Title: A Pedagogy Quality Evaluation Model: Assessing the Quality of Human-machine Interactive Learning in Econometrics
Stream: Teaching Experiences, Pedagogy, Practice & Praxis
Presentation Type: Oral Presentation
Pascal Stiefenhofer, Newcastle University, United Kingdom
The aim of this paper is to evaluate the pedagogical quality of a human-machine interaction-based active learning pedagogy in which students co-create their own learning experience of econometrics in a digitalised learning environment with Interactive Learning Documents (ILDs). ILDs are dynamic interactive documents developed in Jupyter notebook using Python programming language designed to facilitate interactive learning of data analysis, modelling and visualisation. To assess the pedagogical quality of an ILD based pedagogy we consider fuzzy evaluation mappings balancing expert and student data input within a multistage analytic hierarchical process. Our quality assurance model produces a distribution of strength of pedagogical quality from which a representative index can be derived. An in-class experiment with Newcastle University postgraduate students reveals that the strength of quality of our new pedagogy characterized as good, very good, and extremely good is 82%.
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