Online Driver Model
The Online Driver Model is based on technology as its main source for delivering lectures.
Students are remotely facilitated in this model by teachers.
As technology is advancing so is the flexibility in education. The Online Driver model is one such example of hybrid learning where students can be facilitated through remote learning. In the online driver model, teachers and students can work from anywhere with access to the internet at any time, be it at home, in another country, or anywhere else. In addition, it reduces the need for physical space and resources, which makes education cheaper.
Furthermore, it allows for the customization of course materials, so that students can have a better learning experience. Students could, for example, select resources from a list for completing an assignment. Individualized learning is made possible through this method.
There are two primary types of online teaching content used by online driver models, some of which are delivered by instructors, others by technology such as live streaming services like Zoom. The method of synchronous teaching means that all the students in an entirely virtual class receive the same instructor-led instruction simultaneously. Live webinars are a popular way to hold this event, but text-based questions and answers following a video, podcast, or video presentation can also be used.
When students and teachers aren't in close proximity to each other, the online driver model is ideal since all content can be delivered through digital technologies. It may be the case that the teacher is unable to travel due to health reasons or because they live on the other side of the world from the students they will be teaching.
Hybrid machine learning uses intelligent machines and algorithms to perform classification and analysis of enormous amounts of data, which is then analyzed for the purpose of pattern recognition, data mining, and health monitoring. Data-driven organizations are those who understand that data and data-processing are the driving force behind the modern age. In conjunction with hybrid machine learning frameworks for their data processing needs, companies will be able to provide services faster and more precisely, maintaining an accurate understanding of their customers' needs and their own internal framework.
Despite the fact that blended learning relies on technology, the online driver model has fewer setup expenses than other models. Computer labs do not have to be set up in classrooms, for instance, because colleges do not have to provide them. A suitable device must be supplied by the student in most cases in order to access course content. The device can be anything from a handheld tablet to a quick desktop.
It will also be vital to provide appropriate technology to teachers at home. There may need to be an upgrade to their internet connection, but this won't always be necessary in order to offer streaming lessons and demonstrations in a higher resolution. An HD document camera, webcam, and good microphone will suffice for delivering course material in a curriculum.
Our developed hybrid learning method ensures the precision of classification. It works with precision with any data classification model.
It allows you to find and recover information from complicated data inferences.
We use the best predictive method in a hybrid learning framework for correct classification and regression.
It can fit in a wide range of industries, ranging from supply chain management to robotics.