Enhancing e-Learning Experiences through AI-ML based Platform

Enhancing e-Learning Experiences through AI-ML based Platform - LearningTree NextGen Pvt Ltd

The global e-learning market is poised to grow by USD 93.64 billion by 2024, according to a research report by Technavio. Increasing student engagement in classrooms through gamification has been instrumental in driving the growth of this segment. Moreover, the advent of modular learning and instant solutions has propelled gamification and e-learning to an engagement-retention and goal-based learning approach, which is the key for the new-age learners.

However, e-learners find extensive learning a heavy burden, and therefore, E-learning and gamification solution providers should provide them with solutions that will not make learning a burden and keep e-learners engaged and meet their requirements.

This is where LearningTree NextGen’s AI-ML based platform comes into the picture. Perfectly understanding the aforementioned requirements, the company has developed an adaptive platform that seamlessly integrates and delivers content, assessments, and learning adaptively and the learner not getting an impression of deviating or indulging in extensive curriculums.

The engagement models are gamified and inclusive to keep the learner motivated and provide satisfaction on completion of each learning milestone, thereby enabling immersive technology to deliver to the learner’s preferences. LearningTree NextGen’s platform is developed based on understanding user trends and preferences for content types, affinity to learning approaches and constant evaluation and feedback through a gamified assessment approach, which keeps the learner engaged and enables goal-based learning for all user types.

Focused approach in creating Products and Solutions

The company follows a focused approach to creating products and solutions that help improve the learning experience and enable the learner to be more informed of the learning progress. LearningTree NextGen has comprehensive features of learning and assessments that meet and exceed the requirements of the learning space. While engaging learners of all age groups, the platform intuitively tracks, monitors, analyses and delivers to the learner the best solution that can create the most impact in their learning progress.

ML algorithms for detailed tracking and analysis

LearningTree NextGen’s built-in machine learning algorithms enable detailed tracking and data analysis of each learner’s usage and consumption, drawing patterns in learning styles and providing insights to drive the Artificial Intelligence engines that are built in to deliver effective and specific learning components that enhance the learner’s experience.

LearningTree NextGen provides a whole gamut of services and products that cater to the end-to-end requirements for learning and assessments.

“A multitude of players in this segment have come up with innovative solutions but most of them address a single problem or a part of the entire process. But we provide a whole gamut of services and products that cater to the end-to-end requirements for learning and assessments,” says Sasi Kant, CEO of LearningTree NextGen Pvt Ltd.

Well-Established, End-to-End Product and Process Architecture

LearningTree NextGen fields a robust and scalable product that has been tried and tested in multiple geographies and different learning needs for Schools, Institutes, Corporates, and Universities. Not just that, LearningTree NextGen also has a well-established, end-to-end product and process architecture that is ready to meet and exceed requirements for the current market aspirations and this is what differentiates LearningTree NextGen from the other players in this segment.

Customer-Centric approach

LearningTree NextGen continuously strives to improve its platform and solutions that enhance content availability and delivery to any medium through engagement and interaction. “We build our solutions based on a customer-centric approach and also conduct intensive research on consumption patterns, behaviours, and feedback. We hope to fulfil the needs for a technology-driven platform that can deliver to these and many other requirements as deemed necessary, now and in the future,” concludes Sasi Kant.

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