Primary and secondary education are crucial stages to build a strong foundation in each student before delving into specialised subjects in colleges and universities. To ace our present education system, students are required to have a profound understanding of concepts according to standardised curriculums, syllabus, and critical problem-solving skills.
In current school settings, classes are taught with 30 to 40 students per class. A “one size fits all” approach is not the most productive as everyone learns differently at a different pace.
To solve the problem, QLASSROOM established a research collaboration with Singapore's renowned university, Singapore University of Technology and Design (SUTD), to formulate a unique approach to help students learn better. Our research-backed curriculum is synthesised through a robust testing algorithm of Big Data. Our joint publication introduced the state-of-the-art synthesis that derives the concept of scalable personalised education by AI.
Self-Evolving Adaptive Learning (SEALTM)
Every student has their own distinct learning style and preference. Therefore, education can only be effective if the students learn at their ideal pace and structure. With our proprietary SEALTM engine, QLASSROOM enhances our academic programmes with personalised learning experiences. Our AI-enabled learning platform ensures that all students stay updated about their learning progress and knowledge profile.
Core Technology
Adaptive Assessment
Adaptive Assessment feature recommends questions to assess the student’s understanding, and in return, recommends learning content based on the students’ profile, learning preferences and the state of their knowledge. QLASSROOM’s comprehensive question tagging system allowed adaptive question creation and helps better profile student’s learning abilities.
Learning Analytic
QLASSROOM’s Learning Analytics service aggregates student activity data such as their question attempts and content interactions to provide insight into a student’s learning progress, as well as the effectiveness of various content. The analytic reports are generated and made accessible to students in visual form, short descriptions, and suggestions to guide students through their self-driven learning journey. The visual report also presented areas/topics the student is weak in, which enable students to understand their own performance.
Recommender
QLASSROOM’s dynamic recommendation takes into account the students’ learning objective and performance, consolidate the most suitable set of questions for the student. Our system optimise the recommended practice set to help student learn and improve at their comfortable speed and build students’ confidence in learning.
