- Elearning /
- artificial intelligence /
- conversational AI /
- digital transformation /
- online learning /
- adaptive learning /
Due to COVID-19’s stay-home and social distancing regulations this year, institutes have had to rely heavily on E-learning. The unprecedented situation has made teaching authorities and curriculum managers pinpoint the shortcomings of current E-learning capabilities while looking for a better alternative, particularly for Higher Education.
As schools and workplaces transition into learning and working from home, teachers and learners alike have faced countless problems. For starters, it can be hard to stay focused during dry online courses where you are expected to sit in front of a small screen in your bedroom for hours on end.
Lower-income students may face difficulties in procuring a laptop, creating a learning space, and getting stable Wi-Fi to participate in classes. Technical difficulties often arise, which can cause a multitude of problems including, but not limited to, lagging screens, missing information, miscommunication, and late submissions.
On top of that, it is challenging for teachers to answer all questions virtually and track every student’s attentiveness. Institutes also struggle to measure learning outcomes and monitor students' wellbeing. Thus, the current E-learning capabilities are still lacking in their ability to meet both teaching and learning needs.
“Everybody is a genius. But if you judge a fish by its ability to climb a tree, it will live its whole life believing that it is stupid.”
Since everyone has different characteristics, skills, and weaknesses, it makes sense that every student has a different learning preference. Enter adaptive learning, a customised teaching method that allows teachers to use specific devices that help the learner effectively absorb information and understand concepts. Whether your student is an auditory, visual, or kinaesthetic learner, adaptive learning can cater to them to best suit their needs.
The traditional approach to teaching usually results in a handful of students scoring well, but with the rest of the class barely passing without little understanding of key concepts. In contrast, the use of artificial intelligence (AI) in educational software creates a learning path that matches students’ level of competency in a subject. Teachers are then able to monitor their students' progress and adjust the programs accordingly through the adaptive learning system that is based on technology and data analysis. AI will help to make E-learning more efficient and effective with customisable methods and real-time analytics.
Even though adaptive learning sounds like an unconventional method is hard to implement, it’s easier than one might think. In reality, the development and implementation process does not require more effort than the existing methods and the implementation process is also gradual, giving everyone time to adjust to the new system before settling comfortably. It is extremely helpful that the system can be monitored and adjusted regularly.
Students will be able to learn at their own pace and teachers will be able to constantly upgrade themselves with help from detailed feedback and analytics. Adaptive learning is breaking boundaries in teaching, expanding E-learning capabilities, and improving the learning experience for students.
Meet Carissa. She regularly writes for Noodle Factory, covering a breadth of EdTech, AI and technology topics. You'll often find her underwater, on a yoga mat, or in a new restaurant. Contact her at email@example.com.