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FundersNYComputer Science Teachers Association LLC › 2023

Grants paid by Computer Science Teachers Association LLC, tax year 2023

EIN 27-0115816 · New York, NY · Form 990, Schedule I · NTEE B60

In tax year 2023, Computer Science Teachers Association LLC (EIN 27-0115816) reported 6 grants paid totaling $245,520. Dataset version 2026.09.0, built 2026-09-03.

202020212022202320242025

Every grant, 2023

Grants reported by Computer Science Teachers Association LLC for tax year 2023
Tax yearRecipientMatchAmountTypePurposeSource filing
2023Computer Science Alliance Santa Fe, NMA$200,000paidSUPPORT FOR LOCAL PD EVENTS202421309349302317
2023Csta Connecticut Manchester, CTA$11,875paidSUPPORT FOR CHAPTER MEMBERSHIP AND EVENTS202421309349302317
2023Csta Dallas Fort Worth Dallas, TXA$9,785paidSUPPORT FOR CHAPTER MEMBERSHIP AND EVENTS202421309349302317
2023Csta Miami North Miami, FLA$9,440paidSUPPORT FOR CHAPTER MEMBERSHIP AND EVENTS202421309349302317
2023Csta New Jersey Randolph, NJA$9,120paidSUPPORT FOR CHAPTER MEMBERSHIP AND EVENTS202421309349302317
2023Kentucky Science and Technology Corporation Lexington, KYA$5,300paidSUPPORT FOR CHAPTER MEMBERSHIP AND EVENTS202421309349302317

Match tier: A Reported EIN · B Exact name and place · C Strong name match · D Probable name match · U Unresolved. Tiers C and D are inferred, not reported; see how matching works.

Recipient matching for this dataset version has not yet completed its independent precision check. Tier A rows carry the EIN the filer reported; tiers B–D are the matcher's inference and should be read as leads until the check is published on the methodology page.

Derived from IRS Form 990 e-file XML. Dataset version 2026.09.0, built 2026-09-03. All years for this funder.

The same organization elsewhere in the program: exempt status and filing health · federal awards · grant guidance · open opportunities.

This is informational only, derived from public data on the dates shown. It is not an eligibility determination, and not legal, tax, or accounting advice. Verify against the official source before relying on it.