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Table of Contents
Part 1: Theoretical and ethical concerns
1 Big Data in academic researchChallenges, pitfalls, and opportunities
Part 2: Teaching people to use Big Data effectively
2 Big Data for Early Learners
3 Using Big Data in a Master of Applied Statistics unit
4 Statistical education as part of the digital transformation of statistical offices
Part 3: Using Big Data to improve teaching
5 Big data, analytics and education: Challenges, opportunities and an example from a large university unit
6 Enhancing learning outcomes with big data from pedagogy for conceptual thinking with meaning equivalence reusable learning objects (MERLO) and interactive concept discovery (INCOD)
7 Employing Authentic Analytics for More Authentic Tasks
8 Learning from Learning Analytics: How much do we know about patterns of student engagement?
Part 4: Educational systems that use Big Data
9 Museum Big Data: Perceptions and practices
10 Analysing aspects of Brazilian curricula for teaching statistics involving Big Data
Part 5: Concluding Comments.
1 Big Data in academic researchChallenges, pitfalls, and opportunities
Part 2: Teaching people to use Big Data effectively
2 Big Data for Early Learners
3 Using Big Data in a Master of Applied Statistics unit
4 Statistical education as part of the digital transformation of statistical offices
Part 3: Using Big Data to improve teaching
5 Big data, analytics and education: Challenges, opportunities and an example from a large university unit
6 Enhancing learning outcomes with big data from pedagogy for conceptual thinking with meaning equivalence reusable learning objects (MERLO) and interactive concept discovery (INCOD)
7 Employing Authentic Analytics for More Authentic Tasks
8 Learning from Learning Analytics: How much do we know about patterns of student engagement?
Part 4: Educational systems that use Big Data
9 Museum Big Data: Perceptions and practices
10 Analysing aspects of Brazilian curricula for teaching statistics involving Big Data
Part 5: Concluding Comments.