With a precise objective of providing personalised assessments to individual students, Next Education India Pvt. Ltd., India’s leading education solutions provider, has recently launched machine learning-powered adaptive test for students in grades 6 to 10.
The adaptive test implemented by Next Education is based on Item Response Theory (IRT) to gauge the chapter-wise level of knowledge gained by a student in a short span, thereby driving deeper learning. This innovative approach ensures that students can challenge their current ability and knowledge while remaining focused throughout the test. The tests are available for schools registered on the NextLearning Platform. Individual students can also take them for free on the company’s self-learning solution, LearnNext.
Through this new feature, Next Education enables learners to evaluate themselves at any time and a place with an exhaustive bank of 60,000 questions. Moreover, the award-winning in-house content consisting of HD animated videos and digital books available on LearnNext/NLP further allows the students to independently bridge the gaps in their learning.
Speaking on the success of their newly launched adaptive test, Mr Beas Dev Ralhan, CEO & Co-founder of Next Education, said, “Education should meet the requirement of each and every student, which is why there is a need to precisely evaluate where individual learners stand at the beginning of an academic course. Adaptive tests based on IRT are the best possible way of such an assessment. The sophisticated ML algorithm used to design the test is adept at adjusting the difficulty of the question to suit the level of the student. The program keeps throwing questions until the ability of the student is measured satisfactorily.”
“We have an extensive database of millions of responses collected anonymously since 2007, which helps us ensure high accuracy for our adaptive tests. Such tests not just reduce the duration of examination by 50-75% compared to standard fixed tests, they also act as a morale booster since the chances of discouragement or boredom are reduced among the examinee. It also reduces the pressure on teachers of creating tests suited to the abilities of individual learners, enabling them to assess and design personalised learning paths for them,” he added.
Within 2 months of its launch, Next Education’s adaptive tests have been attempted by more than 63,000 students looking to substantially improve their exam percentiles.
Aditya Batra, a 7th standard student from Bhavan’s School, Hinganghat, and a KBC winner, scored 91 percentile by taking the adaptive test through the Next Education platform. He said, “It was a wonderful experience. Every question was from our course curriculum, which I had practised before. I was also fully engaged throughout the test and never felt disinterested. Through this test, I could accurately assess my preparation of each topic.”
Sharvari Mude, another 7th standard student from Bhavan’s School, Hinganghat, and the winner of the Homi Bhabha Balvagyanik Competition, scored a remarkable 99 percentile in the adaptive test attempted in her school. “It was an interesting exercise. The questions helped us to recognise how much we have actually learned about a particular chapter or topic. It was fun attempting the test. I would recommend every student to take it and would love to attempt it once again at home,” she added.
The concept of the computerised adaptive test is used widely in tests such as GRE, TOEFL and SAT developed by the Educational Testing Service, as well as GMAT conducted by the Graduate Management Admission Council for admissions to universities in the USA. The National Testing Agency (NTA) in India has also proposed the use of adaptive assessments to conduct entrance examinations for higher educational institutions — JEE Main, NEET UG and NET— so as to bring higher reliability and for assessing the actual aptitude of aspirants. By launching this approach on its platform for school students at an early age, Next Education aims to create an adaptive learning environment that can appropriately assess individual differences of students and create customised learning paths for them.