With the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can be easily collected. This non-conventional structured or unstructured data source may bring new perspectives to better understand the assessment products or accuracy and the process how an item product was attained. The analysis of the conventional and non-conventional assessment data calls for more methodology other than the latent trait modeling. Natural language processing (NLP) methods and machine learning algorithms have been successfully applied in automated scoring. It has been explored in providing diagnostic feedback to test-takers in writing assessment. Recently, machine learning algorithms have been explored for cheating detection and cognitive diagnosis. When the measurement field promote the use of assessment data to provide feedback to improve teaching and learning, it is the right time to explore new methodology and explore the value added from other data sources. This book presents the use cases of machine learning and NLP in improving the assessment theory and practices in high-stakes summative assessment, learning, and instruction. More specifically, experts from the field addressed the topics related to automated item generations, automated scoring, automated feedback in writing, explainability of automated scoring, equating, cheating and alarming response detection, adaptive testing, and applications in science assessment. This book demonstrates the utility of machine learning and NLP in assessment design and psychometric analysis.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : Brook Bookstore On Demand, Napoli, NA, Italie
Etat : new. N° de réf. du vendeur YPO8FPCNFL
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 47591081-n
Quantité disponible : Plus de 20 disponibles
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur FW-9798887306056
Quantité disponible : 15 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 47591081
Quantité disponible : Plus de 20 disponibles
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9798887306056_new
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 47591081-n
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 47591081
Quantité disponible : Plus de 20 disponibles
Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextWith the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can. N° de réf. du vendeur 1498366421
Quantité disponible : Plus de 20 disponibles
Vendeur : preigu, Osnabrück, Allemagne
Buch. Etat : Neu. Machine Learning, Natural Language Processing, and Psychometrics | Hong Jiao (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2024 | Information Age Publishing | EAN 9798887306056 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 128792877
Quantité disponible : 5 disponible(s)
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - With the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can be easily collected. This non-conventional structured or unstructured data source may bring new perspectives to better understand the assessment products or accuracy and the process how an item product was attained. The analysis of the conventional and non-conventional assessment data calls for more methodology other than the latent trait modeling. Natural language processing (NLP) methods and machine learning algorithms have been successfully applied in automated scoring. It has been explored in providing diagnostic feedback to test-takers in writing assessment. Recently, machine learning algorithms have been explored for cheating detection and cognitive diagnosis. When the measurement field promote the use of assessment data to provide feedback to improve teaching and learning, it is the right time to explore new methodology and explore the value added from other data sources. This book presents the use cases of machine learning and NLP in improving the assessment theory and practices in high-stakes summative assessment, learning, and instruction. More specifically, experts from the field addressed the topics related to automated item generations, automated scoring, automated feedback in writing, explainability of automated scoring, equating, cheating and alarming response detection, adaptive testing, and applications in science assessment. This book demonstrates the utility of machine learning and NLP in assessment design and psychometric analysis. N° de réf. du vendeur 9798887306056
Quantité disponible : 2 disponible(s)