> For the complete documentation index, see [llms.txt](https://docs.lamsfoundation.org/lams/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.lamsfoundation.org/lams/question-bank/matching-pairs.md).

# Matching Pairs

## Create a Matching Pairs question

Use a matching pairs question when you want students to connect each prompt with its corresponding answer. Typical uses include matching:

* terms with definitions;
* concepts with examples;
* events with dates or consequences;
* methods with appropriate applications;
* representations with equivalent forms; or
* parts of a system with their functions.

A matching task is a set of related selected-response items. It works best when the learning outcome requires students to recognise meaningful relationships within one clearly defined category.

Do not use matching pairs merely to fit unrelated facts into one question. If students need to explain a relationship, justify a classification, construct an answer or demonstrate a process, choose a question type that captures that evidence directly.

### Before you create the question

Start with the learning outcome and identify the relationship students must recognise. Decide whether matching provides valid evidence of that outcome.

Keep one matching question focused on a single dimension. For example, ask students to match statistical tests with their appropriate uses, rather than mixing tests, researchers, dates and definitions in the same set.

The LAMS editor creates one answer for every prompt. This makes authoring straightforward, but it also means students may obtain later matches by eliminating answers they have already used. Treat the complete set—not each pair in isolation—as the assessment item when you judge its difficulty, weighting and validity.

### Create the question

1. Enter a short, distinctive **Question's title**.

   Use the title to identify and manage the item in the Question Bank. Include information that distinguishes it from similar items, such as the topic and intended cognitive demand. Do not put information here that students need in order to complete the task.
2. Enter the task and directions in **Question's description**.

   State the basis for matching explicitly. For example: **Match each research design with the description that best represents it.** Tell students that each answer is paired with one prompt if this is not already evident in the delivered activity.
3. Enter the first prompt in **Question 1** and its matching response in **Answer 1**.
4. Complete the remaining pairs.

   LAMS provides three matching pairs initially. Select **Add another pair** when you need an additional pair.
5. Add general feedback if it will help students learn from the task.
6. Review the advanced settings, tag the relevant learning outcome or outcomes, and select **Save**.

### Write effective matching pairs

* Use one homogeneous category for all prompts and one homogeneous category for all answers.
* Make each relationship unambiguous. Every prompt should have one defensible match within the set.
* Keep prompts and answers concise. Long or syntactically complex entries can turn the task into a test of working memory or reading endurance.
* Put the longer contextual statement in the **Question** field and the shorter label or phrase in the **Answer** field where practical.
* Use parallel grammar and a consistent level of detail. Differences in wording, length or grammatical form should not reveal a match.
* Avoid repeating distinctive words in only one prompt and one answer unless recognising that terminology is the intended skill.
* Avoid overlapping categories. If two answers could reasonably fit the same prompt, revise the set or supply enough context to distinguish them.
* Keep the set manageable on the devices students will use. Split a large collection into several focused questions rather than creating one visually and cognitively burdensome task.
* Check factual accuracy, spelling, capitalisation and units across the whole set.

Matching items are efficient, but sound construction requires brevity, a common context and clear directions. Published assessment guidance also recommends systematic organisation and stating whether responses can be reused ([Janke et al., 2019](https://pmc.ncbi.nlm.nih.gov/articles/PMC6788158/)). In the current LAMS pairs format, author each relationship once and verify the student view rather than assuming support for reusable or unused responses.

### Account for cueing and elimination

Because the editor creates the same number of prompts and answers, the last unmatched response can be selected by elimination. Earlier correct matches also reduce the number of alternatives available for later prompts.

This has several implications:

* Do not interpret every correct pair as an independent demonstration of knowledge.
* Avoid giving a large proportion of a high-stakes assessment to one matching set.
* Consider several smaller, independently focused sets when you need broader sampling.
* Use another question type if your scoring model requires unused distractors, reusable responses or independent decisions for every prompt.
* Combine matching evidence with constructed responses or performance evidence when the outcome requires explanation, production or judgement.

This is not simply a technical limitation. Cueing changes what the task measures: a student may arrive at a correct response through the structure of the set rather than through the intended knowledge.

### Add feedback for students

Enter **General feedback** that will help students understand the relationships after completing the task. You can:

* explain the principle that connects each pair;
* provide a concise answer rationale for pairs that students commonly confuse;
* link to a worked example or relevant resource; or
* prompt students to compare two easily confused concepts.

The matching pairs editor provides one general feedback field rather than separate feedback for each pair or response category. Write feedback that remains coherent for students with different response patterns. If detailed diagnostic feedback is central to the learning design, consider following the question with an activity that reveals and discusses each relationship.

Feedback is most useful when students receive it in time to act on it. Check the settings of the activity that uses the banked question, because that activity determines when students can see the feedback.

### Configure the advanced settings

#### Default question grade

Enter the total mark for the complete matching question. The interface accepts an integer, for example `1`, `5` or `10`.

LAMS divides the default question grade across the number of pairs. For example, the editor shows **0.33 marks per each correct matching pair** when the default grade is `1` and the question contains three pairs.

Review the per-pair value after adding or removing pairs. The displayed value may be rounded, so preview the completed question and confirm that the total awarded score behaves as intended. Keep the overall weighting proportionate to the evidence the matching set supplies.

#### Penalty factor

Enter the penalty that should apply in a context where students can make another attempt. The field accepts a floating-point number.

Use a penalty only when it serves a clear assessment purpose. Its effect can depend on how the receiving LAMS activity handles attempts, so test the question in that activity before relying on the calculation. Explain any penalty to students in advance. Avoid using penalties merely to counter guessing; elimination is built into the structure of the matching set, and penalising attempts may also measure risk-taking behaviour.

#### Shuffle answers?

Turn this on to vary the order of the answers when the question is delivered.

Shuffling reduces reliance on the authoring order and is usually appropriate for independent pairs. It does not remove the cueing created by a shrinking pool of answers.

Leave shuffling off when answer order carries meaning that is part of the task, although a matching question may then be the wrong format. Do not refer to an answer by its displayed position in the question directions or feedback when shuffling is enabled.

#### Learning outcomes

Search by outcome name or code, then select every learning outcome for which the matching task provides meaningful evidence.

Tag the outcome at the level actually assessed. Matching a term with a supplied definition usually demonstrates recognition, not the ability to explain, evaluate or apply the concept independently. A scenario-based set may assess application, but only if students must interpret the scenario rather than spot repeated words.

Avoid tagging every broadly related outcome. Across an assessment, review the distribution of questions by outcome, cognitive demand and weighting so that Question Bank metadata supports meaningful blueprinting rather than merely describing the topic.

### Use matching pairs within a programme of assessment

Treat performance on a matching set as one data point. Programmatic assessment uses individual assessment events to promote learning and feedback, while higher-stakes decisions draw on multiple data points collected over time ([van der Vleuten et al., 2012](https://pubmed.ncbi.nlm.nih.gov/22364452/)).

Matching pairs can efficiently sample associations and classifications. They cannot, by themselves, demonstrate that students can recall an answer without cues, explain why a relationship holds or apply it in authentic practice. Combine them with other assessment methods when the learning outcome includes communication, creation, performance or professional judgement.

### Review the question after use

Review the complete task and the response evidence before you reuse it.

* Identify pairs that most students answer correctly and consider whether wording or elimination made them too easy.
* Look for pairs that students frequently confuse; this may reveal a misconception, ambiguity or insufficient distinction between answers.
* Check whether students succeed through obvious word matching rather than the intended reasoning.
* Review accessibility and layout on the devices students actually use.
* Investigate unexpected patterns before attributing them to ability; teaching coverage, language demand or an incorrect pairing may be responsible.
* Record substantive revisions as a new version so that you do not treat results from materially different tasks as directly comparable.

Use statistics as prompts for review, not as automatic rules for keeping or discarding a question. Each pair is dependent on the other options available in that version of the set, so changes to one pair may change the difficulty of several others.

### Final check

Before you save or deploy the question, confirm that:

* the task measures a tagged learning outcome at the intended cognitive level;
* the description states exactly what students must match;
* all prompts belong to one coherent category;
* all answers belong to one coherent category;
* every prompt has one unambiguous answer;
* wording, length and grammar do not reveal the matches;
* the total and per-pair grades match your assessment plan;
* any penalty has been tested in the receiving activity;
* shuffling does not damage meaning;
* feedback helps students understand the relationships;
* the question is accessible and usable on the target devices; and
* you have previewed the question in the LAMS activity where students will answer it.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.lamsfoundation.org/lams/question-bank/matching-pairs.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.