Full Description
This book provides a significant contribution to the increasing conversation concerning the place of big data in education. Offering a multidisciplinary approach with a diversity of perspectives from international scholars and industry experts, chapter authors engage in both research- and industry-informed discussions and analyses on the place of big data in education, particularly as it pertains to large-scale and ongoing assessment practices moving into the digital space. This volume offers an innovative, practical, and international view of the future of current opportunities and challenges in education and the place of assessment in this context.
Contents
1: Transforming schooling through digital disruption: Big data, policy, teaching and assessment; 2: Automated knowledge discovery: Tracing the frontiers, infrastructures and practices of education and data science; 3: Artificial intelligence and machine learning: A practical and ethical guide for teachers; 4: The relationship between humans and machines in public policy; 5: Amazon Go for education? Artificial intelligence, disruption and intensification; 6: Pearson's digital transformation and the disruption of public education; 7: Costs of big data: Challenges and possibilities of cost-benefit analysis of ILSAs - Laura C. Engel and David Rutkowski; 8: Data infrastructures and the (ambivalent) effects of rising data interoperability: Insights from Germany; 9: Datafication and surveillance capitalism: The Texas Teacher Evaluation and Support System (T-TESS); 10: Governing by dashboard: Reconfiguring education governance in the Global South; 11: Next generation online assessments, technical democracy and responding to digital disruption; 12: 'Lenses on COVID-19' - Provocations
