Monday 5 August 2019

Presenter Information

Dragan Gašević, Monash University

Start Date

5-8-2019 10:30 AM

End Date

5-8-2019 11:30 AM

Subjects

Learning analytics, Generic skills, Data analysis, Self management, Learning strategies, Problem solving, Cooperation, Group activities, Measurement, Network analysis

Abstract

The unprecedented opportunities to collect data about learning and contexts in which learning occurs has attracted great attention in education. The use of data analytics and machine learning methods have offered much potential to address many relevant questions in education. This talk will focus on the use of learning analytics to measure 21st-century skills in education and outline the types of data commonly used. It will also discuss approaches that are used for analysis and modelling of relevant learning processes and outline the ways in which learning analytics can be used to track learning progression and how the validity of the findings with data analytics is assured. Numerous empirical studies will be drawn upon to look at self-regulated learning, learning strategies, and problem solving in individual and group activities.

RC2019_Gasevic_Powerpoint.pdf (2359 kB)
Using learning analytics to measure 21st century skills presentation

Place of Publication

Melbourne, Australia

Publisher

Australian Council for Educational Research (ACER)

ISBN

9781742865546

Share

COinS
 
Aug 5th, 10:30 AM Aug 5th, 11:30 AM

Using learning analytics to measure 21st-century skills

The unprecedented opportunities to collect data about learning and contexts in which learning occurs has attracted great attention in education. The use of data analytics and machine learning methods have offered much potential to address many relevant questions in education. This talk will focus on the use of learning analytics to measure 21st-century skills in education and outline the types of data commonly used. It will also discuss approaches that are used for analysis and modelling of relevant learning processes and outline the ways in which learning analytics can be used to track learning progression and how the validity of the findings with data analytics is assured. Numerous empirical studies will be drawn upon to look at self-regulated learning, learning strategies, and problem solving in individual and group activities.

 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.