Technology peripherals
AI
Breaking through the boundaries of school education, what potential does artificial intelligence have in the education industry?
Breaking through the boundaries of school education, what potential does artificial intelligence have in the education industry?
Education, talent, and science and technology are the basic and strategic supports for comprehensively building a modern socialist country. "Smart education" is the key to adapt to the development of the times, keep up with the pace of the times, and cultivate "smart talents" in the new era. As a new classroom format, "smart classroom" broadens the traditional teaching model through the application of new technologies such as 5G, big data, cloud, and artificial intelligence, making the role interaction between teachers and students a brand-new teaching model.
The key to the smart transformation of the education industry is that teachers can master the characteristics of different technologies and actively use information technology in teaching according to different teaching methods and content. Among them, artificial intelligence technology continues to deepen All aspects of education and play an indispensable role. Today, let’s discuss in depth the potential of artificial intelligence in the education industry and its in-depth application scenarios.
What are the applications of artificial intelligence in education?
In recent years, with the continuous development of artificial intelligence technology, it has been widely used in various fields of the education industry and plays a pivotal role in the education field. Nowadays, with the help of artificial intelligence, the school learning environment is becoming more and more intelligent. Smart classrooms, smart recording rooms, smart libraries, smart writing systems, and campus safety warning systems all have good application prospects. For example, cameras installed at school gates can identify bad elements; classrooms are equipped with photoelectric pens that can digitize notes written by students and compare them with what they have written. The above scenario is a manifestation of the increasingly intelligent learning environment and reflects the charm of artificial intelligence.
While the learning environment is becoming intelligent, students’ learning process is also becoming more and more intelligent. Artificial intelligence will support students’ learning. For example, data can be used to describe students' knowledge structure and ability structure, allowing teachers to better understand students' learning status and provide them with appropriate learning resources based on their needs. For another example, detect your classroom situation, observe your performance, analyze your expression, and determine whether you are tired. If you are too tired, your learning efficiency will decrease. Also, virtual reality can be combined with artificial intelligence to provide students with an enhanced virtual learning environment. Through virtual scenes, you can instantly go back to more than 2,000 years ago and understand the history and evolution at that time. Here, artificial intelligence can provide both good and abundant support for the learning environment and learning process.
Not only that, AI can also assist teachers in evaluating the learning process. Artificial intelligence can analyze your knowledge, core abilities, physical fitness, and mental state, and realize the single-subject knowledge evaluation of educational evaluation to a comprehensive comprehensive evaluation. It can allow us to transform from the only one final assessment in the past to a process. assessments that can be embedded into your learning process to assess student abilities. Overall, artificial intelligence's evaluation of the learning process can significantly reduce teachers' work pressure.
In addition, artificial intelligence plays a big role in teachers’ work, equivalent to teachers’ assistants. For example, intelligent question setting, intelligent grading, intelligent scoring, intelligent tutoring, various assessment reports, and personalized feedback for different students. Our teachers have to deal with 40-50 students at the same time. Due to their limited time and energy, they cannot understand their specific situations. Using artificial intelligence technology to provide personalized feedback for each student based on different problems, thereby achieving personalized support for students and achieving scale and personalization, this is what China's Education Modernization 2035 aims to achieve.
Breaking through the boundaries of education, how to do a good job in smart education?
Recently, at the World Digital Education Conference organized by the Ministry of Education and the Chinese National Committee for UNESCO, the Chinese Academy of Educational Sciences officially released the "China Smart Education Blue Book (2022)" and the 2022 China Smart Education Blue Book at home and abroad. Smart Education Development Index Report. In addition to affirming the value of artificial intelligence, this blue paper also puts forward new guiding opinions in terms of core concepts, system architecture, teaching paradigms, educational content, and educational governance.
The blue book believes that smart education is a new form of education in the digital era, which is qualitatively different from the education form in the industrial era. At the conceptual level, smart education will empower education reform in an all-round way through technology empowerment and data drive, systematically build a new ecology of education and social relations, provide suitable education for each learner, and turn the millennium dream of teaching students in accordance with their aptitude into a reality. . In terms of system structure, smart education will break through the boundaries of school education, promote the diversified combination of various education types, resources, elements, etc., and promote a system of collaborative education among schools, families, and society.
In terms of teaching paradigm, smart education will integrate physical space, social space and digital space, innovate educational and teaching scenarios, promote the integration of human skills, cultivate a cross-grade, cross-class, cross-discipline, and cross-time and space learning community, and achieve large-scale The organic combination of education and personalized training. In terms of educational content, smart education establishes a digital knowledge map based on systematic logical relationships of knowledge points, innovates content presentation methods, makes learning a wonderful experience, and cultivates learners' high-order thinking ability, comprehensive innovation ability, and lifelong learning ability.
In addition, smart education will take data governance as the core and digital intelligence technology as the driving force, promote the overall reengineering of education management and business processes, and enhance the modernization of the education governance system and governance capabilities. Overall, smart education integrates artificial intelligence and other related technologies, is based on the reality of the initial stage of smart education, and provides a quantitative assessment of the development level of smart education in China. Starting from these five aspects will also promote the development of smart education.
Written at the end
The times are developing. In 2022, China implemented the national education informatization strategy, built a national smart education public service platform, and built the world's largest education and teaching resources, accumulating It has been visited 5.87 billion times and has users in more than 200 countries and regions. It has played an important role in supporting the anti-epidemic policy of "continuing learning even if classes are suspended" and narrowing the digital divide. It has taken the lead in opening up the road to smart education. In the future, with the help of emerging technologies such as big data, artificial intelligence, and cloud computing, the development of smart education will surely usher in a new stage of development.
The above is the detailed content of Breaking through the boundaries of school education, what potential does artificial intelligence have in the education industry?. For more information, please follow other related articles on the PHP Chinese website!
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
AI Hentai Generator
Generate AI Hentai for free.
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1377
52
Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions
Jun 28, 2024 am 03:51 AM
This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP
Context-augmented AI coding assistant using Rag and Sem-Rag
Jun 10, 2024 am 11:08 AM
Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application
Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations
Jun 11, 2024 pm 03:57 PM
Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it
Seven Cool GenAI & LLM Technical Interview Questions
Jun 07, 2024 am 10:06 AM
To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text
To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework
Jul 25, 2024 am 06:42 AM
Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A
Five schools of machine learning you don't know about
Jun 05, 2024 pm 08:51 PM
Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing
SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time
Jul 17, 2024 pm 06:37 PM
Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S
Laying out markets such as AI, GlobalFoundries acquires Tagore Technology's gallium nitride technology and related teams
Jul 15, 2024 pm 12:21 PM
According to news from this website on July 5, GlobalFoundries issued a press release on July 1 this year, announcing the acquisition of Tagore Technology’s power gallium nitride (GaN) technology and intellectual property portfolio, hoping to expand its market share in automobiles and the Internet of Things. and artificial intelligence data center application areas to explore higher efficiency and better performance. As technologies such as generative AI continue to develop in the digital world, gallium nitride (GaN) has become a key solution for sustainable and efficient power management, especially in data centers. This website quoted the official announcement that during this acquisition, Tagore Technology’s engineering team will join GLOBALFOUNDRIES to further develop gallium nitride technology. G
