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1. |
Record Nr. |
UNINA9910971407303321 |
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Autore |
Stainthorp Rhona |
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Titolo |
Learning from children who read at an early age / / Rhona Stainthorp and Diana Hughes |
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Pubbl/distr/stampa |
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London ; ; New York, : Routledge, 1999 |
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ISBN |
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1-134-68610-2 |
0-415-17494-5 |
1-134-68611-0 |
1-280-33619-6 |
0-203-20123-X |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (x, 179p. ) : ill., facsims |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Reading readiness |
Reading (Early childhood) |
Language arts (Early childhood) |
Literacy |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references (p. 167-171) and indexes. |
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Nota di contenuto |
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1. In the Beginning Reading and Writing 2. The Project 3. The Children 4. Reading 5. Writing 6. Teacher Interviews 7. Interviews with Parents 8. Child Interviews 9. Learning from Successful Readers |
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Sommario/riassunto |
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This work is the result of a three-year research project in which the authors studied a group of children who learnt to read without being taught. |
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2. |
Record Nr. |
UNINA9911028753303321 |
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Autore |
Garcia-Cardona Cristina |
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Titolo |
Advances in Data Science : Women in Data Science and Mathematics (WiSDM) 2023 |
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Pubbl/distr/stampa |
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Cham : , : Springer, , 2025 |
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©2025 |
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ISBN |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (539 pages) |
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Collana |
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Association for Women in Mathematics Series ; ; v.37 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Intel·ligència artificial |
Teoria de grafs |
Reconeixement de formes (Informàtica) |
Enginyeria de programari |
Dades massives |
Teoria de la informació |
Llibres electrònics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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This volume features recent advances in data science ranging from algebraic geometry used for existence and uniqueness proofs of low rank approximations for tensor data, to category theory used for natural language processing applications, to approximation and optimization frameworks developed for convergence and robustness guarantees for deep. |
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