Dr Theodosia Prodromou is a senior lecturer of Mathematics Education at the University of New England in Australia. She has published numerous journal articles, book chapters and edited/authored books on a wide range of subjects, including the use of big data in educational settings, the relationship between technology and mathematical thinking, the integration of digital technologies in the teaching and learning of mathematics, STEM education, augmented reality in Educational settings, professional development of mathematics teachers, and statistical thinking including perceptions of probability and chance.Her most recent edited/authored books were, Augmented reality in educational settings (2020) and Primary and Middle Years Mathematics: Teaching Developmentally (2019).

• Part 1: Theoretical and ethical concerns.- 1 Big Data in academic research—Challenges, 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.

Dr Theodosia Prodromou is a senior lecturer of Mathematics Education at the University of New England in Australia. She has published numerous journal articles, book chapters and edited/authored books on a wide range of subjects, including the use of big data in educational settings, the relationship between technology and mathematical thinking, the integration of digital technologies in the teaching and learning of mathematics, STEM education, augmented reality in Educational settings, professional development of mathematics teachers, and statistical thinking including perceptions of probability and chance.Her most recent edited/authored books were, Augmented reality in educational settings (2020) and Primary and Middle Years Mathematics: Teaching Developmentally (2019).

• Part 1: Theoretical and ethical concerns.- 1 Big Data in academic research—Challenges, 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.

Dr Theodosia Prodromou is a senior lecturer of Mathematics Education at the University of New England in Australia. She has published numerous journal articles, book chapters and edited/authored books on a wide range of subjects, including the use of big data in educational settings, the relationship between technology and mathematical thinking, the integration of digital technologies in the teaching and learning of mathematics, STEM education, augmented reality in Educational settings, professional development of mathematics teachers, and statistical thinking including perceptions of probability and chance.Her most recent edited/authored books were, Augmented reality in educational settings (2020) and Primary and Middle Years Mathematics: Teaching Developmentally (2019).

• Part 1: Theoretical and ethical concerns.- 1 Big Data in academic research—Challenges, 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.