Essential Questions Open Ended Transfer Goal Bank
Query the caller's independently approved essential-question bank by transfer-goal topic. Preserves supplied text; does not automatically judge open-endedness, curriculum relevance or learner intent.
Description
Essential questions connect a learning activity to a broader understanding or transfer goal.
Essential questions connect a learning activity to a broader understanding or transfer goal.1
This tool retrieves matching entries from your supplied material bank without rewriting the text.
When to use Essential Questions Open Ended Transfer Goal Bank
Use this tool to retrieve the supplied material entries matching a topic. Establish the learning task, observed evidence and applicable framework or policy edition.
How to use Essential Questions Open Ended Transfer Goal Bank and understand its results
- Establish the learning task, observed evidence and applicable framework or policy edition.
- Enter callerEssentialQuestionsItemIds, callerEssentialQuestionsTexts, callerEssentialQuestionsTopicIds, queryTopicId, using the field meanings and rules below, then run the tool.
- Read matchedItemIds, matchedItemTexts. Inspect nested result fields where present, and review unknown records separately from known matches.
- Correct any reported input issue and run again. Before using a successful result, check the stated units, signs, reference scope and observation coverage.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| callerEssentialQuestionsItemIds | Caller essential questions item ids | list of string | Required |
| callerEssentialQuestionsTexts | Caller essential questions texts | list of string | Required |
| callerEssentialQuestionsTopicIds | Caller essential questions topic ids | list of string | Required |
| queryTopicId | Query topic id; use the exact reference token or coordinate domain stated below | string | Required |
Use nonempty aligned entry IDs, texts and topic keys, with IDs unique and nonblank. Match one query topic exactly and return all matching IDs and texts in supplied order. Topic keys may repeat; an unknown topic fails. Texts and topic strings are not semantically checked, and no new content is generated.
matches=[entry_i where topic_i=queryTopic] Use the matching field units and the exact boundary, ordering and reference rules above.
| Output field | Meaning | Value type |
|---|---|---|
| matchedItemIds | Matched item ids | list of string |
| matchedItemTexts | Matched item texts | list of string |
{
"input": {
"callerEssentialQuestionsItemIds": [
"a",
"b"
],
"callerEssentialQuestionsTexts": [
"independently approved item a",
"independently approved item b"
],
"callerEssentialQuestionsTopicIds": [
"topic-a",
"topic-b"
],
"queryTopicId": "topic-b"
},
"output": {
"matchedItemIds": [
"b"
],
"matchedItemTexts": [
"independently approved item b"
]
}
}Limitations and assumptions
Bank content, approval, task suitability and accessibility must be established separately. Topic matching does not assess question difficulty, learner intent or educational effect; the title does not impose a universal time budget.
Missing required fields, unknown fields, wrong types and violated rules return input issues. Numeric values and outputs must be finite. Lists and matrices must be dense, without missing cells. Numeric lists allow at most 10000 entries; ordinary string lists allow at most 128 strings of 128 UTF-16 units each; numeric matrices allow at most 128 rows and 128 columns, subject to narrower requirements above.
Alternative or Complementary methods
For a related step, use Backward Design Three Stage Wiggins Mctighe UbD Lookup: Understanding by Design starts with desired results, then considers acceptable evidence and a learning plan. For a complementary comparison, use Higher Order HOTS Question Stems By Bloom Level Bank: Higher-order question stems need to be matched to the task and intended thinking rather than a verb alone.
References
Similar or alternative tools
- Backward Design Three Stage Wiggins Mctighe UbD Lookup
Understanding by Design starts with desired results, then considers acceptable evidence and a learning plan.
- Higher Order HOTS Question Stems By Bloom Level Bank
Higher-order question stems need to be matched to the task and intended thinking rather than a verb alone.