Cognitive Psychology

Code:

MCI0013

Acronym:

PCOG

Keywords
Classification	Keyword
OFICIAL	Social Science

Instance: 2024/2025 - 1S

Active?	Yes
Web Page:	https://sigarra.up.pt/feup/en/UCURR_GERAL.FICHA_UC_VIEW?pv_ocorrencia_id=540007
Responsible unit:	Department of Informatics Engineering
Course/CS Responsible:	Master in Information Science

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MCI	16	Plano de estudos oficial	1	-	6	42	162

Teaching language

English

Objectives

This curricular unit has the following objectives:

1.To know the fundamentals of Cognitive Psychology;
2.Analyze the applications of this knowledge in the development of information behavior and User Experience;
3. Relate Cognitive Psychology and/it application in Artificial Intelligence development.

 

 

Learning outcomes and competences

On completion of the course, students should be able to::

1. To know the fundamentals of Cognitive Psychology.
2. Apply the knowledge acquired in production processes, organization and studies within the scope of information behavior;
3. To have the ability of using and developing scientific approaches.
4. To have organization and presentation skills when developing individual or team work.
5.To develop critical skills toward new knowledge.
6. To solve problems - to apply research results to new problems in their professional area and to heve the ability to organize and plan research work.

Working method

Presencial

Program

The program consists of the following topics:

1. Cognitive Psychology and its relationship with Information Science.

2.Cognitive processes and their relationship with production, organization and information behavior:
a.Perception and attention
b.Memory
d.Knowledge and comprehension
e.Language
f.Problem solving and creativity
g.Logical reasoning and decision making
h.Individual differences in cognition

3.Cognition in emotion and informational decision making.

4.AI and Cognitive Psychology: The Intersection

Mandatory literature

da Silva, A.M., Ribeiro, F., Martins, F. ; Information Science and Cognitive Psychology: A Theoretical Approach , Springer, Berlin, Heidelberg, 2010. ISBN: 978-3-642-16032-5
Ellis, H. C. & Hunt, R. R. ; Fundamentals of cognitive Psychology, WCB Brown & Benchmark Publishers, 1993
Williams G. , Lim S.; Psychology of AI: How AI impacts the way people feel, think, and behave, 2024. ISBN: https://doi.org/10.1016/j.copsyc.2024.101835
Matlin, M. W. ; Cognition, Harcourt Brace Publishers, 1994
Martins. F.; Influência das emoções no desempenho cognitivo: ira e processamento de informação, Universidade do Minho, 1999
Murray Brian; Cognitive Computing: Revolutionizing Problem-Solving and Decision-Making through Artificial Intelligence. ISBN: 979-8393092801
Sternberg, R. J.; Estilos de pensamento: a importância do seu conhecimento na escolha de estratégias de aprendizagem, Editora Replicação, Lda., 2002

Complementary Bibliography

Pandey D.; Neural networks in computer engineering: insights from cognitive psychology, 2024. ISBN: 3025-5821
Jordan Richard Schoenherr ; Ethical Artificial Intelligence from Popular to Cognitive Science: Trust in the Age of Entanglement, 2022. ISBN: 036769798X

Teaching methods and learning activities

Dynamic class, between the Professor's exposure and student participation. Participation develops through small assignments, with presentation and discussion in class.
Collaborative construction of information, resulting in the incorporation of this work into the class slides made available later in Moodle.

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Trabalho escrito	75,00
Participação presencial	25,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	20,00
Trabalho escrito	100,00
Frequência das aulas	42,00
Total:	162,00

Eligibility for exams

Attendance is obtained by fulfilling C1 and C2, referred to in the Final Grade Calculation Formula field.

Calculation formula of final grade

Final Grade = 75% C1 + 25% C2


C1: 3 mini-tests (25% each), minimum 8.00 points
C2: class participation

Final Grade (TE) = 75% C1 + 25% C2

C1: 3 mini-tests (25% each), minimum 8.00 points
C2: completion and presentation of an individual assignment

Special assessment (TE, DA, ...)

Working students are not exempt from fulfilling all the assessment components.

Classification improvement

The result obtained in C1 could be improved during the appeal period.
The C2 result will not be reassessed.
The UC allows improvement by frequency.