Topic outline

  • General



    The lecture will take place on campus!
    No Lecture on the 14th of May. 
    The exam will be held on the 6th of June. 


    This course will provide an overview of cognitive psychology with applied excursions to hot topics in engineering psychology. Through lectures and in-class experiments, students will learn about the psychology of learning, memory, problem-solving, reasoning and decision-making The course will also include specialty lectures to deepen knowledge in some focus areas of cognitive psychology. 


    Lecturer


    Assistant Prof. Dr. Robin Welsch/ Department of Computer Science/ Aalto University

    Teaching Assistant


    Alli Kolho alli.kolho@aalto.fi

    Book

    Anderson, J. R. (2020). Cognitive psychology and its implications. Macmillan 

    Lecture 1: 1-12; 12 pages

    Lecture 2-5: 285-288; 184-204;207-228;230-244;135-160; 84 pages

    Lecture 6-8;245-282; 17 pages

    Lecture 9-10: 345-374; 29 pages

    Reading tips:
    • Brain regions will not be relevant for the exam
    • Start reading on day 1; It's about 12 pages per week
    • Take a short break every 30 minutes
    • Make it an active process; -->take notes while reading

    The book can be found in the learning center.


    Format

    The course has mandatory components and components that will support your self-study. 


    Mandatory components are: 

    • Attendance of the lecture with active participation
    • Reading of the textbook

    Self-study components are:
    • Completing self-assessments to test your learning
    • Building a glossary of terms
    • Quizzes


    Grading

    Grading is based on a final exam  (open questions and multiple choice). The scale is from 1-5. 


    Lecture

    Lecture slides will be uploaded before each lecture. The lecture will cover the following topics: 

    1. Introduction to Cognition 

    This lecture provides an overview of the field of cognitive psychology. We will examine the history of cognitive psychology, from ancient philosophical inquiries to the latest advancements in artificial intelligence. A cognitive revolution in the field will also be highlighted, as well as behaviorism. 

    2. Learning

    This lecture focuses on the basic questions of learning and provides definitions of important terms related to learning. An overview of different types of learning will be presented, including classical and instrumental conditioning. Models for acquiring skills for technology use will also be discussed. This lecture will equip students with a comprehensive understanding of the fundamental concepts and theories of learning.

    3. Memory I

    This lecture provides an overview of the basic questions and concepts of memory. Students will become familiar with the various models of memory psychology, including the concepts of sensory memory

    4. Memory II
    In this lecture, we will look at working memory. The lecture will also cover the topic of memory span and its correlations, as well as the processes of forgetting at different levels of memory.. By the end of this lecture, students will have a comprehensive understanding of the fundamental concepts and theories of working memory.

    5. Memory III

    This lecture focuses on the models of long-term memory and the consolidation processes involved in its formation. Topics such levels of  processing, the schema concept, and the structures of long-term memory will be covered; including episodic memory, autobiographical memory, and semantic memory. We will apply this to memories from digital media. From this lecture, students will take away a comprehensive understanding of the fundamental concepts and theories related to long-term memory.

    6. Problem-Solving I

    This lecture provides an overview of the basic problem-solving concepts, including barrier categories and problem typologies. Students will become familiar with the phenomenology of problem-solving. The learning outcome will be a foundational knowledge of the concepts and theories of problem-solving.

    7. Problem Solving II

    This lecture builds upon the concepts introduced in the first problem-solving lecture, delving deeper into the findings about analogies and problem-solving. Problem space theory will be covered and we will discuss insight while solving problems. The lecture will also cover the General Problem Solver and its application to real-world problems. Additionally, students will be introduced to an integrative model of problem-solving and will have the opportunity to apply this model to well-defined problems. By the end of this lecture, students will have a comprehensive understanding of advanced concepts and theories related to problem-solving.

    8.  Complex Problem Solving III + Expertise

    This lecture focuses on the concepts of expertise and complex problem-solving. Students will become familiar with Dörner's classification of complex problems and will be able to evaluate problems accordingly. Findings and paradigms for problem-solving research using simulation will also be covered, along with the effect of expertise on information processing. By the end of this lecture, students will have a comprehensive understanding on expertise and complex problem-solving in cognition.

    9 + 10 Reasoning & Decision Making 

    These lectures focus on the basic concepts of decision-making and reasoning. In the decision-making lecture, students will become familiar with the Monty-Hall problem and use the Bayes theorem to solve it. The lecture will also cover prescriptive and descriptive utility theories and decision heuristics. Additionally, students will be introduced to multi-attribute decision models and apply them to the case of online shopping with recommender systems. By the end of this lecture, students have a comprehensive understanding of the fundamental concepts and theories related to decision-making.