From Recall to Reflection: New Ways to Engage Learners with New Question Types and Conversational AI

Ulla-Maaria Koivula July 7, 2026

Great learning experiences don’t rely on a single type of interaction. Sometimes learners need to recall key facts. Sometimes they need to recognize patterns, apply concepts, explain their thinking, or reflect on what they’ve learned.

That’s why we’re excited to introduce new activity types in ThingLink, giving creators more ways to engage learners and support different learning goals.

ThingLink’s question and activity types now include:

Question Block

Fill in the Blanks
Multiple choice
Matching
Correct phrase
Open Question

Activity Block

Pick a Point
Grouping

Conversational AI Block

These blocks can be used inside the ThingLink Scenario Builder, perfect for simulations, branching scenarios and other micro-learning experiences.

From Recall to Reflection

One useful way to think about the different question types is through a progression from simple recall to deeper reflection in learning.

Many educators are familiar with Bloom’s Taxonomy, which describes how learning can progress from remembering and understanding information to applying, analyzing, evaluating, and creating. While no single activity can capture every aspect of learning, different question types can support different stages of that journey.

That’s why we’ve expanded the range of activities available in ThingLink. Whether you’re helping learners remember key concepts, apply knowledge in context, explain their reasoning, or reflect on their learning, you can now choose from more interactions that better match your learning goals.

Building recall

Activities and question types that help learners remember important facts, terms, and concepts include multiple choice questions (MCQ), fill-in-the-blank activities, and matching exercises.

For example, learners might identify the correct procedure, recall key terminology, or match concepts with their definitions.

These activities provide an effective way to reinforce foundational knowledge and check understanding before moving on to more complex tasks.

Developing understanding

Activities and question types that encourage learners to organize information and recognize relationships include grouping and categorization activities, matching related concepts, and short-answer questions.

For example, learners may identify relevant equipment in a workspace, group observations from a scene into meaningful categories, or connect symptoms, procedures, and outcomes in a realistic scenario.

These activities help learners move beyond simple recall by recognizing patterns and developing a deeper understanding of how ideas relate to one another.

Applying knowledge in context

Activities and question types that give learners opportunities to use knowledge in context include branched scenario-based activities, decision-making exercises with multiple-choice questions, and Conversational AI interactions.

For example, learners can apply their knowledge within realistic situations, making decisions based on the information available and exploring how different choices may lead to different outcomes.

By combining different questions and activity types, you can create contextual, digital learning experiences that move beyond simple knowledge checks and support deeper engagement with the topic.

In Action: Patient Room Orientation

Encouraging reflection

Activities and question types that encourage learners to explain, justify, and evaluate their thinking include open-ended responses, reflective prompts, and AI-guided conversations. Rather than simply selecting the correct answer, learners might be asked not only what decision they would make in a situation, but also why they chose that course of action and what alternative approaches they considered.

With the new Conversational AI tool, learners can engage in a guided discussion about their reasoning, receive follow-up questions, and reflect on how their decisions align with best practices.

By combining different questions and activity types, you can create contextual, digital learning experiences that move beyond simple knowledge checks and support deeper engagement with the topic.

Conversational AI: The bridge between assessment and coaching

While structured question types are excellent for checking understanding, practicing concepts, and reinforcing key knowledge, some learning goals require learners to explain their reasoning, justify decisions, and reflect on their experiences. That’s where Conversational AI comes in.

ThingLink’s Conversational AI activities allow learners to engage in natural, guided discussions directly within immersive learning experiences. The AI can draw on materials you upload, such as training manuals, policies, course materials, or reference documents, while also taking into account the context of the surrounding scenario. This enables more personalized and context-aware learning conversations that go beyond right-or-wrong answers.

You can also define a role and purpose for the AI.

For example, the AI might act as an experienced nurse mentor helping a nursing student reflect on patient registration procedures, a safety supervisor guiding an employee through workplace decisions, or a historical expert encouraging students to analyze events from multiple perspectives. By combining immersive scenarios, structured activities, and conversational guidance, learners can move from recalling information toward applying knowledge, explaining their thinking, and reflecting on their actions.

Conversational AI Example in Action!

Here’s an activity to show different responses to differenct situations

Further Support

Explore the Question block, Activity block and Conversational AI block to discover the different ways you can bring these learning experiences to life.