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Machine learning in higher education (Paperback)
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Paperback. Condizione: new. Paperback. To design a systematic review protocol with bibliometric analysis on the use of machine learning models to predict academic performance and dropout risk in university students during the period 2024-2026.A systematic review is proposed in accordance with PRISMA 2020 and PRISMA-S, with searches in Scopus, Web of Science, ScienceDirect, SpringerLink, ERIC, PubMed, IEEE Xplore, Dialnet and REDALYC. The protocol defines eligibility criteria, Boolean chains, debugging strategy, extraction matrix, methodological quality assessment and synthesis plan. Records, duplicates, exclusions, included studies and bibliometric distributions should be documented only after running searches in primary databases and verifying metadata, full text and quartiles.The review will examine supervised and assembly algorithms, scholarly and digital data sources, predictive metrics, interpretability, explainability, and early warning systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9786630137132
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Machine learning in higher education
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PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9786630137132
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Machine learning in higher education
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Condizione: New. Codice articolo I-9786630137132
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Machine learning in higher education
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PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9786630137132
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Machine learning in higher education
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Our Knowledge Publishing Jun 2026, 2026
ISBN 10: 6630137132
ISBN 13: 9786630137132
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 52 pp. Englisch. Codice articolo 9786630137132
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Machine learning in higher education : Bibliometric Systematic Review Protocol 2024-2026
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Our Knowledge Publishing, 2026
ISBN 10: 6630137132
ISBN 13: 9786630137132
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - To design a systematic review protocol with bibliometric analysis on the use of machine learning models to predict academic performance and dropout risk in university students during the period 2024-2026.A systematic review is proposed in accordance with PRISMA 2020 and PRISMA-S, with searches in Scopus, Web of Science, ScienceDirect, SpringerLink, ERIC, PubMed, IEEE Xplore, Dialnet and REDALYC. The protocol defines eligibility criteria, Boolean chains, debugging strategy, extraction matrix, methodological quality assessment and synthesis plan. Records, duplicates, exclusions, included studies and bibliometric distributions should be documented only after running searches in primary databases and verifying metadata, full text and quartiles.The review will examine supervised and assembly algorithms, scholarly and digital data sources, predictive metrics, interpretability, explainability, and early warning systems. Codice articolo 9786630137132
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Machine learning in higher education (Paperback)
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Paperback. Condizione: new. Paperback. To design a systematic review protocol with bibliometric analysis on the use of machine learning models to predict academic performance and dropout risk in university students during the period 2024-2026.A systematic review is proposed in accordance with PRISMA 2020 and PRISMA-S, with searches in Scopus, Web of Science, ScienceDirect, SpringerLink, ERIC, PubMed, IEEE Xplore, Dialnet and REDALYC. The protocol defines eligibility criteria, Boolean chains, debugging strategy, extraction matrix, methodological quality assessment and synthesis plan. Records, duplicates, exclusions, included studies and bibliometric distributions should be documented only after running searches in primary databases and verifying metadata, full text and quartiles.The review will examine supervised and assembly algorithms, scholarly and digital data sources, predictive metrics, interpretability, explainability, and early warning systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9786630137132
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Machine learning in higher education
Editore:
Our Knowledge Publishing Jun 2026, 2026
ISBN 10: 6630137132
ISBN 13: 9786630137132
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware 52 pp. Englisch. Codice articolo 9786630137132
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Machine learning in higher education | Bibliometric Systematic Review Protocol 2024-2026
Editore:
Our Knowledge Publishing, 2026
ISBN 10: 6630137132
ISBN 13: 9786630137132
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Taschenbuch
Da: preigu, Osnabrück, Germania
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Taschenbuch. Condizione: Neu. Machine learning in higher education | Bibliometric Systematic Review Protocol 2024-2026 | Ariel Herrera (u. a.) | Taschenbuch | Englisch | 2026 | Our Knowledge Publishing | EAN 9786630137132 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Codice articolo 135791907
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