Data Analytics Applications in Education
Herausgeber: Vanthienen, Jan; De Witte, Kristof
Data Analytics Applications in Education
Herausgeber: Vanthienen, Jan; De Witte, Kristof
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In education, big data analytics is being used to enhance the learning process, evaluate efficiency, improve feedback, and enrich the learning experience. Integrating data from different institutions enables data-driven decision-making. This book presents innovative applications of data analytics in primary, secondary, and tertiary education.
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In education, big data analytics is being used to enhance the learning process, evaluate efficiency, improve feedback, and enrich the learning experience. Integrating data from different institutions enables data-driven decision-making. This book presents innovative applications of data analytics in primary, secondary, and tertiary education.
Produktdetails
- Produktdetails
- Verlag: CRC Press
- Seitenzahl: 276
- Erscheinungstermin: 30. Juni 2021
- Englisch
- Abmessung: 234mm x 155mm x 18mm
- Gewicht: 399g
- ISBN-13: 9781032096292
- ISBN-10: 1032096292
- Artikelnr.: 62152546
- Verlag: CRC Press
- Seitenzahl: 276
- Erscheinungstermin: 30. Juni 2021
- Englisch
- Abmessung: 234mm x 155mm x 18mm
- Gewicht: 399g
- ISBN-13: 9781032096292
- ISBN-10: 1032096292
- Artikelnr.: 62152546
Kristof De Witte is a tenured associate professor at the Faculty of Economics and Business at KU Leuven, Belgium, and he holds the chair in "Effectiveness and Efficiency of Educational Innovations" at Top Institute for Evidence-Based Education Research at Maastricht University, the Netherlands. Kristof De Witte is further an affiliated member of the CESifo Network (Ludwig-Maximilians University and Ifo Institute). At KU Leuven, Kristof De Witte is director of the research center "Leuven Economics of Education Research." His research interests include education economics, performance evaluation, and early school leaving. He has published his work in many international academic journals, including The Economic Journal, Journal of Urban Economics, European Journal of Operational Research, Economics of Education Research, European Journal of Political Economy, and Scientometrics. Jan Vanthienen is full professor of information systems at KU Leuven, Belgium, Department of Decision Sciences and Information Management, Information Systems Group, where he is teaching and researching on business intelligence, analytics, business rules, processes and decisions, business information systems, and information management. He has published more than 200 full papers in reviewed top international journals (such as MIS Quarterly, Machine Learning, Management Science, Journal of Machine Learning Research, IEEE Transactions on Neural Networks, Expert Systems with Applications, IEEE Transactions on Knowledge and Data Engineering, Information Systems, and Health Information Management Journal) and conference proceedings. He is a founding member and currently coordinator of the Leuven Institute for Research in Information Systems (LIRIS) and co-chairholder of the bpost bank research chair on Actionable Analytics, and the Colruyt-Symeta Research Chair on Smart Marketing Analytics. He received an IBM Faculty Award in 2011 on smart decisions and the Belgian Francqui Chair 2009 at FUNDP on smart systems. He is co-founder and president-elect of the Benelux Association for Information Systems (BENAIS).
Introduction: Big Data Analytics in a Learning Environment. I. Data
Analytics to Improve the Learning Process. Improved Student Feedback with
Process and Data Analytics. Toward Data for Development: A Model on
Learning Communities as a Platform for Growing Data Use. The Impact of
Fraudulent Behavior on the Usefulness of Learning Analytics Applications:
The Case of Question and Answer Sharing with Medium-Stakes Online Quizzing
in Higher Education. II. Data Analytics to Measure Performance.
Disentangling Faculty Efficiency from Students' Effort. Using Data
Analytics to Benchmark Schools: The Case of Portugal. The Use of
Educational Data Mining Procedures to Assess Students' Performance in a
Bayesian Framework. Using Statistical Analytics to Study School Performance
through Administrative Datasets. III. Policy Relevance and the Challenges
Ahead. The Governance of Big Data in Higher Education. Evidence-Based
Education and Its Implications for Research and Data Analytics with an
Application to the Overeducation Literature.
Analytics to Improve the Learning Process. Improved Student Feedback with
Process and Data Analytics. Toward Data for Development: A Model on
Learning Communities as a Platform for Growing Data Use. The Impact of
Fraudulent Behavior on the Usefulness of Learning Analytics Applications:
The Case of Question and Answer Sharing with Medium-Stakes Online Quizzing
in Higher Education. II. Data Analytics to Measure Performance.
Disentangling Faculty Efficiency from Students' Effort. Using Data
Analytics to Benchmark Schools: The Case of Portugal. The Use of
Educational Data Mining Procedures to Assess Students' Performance in a
Bayesian Framework. Using Statistical Analytics to Study School Performance
through Administrative Datasets. III. Policy Relevance and the Challenges
Ahead. The Governance of Big Data in Higher Education. Evidence-Based
Education and Its Implications for Research and Data Analytics with an
Application to the Overeducation Literature.
Introduction: Big Data Analytics in a Learning Environment. I. Data
Analytics to Improve the Learning Process. Improved Student Feedback with
Process and Data Analytics. Toward Data for Development: A Model on
Learning Communities as a Platform for Growing Data Use. The Impact of
Fraudulent Behavior on the Usefulness of Learning Analytics Applications:
The Case of Question and Answer Sharing with Medium-Stakes Online Quizzing
in Higher Education. II. Data Analytics to Measure Performance.
Disentangling Faculty Efficiency from Students' Effort. Using Data
Analytics to Benchmark Schools: The Case of Portugal. The Use of
Educational Data Mining Procedures to Assess Students' Performance in a
Bayesian Framework. Using Statistical Analytics to Study School Performance
through Administrative Datasets. III. Policy Relevance and the Challenges
Ahead. The Governance of Big Data in Higher Education. Evidence-Based
Education and Its Implications for Research and Data Analytics with an
Application to the Overeducation Literature.
Analytics to Improve the Learning Process. Improved Student Feedback with
Process and Data Analytics. Toward Data for Development: A Model on
Learning Communities as a Platform for Growing Data Use. The Impact of
Fraudulent Behavior on the Usefulness of Learning Analytics Applications:
The Case of Question and Answer Sharing with Medium-Stakes Online Quizzing
in Higher Education. II. Data Analytics to Measure Performance.
Disentangling Faculty Efficiency from Students' Effort. Using Data
Analytics to Benchmark Schools: The Case of Portugal. The Use of
Educational Data Mining Procedures to Assess Students' Performance in a
Bayesian Framework. Using Statistical Analytics to Study School Performance
through Administrative Datasets. III. Policy Relevance and the Challenges
Ahead. The Governance of Big Data in Higher Education. Evidence-Based
Education and Its Implications for Research and Data Analytics with an
Application to the Overeducation Literature.