This book presents insight into the progress made towards establishing effective, valid and reliable strategies, in regards to teaching, learning and assessment when context, agency and individual characteristics are taken into account. It was originally published as a special issue of Educational Research and Evaluation.
This book presents insight into the progress made towards establishing effective, valid and reliable strategies, in regards to teaching, learning and assessment when context, agency and individual characteristics are taken into account. It was originally published as a special issue of Educational Research and Evaluation.
Michele Notari teaches and researches at the University of Teacher Education in Bern, Switzerland. He has published in key journals in the area of technology-enhanced learning, a book and several book chapters related to collaborative learning using participative technologies. His current research focus is on using mobile and wearable technologies for learning. Stewart Martin is Professor of Educational Research at the University of Hull, UK, where his research interests include the educational use of digital technology; immersive virtual reality; images of the self; psychometrics; cognition, learning and technology; and educational leadership and organisational change. He is a National Teaching Fellow of the UK Higher Education Academy, and has published widely in the field of technology and education, is visiting professor at several international universities and is a member of the Editorial Board for the journal Educational Research and Evaluation.
Inhaltsangabe
1. Modelling blended solutions for higher education: teaching, learning, and assessment in the network and mobile technology era 2. Expectancy theory outcomes and student evaluations of teaching 3. What response rates are needed to make reliable inferences from student evaluations of teaching? 4. Challenges for collaborative blended learning in undergraduate students 5. Measuring cognitive load and cognition: metrics for technology-enhanced learning
1. Modelling blended solutions for higher education: teaching, learning, and assessment in the network and mobile technology era 2. Expectancy theory outcomes and student evaluations of teaching 3. What response rates are needed to make reliable inferences from student evaluations of teaching? 4. Challenges for collaborative blended learning in undergraduate students 5. Measuring cognitive load and cognition: metrics for technology-enhanced learning
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