Learning Analytics: Shaping the Future of Education with Data Science (Future Generation Information Systems) - Tapa dura
Sinopsis
This book explores how data science, which involves preparing, analyzing, visualizing, and interpreting data, can revolutionize the field of education. The authors delve into how schools and universities can analyze data to improve teaching methods, enhance student learning, and design effective evaluations.
Learning Analytics: Shaping the Future of Education with Data Science examines how machine learning algorithms can analyze individual student performance data to tailor personalized adaptive learning paths, ensuring the best educational experience. Through real-world examples, this book discusses how valuable insights and opportunities can be gained through the application of data science in educational environments. The authors discuss the application of natural language processing (NLP) to analyze educational content, providing insights into language usage, comprehension levels, and improving the effectiveness of instructional materials and examines computer vision in classroom dynamics to measure student engagement. The book also exposes the reader to the crucial role of cybersecurity in safeguarding sensitive student and institutional information, ensuring a secure learning environment, and protecting against cyber threats. It also addresses the ethical considerations and privacy concerns associated with collecting, analyzing, and making decisions from educational data. Finally, it emphasizes the importance of responsible practices to protect the rights and well-being of students and educators.
The book is intended for engineers from computer science, government policymakers, institutions, and educational stakeholders. It shows how computer science, statistics, and data can personalize learning, improve educational tools, enhance classroom dynamics, secure academic records with blockchain, and ensure online safety.
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Acerca del autor
Dr. Mohd Anas Wajid is a Post Doctoral Research Associate in Data Science at TEC de Monterrey, Mexico. He received his PhD degree in Computer Science from Aligarh Muslim University, India. He was awarded with the MITACS-SICI Globalink Research Award by Mitacs in collaboration with HRD ministry, Government of India to do a project at the University of Athabasca, Edmonton, Alberta, Canada. The ACM India Council named him an ACM India Anveshan Setu Fellow, and he received a fellowship to conduct a part of his research at IIIT-Delhi. His contribution to Neutrosophic research earned him a Diploma from the Neutrosophic Science International Association (NSIA), University of New Mexico, United States (USA). He has keen interest in Soft Computing, Machine Learning, Data Science, Information Retrieval, and Neutrosophy. He has academic as well as industrial experience.
Prof. Claudia Camacho-Zuñiga is a researcher at the Institute for the Future of Education and a professor at the School of Engineering at Tecnologico de Monterrey, Mexico. She is a leader in research, innovation, and transformation in higher education with over 29 years of experience in the field. Since 2014, Professor Camacho-Zuñiga has been a driving force in educational innovation and research in Mexico and Latin America; she has leveraged her expertise in teaching and data science tools to foster a passion for science, ethical and civic engagement, and appreciation for diversity of knowledge and people among undergraduate students and academia.
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Learning Analytics (Hardcover)
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Taylor & Francis Ltd, London, 2026
ISBN 10: 1041151934
ISBN 13: 9781041151937
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Hardcover. Condición: new. Hardcover. This book explores how data science, which involves preparing, analyzing, visualizing, and interpreting data, can revolutionize the field of education. The authors delve into how schools and universities can analyze data to improve teaching methods, enhance student learning, and design effective evaluations.Learning Analytics: Shaping the Future of Education with Data Science examines how machine learning algorithms can analyze individual student performance data to tailor personalized adaptive learning paths, ensuring the best educational experience. Through real-world examples, this book discusses how valuable insights and opportunities can be gained through the application of data science in educational environments. The authors discuss the application of natural language processing (NLP) to analyze educational content, providing insights into language usage, comprehension levels, and improving the effectiveness of instructional materials and examines computer vision in classroom dynamics to measure student engagement. The book also exposes the reader to the crucial role of cybersecurity in safeguarding sensitive student and institutional information, ensuring a secure learning environment, and protecting against cyber threats. It also addresses the ethical considerations and privacy concerns associated with collecting, analyzing, and making decisions from educational data. Finally, it emphasizes the importance of responsible practices to protect the rights and well-being of students and educators.The book is intended for engineers from computer science, government policymakers, institutions, and educational stakeholders. It shows how computer science, statistics, and data can personalize learning, improve educational tools, enhance classroom dynamics, secure academic records with blockchain, and ensure online safety. The book provides detailed descriptions of nonlinear optical phenomena starting from basic principles to state of the art applications. The content is balanced between description of nonlinear optical properties of various photonic materials and a description of application of nonlinear phenomena in free space optics and in waveguides. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781041151937
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Learning Analytics (Hardcover)
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Taylor & Francis Ltd, London, 2026
ISBN 10: 1041151934
ISBN 13: 9781041151937
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Hardcover. Condición: new. Hardcover. This book explores how data science, which involves preparing, analyzing, visualizing, and interpreting data, can revolutionize the field of education. The authors delve into how schools and universities can analyze data to improve teaching methods, enhance student learning, and design effective evaluations.Learning Analytics: Shaping the Future of Education with Data Science examines how machine learning algorithms can analyze individual student performance data to tailor personalized adaptive learning paths, ensuring the best educational experience. Through real-world examples, this book discusses how valuable insights and opportunities can be gained through the application of data science in educational environments. The authors discuss the application of natural language processing (NLP) to analyze educational content, providing insights into language usage, comprehension levels, and improving the effectiveness of instructional materials and examines computer vision in classroom dynamics to measure student engagement. The book also exposes the reader to the crucial role of cybersecurity in safeguarding sensitive student and institutional information, ensuring a secure learning environment, and protecting against cyber threats. It also addresses the ethical considerations and privacy concerns associated with collecting, analyzing, and making decisions from educational data. Finally, it emphasizes the importance of responsible practices to protect the rights and well-being of students and educators.The book is intended for engineers from computer science, government policymakers, institutions, and educational stakeholders. It shows how computer science, statistics, and data can personalize learning, improve educational tools, enhance classroom dynamics, secure academic records with blockchain, and ensure online safety. The book provides detailed descriptions of nonlinear optical phenomena starting from basic principles to state of the art applications. The content is balanced between description of nonlinear optical properties of various photonic materials and a description of application of nonlinear phenomena in free space optics and in waveguides. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9781041151937
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Learning Analytics
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Learning Analytics
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Condición: New. Dr. Mohd Anas Wajid is a Post Doctoral Research Associate in Data Science at TEC de Monterrey, Mexico. He received his PhD degree in Computer Science from Aligarh Muslim University, India. He was awarded with the MITACS-SICI Globalink Research Award by M. Nº de ref. del artículo: 2719961272
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Learning Analytics : Shaping the Future of Education with Data Science
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Taylor & Francis Ltd Jun 2026, 2026
ISBN 10: 1041151934
ISBN 13: 9781041151937
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Buch. Condición: Neu. Neuware - This book explores how data science, which involves preparing, analyzing, visualizing, and interpreting data, can revolutionize the field of education. The authors delve into how schools and universities can analyze data to improve teaching methods, enhance student learning, and design effective evaluations.Learning Analytics: Shaping the Future of Education with Data Science examines how machine learning algorithms can analyze individual student performance data to tailor personalized adaptive learning paths, ensuring the best educational experience. Through real-world examples, this book discusses how valuable insights and opportunities can be gained through the application of data science in educational environments. The authors discuss the application of natural language processing (NLP) to analyze educational content, providing insights into language usage, comprehension levels, and improving the effectiveness of instructional materials and examines computer vision in classroom dynamics to measure student engagement. The book also exposes the reader to the crucial role of cybersecurity in safeguarding sensitive student and institutional information, ensuring a secure learning environment, and protecting against cyber threats. It also addresses the ethical considerations and privacy concerns associated with collecting, analyzing, and making decisions from educational data. Finally, it emphasizes the importance of responsible practices to protect the rights and well-being of students and educators.The book is intended for engineers from computer science, government policymakers, institutions, and educational stakeholders. It shows how computer science, statistics, and data can personalize learning, improve educational tools, enhance classroom dynamics, secure academic records with blockchain, and ensure online safety. Nº de ref. del artículo: 9781041151937
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