Applying Data Science and Learning Analytics Throughout a Learner’s Lifespan - Couverture souple

Couverture souple

ISBN 10 : 1799896455 ISBN 13 : 9781799896456

Editeur : Business Science Reference, 2022

Synopsis

Research in the domains of learning analytics and educational data mining has prototyped an approach where methodologies from data science and machine learning are used to gain insights into the learning process by using large amounts of data. As many training and academic institutions are maturing in their data-driven decision making, useful, scalable, and interesting trends are emerging. Organizations can benefit from sharing information on those efforts. Applying Data Science and Learning Analytics Throughout a Learner's Lifespan examines novel and emerging applications of data science and sister disciplines for gaining insights from data to inform interventions into learners' journeys and interactions with academic institutions. Data is collected at various times and places throughout a learner's lifecycle, and the learners and the institution should benefit from the insights and knowledge gained from this data. Covering topics such as learning analytics dashboards, text network analysis, and employment recruitment, this book is an indispensable resource for educators, computer scientists, faculty of higher education, government officials, educational administration, students of higher education, pre-service teachers, business professionals, researchers, and academicians.

A propos du livre

À propos des auteurs

Goran Trajkovski , Ph.D., has 30 years of experience in educational design, focusing on learner-centered approaches. His expertise covers data science, artificial intelligence, machine learning, and learning analytics. He has developed programs and courses in these areas for various educational institutions. His research interests are in cognitive and developmental robotics, leading to the establishment of an NSF-funded research lab. Dr. Trajkovski has a significant publication record, including more than 20 books and over 300 articles, with his involvement in AI research starting in 1995. He prioritizes ongoing learning and skill development, consistently seeking to broaden his knowledge.

Marylee Demeter possesses administrative and academic experience in higher education serving in assessment leadership and adjunct positions at Rutgers University and Middlesex County College. She championed efforts as Chair of the Professional Development Committee for the Student Affairs Assessment Leaders, where she collaboratively developed the MOOC “Developing and Leading Assessment in Student Affairs.” She currently serves as a Senior Assessment Developer at Western Governors University.

Heather Hayes , PhD, is a psychometrician for the Colleges of Information Technology and Business at Western Governors University. She has been involved in the construction and validation of both cognitive ability and personality assessments for over 20 years. Her research interests center on the conjoint use of cognitive theory and Item Response Theory to aid in the construct validation of test scores as well as to improve the test experience itself through computer adaptive testing and automatic item generation. Her current focus is application of this line of research to developing and validating educational tests for online, competency-based education programs.

Détails de l'édition

• Éditeur: Business Science Reference
• Date d'édition: 2022
• Langue: anglais
• ISBN 10: 1799896455
• ISBN 13: 9781799896456
• Reliure: Broché
• Nombre de pages: 314
• Éditeur: Trajkovski Goran, Demeter Marylee, Hayes Heather
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible