Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Today, all higher education institutions, especially computer and engineering colleges, face challenges in the admissions process. Each university should strive for an admissions system based on valid and reliable admissions criteria that select candidates likely to succeed in its programs. In addition, each university should use the best possible techniques for predicting applicants' future academic performance before admitting them. This would support university decision-makers as they set efficient admissions criteria. However, most higher education institutions face challenges when they analyze their large educational databases to predict students' performance. This is because they use only conventional statistical methods rather than new and efficient predictive techniques such as Educational Data Mining, which is the most popular technique to evaluate and predict student performance. 80 pp. Englisch. Codice articolo 9786206738237
Quantità: 2 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Today, all higher education institutions, especially computer and engineering colleges, face challenges in the admissions process. Each university should strive for an admissions system based on valid and reliable admissions criteria that select candidates likely to succeed in its programs. In addition, each university should use the best possible techniques for predicting applicants' future academic performance before admitting them. This would support university decision-makers as they set efficient admissions criteria. However, most higher education institutions face challenges when they analyze their large educational databases to predict students' performance. This is because they use only conventional statistical methods rather than new and efficient predictive techniques such as Educational Data Mining, which is the most popular technique to evaluate and predict student performance. Codice articolo 9786206738237
Quantità: 1 disponibili
Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Today, all higher education institutions, especially computer and engineering colleges, face challenges in the admissions process. Each university should strive for an admissions system based on valid and reliable admissions criteria that select candidates . Codice articolo 987550792
Quantità: Più di 20 disponibili
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Today, all higher education institutions, especially computer and engineering colleges, face challenges in the admissions process. Each university should strive for an admissions system based on valid and reliable admissions criteria that select candidates likely to succeed in its programs. In addition, each university should use the best possible techniques for predicting applicants' future academic performance before admitting them. This would support university decision-makers as they set efficient admissions criteria. However, most higher education institutions face challenges when they analyze their large educational databases to predict students' performance. This is because they use only conventional statistical methods rather than new and efficient predictive techniques such as Educational Data Mining, which is the most popular technique to evaluate and predict student performance.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch. Codice articolo 9786206738237
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Student Performance to Support Decision Making in University Admission | for higher education Institutions | Sandhya Gandham | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206738237 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 127333310
Quantità: 5 disponibili