Incorporating The Know-How Into The Decision Process

Credits
1.5
Types
Elective
Requirements
This subject has not requirements , but it has got previous capacities
Department
EIO
Web
https://www-eio.upc.edu/~karina/datamining/IKPD/
Mail
karina.gibert@upc.edu
The course provides tools to take as much advantage as possible of the data registered in information systems of any organization, with regards to decision making processes. The course works over central elements in decision-making-oriented information explotation; elements with high impact, too often dismissed. Mainly, the impact of a priori knowledge on the data-driven analysis of the organization will be addressed, as well as the dangers associated with the impact of the implicit knowledge managed by the experts in decisional processes. The course is organized under a real case analysis approach

Teachers

Person in charge

Competences

Technical Competences of each Specialization

Direcció i gestió

  • CDG1 - Capability to integrate technologies, applications, services and systems of Informatics Engineering, in general and in broader and multicisciplinary contexts.

    • Especifics

  • CTE9 - Capability to apply mathematical, statistical and artificial intelligence methods to model, design and develop applications, services, intelligent systems and knowledge-based systems.

    • Generic Technical Competences

    Generic

  • CG8 - Capability to apply the acquired knowledge and to solve problems in new or unfamiliar environments inside broad and multidisciplinary contexts, being able to integrate this knowledge.

    • Transversal Competences

    Teamwork

  • CTR3 - Capacity of being able to work as a team member, either as a regular member or performing directive activities, in order to help the development of projects in a pragmatic manner and with sense of responsibility; capability to take into account the available resources.

    • Information literacy

  • CTR4 - Capability to manage the acquisition, structuring, analysis and visualization of data and information in the area of informatics engineering, and critically assess the results of this effort.

    • Reasoning

  • CTR6 - Capacity for critical, logical and mathematical reasoning. Capability to solve problems in their area of study. Capacity for abstraction: the capability to create and use models that reflect real situations. Capability to design and implement simple experiments, and analyze and interpret their results. Capacity for analysis, synthesis and evaluation.

    • Basic

  • CB6 - Ability to apply the acquired knowledge and capacity for solving problems in new or unknown environments within broader (or multidisciplinary) contexts related to their area of study.
  • CB7 - Ability to integrate knowledges and handle the complexity of making judgments based on information which, being incomplete or limited, includes considerations on social and ethical responsibilities linked to the application of their knowledge and judgments.
  • CB8 - Capability to communicate their conclusions, and the knowledge and rationale underpinning these, to both skilled and unskilled public in a clear and unambiguous way.

    • Objectives

    1. Identify decisional variables in a real problem
      Related competences: CTR4,
    2. Identify the relevant a priori knowledge for decision-making
      Related competences: CTR4, CTR6,
    3. Elicit the relevant implicit knowledge for the target problem
      Related competences: CTR3, CTR4, CB7, CB8,
    4. Design information extraction procedures from data, which take into account the elicited a priori knowledge
      Related competences: CDG1, CTR3, CTR4, CTR6, CB6, CG8,
    5. Apply the information extraction processes to a real case and present the final results
      Related competences: CTE9, CB6, CB8, CG8,

    Contents

    1. Introduction
    2. A priori knowledge
      Concept
      Representation formalisms
      How to introduce it in data analysis?
      Case: Analysis of mental health systems from the WHO
      Case: Identification of typical situations in wastewater treatment plants
    3. Implicit knowledge
      Concept
      Impact of implicit knowledge in Knowledge Discovery
      Tools to elicit implicit knowledge
      Case: Efects of elecktroconvulsive therapy over reaction times in schyzophrenia
      Case: Dependency Law in Catalunya

    Activities

    Activity Evaluation act


    Reading, comprehension, analysis of a text about decision-making. Fill-in a brief form


    Objectives: 1 2
    Contents:
    Theory
    0h
    Problems
    0h
    Laboratory
    0.5h
    Guided learning
    0h
    Autonomous learning
    3h

    Development of a case


    Objectives: 1 2 3 4 5
    Contents:
    Theory
    0h
    Problems
    0h
    Laboratory
    5h
    Guided learning
    0h
    Autonomous learning
    15h

    Final presentation of developed cases and common discussion of all the works developped


    Objectives: 5
    Theory
    0h
    Problems
    0h
    Laboratory
    1.5h
    Guided learning
    0h
    Autonomous learning
    3h

    Presentation, analysis and discussion of illustrative cases


    Objectives: 1 2 3 4
    Contents:
    Theory
    1.5h
    Problems
    0h
    Laboratory
    3.5h
    Guided learning
    0h
    Autonomous learning
    3h

    Introduction



    Theory
    0.5h
    Problems
    0h
    Laboratory
    1h
    Guided learning
    0h
    Autonomous learning
    0h

    Teaching methodology

    Very specific course, contentrated on time. Totally given in the laboratory room. Case-based learning approach, with small conceptual introductions. Small practical works to consolidate the obtained knowledge. During the first week the conceptual bases of the course will be presented and the activities to be developed by every student will be distributed.
    There is an exercise based on the reading of a text about decision-making, where the student must identify the use of the a priori knowledge made, the assumptions, and must analyze drawbacks and advantages of the decision process described on the paper.
    In a second exercice, in groups, a new application will be developed. The case can be proposed by both the students or the conductor of the course.
    Besides the acquisition of specific technical skills, some transversal competences will be also developed during the course, like knowledge integration, capacities of analysis, sinthesis, oral, visual and written comunication. The works will be presented to the whole group and a global discussion will perform as an oral evaluation.

    Evaluation methodology

    The final qualification is composed by 4 components:
    *) Q: questionaire about the reading of a text about decision-making
    *) P: practical work over a real case (includes public presentation)
    *) C: participation in classes

    The final score is obtained as:

    N= 0.3 Q + 0.6 P+ 0.10 C

    Bibliography

    Basic