Information Systems: Digital Transformation and AI

Information Systems in Theory and Practice

• Exercise 1 & 2 are part of a semester-long course on information systems
• The exercise focuses on digital transformation and information management
• Topics covered include game-based learning, gamification, information systems, AI, and automation

Aims of the Exercise

• Learning objectives: Examination of information systems & AI, introduction to game-based learning and gamification, understanding of ethical aspects, RPA, and "human-friendly automation", practical prototyping for a serious game
• Methodology: Interactive group work, project-based learning and play approaches, prototyping

Semester Structure

• 17.10.2024: Introduction to Game Based Learning/Gamification
• 31.10.2024: CANCELLED - play games instead!
• 14.11.2024: Information Systems and AI; Automation (RPA/HFA); Ethical introduction of AI technologies in organizations; Presentation of practical project scenario
• 28.11.2024: Stakeholder management & change processes; Character design
• 12.12.2024: Game Design Basics; Process Modeling
• 09.01.2025: Prototyping & Testing
• 23.01.2025: Presentation & conclusion

What is "Learning" through Games?

• A simplified diagram shows the connection between playing a game and improvement of learning outcomes
• A diagram illustrates the cognitive theory of multimedia learning, highlighting the stages of multimedia presentation, sensory memory, working memory, and long-term memory, including factors like verbal, visual, auditory, and pictorial methods

What is Game-Based Learning (GBL)?

• GBL uses games or game-like elements to educate
• A "serious game" prioritizes education over entertainment
• Key features: learning through play, active and independent learning, and using playful activities for reinforcement

Advantages of Game-Based Learning

• Increased motivation through playful elements
• Enhanced problem-solving skills through trial and error
• Direct interaction with learning material

What is Gamification?

• Using game-like elements in non-game settings to create engaging experiences
• Possible elements include: points and reward systems, rankings, and levels and challenges

Difference Between GBL and Gamification

• Game-Based Learning (GBL): All learning is based on a game or simulation
• Gamification: Game mechanics are integrated into non-game learning contexts (e.g., a points system for participation or performance in a course)

Why Game Elements in Learning?

• Promoting intrinsic motivation, "funification", "immersion", and "flow"
• Direct feedback through feedback mechanisms
• Learning through trial and error, like "dying" in a game

Relevance & Connection with Information Systems

• Digital transformation & RPA: Game-based learning helps present and learn automation and information systems.
• Gamification for IS implementation: Gamified systems support training and change processes.
• User experience & efficiency: Game mechanics promote user-friendliness and motivation in IS

Ideal Structure of Serious Games

• Clear objectives to focus player attention
• Achievement leads to a feeling of self-efficacy
• Noticeable progress motivates players
• Feedback on performance encourages players to strive for goals

Practical Part: Reflection & Group Task

• Reflect on how games could support learning in this exercise.
• In small groups, develop an idea of how an Information Systems topic can be transformed into a game.

Step-by-Step: Developing a Game Idea

• Define learning objectives
• Define the target group
• Select core mechanics
• Determine story and scenario

Examples of Simple Game Mechanisms

• Lists various game mechanisms, such as Memory, Battleship, Monopoly, Who Wants to be a Millionaire?, Jeopardy!, Scrabble, and Risk

Serious Games | Gamification - Examples to Try Out

• Provides links to different serious games and gamification examples (e.g., Lifesaver, Duolingo)

Tasks Until Next Time

• Play assigned games in Moodle
• Report on any known and good serious games or examples of gamification

Conclusion & Outlook

• Key concepts: game-based learning & gamification, benefits in practice, knowledge transfer
• Outlook: AI & AI ethics, basics of robotic process automation (RPA), human-friendly automation (HFA)

Contact Information

• Includes contact details for the course instructor

Information Systems - Basics

• Definition according to Laudon & Laudon: Interrelated components collecting, processing, storing, and distributing information for decision-making and control.
• Current Development trend: Pure data processing systems developing into intelligent, adaptive systems
• Importance for modern organizations: Flexible learning structures, regulatory guidelines

Automation

• Definition: Using technologies (machines or software) for tasks with minimal human intervention
• Development history: Industrialization, Early Electronics/automation, and Digital revolution, and modern automation

What is Robotic Process Automation (RPA)?

• Definition of RPA: A technology enabling the automation of rule-based, recurring business processes using software robots.
• Key features: Simulates human interactions (e.g., data processing, form filling), works through existing interfaces without in-depth integration, increases efficiency & reduces human error in repetitive tasks

Automation - Spectrum and Species

• RPA, IPA (Intelligent Process Automation-Al-enhanced automation), and their rule-based and Al-based distinctions, plus their relevant applications

What Does Automation Mean for Certain Jobs?

• Information and inspiration related to the impacts of automation on jobs

Relevance of Automation

• Discusses instances of automation impacting companies and workers, such as Amazon firing employees by algorithm

AI, Automation, and Fears

• Machines will deliver larger work parts, requiring humans to provide added value and create new value
• "Industry 4.0" means machines talking to computers

Change: Possible Fears & Coping Mechanisms

• Possible fears: existential fears and job security, competency-related fears, psychosocial stress, and organizational resistance
• Coping mechanisms: Transparent communication, participatory design, needs-based competence development, psychological support, and change management structure

Ethical Dimensions of Automation

• Key ethical principles: Beneficence (charity), Non-maleficence (avoidance of damage), and Autonomy (autonomy), Justice and Explicability

Ethical Dimensions of Automation

• Summary statements: No group of people should be systematically disadvantaged (in automated decision making), should be transparency and traceability of decisions, fairness and responsibility in the automated systems

Best Practices for Implementation

• Implementation process phases: Process analysis, Pilot project, and Roll-out
• Criteria for choosing implementation tools, such as team size and available resources
• Ongoing review and update processes are crucial

Current Challenges

• Technical challenges: Integration, Scaling, and Maintenance
• Organizational challenges: Structures, Processes, and Culture

Explore digital transformation and information management in this exercise. Covers game-based learning, AI, automation, and ethical considerations within information systems. This exercise uses interactive group work and project-based learning.