Reviewing an Amplifire Course

There is a lot to consider when you're reviewing a course in Amplifire. Here are some of the elements you should check:

• Question types
• Accuracy and relevance
• Incorrect answer plausibility
• Design considerations
• Reporting analytics

Consider Question Types

Amplifire allows for the creation of three different question types:​

• Multiple choice: The most effective question type when promoting long-term memory and higher-order thinking​
• Matching: Useful when teaching about “pairs” of information, terms and definitions, etc.
• Multiple correct: Appropriate to use when there is more than one correct way to do something​

Review Content for Accuracy and Relevance

Please consider:

• Is the information important to learners and in line with the topics and learning objectives in the course?
• Are the correct answers correct and the incorrect answers incorrect?
• Do the explanations include all necessary information to explain why the correct answers are correct and the incorrect answers are incorrect?

Consider Plausibility of Distractors

Amplifire modules seek to correct Confidently Held Misinformation (CHM) through questions. Correcting CHM relies upon distractors by providing answers learners may plausibly choose as wrong answers. That way, when learners are confronted with the reality that what they thought they knew was wrong, they are more motivated to learn the correct answers.

As you review, consider the common mistakes learners make in the settings being discussed and recommend those as distractors.

Review Amplifire Design Considerations

Priming, Not Testing​

Amplifire content is designed to teach while assessing. That way, learners who knew the correct answers are not burdened by additional and unnecessary information, and learners who did not know it are able to gain it.​

Trick questions are not useful and can frustrate learners. You can spot them by looking for works such as "except," "not," and "most," or "least." We don't trick learners into wrong answers. Instead, we use tricky questions​ that challenge learners' knowledge and push them just enough to keep them learning.

Less is Ideal

​Question counts​ are far less important than question content. If there are questions in a module that are unnecessary, it's best to remove them.

Use clear, concise language​ to communicate. The fewer the words, the more likely learners will read them all.

Other Design Considerations

• Questions are shuffled by the Amplifire algorithm​, so learners will not see them in the order in which they were written.

• Don’t be afraid of controversial/confusing topics​. These can challenge learners and keep them interested.
• Address “soft” topics (humans interacting with humans)​.

Topics and Reporting​

Topics entered into Authoring also appear in the Amplifire Reporting dashboard, so be sure to aim for a collection of three or more questions per topic and consider how you'd like to analyze the content in the course. This ensures meaningful conclusions can be drawn from learner performance on each topic and provide powerful knowledge regarding your learners and their needs.