Brain Racers Utilizes AI to Personalize Learning Experience for Students
Brain Racers, an esports platform enhanced with AI for educational purposes, has introduced an intelligence engine to proactively address the issue of learning loss. This innovative tool employs a combination of statistical analysis and machine learning to provide a tailored learning experience to each student, thereby expediting their learning and providing them with an edge over conventional education channels. Brain Racers is already successfully engaging students by gamifying curriculum-based content, and it also utilizes esports to increase student motivation.
Prior to 2020, the majority of learning loss in schools was typically attributed to the summer break when students tended to spend less time actively engaging in learning activities. It was not uncommon for students to experience a setback of up to a month, especially in subjects such as reading and math. However, educators had grown accustomed to this annual adjustment and were prepared for it.
However, when the COVID-19 pandemic resulted in school closures and students transitioning from traditional classrooms to home-based learning environments, the effects of an unregulated learning system on student academic performance were unknown. It was widely anticipated that the impact of this disruption would be significant.
An article from the Brookings Institution presented the following information:
‘We tracked changes in math and reading test scores across the first two years of the pandemic using data from 5.4 million U.S. students in grades 3 - 8. We focused on test scores from immediately before the pandemic (fall 2019), following the initial onset (fall 2020), and more than one year into pandemic disruptions (fall 2021).
Average fall 2021 math test scores in grades 3 - 8 were 0.20 - 0.27 standard deviations (SDs) lower relative to same-grade peers in fall 2019, while reading test scores were 0.09 - 0.18 SDs lower. This is a sizable drop. For context, the math drops are significantly larger than estimated impacts from other large-scale school disruptions, such as after Hurricane Katrina-math scores dropped 0.17 SDs in one year for New Orleans evacuees.’
The AI-driven engine of Brain Racers has the capability to comprehend and adapt to the distinct learning requirements of each student by analyzing their gameplay results, resulting in more efficient progress. Brain Racers has devised a unique system that places a strong emphasis on student engagement, with the added support of a guided teacher, resulting in learning time reductions of between 30 to 60 percent.
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Providing individualized attention to students is an ideal educational approach, but due to time constraints and high student-to-teacher ratios, it is often unfeasible. Brain Racers offers teachers supplemental support that enables them to focus on enhancing the quality of their instructional output, thereby overcoming these limitations. By gaining more time and concentrating on core areas of importance, both students and teachers can experience positive impacts.
According to Gianender Khanna, CEO of Brain Racers, their personalization engine will continue to evolve and improve through a combination of creative content, gamified mechanics, and pedagogical modalities. This innovative approach has resulted in accelerated learning outcomes that have exceeded their initial expectations.
Through the utilization of the software's data, teachers can detect areas where students are struggling and tailor their learning experience to address these deficiencies, thereby enhancing the overall learning experience.
Gianender emphasizes that it's not just about accelerating the pace towards mastery of the curriculum, but also about providing a fun and sustainable path forward for students. This involves curating content that enables students to answer questions correctly, boosting their confidence and fostering a love for the subject matter.
Due to the fact that personalization is the primary focus of Brain Racers' deep learning engine, their distinctive dataset cannot be replicated. As the engine continues to learn and develop, it becomes increasingly intelligent, positioning Brain Racers to revolutionize the early education sector.
The AI team, spearheaded by Koyuki Nakamori, has over 15 years of experience in machine learning, including a previous stint as the Head of Machine Learning for Headspace. Qi Shao also brings an additional 10 years of experience in machine learning to the team.
The newly developed AI-powered engine is currently in the beta testing phase and is anticipated to be rolled out to additional teachers and students in stages.