What is Zhida AI
Zhida AI is an AI intelligent teaching assistant built for all educational scenarios, breaking down single-stage barriers and covering the three major fields of K12 basic education, vocational education, and special education. Zhida AI features a built-in education-specific large model and a knowledge base of over ten million entries, supporting core functions such as intelligent lesson preparation, question generation and test paper assembly, homework grading, learning condition analysis, and essay tutoring, while also providing the ability to quickly produce teaching resources such as PPTs, mind maps, and experimental courseware. It adopts a membership and points purchase model, providing frontline teachers, students, and parents with a one-stop solution for teaching, learning, research, and management, helping to advance the digital transformation of education and the implementation of personalized teaching.

Main functions of Zhida AI
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Intelligent lesson preparation: Generate various regular and specialized lesson plans with one click, covering teaching needs across all subjects.
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Question generation and test paper assembly: Accurately generate questions and assemble test papers across all subjects, supporting intelligent test paper generation and resource library development.
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Homework grading: Intelligently grade test papers, essays, and practical training reports, with automatic statistics and analysis of learning conditions.
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Learning condition analysis: Precisely identify students' weak points in learning and output professional learning condition analysis reports.
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Teaching resource generation: Quickly generate diverse teaching materials such as PPTs, mind maps, and experimental courseware.
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Student self-directed learning: Provide self-directed learning services such as Q&A tutoring, consolidation of incorrect questions, and personalized training.
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Home-school communication: Includes auxiliary functions such as student management and home-school communication to improve collaboration efficiency.
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School-based knowledge base: Supports the construction of school-based private knowledge bases and the creation of customized intelligent agents.
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Cross-regional collaboration: Enables cross-regional sharing and collaboration of teaching resources.
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Vocational education specialization: Provides course design, project-based teaching, skills question bank development, and practical training report generation.
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Special education customization: Customizes exclusive lesson plans, visualized teaching content, and personalized training plans.
How to use Zhida AI
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Visit the official website to register: Go to the Zhida AI teaching assistant official website https://www.zida.school/ to complete account registration and login.
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Choose identity scenario: According to the identity of teacher, student, or parent, choose the corresponding function module entry.
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Use core functions: Enter teaching requirements to generate teaching resources such as lesson plans, test papers, and PPTs with one click.
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Intelligent grading and analysis: Upload homework or test papers to obtain intelligent grading results and learning condition analysis reports.
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Personalized learning: Students can use functions such as Q&A tutoring and consolidation of incorrect questions for self-directed learning improvement.
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Knowledge base management: Teachers can build school-based private knowledge bases and create customized intelligent agents to achieve resource sharing.
Core advantages of Zhida AI
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Full-scenario coverage: Breaks down single-stage barriers, covering all types of educational scenarios including basic education, vocational education, and special education.
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Full-process intelligence: From lesson preparation, teaching, homework, and evaluation to learning condition analysis, forming a complete teaching loop.
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Massive knowledge base: Built-in knowledge base with over ten million educational resources, supporting precise services and resource access across all subjects.
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Personalized Customization: Supports the construction of school-based private knowledge bases and the creation of custom agents to meet differentiated teaching needs.
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Efficient Burden Reduction: Automates repetitive teaching tasks, helping teachers save a significant amount of time and energy.
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Data-Driven: Precisely identifies learning weaknesses, outputs professional learning analytics reports, and guides precise teaching decisions.
Comparison of Zhida AI with Similar Competitors
| Comparison Dimensions | Zhida AI Teaching Assistant | Spark Teacher Assistant | Seewo Whiteboard |
|---|---|---|---|
| Product Positioning | Educational AI community with a built-in education-specific large model and over ten million knowledge resources, covering the full scenarios of teaching, learning, research, and management | A teacher AI assistant based on the Spark Cognitive Large Model, focusing on "efficient preparation, precise teaching, personalized learning, and scientific management" | An interactive multimedia teaching platform designed specifically for informatized teaching, covering the full process of "lesson preparation—instruction—post-class review" |
| Educational Stages Covered | All types of educational scenarios: basic education (primary/junior high/senior high), vocational education, and special education | Mainly basic education, covering all K12 stages, while also including higher education and vocational education | All stages and subjects from preschool to senior high, extending to vocational education practical training and family education |
| Core Functions | Intelligent lesson preparation, question generation and paper assembly, homework grading (exam papers/essays/practical training reports), learning analytics, PPT/mind map/experimental courseware generation, Q&A tutoring, wrong-question consolidation, school-based knowledge base, custom agents | Spark Teacher Assistant (instructional design/courseware creation/learning diagnosis), Spark Smart Blackboard (multimodal interaction/virtual human teaching assistance), Spark Intelligent Grading Machine (OCR grading/original paper trace retention), AI Learning Companion (personalized Q&A/wrong-question attribution) | AI lesson preparation (one-click generation of instructional design/courseware/lesson plans), classroom interaction (gamified templates/random roll call/group competitions/voting questionnaires), cloud courseware synchronization, subject tools (math drawing board/simulation experiments), mind maps, knowledge capsules (micro-lesson recording), AI agents embedded in courseware, classroom activity library |
| Technology Foundation | Education-specific large model + over ten million massive knowledge resources | iFlytek Spark Cognitive Large Model (V4.0 Turbo), featuring multimodal understanding and recommendation, OCR recognition, knowledge graphs, and voice interaction | Seewo Teaching Large Model 2.0, supporting localized AI computing power deployment and offline applications |
| Hardware Dependence | Pure software/SaaS platform, no hardware dependence, supports web-based use | Strong hardware ecosystem: Spark Smart Blackboard, intelligent grading machine, dot matrix pen, AI learning machine, etc., with integrated software and hardware | Combination of software and hardware: Seewo Whiteboard software, smart blackboard, all-in-one machine, PC, mobile end, supports web version; mobile phone can control the large screen and upload photos |
| AI Interaction Form | Conversational AI teaching assistant, custom agents, role-playing agents | Virtual human teaching assistance, AI learning companion, voice smart pen control, real-time classroom interaction | AI lesson preparation assistant, conversational agents embedded in courseware (such as role-playing as "Emperor Chongzhen" and "Van Gogh"), classroom interactive games, mobile phone scan-code teaching |
| Learning Analytics | Accurately identify weak points, output professional academic analysis reports, and automatically compile wrong-answer data statistics | Based on the big data precision teaching system, generate personalized learning manuals, academic radar charts, and error-cause tree analysis | Real-time statistics of classroom activity data (answer accuracy rate, etc.); the intelligent classroom feedback system generates multi-dimensional analysis reports (supporting hardware required) |
| Resource Generation | One-click generation of lesson plans, PPTs, mind maps, experiment courseware, picture books, and speeches | Intelligently generate instructional designs, courseware, review test papers, micro-lesson recordings, mind maps, and variant question training | Automatically generate instructional designs, courseware, and lesson plans after entering a topic; built-in 300,000+ online question bank, 5,000+ course videos, 800+ mathematics drawing board lesson examples, with the resource library updated daily |
| Grading Capability | Intelligent grading of test papers, essays, practical training reports, English continuation writing, and dictation cards | The Spark Intelligent Grading Machine supports automatic grading of objective questions, annotation of key points for subjective questions, sentence-by-sentence detailed grading of essays, and original paper trace retention | Real-time feedback statistics for classroom activities; subjective question grading capability is limited, mainly relying on classroom interactive answering and answer device collection |
Application Scenarios of Zhida AI
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Daily Teaching Preparation: Quickly generate teaching resources such as lesson plans, courseware, and mind maps.
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Exam and Assessment Management: Intelligent question generation and test paper assembly, test paper grading, and academic analysis report generation.
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Homework Tutoring and Feedback: Essay grading, practical training report grading, wrong-question consolidation, and personalized training.
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Vocational Education Practical Training: Course design, project-based teaching, skill question bank construction, and practical training report generation.
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Special Education Support: Customized lesson plans, visualized teaching content, and personalized training plans.
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Teaching Research Management Collaboration: Teaching research planning, cross-regional resource sharing, and school-based knowledge base construction and management.