The St. Xavier’s school in Australia has a staff of 50-60 members and students about 700-800. The school has the majority of English speaking students, but still there are 3 other languages as the first language of other pupils. The client asked for a custom app for its school with the most user-friendly features and interactive experience.
Machine learning enabled teaching techniques are transforming edutech in 2017
We're living in the era where huge data are being consumed, shared and stored using various platforms and devices, rapidly. In industries like retail, banking and financial services, healthcare and even education, such data are being analyzed with various techniques to derive actionable insights.
One of those techniques is machine learning. It is a data analysis method having the ability to automate analytical model by adapting algorithms that constantly learn from data.
It allows computers to find insights without the need of any specific programming for data analysis.
The most innovative examples where machine learning is used are self-driving cars, effective web search, and practical speech recognition.
Teachers armed with performance-based data of students can derive personalized insights of each student's learning capability by using machine learning models.
Following are the five machine learning technologies based on such modeling that is used to enhance the learning experience in the education industry. Let’s explore how machine learning can be used in different ways…
Machine learning along with predictive analytics can help to find the difficult grasping areas and provides deep understanding. It recognizes the weak point of the student by analyzing the performance of the student.
Predictive analytics are also helping in the process of hiring the teacher. Hiring tools based on predictive analysis use certain key factors to identify effective teacher candidates.
Machine learning helps in the measurement, analysis, collection and reporting of data about learners and their contexts. Learning analytics is an impressive tool for an easy track of student knowledge.
The system first analyzes the whole record of student performance. Then it recommends next step, according to the performance of the student.
Machine learning techniques along with content analytics are very effective in organizing and optimizing the content modules. Content analytics systematize content like assignments, e-Books, video lectures, etc.
The software like IBM Watson and Gooru are the best examples to understand content analytics.
Dynamic scheduling searches for an optimal teaching policy that can help students to learn more efficiently. It uses learning analytics to schedule personalized learning experience.
Dynamic scheduling can effectively connect a student with the available teacher. For example, if a student is weak in biology, then the system will create a schedule.
The schedule will inform the student whenever the teacher is free to help.
Machine learning is a useful process to assign the grades to the students. Programs like WriteToLearn and Light side are the best example to explain the effect of machine learning on the grading system.
Implementing machine learning with student information system, assignments and tests can help in the effective assessment of each student’s progress individually.
Excellent WebWorld helps educational institutes and educators from across the globe to adopt an innovative yet effective approach that utilizes big data and latest technologies. Such digitization in the education industry empowers students and teachers with data-driven insights and growth.
The company has proven track record of delivering custom digital edtech solutions to schools, institutes, and universities that enhance the overall learning and teaching experience.
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