LIST OF FIGURES AND TABLES
Figure 1.1. | A Virtual Automotive Shop |
Figure 1.2. | Learner Actions (on Right) Compared with Expert Actions (on Left) |
Figure 1.3. | The Learner Can Access Virtual Advisors for Wedding Planning |
Table 1.1. | Scenario-Based e-Learning vs. Directive Training Environments |
Figure 1.4. | A Scenario-Based e-Learning Simulation of Treatment of a Dog for Blood Loss |
Figure 1.5. | A Branched Scenario Can Be Based on Links in Presentation Software |
Table 2.1. | Common Knowledge and Skills Required in Workplace Tasks Involving Critical Thinking |
Figure 2.1. | Unnecessary Causalities Result from Poor Leadership Decisions |
Table 2.2. | Eight Scenario Learning Domains in Workforce Training |
Table 2.3. | Scenario-Based e-Learning Interface-Navigation Options |
Figure 2.2. | There Is Time Only to Select a Single Action |
Figure 2.3. | A Menu-Driven Interface for Bank Loan Analysis |
Figure 2.4. | A Virtual World Sales Training Environment |
Figure 3.1. | A Design Model for Scenario-Based e-Learning Lessons |
Table 3.1. | Typical Learning Objectives by Domain |
Figure 3.2. | An Introductory Screen in a Bank Analysis Scenario-Based e-Learning Lists Anticipated Outcomes |
Figure 3.3. | Persistent Failure Symptoms Provide Intrinsic Feedback to Selection of an Incorrect Failure Cause |
Figure 3.4. | Questions (Upper Left) Promoting Review and Reflection on Interview Techniques in Lessons Learned Box (Lower Right) |
Figure 4.1. | Factors Influencing the Complexity of Multimedia Design |
Figure 4.2. | Multiple-Choice Response Options on Left Panel and Pull-Down Type in Response Fields on the Right Worksheet |
Figure 4.3. | In Bioworld the Learner Prioritizes Data Using Drag-and-Drop Interactions |
Figure 4.4. | Learners Indicate Confidence in Their Hypotheses with the Belief Meter Slider Bar (Upper Left Corner) |
Table 4.1. | Some Typical Objectives and Associated Response Options for Learning Domains |
Table 4.2. | Common Multimedia Response Options |
Table 5.1. | Some Settings and Trigger Events for Scenario-Based e-Learning Domains |
Figure 5.1. | The Upper Tabs and Left Menu Links Link to Scenario Data |
Figure 5.2. | To Interview Client Managers, the Learner Must Select Relevant Questions in a Limited Time Frame |
Table 5.2. | Examples of Case Data for Scenario-Based e-Learning Domains |
Figure 5.3. | Client Data Is Saved in the Worksheet on the Right, Including the Lower-Left Notes Field |
Figure 6.1. | A Customer Service Scenario-Based e-Lesson |
Figure 6.2. | An Automotive Troubleshooting Scenario-Based e-Lesson |
Table 6.1. | Techniques for Guidance in Scenario-Based e-Learning |
Figure 6.3. | Fade Support and Increase Complexity as Scenarios Progress |
Figure 6.4. | Following a Video Example of Responding to Objections, Questions Are Used to Promote Engagement with the Example |
Figure 6.5. | A Multiple-Choice Response Screen in Automotive Troubleshooting Lessons with Many Solution Options |
Figure 6.6. | The Album and Advisor Tabs (Upper Right) Link to Guidance in the Bridezilla Lesson |
Table 6.2. | Potential Advisors for Each Learning Domain |
Figure 6.7. | Selecting a Specific Advisor (See Figure 6.6) Leads to Topic-Specific Information |
Table 7.1. | Some Sample Terminal and Enabling Learning Objectives by Domain |
Figure 7.1. | Clicking on the Tutorial Button (Lower Right) Leads to a Short Demonstration on Completing the Form |
Figure 7.2. | The Computer in the Virtual Auto Shop Links to Technical References |
Figure 7.3. | A Wall Chart Provides a Reference for a Laboratory Procedure |
Figure 7.4. | A Cognitive Modeling Example Illustrates Not Only the How But Also the Why |
Table 8.1. | A Summary of Feedback Features |
Figure 8.1. | A Summary of the Learner’s Actions (on the Right) Is Displayed Next to an Expert Solution Process (on Left) |
Figure 8.2. | Response Windows (on the Right Side of the Screen) Encourage Learners to Reflect on Feedback |
Table 8.2. | Some Feedback Options by Scenario Domain |
Figure 8.3. | A Feedback Checklist for a Needs Assessment Interview Role Play |
Figure 8.4. | Instructional Feedback for the Automotive Repair Scenario |
Figure 9.1. | A Screen from Beyond the Front, Suicide Prevention Scenario-Based e-Learning |
Table 9.1. | Some Typical Evaluation Questions for Scenario-Based e-Learning Courses |
Table 9.2. | Sample Test Items to Measure Scenario-Based e-Learning Outcomes |
Figure 9.2. | A Sample Test Item with Rater Guidance |
Figure 9.3. | A Distribution of Competent and Non-Master Performer Scores on a Test |
Figure 10.1. | Learning from Directive Versus Scenario-Based Versions of an Excel Class |
Figure 10.2. | Learning from Direct Instruction First Versus Productive Failure First |
Figure 10.3. | Collaboration Improves Learning from More Difficult Problems |
Figure 10.4. | The Bioworld Interface Uses a Pull-Down Menu to Offer Hypotheses Options |
Figure 10.5. | The Coach Orients the Learner to the Bridezilla Scenario |
Figure 10.6. | Acceleration of Expertise Using Sherlock Troubleshooting Simulation Trainer |
Table 11.1. | Three Approaches to Knowledge Elicitation |
Figure 11.1. | Typical Directions for Concurrent Verbalization |
Figure 11.2. | Typical Directions to Initiate the Critical Decision Method |
Figure 11.3. | Sample Directions for Identifying Past Scenarios |
Figure 11.4. | Amount of Knowledge Elicited by Three Methods |
Table 11.2. | Six Types of Knowledge to Elicit |
Figure 11.5. | A Comparison of Problem-Solving Patterns Between Novices and Expert Mathematicians |
Table 11.3. | Sample Questions to Elicit Knowledge Types |
Table 11.4. | How to Use Knowledge Types in Scenario-Based e-Learning |
Figure 11.6. | Learners Compare Their Prioritized Evidence (Right) with Expert Priorities (Left) |
Table 12.1. | Time to Reach Automotive Troubleshooting Competency in Three Learning Environments |
Table 12.2. | Steps to Compare Training Delivery Alternatives |
Table 12.3. | Hours and Cost Comparisons for One Troubleshooting Scenario for Menu, Branched, and Whole-Screen Designs |
Figure 12.1. | A Sample Template for Whole-Screen Automotive Troubleshooting |
Figure 12.2. | A Sample Template for Menu Design of Automotive Troubleshooting |
Figure 12.3. | A Sample Template for Branched Scenario Design of Automotive Troubleshooting |
Figure 12.4. | Part of the Introduction to the Bridezilla Course |
Figure A.1. | A Virtual Automotive Shop |
Figure A.2. | The Learner Can Access Virtual Advisors for Wedding Planning |
Figure A.3. | A Branched Scenario Can Be Based on Links in Presentation Software |
Figure A.4. | The Learner Has the Opportunity to Make Better Decisions to Avoid This Failed Situation |
Figure A.5. | To Interview Client Managers, the Learner Must Select from a List of Questions in a Limited Time Frame |
Figure A.6. | Learners Indicate Confidence in Their Hypotheses with the Belief Meter Slider Bar (Upper Left Corner) |
Figure A.7. | Following a Video Example of Responding to Objections, Questions Are Used to Promote Engagement with the Example |
Figure C.1. | A Valid Test Links Test Questions to Job Knowledge and Skills via Learning Objectives |
Figure C.2. | A Sample Multiple-Choice Item to Measure Facts or Concepts |
Figure C.3. | A Knowledge Question for the Bridezilla Course |
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