LearningLemur supports two main question types: Open Answer and Multiple Choice.

Each question type is designed for different teaching scenarios and evaluation strategies. Understanding their differences helps teachers choose the most appropriate format for their exercises and assessments.

What It Is

In LearningLemur, a question type defines how students interact with a question and how their responses are evaluated. The platform currently provides two primary question types:

Open Answer questions

Students enter their own mathematical expression or numerical value. The system evaluates the answer using a mathematical interpretation engine.

Multiple Choice questions

Students select one answer from a list of predefined options created by the teacher. Each type is suited to different educational objectives, depending on whether students must produce their own solution or choose among possible answers.

Why It Matters

Selecting the appropriate question type affects how students engage with the exercise and how the system evaluates their responses.

• Open answer questions allow teachers to assess students' ability to produce mathematical results independently, accepting equivalent expressions when provided
• Multiple choice questions allow teachers to quickly evaluate conceptual understanding by using predefined answer options and automated grading.

By choosing the appropriate question type, teachers can design exercises that better match their learning objectives.

How It Works

When creating a new question in LearningLemur, teachers select the desired question type in the question editor. Once selected, the interface adapts to provide the configuration options specific to that question type.

For Open Answer questions, teachers define:

• The expected mathematical answers
• The evaluation criteria
• Answer normalization rules
• Optional advanced logic and random variables

For Multiple Choice questions, teachers define:

• The list of answer options
• Which answers are correct or partially correct
• The score weight associated with each answer
• Optional feedback for each answer

Although their configurations differ, both question types share the same core structure in the quiz editor, including question content, feedback, and advanced configuration settings.

Comparison

Key Rules or Behaviours

• Open Answer questions evaluate mathematical expressions entered by the student
• Multiple Choice questions evaluate selected answer options
• Both question types support custom feedback and grading configuration
• Both question types can use random variables to generate dynamic question values
• The selected question type determines which configuration panels appear in the question editor

Examples

Example 1: Open Answer question

A teacher asks students to compute:​

Students must enter the result as a mathematical expression. The system evaluates the answer mathematically and can accept equivalent representations depending on the configuration.

Example 2: Multiple Choice question

A teacher asks: Which fraction is equivalent to 1/2?

Students select one answer from the provided options.

Common Misunderstandings

Misconception: Multiple choice questions are easier to configure than open answer questions

Clarification: Both question types require careful configuration depending on the learning objective.

Misconception: Open answer questions only accept one specific format of the answer

Clarification: LearningLemur can recognize mathematically equivalent expressions depending on the evaluation configuration.

Related Concepts

• Understanding the LearningLemur Workspace
• Understanding the Open Answer Question Interface
• Understanding the Multiple Choice Question Interface