Method, device, equipment and medium for large unit learning design

Abstract

The invention relates to the technical field of education and learning, and discloses a method, device and equipment for large unit learning design and a medium, and the method comprises the steps: obtaining user input data based on a preset large unit learning design template; in the process of obtaining the data input by the user, if the data input by the user does not meet the requirement of a preset rule, based on the preset rule, providing guide type prompt information, responding to the modification of the data input by the user by the user, and re-obtaining the data input by the user, and determining the preset rule based on a preset large unit learning design template; and generating a large-unit learning design based on the user input data meeting the preset rule. The design efficiency can be greatly improved, the preset large unit learning design template provides a clear and normative design framework for a designer, so that the designer can quickly and clearly know the direction and key points of design, the process of exploring from zero is avoided, and the accuracy of the whole large unit learning design can be ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of education and learning, and particularly to a method, device, equipment and medium for large unit learning design. Background Art

[0002] Large unit teaching design refers to a structured and scientifically designed overall plan with multiple teaching types centered around a large theme or task, which analyzes, integrates, reorganizes and develops learning content to form a structured plan with clear elements such as theme, goal, task, situation, activity or evaluation. With the continuous development of educational concepts and the progress of technical means, how to more efficiently and accurately conduct large unit learning design for knowledge integration and interdisciplinary connection has become an urgent problem in the current educational field.

[0003] In related technologies, learning design often relies on experience and intuition to organize content, manually analyzes and classifies teaching objectives and resources, which is time-consuming and prone to omissions or repetitions, and it is difficult to effectively monitor and adjust the overall structure and effect of the design. Summary of the Invention

[0004] In view of this, the present invention provides a method, device, equipment and medium for large unit learning design to solve the problem that it is difficult to effectively monitor and adjust the overall structure and effect of learning design in related technologies.

[0005] In a first aspect, the present invention provides a method for large unit learning design, the method comprising: obtaining user input data based on a preset large unit learning design template; during the process of obtaining the user input data, if the user input data does not meet the requirements of a preset rule, providing guided prompt information based on the preset rule, and in response to the user's modification of the user input data, re-obtaining the user input data, wherein the preset rule is determined based on the preset large unit learning design template; generating a large unit learning design based on the user input data that meets the preset rule.

[0006] In an optional embodiment, the foregoing method for large unit learning design further comprises presenting the process of generating the large unit learning design: obtaining structural elements in the process of generating the large unit learning design; determining the association relationship between each of the structural elements; presenting the structural elements and the association relationship based on a preset chart type.

[0007] In an alternative embodiment, the preset large unit learning design template includes: lesson learning designs generated based on unit learning planning; unit learning designs generated based on a preset unit learning design template; wherein the unit learning design includes at least one of the lesson learning designs, and the unit learning design is implemented based on the lesson learning designs.

[0008] In an alternative embodiment, if the user input data does not meet the requirements of the preset rules, guided prompt information is provided based on the preset rules, including: if the user input data does not meet the content structuring requirements, based on the guided prompt information, the user is prompted to organize the content of the large unit learning design in a preset order; if the user input data does not meet the format requirements of the large unit learning design, based on the guided prompt information, the user is prompted to determine the content of the large unit learning design based on the format requirements; if the user input data does not meet the language specification requirements, based on the guided prompt information, the user is prompted to determine the content of the large unit learning design based on the language specification requirements, wherein the preset rules include the content structuring requirements, the format requirements, and the language specification requirements.

[0009] In an alternative embodiment, obtaining the structural elements in the process of generating the large unit learning design includes: obtaining a combination of one or more of the following structural elements, the structural elements included in the unit learning design cascading relationship, the structural elements included in the unit task design cascading relationship, the structural elements included in the unit evaluation design cascading relationship, and the structural elements included in the lesson planning analysis cascading relationship.

[0010] In an alternative embodiment, determining the association relationships between the structural elements includes determining the association relationships between the structural elements included in the unit learning design cascading relationship: based on the learning objectives of the large unit learning design, determining the core competencies of the large unit learning design; based on the core competencies, determining the big ideas that support subject understanding; based on the big ideas, setting big goals, and based on the big goals, representing the knowledge that students should master through the large unit learning design; determining the big strategies for achieving the big goals, and based on the big strategies, representing learning methods; based on the big strategies, cultivating students' ability to solve big problems; achieving the big goals by completing big tasks, and based on the big tasks, representing the core tasks of the large unit learning design; generating unit evaluations based on students' performance in solving the big problems; based on the foregoing structural elements, determining the lesson planning, and based on the lesson planning, achieving the learning objectives.

[0011] In an alternative embodiment, the lesson learning design includes one or a combination of several of the following: learning content analysis, learner analysis, soul goal design, learning strategy design, learning tasks, learning session design, learning activity design, and tool design; the unit learning design includes one or a combination of several of the following: unit learning theme, unit teaching analysis, unit goal design, unit teaching design, learning evaluation, and lesson planning.

[0012] In a second aspect, the present invention provides an apparatus for large unit learning design, the apparatus comprising: an acquisition module for acquiring user input data based on a preset large unit learning design template; a preprocessing module for providing guided prompt information based on the preset rules if the user input data does not meet the requirements of the preset rules during the process of acquiring the user input data, and re-acquiring the user input data in response to the user's modification of the user input data, wherein the preset rules are determined based on the preset large unit learning design template; and a generation module for generating a large unit learning design based on the re-acquired user input data and the user input data that meets the preset rules.

[0013] In a third aspect, the present invention provides a computer device comprising: a memory and a processor, which are communicatively connected to each other, wherein the memory stores computer instructions, and the processor executes the computer instructions to execute the method for large unit learning design according to the first aspect or any corresponding embodiment thereof.

[0014] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, and the computer instructions are used to cause a computer to execute the method for large unit learning design according to the first aspect or any corresponding embodiment thereof.

[0015] In a fifth aspect, the present invention provides a computer program product comprising computer instructions, and the computer instructions are used to cause a computer to execute the method for large unit learning design according to the first aspect or any corresponding embodiment thereof.

[0016] Obtaining user output data based on a preset large-unit learning design template can greatly improve the design efficiency. The preset large-unit learning design template provides a clear and standardized design framework for designers, enabling them to quickly clarify the design direction and key points, and avoiding the process of groping from scratch. For user input data that does not meet the preset rules, providing guided prompt information can help designers avoid common design misunderstandings, provide targeted suggestions, prevent users from deviating from the preset design standards due to improper operations, ensure the accuracy of the overall large-unit learning design, effectively monitor and adjust the large-unit learning design process, ensure the organic coordination and harmony among various design elements, and further enhance the systematicness and consistency of the design. Brief Description of the Drawings

[0017] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the related art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the related art. Obviously, the following-described drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0018] Figure 1 Shows a flowchart of the method for large-unit learning design according to an embodiment of the present invention;

[0019] Figure 2 Shows a schematic diagram of the cascading relationship of unit learning design;

[0020] Figure 3 Shows a schematic diagram of the cascading relationship of unit task design;

[0021] Figure 4 Shows a schematic diagram of the cascading relationship of unit evaluation design;

[0022] Figure 5 Shows a schematic diagram of the cascading relationship of lesson planning analysis;

[0023] Figure 6 Shows a schematic diagram of guided prompt information;

[0024] Figure 7 Shows a schematic diagram of another guided prompt information;

[0025] Figure 8 Shows a schematic diagram of the structure of the device for large-unit learning design;

[0026] Figure 9 Is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Embodiments

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0028] With the rapid development of information technology and artificial intelligence technology, learning design based on data analysis has gradually become an effective way to solve the problem of efficiently carrying out large-unit learning design, especially having significant advantages in interdisciplinary integration and problem-oriented large-unit learning design. Automated data analysis of learning design can not only improve the design efficiency but also make real-time adjustments according to the changes in the design process, thereby improving the accuracy and flexibility of learning design.

[0029] However, although there are already some learning design tools on the market, many still focus on basic information input and single data management, and it is difficult to provide a structured and visual display of the design process, resulting in designers being unable to clearly see the internal connection between the design process and the structure, lacking intuitive design effect analysis and timely and clear feedback, and being prone to overlooking potential problems or optimization spaces. Therefore, how to provide a comprehensive and highly intelligent learning design tool has become the key to the current technological development.

[0030] According to an embodiment of the present invention, a method embodiment for large-unit learning design is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0031] In this embodiment, a method for large-unit learning design is provided, which can be used in mobile terminals such as mobile phones, tablet computers, or desktop computers, and can be applied to technical fields such as teacher lesson preparation, teaching research, big data analysis, and applications. Figure 1 The flowchart of the method for large-unit learning design according to the embodiment of the present invention is shown, as Figure 1 shown, the process includes the following steps:

[0032] Step S101, based on a preset large-unit learning design template, obtain user input data.

[0033] In this step, after the user registers a personal account, the user can fill in the learning design data required by the preset large unit learning design template. During the personal account registration process, the basic information that the user needs to fill in is mandatory information. During the personal account registration process, the basic information filled in by the user belongs to the user input data.

[0034] The preset large unit learning design template includes a unit learning design template and a lesson learning design template. Specifically, it may include unit basic information, learning objectives and key points and difficulties, overall teaching ideas and structures, lesson teaching designs, teaching reflections and improvement measures, evaluation methods, and large task designs, etc.

[0035] The tool for large unit learning design generated based on the present invention supports the user to create a large unit learning design online, can record and store the learning design data generated during the user design process, and display it in a list form on the tool page. These learning design data can be stored in the storage module in the background for subsequent calculation and analysis. At the same time, the user can preview the entered learning design data in real time.

[0036] Step S102, during the process of obtaining user input data, if the user input data does not meet the requirements of the preset rules, based on the preset rules, provide guided prompt information, and in response to the user's modification of the user input data, re-obtain the user input data, wherein, based on the preset large unit learning design template, determine the preset rules.

[0037] In this step, the preset rules can be determined based on the requirements for the learning design content in the preset unit learning design template. Through the preset rules, according to the content entered in the input box in the preset unit learning design template, display the prompt content corresponding to the foregoing input content. Based on the preset rules, it can help the designer understand and follow specific standards and formats. At the same time, the preset rules provide a clear framework and guiding principles for generating guided prompt information.

[0038] The user input data can be monitored in real time, the position where the user clicks on the input box in the preset large unit learning design template can be located, the user's interaction behavior can be dynamically recognized, and the activation status of each input box can be recorded to respond to the user operation in real time; the prompt information and examples are displayed in a pop-up window in the form of pattern matching of the input content according to the preset rules, and the content of the pop-up window will be automatically updated according to the context of the input.

[0039] Specifically, based on a preset large unit learning design template, interpret the content of the teaching material unit, determine the attribution of the learning task group, and accordingly formulate rules for the format, type, range, etc. of the user input data. According to the unit learning objectives and key points and difficulties, clarify the key information and necessary details that the user input data should contain. The guided prompt information can provide modification suggestions or examples to help the user understand and correct the input data. After the user enables the "user prompt information" and clicks on the input box in the preset large unit learning design template, relevant guided prompt information can be prompted based on the real-time monitored input content and the preset rules. The guided prompt can be in the form of a pop-up window or voice. After the user modifies the input data according to the guided prompt information, the modified data can be retrieved and verified again, repeating the above verification and prompting process until the user input data meets the requirements of the preset rules. This can help designers avoid common design misunderstandings, provide targeted suggestions and specifications, and prevent users from deviating from the preset design standards due to improper operations.

[0040] In this way, based on the guided prompt information and the preset large unit learning design template, the learning design data filled in by the user can be identified and transformed, enabling the collected and transformed data to be standardized, thus making the transformation process of the learning design data clearer and more systematic, and avoiding the complexity and uncertainty of the learning design process. The standardized design provides a convenient basis for users to adjust and optimize, supports the continuous improvement process, and the standardized template and data format make it easier for different team members or designers to collaborate through sharing.

[0041] Step S103: Generate a large unit learning design based on the user input data that meets the preset rules.

[0042] In this step, the user fills in the learning design data according to the preset large unit learning design template and the guided prompt information to generate a standardized and content-coherent and collaborative large unit learning design.

[0043] The method for large unit learning design provided in this embodiment can greatly improve the design efficiency by obtaining the user output data based on the preset large unit learning design template. The preset large unit learning design template provides a clear and standardized design framework for designers, enabling them to quickly clarify the design direction and key points and avoiding the process of groping from scratch; for the user input data that does not meet the preset rules, guided prompt information is provided, which can help designers avoid common design misunderstandings, provide targeted suggestions, and prevent users from deviating from the preset design standards due to improper operations, ensuring the accuracy of the overall large unit learning design, effectively monitoring and adjusting the large unit learning design process, and ensuring the organic cooperation and coordination among various design elements, further enhancing the systematicness and consistency of the design.

[0044] In some alternative embodiments, the aforementioned method for large unit learning design further includes presenting the process of generating a large unit learning design: obtaining the structural elements in the process of generating a large unit learning design; determining the association relationships between the structural elements; and presenting the structural elements and the association relationships based on a preset chart type.

[0045] In this embodiment, the structural elements are the core elements of data analysis and are key numerical values used to evaluate and measure specific goals or phenomena. The association relationships between the structural elements can be complex relationships, which can reflect the internal connection between the structural elements and the lesson design, and can further reveal the collaborative effect of each structural element in the overall design framework.

[0046] Specifically, the association relationships between the structural elements include a cascading relationship of unit learning design, a cascading relationship of unit task design, a cascading relationship of unit evaluation design, and a cascading relationship of lesson planning analysis.

[0047] Based on the association relationships between multiple structural elements, through a preset chart type, the mutual relationships between the various structural elements in the unit learning design of the large unit learning design and the internal connection between the structural elements and the lesson design can be presented.

[0048] Presenting the structural elements and the association relationships based on a preset chart type includes a bar chart presenting the distribution of learning objectives, learning links, the number of learning activities, etc., and a pie chart showing the distribution of activity time, the proportion of activity types, etc.

[0049] Specifically, it includes: obtaining the learning design content and directly presenting the content or results in text and numerical values; presenting the number of activities corresponding to each type of learning objective with a bar chart or a column chart, or presenting the number of activity types corresponding to each learning link with a bar chart or a column chart; presenting the proportion of the number of various learning objectives with a pie chart, or presenting the proportion of the duration of various learning activities with a pie chart; or presenting the cascading relationship between core literacy - big concept - big goal - big strategy - big problem - big task - unit evaluation - lesson planning through a tree diagram.

[0050] In this way, presenting the process of large unit learning design in a structured and visual manner not only ensures the orderly generation of the content of large unit learning design, but also helps the designer quickly clarify their thinking, improve the design efficiency and accuracy, and promote the precise optimization and real-time iteration of large unit learning design; the presentation in the form of charts makes the large unit learning design more intuitive and understandable, and the visual presentation of the design content and analysis results helps users clearly understand the overall structure and operating status of the design.

[0051] Meanwhile, the solution for the big unit learning design supports real-time preview, download, and sharing. Users can review, modify, and provide feedback on the design solution individually or as a team according to their needs. Charts display the design process, structural relationships, statistical data, etc., which can visually present the relationships and interactions among various elements in the design process, avoiding misunderstandings and chaos of complex content that may occur in traditional designs. The visualization method not only improves the communication efficiency of the design content but also provides users with real-time feedback results to help them optimize and adjust the design.

[0052] Meanwhile, it is difficult to coordinate between design elements. The instructional design is complex and involves multiple elements. Traditional design tools may lead to misunderstandings of design intentions and details due to insufficient written descriptions, unclear hierarchies, or ambiguous explanations. However, the visualized preset charts can more intuitively and clearly display the design levels and elements.

[0053] In some alternative embodiments, the structural elements in the process of obtaining the big unit learning design are obtained, including: obtaining one or a combination of the following structural elements: the structural elements included in the cascading relationship of unit learning design, the structural elements included in the cascading relationship of unit task design, the structural elements included in the cascading relationship of unit evaluation design, and the structural elements included in the cascading relationship of lesson planning analysis.

[0054] In this embodiment, the cascading relationship of unit learning design includes structural elements such as core literacy, big concepts, big goals, big strategies, big questions, big tasks, unit evaluation, and lesson planning. The cascading relationship of unit task design includes structural elements such as big tasks, subtasks obtained by decomposing big tasks, and unit refinement goals. The cascading relationship of unit evaluation design includes structural elements such as unit learning evaluation and subtask evaluation. The cascading relationship of lesson planning analysis includes structural elements such as lesson planning and subtasks.

[0055] These structural elements form a tight cascading relationship and jointly constitute the complete framework of the big unit learning design. By clarifying these elements and understanding the relationships between them, we can design and implement big unit learning more systematically, improving teaching effects and the learning quality of students.

[0056] In some optional embodiments, the association between each structural element is determined, including determining the association between the structural elements included in the cascading relationship of the unit learning design: based on the learning objectives of the large unit learning design, determine the core literacy of the large unit learning design; based on the core literacy, determine the big concepts that support subject understanding; based on the big concepts, set big goals, and based on the big goals, represent the knowledge that students should master through the large unit learning design; determine the big strategies to achieve the big goals, and based on the big strategies, represent the learning methods; based on the big strategies, cultivate students' ability to solve big problems; achieve big goals by completing big tasks, and based on the big tasks, represent the core tasks of the large unit learning design; based on students' performance in solving big problems, generate unit evaluations; based on the aforementioned structural elements, determine the class schedule, and based on the class schedule, achieve the learning objectives.

[0057] In this embodiment, Figure 2 A schematic diagram of the cascading relationship of unit learning design is shown, such as Figure 2 As shown, the unit learning design has a cascading relationship: core competencies - big concepts - big goals - big strategies - big problems - big tasks - unit evaluation - lesson planning, which reflects the organic connection and gradual development process from core competencies to lesson planning.

[0058] Taking core competencies as the starting point, it is gradually expanded through major concepts, major goals, major strategies and other levels, and each level provides support for the next level; sub-tasks correspond to the detailed goals of each unit, and unit evaluation and lesson planning correspond to the sub-tasks.

[0059] Specifically, based on the learning objectives of the large unit learning design, the core literacy of the large unit learning design is determined. The core literacy defines the key abilities that students need to cultivate in the learning process. These literacy is the starting point of the unit design. Determining the core ideas of the big concepts to support the understanding of the subject based on the core literacy can help students establish a systematic knowledge framework. Set big goals around the big concepts, that is, the specific knowledge and ability levels that students should achieve through learning. In order to achieve the big goals, design corresponding big strategies to select teaching methods. On this basis, design big questions to guide students to deeply understand the subject content and cultivate problem-solving skills. Big tasks are the core tasks of unit learning, and big goals are achieved by completing big tasks. Unit evaluation helps teachers comprehensively evaluate students' performance in the entire unit learning to ensure whether students have achieved the predetermined learning goals. Lesson planning transforms this series of designs into specific classroom activities and teaching arrangements to ensure that each class serves to achieve the unit goals.

[0060] In the process of determining the association relationship between various structural elements, the user input data can be processed and transformed to facilitate visual presentation.

[0061] In this way, the large-unit learning design is decomposed into a hierarchical structure. Through the above logical chain, it is ensured that each structural element has a clear dependency relationship, which can ensure that the elements are closely connected and support each other, jointly promoting the achievement of learning goals. At the same time, it also provides clear teaching guidance and evaluation basis for teachers, helping to improve teaching quality and effectiveness.

[0062] In some optional embodiments, determining the association relationships between the structural elements further includes determining the association relationships between the structural elements included in the cascading relationship of unit task design: decomposing a grand task into multiple specific subtasks and closely combining them with the refined unit goals of each task. The grand task is the core goal that students ultimately need to complete, while the subtasks are the specific steps to achieve the grand task, and each subtask is centered around a clear refined unit goal.

[0063] Figure 3 The schematic diagram of the cascading relationship of unit task design is shown, as Figure 3 shown, the grand task includes subtask 1, subtask 2, and subtask 3. Subtask 1 is closely combined with the refined unit goal 2, subtask 2 is closely combined with the refined unit goal 1, and subtask 3 is closely combined with the refined unit goal 3.

[0064] In this way, the refined unit goals related to the subtasks clarify the specific achievements that students should reach in each link, helping students gradually accumulate knowledge and ultimately complete the entire grand task.

[0065] In some optional embodiments, determining the association relationships between the structural elements further includes determining the association relationships between the structural elements included in the cascading relationship of unit evaluation design: combining the learning evaluation of the unit and the evaluation of specific subtasks.

[0066] Figure 4 The schematic diagram of the cascading relationship of unit evaluation design is shown, as Figure 4 shown, the learning evaluation includes evaluation 1 and evaluation 2. Evaluation 1 is used to evaluate the learning progress and achievements of students in subtask 1, and evaluation 2 is used to evaluate the learning progress and achievements of students in subtask 3. Each subtask represents a key step in achieving the unit goal, and the learning evaluation helps teachers judge whether students have mastered the necessary knowledge and skills by measuring the specific performance of students in each subtask. The unit evaluation is an assessment of the comprehensive performance of students in the entire unit learning. Through the included learning evaluations, the learning progress and achievements of students in each subtask are gradually evaluated.

[0067] In this way, it can ensure a comprehensive assessment of the learning process and achievements of students.

[0068] In some alternative embodiments, determining the association relationships between various structural elements further includes determining the association relationships between the structural elements included in the cascading relationship of lesson planning analysis: combining the overall lesson plan with specific subtasks.

[0069] Figure 5 A schematic diagram of the cascading relationship of lesson planning analysis is shown, as Figure 5 shown, the lesson plan includes Lesson 1 and Lesson 2. Lesson 1 is designed according to Subtask 1, and Lesson 2 is designed according to Subtask 2. The lesson plan is the time allocation and arrangement for the entire unit learning content. It breaks down the big tasks and subtasks one by one, and the subtasks represent the specific steps to achieve the unit goals. Each lesson is designed based on these subtasks to ensure that students gradually master the required knowledge and skills.

[0070] In this way, it can be ensured that the design of each lesson is closely related to the unit goals and tasks.

[0071] In some alternative embodiments, a large unit learning design template is preset, including: the lesson learning design generated based on the unit learning plan; the unit learning design generated based on the preset unit learning design template; wherein, the unit learning design includes at least one lesson learning design, and the unit learning design is implemented based on the lesson learning design.

[0072] In this embodiment, the unit learning design and the lesson learning design have an inheritance and inclusion relationship at the content level, which is a hierarchical progressive process from macro to micro. The unit learning design contains multiple lessons, providing the overall framework and goals, while the lesson learning design is to gradually implement the unit design within the framework of the unit learning design by refining the goals, arranging specific content and activities, etc.

[0073] The large unit learning design template has been verified by education experts and teaching practitioners and meets the effectiveness standards in educational practice. In the learning design for different disciplines, the template will arrange specific core qualities, learning strategies, etc. according to the characteristics of the disciplines to ensure that the teaching design meets the special requirements and learning needs of the disciplines. Moreover, the large unit learning design template pays attention to the organic connection of each structural element, thus ensuring the coherence and systematicness of teaching. Through this design, the teaching process can form a closed loop to ensure that the whole process from learning goal setting to evaluation and feedback is effectively monitored and adjusted.

[0074] In this way, presetting the large unit learning design template and customizing the design according to the characteristics and goal requirements of the disciplines can help teachers quickly and efficiently complete the teaching design that meets the standards, can solve the cumbersome and uncertain problems in the learning design process, and the problems that different disciplines have different requirements for teaching goals, core qualities, learning strategies, etc., and contribute to the optimization of the large unit learning design and the improvement of learning effects.

[0075] In some alternative embodiments, if the user input data does not meet the requirements of the preset rules, based on the preset rules, guided prompt information is provided, including: if the user input data does not meet the content structuring requirements, based on the guided prompt information, the user is prompted to organize the content of the big unit learning design in a preset order; if the user input data does not meet the format requirements of the big unit learning design, based on the guided prompt information, the user is prompted to determine the content of the big unit learning design according to the format requirements; if the user input data does not meet the language specification requirements, based on the guided prompt information, the user is prompted to determine the content of the big unit learning design according to the language specification requirements, where the preset rules include content structuring requirements, format requirements, and language specification requirements.

[0076] In this embodiment, the content structuring requirements require that the content of the learning design be organized in a certain hierarchy and order to ensure that each learning module, link, and activity has a clear logical structure and unfolds layer by layer from the whole to the details; the format requirements mainly target the typesetting and presentation methods of the learning design content to ensure the unity and standardization of the design document and improve the readability and professionalism of the overall document; the language specification requirements ensure that the expression language of the design content is clear, concise, and conforms to academic or professional writing standards, avoiding the use of ambiguous or vague expressions, and ensuring that each learning objective, activity, and link has a clear and specific description.

[0077] The preset rules can be stored in multiple data tables, including a basic information table, a learning design content table, and an associated data table. The setting of the data report can ensure the systematic management and convenient access of various types of information. The content such as data fields, field thresholds, and field values is defined in each data table.

[0078] Among them, the basic information table contains the basic metadata of each learning design, such as fields such as name, subject, school stage, and teaching teacher. These basic information help to uniquely identify each learning design; the learning design content information table is used to record the data related to the core content of the learning design, which can be specifically divided into data tables such as learning theme, learning objective, learning strategy, learning resource, and learning evaluation; the associated data table enables each design element to be accurately linked and queried, that is, an association is established through the learning design ID with the data tables in the basic information table and the learning design content information table.

[0079] Figure 6 Shows a schematic diagram of the guided prompt information. As Figure 6 shown, the guided prompt information corresponding to the learning design data of the overall learner characteristics analysis is "Please conduct a characteristic analysis of the students from aspects such as the grade where the students are located, physical and mental development, overall four-dimensional / ability development, and learning attitude". Figure 7A schematic diagram showing another guided prompt message is shown. As Figure 7 shown, for what is a large task, the corresponding guided prompt message is "Unit implementation activities that guide students to comprehensively apply knowledge and skills to solve problems".

[0080] In this way, user input data can be detected, analyzed in real time, and guided prompt messages can be provided to assist in generating large unit learning designs. The preset rules provide a clear framework and guiding principles for generating guided prompt content, enabling the display of corresponding prompt content according to the specific requirements of the input box, and avoiding users deviating from the preset design standards due to improper operations. Real-time analysis and prompting can ensure the mutual cooperation between different design elements according to the actual input and preset standards, enhancing the flexibility and adaptability of the design, and reducing design deviations and inconsistencies existing in the design process.

[0081] When facing complex learning design challenges, guided prompt messages are particularly crucial in multi-factor learning design projects. They can monitor and evaluate the status of each element in a timely manner at all stages of the learning design implementation, and can promptly detect and correct deviations.

[0082] In some alternative implementation manners, the lesson learning design includes one or a combination of several of the following: learning content analysis, learner analysis, soul goal design, learning strategy design, learning tasks, learning session design, learning activity design, and tool design; the unit learning design includes one or a combination of several of the following: unit learning theme, unit teaching analysis, unit goal design, unit teaching design, learning evaluation, and lesson planning.

[0083] In this implementation manner, a complete unit learning design document or lesson learning design document can be previewed or output in real time. The unit learning theme is the core and soul of large unit teaching. Usually centered around a large theme or large task, the learning content is reorganized to form clear elements such as themes or topics, goals, situations, tasks, etc.

[0084] The unit teaching analysis includes curriculum standard analysis and learner analysis. Among them, the learner analysis includes the overall characteristics analysis of learners; the mastery of "knowledge and skills" related to the learning content of this unit; the development of literacy related to the "disciplinary core literacy" carried by the learning content of this unit, etc.

[0085] The unit goal design includes disciplinary core literacy (core literacy for a specific discipline), big concepts, big goals, and unit refined goals. The unit teaching design includes big strategies, teaching tips, big questions, big tasks, and unit subtasks. The learning evaluation includes selecting subtasks, who evaluates, who is evaluated, evaluation forms, and evaluation plans. The lesson planning includes lesson types, corresponding subtasks, responsible persons, and the number of lessons.

[0086] The learning content analysis includes overall analysis description, key point analysis of learning, and difficult point analysis of learning. The sub - parts of the soul goal design are soul goal (goal type; goal content) and refined goal (goal type; goal content). The learning strategy design includes learning strategy and teaching situation. The learning link design includes link name, design intention, and stage where the link is located. The learning activity design includes learning activity (activity name; activity time; execution form; supported refined goal), heuristic questions, and learning evaluation (who evaluates; who is evaluated; evaluation form; evaluation plan). The tool design includes the development of tools for implementing the above - mentioned functions.

[0087] In this way, through the fine - grained lesson design, it is ensured that each lesson can efficiently achieve the teaching goals; through the macro - level unit design, it is ensured that the teaching of the entire unit is coherent and systematic, thereby improving the overall teaching effect. The unit learning design emphasizes the integration and application of knowledge, encouraging students to conduct in - depth exploration and reflection; the lesson - based learning design focuses on the mastery of specific knowledge points and skill points. The combination of the two helps to promote students' deep learning.

[0088] In some optional implementation manners, the above - mentioned method for large - unit learning design further includes providing abnormal information feedback to the user during the process of obtaining user input data.

[0089] When data display anomalies or trend changes are detected, relevant data areas will be prominently highlighted through warning icons. These warning icons adopt obvious colors and shapes so that users can quickly identify the parts that need attention. At the same time, clicking on the warning - marked area will display detailed explanatory text, reminding users of possible problems in the completed design and providing targeted design improvement suggestions, such as suggesting to optimize the design of certain links or adjust the activity arrangement to improve data performance and perfect the entire design process.

[0090] To implement the above - mentioned method for large - unit learning design, the tool for large - unit learning design developed includes a front - end function module and a back - end function module. Among them, the front - end function module is used to support users in selecting any large - unit learning design or creating a new learning design according to a preset large - unit learning design template to present the design content and visualization results. The back - end function module covers modules such as data collection, data parsing, data storage, data analysis, data visualization, and data output. These modules respectively have functions such as reading, parsing, storing, calculating and analyzing, generating result visualization, and storing and outputting learning design data. Through the coordinated action of these functions, the back - end function module can strongly support the implementation of the front - end function module.

[0091] In some optional embodiments, the aforementioned method for large-unit learning design also includes visually presenting the large-unit learning design, visually presenting the unit learning design and the lesson learning design completed by the user according to a preset large-unit learning design template, and the design content of the large-unit learning design can be previewed in real time or output in full.

[0092] The method for large-unit learning design provided by the present invention realizes the structured and standardized processing of learning design content through the preset large-unit learning design template verified by educational experts and teaching practitioners, and the output of guided prompt information not only improves the accuracy of the design, but also ensures the timely feedback of the design content, and the formed learning design scheme supports collaborative sharing. This method makes learning design no longer a linear, static process, but a dynamic, feedback-driven process, which can self-adjust and optimize according to data analysis results at different stages of the design, and promotes the intelligence and precision of teaching design.

[0093] The present invention takes the actual needs and expectations of teachers as the starting point, constructs hierarchical and associative structural elements, and visualizes the large-unit learning design, covering the complete process of data collection, analysis indicator calculation, and result visualization output. It can gradually conduct in-depth analysis from local details, comprehensively and systematically express and describe the implicit information in the large-unit learning design, and finally form an overall evaluation of the teaching process, avoiding the drawbacks of relying solely on data-driven and detached from the educational context, and surpassing the limitation of focusing only on a single factor.

[0094] In this embodiment, a device for large unit learning design is also provided, which is used to implement the above embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0095] This embodiment provides a device for large unit learning design. Figure 8 A schematic diagram of the structure of the device used for large unit learning design is shown, Figure 8 As shown, including:

[0096] The acquisition module 801 is used to acquire user input data based on a preset large unit learning design template.

[0097] A preprocessing module 802, which is used to, during the process of obtaining user input data, if the user input data does not meet the requirements of a preset rule, provide guided prompt information based on the preset rule, and in response to the user's modification of the user input data, re-obtain the user input data, wherein the preset rule is determined based on a preset large unit learning design template.

[0098] A generation module 803, which is used to generate a large unit learning design based on the re-obtained user input data and the user input data that meets the preset rule.

[0099] In some alternative embodiments, the aforementioned apparatus for large unit learning design further includes:

[0100] A visualization module, which is used to present the process of generating a large unit learning design: obtain the structural elements in the process of generating a large unit learning design; determine the association relationships between the structural elements; and present the structural elements and the association relationships based on a preset chart type.

[0101] In some alternative embodiments, the acquisition module 801 includes:

[0102] A first acquisition unit, which is used to generate a lesson learning design based on a unit learning plan; generate a unit learning design based on a preset unit learning design template; generate a preset large unit learning design module based on the lesson learning design and the unit learning design; wherein the unit learning design includes at least one lesson learning design, and the unit learning design is implemented based on the lesson learning design.

[0103] In some alternative embodiments, the preprocessing module 802 includes:

[0104] A first preprocessing unit, which is used to, if the user input data does not meet the content structuring requirement, prompt the user to organize the content of the large unit learning design in a preset order based on the guided prompt information; if the user input data does not meet the format requirement of the large unit learning design, prompt the user to determine the content of the large unit learning design based on the format requirement based on the guided prompt information; if the user input data does not meet the language specification requirement, prompt the user to determine the content of the large unit learning design based on the language specification requirement, wherein the preset rule includes the content structuring requirement, the format requirement, and the language specification requirement.

[0105] In some alternative embodiments, the visualization module includes:

[0106] A first visualization unit, which is used to obtain a combination of one or more of the following structural elements: the structural elements included in the unit learning design cascade relationship, the structural elements included in the unit task design cascade relationship, the structural elements included in the unit evaluation design cascade relationship, and the structural elements included in the lesson plan analysis cascade relationship.

[0107] In some alternative embodiments, the visualization module further includes:

[0108] A second visualization unit for determining the association relationships between the structural elements included in the unit learning design cascade relationship: determining the core competencies of the large unit learning design based on the learning objectives of the large unit learning design; determining the big concepts that support subject understanding based on the core competencies; setting big goals based on the big concepts, and representing the knowledge that students should master through the large unit learning design based on the big goals; determining the big strategies for achieving the big goals, and representing the learning methods based on the big strategies; cultivating students' ability to solve big problems based on the big strategies; achieving the big goals by completing big tasks, and representing the core tasks of the large unit learning design based on the big tasks; generating unit evaluations based on students' performance in solving big problems; determining the lesson planning based on the foregoing structural elements, and achieving the learning objectives based on the lesson planning.

[0109] The further function descriptions of the above-mentioned various modules and units are the same as those in the corresponding foregoing embodiments, and will not be elaborated herein.

[0110] The device for large unit learning design in this embodiment is presented in the form of functional units. Here, the unit refers to an Application Specific Integrated Circuit (ASIC) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0111] The embodiment of the present invention further provides a computer device having the above-mentioned Figure 8 device for large unit learning design shown.

[0112] Please refer to Figure 9 , Figure 9 which is a schematic structural diagram of a computer device provided by an alternative embodiment of the present invention. As shown in Figure 9As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Each component communicates with each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of a graphical user interface on an external input / output device (such as a display device coupled to the interface). In some alternative embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a set of blade servers, or a multi-processor system). Figure 9 Take one processor 10 as an example in

[0113] The processor 10 can be a central processing unit, a network processor, or a combination thereof. Among them, the processor 10 can further include a hardware chip. The above-mentioned hardware chip can be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The above-mentioned programmable logic device can be a complex programmable logic device, a field programmable gate array, a general array logic, or any combination thereof.

[0114] Among them, the aforementioned memory 20 stores instructions executable by at least one processor 10, so that the aforementioned at least one processor 10 executes the method shown in the above embodiments.

[0115] The memory 20 can include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the computer device. In addition, the memory 20 can include high-speed random access memory and can also include non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 can optionally include a memory remotely set relative to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0116] The memory 20 can include volatile memory, such as random access memory; the memory can also include non-volatile memory, such as flash memory, a hard disk, or a solid-state drive; the memory 20 can also include a combination of the above types of memory.

[0117] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30, and the output device 40 may be connected by a bus or other means. Figure 9 Taking the connection by bus as an example.

[0118] The input device 30 can receive input digital or character information and generate key signal inputs related to the user settings and function controls of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointing stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., a light-emitting diode), and a tactile feedback device (e.g., a vibration motor), etc. The above display device includes but is not limited to a liquid crystal display, a light-emitting diode, a display, and a plasma display. In some alternative embodiments, the display device may be a touch screen.

[0119] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented as computer code that is originally stored in a remote storage medium or a non-transitory machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiment is implemented.

[0120] A part of the present invention can be applied as a computer program product, such as computer program instructions. When executed by a computer, through the operation of the computer, the methods and / or technical solutions according to the present invention can be called or provided. Those skilled in the art should be able to understand that the forms of existence of computer program instructions in a computer-readable medium include but are not limited to source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include but are not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible by the computer.

[0121] Although embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A method for large unit learning design, characterized in that The method comprises: Based on the preset large unit learning design template, obtain user input data; In the process of obtaining the user input data, if the user input data does not meet the requirements of the preset rules, based on the preset rules, providing guided prompt information, responding to the user's modification of the user input data, and re-obtaining the user input data, wherein the preset rules are determined based on the preset large unit learning design template; A large unit learning design is generated based on the user input data that meets the preset rules.

2. The method according to claim 1, characterized in that The method further includes presenting a process of generating the large unit learning design: Acquire structural elements in the process of generating the large unit learning design; Determining the relationship between the structural elements; Based on a preset chart type, the structural elements and the association relationships are presented.

3. The method according to claim 1, characterized in that The preset large unit learning design template includes: Generate lesson learning design based on unit learning plan; Generate unit learning design based on preset unit learning design template; Among them, the unit learning design includes at least one lesson learning design, and the unit learning design is implemented based on the lesson learning design.

4. The method according to claim 1, characterized in that: If the user input data does not meet the requirements of the preset rules, providing guided prompt information based on the preset rules includes: If the user input data does not meet the content structuring requirements, based on the guided prompt information, prompt the user to organize the content of the large unit learning design based on a preset order; If the user input data does not meet the format requirements of the large unit learning design, based on the guided prompt information, prompting the user to determine the content of the large unit learning design based on the format requirements; If the user input data does not meet the language specification requirements, based on the guided prompt information, the user is prompted to determine the content of the large unit learning design based on the language specification requirements, wherein the preset rules include the content structuring requirements, the format requirements and the language specification requirements.

5. The method according to claim 2, characterized in that: Capture the structural elements in the process of generating the large unit learning design, including: Obtain one or a combination of the following structural elements: the structural elements included in the cascading relationship of unit learning design, the structural elements included in the cascading relationship of unit task design, the structural elements included in the cascading relationship of unit evaluation design, and the structural elements included in the cascading relationship of lesson planning analysis.

6. The method according to claim 5, characterized in that The determining of the association relationship between the structural elements includes determining the association relationship between the structural elements included in the cascade relationship of the unit learning design: Based on the learning objectives of the large unit learning design, determine the core literacy of the large unit learning design; Based on the core competencies, identify the big concepts that support subject understanding; Based on the big concept, set big goals, and based on the big goals, represent the knowledge that students should master through the big unit learning design; Determine a grand strategy for achieving the grand goal, and characterize a learning method based on the grand strategy; Based on the above big strategies, cultivate students' ability to solve big problems; Achieve the big goal by completing the big task, and characterize the core task of the big unit learning design based on the big task; Generate unit assessments based on student performance on the big questions; Based on the aforementioned structural elements, the lesson plan is determined, and based on the lesson plan, the learning objectives are achieved.

7. The method according to claim 3, characterized in that The lesson learning design includes one or a combination of the following: learning content analysis, learner analysis, soul goal design, learning strategy design, learning tasks, learning link design, learning activity design and tool design; The unit learning design includes one or a combination of the following: unit learning theme, unit teaching analysis, unit goal design, unit teaching design, learning evaluation and class planning.

8. A device for large unit learning design, characterized in that: The device comprises: An acquisition module is used to acquire user input data based on a preset large unit learning design template; a preprocessing module, configured to, in the process of acquiring the user input data, if the user input data does not meet the requirements of the preset rules, provide guiding prompt information based on the preset rules, and reacquire the user input data in response to the user's modification of the user input data, wherein the preset rules are determined based on the preset large unit learning design template; A generating module is used to generate a large unit learning design based on the re-acquired user input data and the user input data satisfying the preset rules.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for large-unit learning design according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions for causing a computer to execute the method for large-unit learning design according to any one of claims 1 to 7.

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