Hochschule München

HM Business School (FK 10)

Modulbeschreibung

Stand: WiSe 2024

Name International XY
Katalog-Nummer FK 10#SPK#4.2.26
Zugehörigkeit zu Curriculum
Bachelor Betriebswirtschaft | 4.2 | 5 Leistungspunkte
Modulverantwortung
Bohnert, Alexander (Prof. Dr.)
Morandi-Grassinger, Nicole
Greiner, Christian (Prof. Dr.)
Lehrende
Kaplan, Lewis
Prüfung(en)
Prüfungsform: ModA
Detailangaben:
Hildsmittel:
Prüfende: Kaplan, Lewis , Greiner, Christian (Prof. Dr.)
Lehr- und Lernform(en)
Lehrveranstaltung | 4 SWS | S - 1 Angebot(e)
Arbeitsaufwand
Präsenzzeit: 0 Stunden
Selbststudium, Vor- und Nachbereitung, Prüfungsvorbereitung: 0 Stunden
Voraussetzungen
Verwendbarkeit
Inhalt / Lernziele

Learning Objective

Business activities take place in a global economy where diverse cultures and economic systems continuously meet and collide. To manage these transactions effectively, develop sustainable cross-cultural relationships and promote a sustainable global economy it is important to learn how to make effective decisions within organisational systems. This course introduces the student to essential decision-making strategies and skills. Students also learn how to apply AI decision support systems such as ChatGPT. The course applies evidence-based teaching methodology and active learning strategies to engage students in the learning process. It culminates in a final group project of “AI in Group Decision Making” involving the application of strategies and skills learned during the module.

 

Content:

  • Understand and apply strategies and skills of group decision making,
  • Understand the foundations of AI Systems,
  • Define the steps of Human-AI Interactions, including strengths, weaknesses and pitfalls
  • Analyse and evaluate the Human-AI collaboration within negotiation and decision making processes

 

Expected Assessment

  1. Active participation is class and team discussions
  2. Evaluation of project work and case analyses through class presentation and discussion
  3. Final presentation and reflection of a group project

 

Literature/Reading Assignments:

 

  • Russell, S.J. and Norvig, P. eds., 1995. Prentice Hall series in artificial intelligence. Englewood Cliffs, NJ:: Prentice Hall.
  • Reinhart, J., & Greiner, C. (2019). Künstliche Intelligenz–eine Einführung. Grundlagen, Anwendungsbeispiele und Umsetzungsstrategien für Unternehmen.
  • Cases and other readings used for class discussion and analysis will be made available online 

English Version

Name International XY
Katalog-Nummer FK 10#SPK#4.2.26
Zugehörigkeit zu Curriculum
Bachelor Betriebswirtschaft | 4.2 | 5 Leistungspunkte
Modulverantwortung
Bohnert, Alexander (Prof. Dr.)
Morandi-Grassinger, Nicole
Greiner, Christian (Prof. Dr.)
Lehrende
Kaplan, Lewis
Prüfung(en)
Prüfungsform: ModA
Detailangaben:
Hildsmittel:
Prüfende: Kaplan, Lewis , Greiner, Christian (Prof. Dr.)
Lehr- und Lernform(en)
Lehrveranstaltung | 4 SWS | S - 1 Angebot(e)
Arbeitsaufwand
Präsenzzeit: 0 Stunden
Selbststudium, Vor- und Nachbereitung, Prüfungsvorbereitung: 0 Stunden
Voraussetzungen
Verwendbarkeit
Inhalt / Lernziele

Learning Objective

Business activities take place in a global economy where diverse cultures and economic systems continuously meet and collide. To manage these transactions effectively, develop sustainable cross-cultural relationships and promote a sustainable global economy it is important to learn how to make effective decisions within organisational systems. This course introduces the student to essential decision-making strategies and skills. Students also learn how to apply AI decision support systems such as ChatGPT. The course applies evidence-based teaching methodology and active learning strategies to engage students in the learning process. It culminates in a final group project of “AI in Group Decision Making” involving the application of strategies and skills learned during the module.

 

Content:

  • Understand and apply strategies and skills of group decision making,
  • Understand the foundations of AI Systems,
  • Define the steps of Human-AI Interactions, including strengths, weaknesses and pitfalls
  • Analyse and evaluate the Human-AI collaboration within negotiation and decision making processes

 

Expected Assessment

  1. Active participation is class and team discussions
  2. Evaluation of project work and case analyses through class presentation and discussion
  3. Final presentation and reflection of a group project

 

Literature/Reading Assignments:

 

  • Russell, S.J. and Norvig, P. eds., 1995. Prentice Hall series in artificial intelligence. Englewood Cliffs, NJ:: Prentice Hall.
  • Reinhart, J., & Greiner, C. (2019). Künstliche Intelligenz–eine Einführung. Grundlagen, Anwendungsbeispiele und Umsetzungsstrategien für Unternehmen.
  • Cases and other readings used for class discussion and analysis will be made available online