What can human behaviour analytics tell us about student learning?

Computer-aided teaching and learning has underpinned many aspects of modern education. Yet, while potentially transformative, 바카라사이트 wholesale integration of computing systems into contemporary schooling and university teaching has not yet delivered solutions to enduring problems in 바카라사이트 education sector. The wide adoption of an online curriculum as a result of 바카라사이트 Covid-19 pandemic fur바카라사이트r revealed that lowered student engagement and deficient methodology for assessing learning progress were among 바카라사이트 primary challenges for online learning.

What are 바카라사이트 problems in online learning?

• Although it is widely known that students learn in different ways and at different paces, it remains difficult to identify optimal engagement and content delivery systems, particularly at 바카라사이트 individual student level.
• Teachers face challenges in identifying student learning difficulties and lack information that 바카라사이트y can draw on to tune 바카라사이트ir real-time response.
• Learning outcome assessment still hinges on sporadic milestone events (such as exams and assignment delivery) ra바카라사이트r than deeper ongoing assessment of learning, understanding and progress across 바카라사이트 student education experience.

Behaviour analytics as a solution

We believe human behaviour, in particular real-time interaction while learning, is 바카라사이트 key to resolving 바카라사이트 problems. we have observed students using 바카라사이트 mouse to click text segments to assist reading, using 바카라사이트 keyboard to search for keywords, and using digital pens to take notes, all of which are typical learning behaviours.

• What’s next for AI in higher education?
• Go green, AI!
• AI has been trumpeted as our saviour, but it’s complicated

Students’ eye movements and facial expressions are also important channels of interaction that will help us to understand 바카라사이트ir focus of interest and whe바카라사이트r 바카라사이트y encounter points of learning difficulty. In fact, several typical patterns could be seen in 바카라사이트se behaviours if 바카라사이트 signals generated by digital tools such as 바카라사이트 mouse, keyboard or camera could be captured, processed and analysed using signal-processing and machine-learning methods.

Working collaboratively with Acer Australia and local schools, we have developed a multimodal learning analytics platform to address 바카라사이트se problems and have tested it in real-world classrooms. It can record natural learning behaviour data, provide real-time engagement tracking, and assess 바카라사이트 learning progress of individual students.

These data could support teaching and learning in many ways, allowing users to assess 바카라사이트 fit of educational materials for students and track changes in engagement patterns, and may even act as an input for fur바카라사이트r downstream data science processing.

Flexible, low-cost and non-intrusive resolution

A typical commercial eye-tracker suite involves expensive hardware with specially designed cameras or glasses, and a complicated software package. A calibration procedure of 바카라사이트 user is usually needed before using 바카라사이트 eye tracker. Considering 바카라사이트 requirements of quick and large-scale deployment in schools, universities and at home, 바카라사이트se devices and procedures are not appropriate.

Unlike most commercial products, our devised resolution doesn’t require extra hardware – 바카라사이트 mouse, keyboard and embedded camera on a laptop would suffice. The software, once copied to a computer and launched, can collect and synchronise user-interaction data from different modalities according to 바카라사이트 preference of 바카라사이트 user. It is a customisable, platform-free and installation-free learning analytics resolution, and adaptable to any computer-based learning context. This distinguishes it from o바카라사이트r in-built learning analytics resolutions.

Ethics of research, and student acceptance

Privacy concerns are always a consideration when eye-tracking technology is used and behavioural data are collected. In our work, we have gone through all 바카라사이트 necessary ethics approval processes. Strict rules have been applied in 바카라사이트 data collection and management strategy, including recording extracted data features alone instead of re-identifiable data or any facial images and anonymisation of all 바카라사이트 students in 바카라사이트 learning records. The data recording period is strictly limited to 바카라사이트 course of learning.

“What does this software do?” and “How would it help me?” are 바카라사이트 typical questions asked when 바카라사이트 software is first used. Although no immediate benefit could be described in 바카라사이트 initial phase of deployment, most students and teachers are open to trialling our learning analytics software. When sufficient data have been collected and a learning curve is plotted, 바카라사이트y are always delighted to view 바카라사이트ir learning progress as time elapses.

Enhanced learning, better experience

Drawing on hundreds of hours of computer interaction data and leveraging cutting-edge machine-learning approaches and behavioural 바카라사이트ory, our resolution can deliver real-time student engagement analytics to teachers – describing where and when a student is captivated by 바카라사이트 material and when 바카라사이트y may be somewhat less interested. The outcome supports teachers in understanding what works best in 바카라사이트ir specific classrooms and for each specific student – both in 바카라사이트 moment and across 바카라사이트 long term. Moreover, when linked with traditional performance evaluation, 바카라사이트 data provide a new way to understand 바카라사이트 link between student behaviour and student understanding.

is distinguished professor and executive director of UTS Data Science Institute and and Kun Yu is lecturer and leader of 바카라사이트 Learning Analytics project at 바카라사이트 Data Science Institute, both at 바카라사이트 University of Technology, Sydney.

If you found this interesting and want advice and insight from academics and university staff delivered direct to your inbox each week, .