understand different application in cognitive development• Applying experimental paradigms for the investigation of typical and atypical cognitive development and its relationships with behaviour and emotions• Exploring and reasoning about potential and limits of technological approaches applied to atypical development Making judgmentStudents will gain the ability to independently integrate methodological and theoretical skills in the field of applied cognitive development and to apply them to critically judge previous studies and propose new research projects in the different sub-fields of applied cognitive development, taking into account the specific critical aspects of each research technique and various operational situations. Students will also gain the ability to reorganize the acquired knowledge to promote innovative and original solutions through judgment based on empirical data and a critical reading of the complexities inherent to applied cognitive development. This will be achieved through class discussions and group work. Communication skillsStudents will acquire communication skills that allow effective interaction with various professionals from different cultural and scientific backgrounds; through group presentations, students will learn how to propose innovative research projects in applied cognitive development and to communicate their results and conclusions to an audience of specialists and non-specialists in a clear, detailed, and scientifically grounded manner, using the specific lexicon of the discipline. Students will also learn how to coordinate during teamwork and collaborate effectively and competently in English. Learning skillsThe course will promote the acquisition of the ability to adopt new developments and innovations emerging from international scientific results in applied cognitive development, updating one's skills to the rapid evolution of the field. The course will also promote the use of specialized bibliographic resources to perform in-depth scientific reviews to critically judge current knowledge in applied cognitive development and capitalize on it to propose further advancements in the field (e.g., through the development of new scientific projects). This will be achieved by discussing the available digital instruments to perform bibliographic research and through class discussions.

The course focuses on theory and practice of the research approach to analyze different aspects of cognitive development: • Assessment and treatment of neurodevelopmental disorders, with a focus on Learning Disabilities, ADHD and Autism• Neurological basis of developmental disorders• Trainings for children with neurodevelopmental disorders: how to define a project and how to test their efficacy• Use of new technology, such as robots and virtual reality, to understand and train cognitive processes in children• School inclusion of children with special educational needs• Atypical development of attention and executive function in relation to technological devices, such as video games• Sensitive periods for sensory learning• Sensory and social deprivation

The exam will verify the level of mastery of the course contents with special attention to: Methods and research designs for treatment evaluation Methods and research designs in cognitive development Ability to elaborate course contents Ability to analyze a scientific paper in the field of cognitive development. The exam will be written and will consist of 4 open questions, that the student will need to answer within 90 minutes.The final grade will consist of the sum of points given by the written exam and the two presentations given during the class.

Slides presented in class Papers will be presented at the beginning of the class The bibliography will be provided at the beginning of the class and published in the class web-site.

Knowledge and understanding The application of knowledge from Cognitive Neurosciences to production systems and technological development The use of methodologies and techniques from Cognitive neurosciences to the analysis of responses obtained from human consumers/users Applying knowledge and understanding Ability of transferring the course contents to the planning and development of strategies and research plan in the field of applied cognitive neurosciences. Making judgements -Development of the ability to critically analyze, evaluate and synthesize new and complex scientific ideas (also in relation to issues of international strategic relevance) through group discussions and possible seminar-type activities Communication skills -Development of the ability to communicate information, ideas, problems and solutions clearly and consciously to specialist and non-specialist interlocutors and in different training and work contexts.Development of a solid ability to listen actively, to interact and to work in groups, including interdisciplinary ones, as well as to understand and critically analyze different points of view. Learning skills -Development of the ability to continue one's study/work path independently, strengthened by greater critical awareness and a renewed theoretical-conceptual and methodological sensitivity.

Cerebral anatomy applied to consumer behavior and object design Marketing and design inspired to neural functioning The human senses and their role in applied contests Physiological functions, hormone and homeostasis in the design of services and in consumer behavior Brain-machine interfaces Multisensory processing and product development Neuroscientific techniques and methodologies for the study of consumer behavior and human interactions with technologies Overcoming the limitations of Virtual reality technologies by means of neuroscientific principles

The exam includes a written test with multiple choices questions and an open question that requires a large and critical discussion on one topic of the course. The questions are aimed at ascertaining the effective acquisition of both theoretical knowledge and the ability to connect different aspects of applied neuroscience. The answers to the open question will be evaluated in terms of correctness of the answers, argumentative capacity, and analytic discussion of the topics of the course. For students who request it and that have passed the written test, an oral interview will be also made available, on all the topics of the course.Participation in optional activities (see teaching methods) contributes to the final evaluation.

-Gallace, A., & Spence, C. (2014). In touch with the future: The sense of touch from cognitive neuroscience to virtual reality. Oxford: Oxford University Press. (ch. 9-10-11) -Spence, C. & Gallace, A. (2011). Multisensory design: Reaching out to touch the consumer. Psychology & Marketing, 28, 267-308. - Gallace, A., Ngo, M. K., Sulaitis, J., & Spence, C. (2011). Multisensory Presence in Virtual Reality: Possibilities & Limitations. In: G. Ghinea, F. Andres, & S. Gulliver (Eds.), Multiple Sensorial Media Advances and Applications: New Developments in MulSeMedia. IGI Global. - Nazir, S., Gallace, A., Bordegoni, M., Colombo, S., & Manca, D. (2012). Performance comparison of different training methods for industrial operators. In: De Waard, D., Brookhuis, K., Dehais, F., Weikert, C., Röttger, S., Manzey, D., Biede, S., Reuzeau, F., & Terrier, P. (Eds.), Human Factors of Systems and Technology (pp. 1-8). Available as open source download. - Spence, C., Hobkinson, C., Gallace, A., & Piqueras Fiszman (2013). A touch of gastronomy. Flavour, 2:14. -Additional reading material will be specified during the course

Knowledge and understanding cognitive processes involved in language processing and mechanisms underlying language processing, with a special focus on multilingualism; theoretical implications of psycholinguistic research on models of language processing and cognition; experimental methodologies and paradigms used in the investigation of the cognitive mechanisms involved in language processing; current debates in psycholinguistics (for example, debate on the cognitive advantage of bilingualism; debate on inclusive language proposals, etc.); practical applications in communication: use of linguange in real communicative situations; evaluation of different targets, scopes and means of communication of the message; evaluation of the communicative consequences of lingustic choices. Applying knowledge and understanding reasoning about the cognitive processes involved in language processing and the effect of multilingual exposure evaluating experimental paradigms and tools for the investigation of language use and language comprehension, also in consideration of the population (e.g., monolinguals vs. bilinguals) and the linguistic features of the language under investigation reasoning about implicit content triggered by linguistic items and analysis of non-literal interpretations interpreting behavioral measures (reading/reaction times measures, implicit measures of processing, such as eye-tracking measures and event-realted potentials) analyzing scientific reports critically implementing testable hypothesis of research on language Making Judgment Development of students' critical analysis skills, particularly regarding the interpretation of experimental data used to support research hypotheses. Enhancement of students' ability to critically evaluate research hypotheses and models of data interpretation, including those related to recent scientific debates in the field of psycholinguistics —such as inclusive language and the benefits of multilingualism. These objectives will be supported through active student participation during lectures and through group discussions on controversial topics, encouraging students' engagement and confrontation of diverse perspectives. Communication Skills Development of active listening skills, the ability to argue one's ideas, and to engage in discussion within groups, including interdisciplinary ones. Development of the ability to understand and critically analyze different points of view. Development of the ability to communicate one’s perspective clearly and consciously, and to support one’s arguments by referring to scientific evidence as well as documented and verified data or information. These objectives will be supported by encouraging students' active engagement in class discussions. Learning SkillsDevelopment of greater critical awareness and methodological sensitivity which will strenghten the students' ability to: analyze research data in a critical, detailed, and in-depth manner critically evaluate the interpretation of scientific data — including consideration of alternative hypotheses or explanations construct and defend arguments based on thoroughly analyzed and well-documented sources

On-line processing of spoken languages and cognitive processed involved Prediction and anticipation in language and cognition Experimental methods and techniques used in psycholinguistics to understand how the brain processes language Lexical access and representation in monolingual and multilingual adults Cognitive effects and communicative consequences of lexical processing Discussion of current topics of research on bilingualism, and cross-linguistic influence effects Practical application of language in communicative contexts, such as the use of metaphors and implicit content Discussion of recently debated topic, such as inclusive language efficacy and feasibility

The exam is written and comprises: open questions in order to assess the acquisition of theoretical notions and the ability to extend this competence to cases of real communication; multiple choice questions in order to assess the acquisition of theoretical basic notions; the analysis of one of the graphs discussed in class, in order to assess the ability to interpret and discuss psycholinguistic data a series of exercises in which the student is required to extend the knowledge acquired to real examples of use of language On a voluntary basis, students can give a presentation in class (during the course) consisting of the critical analysis of a scientific paper related to the topics discussed in class (prior approval of the instructor) or a research project following one of the topics/studies discussed.In this case, the final grade will be modulated as detailed below: written examination: 70% of the final grade; presentation in class: 30% of the final grade. The evaluation criteria are the following: accuracy of the answers, ability to argue, synthesize, make connections, and critically analyze phenomena.The assessment will be based on the following criteria: 30 with honors (30 e lode): Excellent exam, both in terms of knowledge and critical/expressive articulation 30: Outstanding exam, complete knowledge, well-articulated, and correctly expressed 27–29: Good exam, comprehensive and satisfactory knowledge, substantially correct expression. 24–26: Fair exam, knowledge is present on key points but is not comprehensive and not always correctly articulated 21–23: Sufficient exam, knowledge is sometimes superficial, with gaps in expression and articulation that are not always appropriate 18–20: Barely sufficient exam, knowledge is present but superficial; expression and articulation of the argument show significant gaps < 18: Insufficient exam, knowledge is absent or heavily flawed, with a lack of critical analysis of the topics covered.

Textbooks:Alber Costa (2020). The bilingual brain: And what it tells us about the science of language. Penguin UK.Julie Sedivy (2019). Language in mind: An introduction to psycholinguistics. Sinauer Associates (only selected chapters - parts will be made available on the course page).Other reading material (including scientific papers) will be specified during the course and detailed on the course page.

Knowledge and understanding Students will develop a solid understanding of how individual, social, and societal factors influence cognitive processes and behaviors. The course explores major socio-cognitive theories that explain human actions in social contexts, as well as the role of attitudes, values, and belief systems in shaping behavior. Students will also gain familiarity with a range of intervention techniques and research methods used to analyze and address real-world social issues. Applying knowledge and understanding Students will learn to apply socio-cognitive knowledge to real-world problems by understanding, analyzing, and evaluating research designs aimed at addressing societal challenges. They will explore diverse applied contexts—such as political, public health, environmental behavior, and technology use—and learn to use various methodological approaches and paradigms. Through critical examination of applied research examples, students will develop practical skills for designing and implementing evidence-based interventions. Making Judgements Students will develop critical thinking and independent judgment through the analysis of empirical studies, the evaluation of socio-cognitive interventions in policy contexts, and the preparation of reports on real-world societal issues. Activities will include classroom discussions, critique of case studies, and the interpretation of research findings. The exam format—open-ended questions in the form of short essays—further supports the development of these skills by encouraging reflective and evidence-based reasoning. Communication Skills Students will enhance their ability to communicate complex concepts effectively through group discussions and the written articulation of research-based arguments, particularly through the development of a group project addressing an applied research question. The use of open-ended essay questions in the final exam also reinforces written communication skills, with a focus on clarity, structure, and relevance when presenting ideas and evaluating the societal impact of socio-cognitive processes and interventions. Learning Skills Students will acquire conceptual and methodological tools that support independent learning beyond the course. By engaging with academic literature, case analyses, and different methodological techniques they will be prepared to autonomously deepen their expertise in applied social cognition and its relevance to public decision-making.

Understanding social issues through applied social cognition Beliefs’ system and attitudes Focus on models of attitude and behavior prediction Interventions and public policies Behavioral intervention strategies Interventions based on social influence Implementation and analysis of researches applied to the different behavioral domains: politics, health, environment, social media, and other new technologies. Thematic sessions: scientific misinformation; conspiracy beliefs; vaccination behavior; climate change; food psychology

The exam is written (computer exam in the lab via the Moodle EsamiOnline Bicocca) with six open-ended questions (equivalent to concise essays) to answer in 90 minutes. The questions aim to ascertain the effective acquisition of socio-cognitive theories and methods to solve societal issues. The evaluation criteria are: Correctness and theoretical relevance of the answers; Critical reasoning and the ability to construct well-founded arguments; Ability to create meaningful connections among the topics; Clarity of expression and coherence in presenting ideas. Participation in optional activities (see teaching methods) contributes to the final evaluation.Special attention will also be devoted to the acquisition of methods and measurement tools in applied social cognition field and the ability to analyze a scientific paper in the field.

Mandatory reading material (research articles) will be made available by the professor during the course on the e-learning page of the course. RECOMMENDED READING:Maio, G. R., Haddock, G., &; Verplanken, B. (2018). The psychology of attitudes and attitude change. Sage Publications Limited. (only chapters indicated on the e-learning page).

By the end of the course, students should: Knowledge and understanding be aware of the implications of psychological research for improving the design and evaluation of computer systems be able to explain the importance of user-centred design consider how technologies should be designed to support communication and collaboration, and how their design can affect these processes Applying knowledge and understanding consider how technologies can affect user experience and how they can encourage changes in behaviour be able to apply major theories in cognitive psychology to practical case studies communicate ideas and research findings by written means group work. Making judgmentStudents will learn to integrate methodological and theoretical skills in the field of cognitive ergonomics and to apply them to propose new projects, aimed either at developing new ideas or at comparing different systems in terms of usability and User Experience. With the help of class discussions and group work students will also be able to develop cretive thinking, in order to design and possibly implement innovative and original digital solutions to promote changes in behaviour. Communication skillsThrough both group presentations and class discussion students will will acquire communication skills to effectively interact with different professionals, in order to teamwork with them to develop new digital tools and systems. Students will also be encouraged to present their work to possibles clients/financiers and donors (and to write a report of their project), in order to learn how to build a "pitch-talk". In this way students will be aware of the difference in communication styles according to different audience and purposes. Learning skillsThe course will promote the acquisition of the ability to apply major theories in cognitive psychology to practical case studies, by stimulating creative thinking and encouraging the application of classical methods in psychological reasearch to frame user needs and to deeply understand the practical meaning of the words "designing for people".

Cognitive ergonomics and cognitive psychology: foundations of cognitive processes; Perception, psychophysical methods, memory and attention, embodied cognition. Usability, accessibility and acceptability. Designing usable products: affordance, mapping and feedback. Interface Analysis: graphic symbols, cognitive tools. Design for the interaction: developing Personas and Scenarios; requirement analysis: interviews and questionnaires; probes and card sorting techniques; case studies. Participative Design. How we think: thinking errors and how to prevent them. User experience. The model of Hassenzhal: self products and act products. Evaluating a product: euristic evaluation; discount euristic evaluation and cognitive walkthrough; cooperative evaluation; codiscovery; evaluation without being there; controlled experiments. Evaluation in practice: usability metrics and mesures; reporting usability evaluation results. Gaming and gamification Measuring User Experience

Oral exam on textbooks and on handouts of the lectures. For students attending lessons, an alternative to the oral exam is the presentation, in both written and oral form, of the working project developed during lessons. The exam will verify the level of mastery of the course contents with special attention with the link between theory and practice in developing user centered designed systems.

Benyon, D. (2014). Designing Interactive Systems. A Comprehensive guide to HCI, UX and interaction design (Chapters 1-13). Pearson.

Knowledge and understandingModels and Theories of decision makingModels and Theories of attitudes and persuasionContexts and Trends of consumptionPrediction of consumer behaviour Applying knowledge and understandingApplication of consumer psychology to marketingResearch MethodsMarketing cases Making judgmentWorking in groups and individually students will be guided in the search and evaluation of research sources and publications to develop individual critical judgements. Communication skillsGroup works are expecially designed to train students in the preparation of effective communicative material and in providing oral presentations where communication strategies will be taught and assessed. Learning skillsStudents improve learning strategies by adopting multiple tecniques, by reading, summarizing, comparing and elaborating on specific topics . They are especially taught how to develop critical thinking by having to find solutions to research issues and applied problems.

The course is divided in three parts. The first one is about theoretical and scientific models for the understanding of the consumer as an individual, and focuses on decision making, perception, and learning.The second part is concerned with motivation, attitudes, identity construction in relation with products consumption and brands, the role of the socio-cultural context, the social group and advertising.The third part explores fields of application such as ‘information communication technologies for consumer research and strategy, food consumption, marketing of experience, social media strategy and analytics, UX and CX research.

Exam is conducted by means of oral colloquium.Mandatory study material is the book indicated in the reading list and the power points slides uploaded on the platform Students will be assessed on their learning of the main theories illustrated during the lessons and on their understanding of the key constructs presented in class and described in the textbook.The evaluation will also take into account the understanding of the research methods and concrete application to the different marketing cases discussed and illustrated during the lessons.

The title of the text will be communicated before the starting of the lectures.

Knowledge and understanding Understand the ideal standards of decision-making both in individual and interactive context Understand why people fail to cope with ideal standards Heuristics in decision-making and associated biases Prospect theory and associated formal modeling of decision making Understand how indirect suggestions can influence decisions (nudging) Applying knowledge and understanding Determination of the optimal course of action in different contexts, with examples from clinical decision making and economic decisions Analysis of the typical decision course of individuals, with critical analysis of their limits Use of software for building and visualizing decision trees Making judgements The course presents various theoretical perspectives on each phenomenon discussed and highlights open questions related to cutting-edge knowledge domains. The examination methods encourage and stimulate critical thinking, informed independent judgement, design skills, problem-solving, and synthesis abilities. Through discussions and case studies, the course trains students in independent data evaluation, the construction of causal models, and inductive hypothesis testing. Group work and exercises on the theoretical content covered in lectures are proposed to foster independent judgement and critical reasoning. Communication Skills The course promotes the development of communication skills through in-class discussions of exercises and more theoretical aspects of the course. The exam includes open-ended questions that require the use of appropriate technical language and the ability to clearly and coherently convey the issues addressed. Learning Skills The course provides a solid theoretical and practical foundation that enables students to independently pursue further learning in related advanced topics. It encourages autonomous exploration and in-depth study of the topics covered, peer discussion, and active and critical learning.

Choice under certainty Judgment under risk and uncertainty Choice under risk and uncertainty Prospect theory and Nudging Decision Trees with sensitivity analysis Cost-Effectiveness Analysis Advice taking Human - AI collaborative decision making

The exam includes a written test to be performed in a computer lab. The test involves three parts: a multiple response test, open questions and an exercise with a decision tree software. The exam aims at ascertaining the effective acquisition of both theoretical knowledge and the ability to connect and apply the different topics of the course. The answers to each question will be evaluated for correctness, argumentative capacity, synthesis, ability to form links among the different areas, and the ability to present the phenomena critically. The activities performed during the course will be part of the overall evaluation.

Angner, E. (2020). A Course in Behavioral Economics (Third edition.). London: Palgrave.Baron, J. (2024). Thinking and Deciding (Fifth edition). Cambridge University Press. Further compulsory material will be made available by the teacher during the course on the elearning website.

Knowledge and understandingBy the end of the course, students will know and understand: the main concepts of Human-Technology Interaction, Human-Computer Interaction, User Experience, interaction design, accessibility and inclusiveness; the role of cognitive, perceptual, attentional, memory-related, motivational and social processes in the design and evaluation of interactive systems; the user-centred design cycle: needfinding, task analysis, requirements discovery, generation of design alternatives, prototyping, evaluation and revision; characteristics, potential and limits of emerging technologies such as virtual reality, augmented reality, mixed reality, conversational systems, AI/ML-based systems, social robotics, wearable technologies, game engines and recommender systems; the basic principles of computational thinking and prototyping with digital tools, including Figma and Unity3D; how innovative products integrating new technologies may generate benefits, risks or use problems due to design choices, technological constraints, user expectations or lack of understanding of the impact of technology. Applying knowledge and understandingBy the end of the course, students will be able to: apply psychological, cognitive and interaction design principles to the analysis of concrete Human-Technology Interaction problems; identify needs, tasks, contexts of use, technological constraints and user requirements; critically evaluate interfaces, products and systems integrating new technologies, identifying design errors, good design practices, technological limits and possible effects on user experience; analyse innovative products, including products awarded or presented in international technology innovation contexts, distinguishing between the actual value of the solution, technological novelty, feasibility, sustainability, usability and user impact; propose design solutions consistent with user needs and technological constraints; select appropriate methods and metrics to evaluate the effectiveness of an interactive solution; develop or discuss a prototype, a design proposal or an evidence-based evaluation of a technology or product. Making judgementsStudents will develop the ability to make autonomous and critically grounded judgements on theories, empirical evidence, technologies, products and design solutions. In particular, they will learn to recognise implicit assumptions, strengths, methodological limitations, technological constraints and possible threats to validity; evaluate whether a technology is actually necessary or whether simpler, cheaper, more accessible or more effective solutions are available; and justify design trade-offs concerning usability, accessibility, cognitive load, safety, inclusion, trust, cognitive biases, privacy and social impact.These skills will be developed through guided discussions, case analyses, presentations of technologies, products and scientific papers, invited talks, exercises and design-oriented activities. Communication skillsStudents will acquire communication skills to present and discuss technologies, products, scientific evidence and design solutions in a clear, structured and scientifically grounded way. Course activities will develop the ability to use the disciplinary vocabulary of HCI, UX and interaction design; present emerging technologies by describing components, capabilities, limits and implications; communicate critical evaluations of technological products; discuss scientific papers and design cases; and collaborate in small groups while making each member’s individual contribution explicit. Learning skillsThe course promotes students’ ability to continue learning autonomously in a rapidly evolving technological field. Students will be guided to approach a new technology systematically, analysing its definition, components, capabilities, limitations, costs, metrics and applications; identify scientific sources, technical documentation, tutorials, examples, use cases and comparisons between solutions; distinguish reliable sources, commercial sources and non-neutral opinions; and transfer the acquired competences to new technologies and application contexts.

Introduction to Human-Technology Interaction: HTI, HCI, UX, UI, interaction design, accessibility, inclusiveness and human-centred technologies. Cognitive and psychological foundations of interaction design: perception, attention, memory, cognitive load, human error, mental models, affordances, trust and onboarding. User-centred design: needfinding, task analysis, requirements discovery, interviews, questionnaires, observation, personas, scenarios, storyboards and design alternatives. Prototyping: low- and high-fidelity prototypes, paper prototyping, wireframes, Wizard of Oz, video prototyping, mockups and interactive prototypes. Evaluation: usability testing, heuristic evaluation, cognitive walkthrough, VR heuristic evaluation, A/B testing, live prototyping, metrics and limits of evaluation. Product evaluation and new technologies: analysis of innovative products, identification of design errors and good design choices, evaluation of usability, accessibility, safety, trust, inclusion, and psychological and social impact. Learning and evaluating a new technology for UX design: components, types, capabilities, limitations, costs, metrics, risks of overestimation, user familiarity and simpler alternatives. Web UX and interface design tools: information architecture, typography, grids, wireframes, design systems, mockups and prototyping with Figma. Computational thinking: algorithms, flowcharts, variables, structures, objects, classes and simple C# exercises. Unity3D and real-time technologies for UX design: game engines, 2D/3D environments, Unity Experiment Framework, interactive prototypes and human-behaviour experiments. Artificial intelligence and human-machine collaboration: AI/ML as interactive technologies, AI-ready design, cognitive biases, AI collaborators and design and ethical implications. Conversational and recommender systems: voice-based UX, conversational UX, conversational agents, question answering, personalisation and recommender systems. Virtual, augmented and mixed reality: XR hardware, input devices, calibration, latency, perception, immersion, presence, sickness and interaction techniques. Human-Robot Interaction and smart technologies: social robots, user profiling, behaviour adaptation, spatial, verbal and non-verbal interaction, wearable technologies and Internet of Things. Serious games, gamification and technologies for wellbeing, therapy and education. Discussion of scientific papers, invited talks and contemporary application cases.

The final exam is oral. Optional in-course activities, consisting of in-class activities, may contribute up to 6 points to the final grade. The grade is expressed out of 30. Points obtained through in-class activities are added to the evaluation of the final exam, but the final grade cannot exceed 30/30; honours may be awarded on the basis of the overall quality of the exam, critical autonomy and completeness of preparation. In-class activities may include:active participation in labs, exercises, invited talks and students’ presentations: cumulatively up to 1 point;in-class presentations, with slides, of at least 2 technologies agreed with the instructor: up to 1 point for each presentation;in-class presentation, with slides, of at least 1 scientific paper agreed with the instructor: up to 1 point;in-class presentations, with slides, of at least 2 innovative products integrating new technologies, for example products awarded in recenteditions of CES or in other international technology innovation contexts agreed with the instructor: up to 1 point for each presentation.Even if the sum of the points obtained in individual activities exceeds 6 points, the maximum contribution of in-class activities to the final grade is 6 points. Product presentations must analyse not only the technical characteristics of the product, but also user base analysis, design choices, possible design errors, good solutions, usability, accessibility, understanding of user needs, user familiarity with the technology, technical limitations, risks of overestimating technological capabilities, and possible psychological, social, ethical or practical impact. The final exam consists of one of the following two options, to be agreed with the instructor: Option A: UX project presentation, possibly as group work, up to 27 points. The project may involve the design, prototyping, revision or evaluation of an interactive solution, an emerging technology or a product integrating new technologies. Option B: presentation of two scientific papers, approximately 15 minutes each, and an individual oral interview on the course material, including slides, technologies, invited talks and presentations discussed during the course, up to 23 points. Students must agree on the project topic, technology, product or paper with the instructor and send the presentation at least one week before the exam date. Project work and technology/product presentations may be organised in groups of at most three students. In group work, each member’s individual contribution must be specified. The final mandatory assessment component maintains an individual component. Assessment will consider: accuracy and completeness of theoretical knowledge; ability to connect psychological principles, HCI/UX methods and technological features; ability to apply design, prototyping and evaluation methods; ability to critically analyse technologies, products, scientific papers and application cases; ability to recognise design errors, good design practices, technological limitations and possible impacts on users; clarity of exposition; appropriate use of disciplinary terminology; autonomy in deepening topics; quality of collaboration and clarity in distinguishing individual contributions. Students who do not take part in in-class activities can still take the final exam; in that case, the topics and competences normally developed through those activities may be discussed during the oral interview.

eaching materials will be made available on the course e-learning platform and, when appropriate, through the University Digital Library. Materials may include lecture slides, scientific papers, book chapters, invited-talk materials, examples of presentations and project work, tutorials and documentation on Figma, Unity3D, C#, computational thinking and prototyping tools.Recommended textbook:Rogers, Y., Sharp, H., & Preece, J. Interaction Design: Beyond Human-Computer Interaction. Wiley.Suggested reading:Hodent, C. The Gamer’s Brain: How Neuroscience and UX Can Impact Video Game Design. CRC Press.Additional materials and readings, including resources on virtual reality, conversational UX, Human-Robot Interaction, artificial intelligence and evaluation of innovative products, will be indicated on the course e-learning page.

Knowledge and understanding Defining intervention in psychology Designing interventions and identifying their implications (e.g., ethics, risks, golden standards, sampling) Assess the quality of interventions (quantitative and qualitative methods) Analyzing costs and benefits of interventions Applying knowledge and understanding Development of an intervention project Critical evaluation of interventions (theoretical and methodological implications) Making judgment Critical and judgment skills will be stimulated through the development of a group project. Students will develop the ability to design an intervention project, selecting appropriate tools to carry out the project and evaluate its effectiveness according to recent literature. Communication Skills Through group work, students will learn to present research ideas and collaborate effectively in English within teams. Students will also practice communicating research findings clearly to both expert and non-expert audiences, using appropriate disciplinary language, when writing the project and during the final presentation of the group work. Learning Skills Students will learn how to search and critically review scientific literature to support the development of new research and intervention ideas. Students will develop the ability to stay updated on new tools and methods to support their intervention projects

Defining intervention in psychology Gold standards of interventions Assessing interventions’ efficacy: Quantitative and qualitative methods Nudge and Decisional Psychology Sampling: sampling strategies, sample size and effect size determination Power analysis Risk Analysis From pilot to large scale: defining costs and benefits of the interventions Elements and pitfalls of costs/benefits analysis

The course will be assessed on a pass/fail basis only. There is no final exam; evaluation will be based on active participation and any assignments or activities carried out during the course.Learning will be assessed through project work. Students will complete the project work in small groups (3-5 people per group), each one developing a psychological intervention project on a specific topic of their choice.The projects will be discussed in the final lesson of the laboratory.

The bibliography (references, lecture slides, and additional material) will be provided at the beginning of the course and made available on the course website.

The course is divided in two modules• Module 1 (4 CFU, 28 hours): Methods and Models for Assessing Intra- and Inter-Individual Differences• Module 2 (4 CFU, 28 hours): Individual Differences in Clinical Domains Details of the learning objectives for each module are reported in their respective pages

See details for each module in their respective pages

The exam is single and includes questions concerning contents of both modules. It is a written exam with multiple-choice questions and open-ended questions, with optional oral exam conditional on passing the written test. Multiple-choice questions will assess the acquisition of knowledge and understanding of the fundamental concepts and contents of the course (evaluation criteria: correctness of answers). The open-ended questions and the optional oral exam will additionally focus on applied knowledge, critical thinking and reasoning skills, basic methodological competencies, and the ability to orally communicate the acquired knowledge (evaluation criteria: clarity of expression; use of appropriate subject-specific language; ability to make connections; basic capacity in research design). There are no mid-term exams.

Detailed information regarding the teaching materials will be published on the e-learning page associated with the course

Knowledge and understanding. Knowing the cognitive, neurobiological and functional bases of social and affective mental processes.. Understanding the genesis and dynamics of alterations and disorders of cognitive, communicative, emotional-motivational and social activity Applying knowledge and understanding• Acquisition of the ability to apply the acquired knowledge in order to design and carry out empirical studies in the field of social and affective neuroscience.• Acquisition of the ability to apply the acquired knowledge in order to personally design and carry out clinical interventions focused on specific patients with socio-affective disorders. Making judgementsStudents will develop the ability to critically evaluate scientific literature and experimental methodologies in social and affective neuroscience, with attention to ethical issues, methodological rigor, and the interpretation of neural data related to human behavior and emotion. Communication skillsParticipants will improve their academic communication skills through the presentation and discussion of scientific findings in both written and oral forms, using appropriate technical terminology in English. They will also be encouraged to communicate complex neuroscientific concepts to non-specialist audiences. Learning skillsThe course will enhance students' ability to engage in autonomous learning through the critical reading of scientific articles, the use of online databases, and active participation in class discussions. These skills will prepare them for further study or research in cognitive, affective, or clinical neuroscience.

Please see the info saved for each of the 2 modules.

The exam will be only written.The written exam consists in short essays (exposition of topics covered in class and described in study material/book chapters)

Please see the info saved for each of the 2 modules.

Knowledge and Understanding At the end of the course, students will acquire knowledge of the main phases of scientific research design and management, including literature review, funding opportunities, proposal writing, ethical aspects of research, dissemination strategies, and peer-review processes. Students will understand the principles underlying the development, evaluation, and communication of research projects in psychological sciences. Applying Knowledge and Understanding At the end of the course, students will be able to identify research gaps, formulate research questions and objectives, develop a research proposal, select appropriate methodological approaches, evaluate funding opportunities, and prepare effective strategies for disseminating scientific results through conferences and scientific publications. Making Judgement At the end of the course, students will be able to critically evaluate scientific literature, assess the quality and impact of scientific publications, identify strengths and weaknesses of research projects, and formulate independent judgments regarding methodological choices, ethical implications, and the scientific relevance of research proposals. Communication Skills Students will acquire communication skills that allow effective interaction with professionals from different cultural and scientific backgrounds. Through oral presentations, poster presentations, peer-review activities and group discussions, students will learn how to present research projects and communicate scientific findings clearly and effectively to both specialist and non-specialist audiences, using appropriate scientific terminology. Learning Skills Students will develop the ability to independently search, evaluate and use scientific literature and bibliographic resources. They will acquire skills necessary for the autonomous development of research projects, continuous updating of scientific knowledge, and critical reflection on research practices throughout their professional and academic careers.

Writing an effective research proposal Identify a research issue and the gap in the literature How to fund your research: identifying the “producer” of the project Outline the state-of-the-art of the theoretical and methodological framework Identify objectives and deliverables Defining the method to achieve the research objectives Ethical Implications Research impact, risk analysis and contingency plans Time management and project planning Disseminating and Communicating research results The research products in a conference: talks and posters The journal article: preparing the manuscript (sections and formats) The journal article: the submission process (APA style and the guidelines for the authors) LLM applications in scientific research and communications Peer review Science communication and public engagement

The last class will host the simulation of a conference: students will be asked to prepare their own contribution for the simulated conference, on the basis of the work carried out during the course. By doing so they will demonstrate the ability to identify relevant information for the development of a research project, critically evaluate scientific literature, prepare a research proposal, and communicate research ideas and results through oral and/or poster presentations. The course is assessed on a pass/fail basis and no numerical grade is assigned. Successful completion of the course requires: attendance of at least 70% of the scheduled teaching activities;timely submission of the assignments, as requested during the course;active participation in the practical exercises, discussions, peer-review activities and conference simulation activities carried out during the course;positive evaluation of the activities and materials developed during the course;attendance and participation in the final conference simulation session. The assessment reflects the achievement of the learning outcomes described in the syllabus, with particular reference to critical evaluation of scientific literature, development of research proposals, scientific communication skills, and collaborative work within a research environment.

Detailed information about the teaching material will be published on the e-learning page associated with the course.