Frost & Sullivan releases the '2024 China Intelligent Learning Device Market White Paper'

The development of intelligent education hardware in our country has a history of over 30 years, going through four development stages, gradually evolving from single-function devices to diversified and multi-scenario offerings. Chinese learning machines have evolved from electronic dictionaries and portable video learning devices to learning computers. With the advent of the digital age, rapid progress in AI large models, computing power, big data, etc., has accelerated the integration with learning machines. This has led to changes in real-time human-computer interaction methods and personalized language learning content generation. Intelligent learning machines will gradually evolve into adaptive intelligent learning devices.

Data source: Analysis by Frost & Sullivan

Driven by intelligent education hardware empowered by technology, favorable policies to boost industry development, clear application scenario layout and strong demand, the B-side and C-side markets of intelligent education hardware are developing in coordination, presenting broad prospects. Technological innovation, personalized educational needs, policy and investment support, as well as the improvement of consumer awareness have jointly driven the growth of the intelligent education hardware market.

With the release of the 'Double Reduction' policy, off-campus subject training has been restricted, and quality education has further developed. Tool-based consumer education smart hardware, which has the ability to integrate knowledge point resources and provide quality education content, has become popular among parents and students.

Data source: Analysis by Frost & Sullivan

Intelligent learning machines have a wide range of application scenarios. The application of adaptive education systems and the release of relevant industrial policies offer tremendous empowerment and enhancement opportunities for intelligent learning machine products.

Adaptive education refers to artificial intelligence education technology that is based on intelligent technologies such as artificial intelligence, big data, and the Internet of Things. It involves data mining and user profiling to tailor teaching methods to individual students' abilities and dynamically adjust teaching and practice content. It provides efficient personalized learning strategies.

Data source: Analysis by Frost & Sullivan

Currently, China is in a development stage of industry transition from partial intelligent adaptation to advanced intelligent adaptation.

Data source: Analysis by Frost & Sullivan

As the key core of intelligent learning machines, adaptive education systems empower these devices to provide personalized learning plans for students. They assist teachers in formulating teaching plans and strategies based on individual student learning situations, enabling schools to scientifically allocate teachers and curriculum resources based on an understanding of students' growth characteristics.

• Student sideIt provides students with personalized learning paths and content, optimizes the learning experience, enables students to more accurately understand their own learning situation, and clearly identify their strengths and weaknesses in the learning process. This is conducive to students adjusting their learning strategies, improving learning efficiency, choosing appropriate learning materials and methods, and also motivating them to explore and learn new knowledge.

   

• Teacher's SideThrough the student learning data collected by adaptive educational applications, teachers can quickly and accurately identify the weak areas and strong areas of the entire class or individual students during the learning process, helping them develop more personalized teaching plans and strategies, focusing on improving teaching quality and effectiveness.

   

• School sideIt enables schools or educational departments to have a deeper understanding of students' performance in different subjects and fields. Intelligent learning machines provide precise data support for curriculum setting and teaching arrangements, empowering schools to formulate more reasonable teaching plans, optimize educational resource allocation, and provide a solid data foundation for achieving true individualized instruction and promoting educational diversion strategies.

Data source: Analysis by Frost & Sullivan

With the continuous development of artificial intelligence technology, many education industry giants have extended their business boundaries and promoted the diversified and multi-scenario development of intelligent learning machine products. Currently, intelligent learning machines play an important role in language learning, question bank planning, curriculum construction, personal growth and learning reports, automatic evaluation and grading, error notebooks, and language learning scenarios.

Data source: Analysis by Frost & Sullivan

Adaptive educationBenefiting from the application of big data analysis and artificial intelligence technology, the growing demand for high-quality education, as well as national and local policy support, the market scale of adaptive education in China has been continuously expanding. As a key tool for realizing adaptive education, the demand for intelligent learning machines will grow in tandem, forming a virtuous cycle that jointly promotes the advancement of educational technology.

policyPolicies such as China's Education Modernization 2035, the "Double Reduction" policy, and the Regulations on the Development of Artificial Intelligence Industries encourage the development of artificial intelligence technology in the field of education. They advocate for the organic combination of large-scale education and personalized cultivation, which has had a profound impact and positive support on China's intelligent learning machine industry.

Large models are gradually being applied to intelligent learning machines, driving the development of adaptive education. Frost & Sullivan has conducted evaluations and comparisons of major large models in the education field based on their internal large model evaluation system. The report takes the multimodal adaptive education large model LAM (developed by Rongshou Ai) and the Spark Cognitive Large Model 4.0 Universal Model (developed by iFlytek) as representatives of Chinese educational large models, while the large language model GPT-4 (adopted by Khan Academy and Duolingo) is represented as an international large model.

Data source: Analysis by Frost & Sullivan

The education industry in China is undergoing technological innovation, with AI education enterprises leading new trends in the industry through their adaptive education systems, becoming key participants in the smart learning machine market. Looking ahead, Chinese education will continue to develop towards intelligence and personalization, and competition between AI education enterprises and traditional education and training companies and other market participants will drive overall progress and innovation in the industry.

According to the main business of enterprises, the core participants in the field of intelligent learning machines in China can be divided into four categories: AI education enterprises, traditional education hardware enterprises, Internet technology enterprises, and Internet education enterprises. Among them, AI education enterprises possess a more complete personalized education learning system, can provide personalized learning suggestions through learning behavior data, and with innovative concepts and advanced technologies, have the ability to attract investment and business recruitment, leading the transformation and upgrading of the intelligent learning machine industry.

Data source: Analysis by Frost & Sullivan