Expert systems

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Expert systems by Mind Map: Expert systems

1. What are they?

1.1. Components

1.1.1. Huge database of collective intelligence of one or more experts

1.1.2. Artificial Intelligence (AI) system with faster-than-human response time and better-than-human patience

1.2. Responses

1.2.1. Proactive: Anticipates learners' needs

1.2.2. Reactive: Responds to learner's inputs

1.3. Purposes

1.3.1. Individualised instruction

1.3.2. Performance support

2. Examples

2.1. BMW AR

2.2. Learning analytics

2.3. To some extent, Computer Adaptive Testing (CAT)

2.4. Vehicular intervention systems

2.4.1. Auto parallel parking

2.4.2. Accident avoidance

2.4.3. Adaptive cruise control

2.5. Simulators with anticipatory/reactive response systems

3. Social expert systems

3.1. Includes both experts and learners as sources of knowledge and as teachers

3.2. Examples (see course wiki)

3.2.1. YouTube examples

3.2.2. Decision tree videos

3.2.2.1. Scenarios and decision-making

3.2.2.2. Multimedia quizzes

3.2.2.2.1. Example 1

3.2.2.2.2. Example 2

3.3. Lower cost, maintenance, and development time

3.4. More accessible

3.4.1. More open platforms

3.4.2. Human more apparent (e.g., comments, feedback, video responses)

3.4.3. User-generated content

4. High cost

5. Long development time

6. High maintenance