Number Talks Mental Math String Problems Sequences

Query actual caller approved mental math problem string bank by concept, not generate unverified progression or require one canonical strategy. Query actual independently approved bounded material bank by exact topic; no inferred learner intent. Caller independently verifies learner/context/evidence and reference edition; not causal learning efficacy, disability eligibility or educational certification.

Description

Number talks use related mental mathematics problems to make strategies available for discussion.

Number talks use related mental mathematics problems to make strategies available for discussion.^[1]

This tool retrieves matching entries from your supplied material bank without rewriting the text.

When to use Number Talks Mental Math String Problems Sequences

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 Number Talks Mental Math String Problems Sequences and understand its results

Establish the learning task, observed evidence and applicable framework or policy edition.
Enter callerNumberTalkStringsItemIds, callerNumberTalkStringsTexts, callerNumberTalkStringsTopicIds, 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
callerNumberTalkStringsItemIds	Caller number talk strings item ids	list of string	Required
callerNumberTalkStringsTexts	Caller number talk strings texts	list of string	Required
callerNumberTalkStringsTopicIds	Caller number talk strings 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

json

{
  "input": {
    "callerNumberTalkStringsItemIds": [
      "a",
      "b"
    ],
    "callerNumberTalkStringsTexts": [
      "independently approved item a",
      "independently approved item b"
    ],
    "callerNumberTalkStringsTopicIds": [
      "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 Concrete Examples Abstract Concept Pairing Guide: Concrete examples can illustrate an abstract concept in several contexts. For a complementary comparison, use Concrete Representational Abstract CRA Progression Lookup: Concrete, representational and abstract approaches connect physical examples, representations and symbolic reasoning.

References

Number Talks Mental Math String Problems Sequences — tool.io

Similar or alternative tools

Concrete Examples Abstract Concept Pairing Guide
Concrete examples can illustrate an abstract concept in several contexts.
Concrete Representational Abstract CRA Progression Lookup
Concrete, representational and abstract approaches connect physical examples, representations and symbolic reasoning.