Guided Course Framework Generation for Non-Expert Instructional Design
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Solution Overview
Problem
Planning the framework of electronic learning courses is challenging due to varying user progression rates and lack of skills in designing content, particularly in electronic learning systems where users may not be familiar with the design or creation of courses.
Innovation Solution
A system and method for guided instructional design that includes presenting course components with natural language objects and controls, allowing users to input parameters, and generating a customized course framework based on educational design elements and user inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users are allowed to freely design course frameworks without guidance, then user autonomy and creativity are improved, but the quality and structure of course design deteriorates due to lack of expertise
Solution Approach 1:
The system introduces an intelligent software intermediary that mediates between the user's design intentions and the actual course framework construction. This intermediary automatically generates structured course frameworks, learning objectives, and content organization based on user inputs, ensuring professional quality without requiring users to have expert-level design skills.
Solution Approach 2:
The system enables users to independently create professional course frameworks through automated tools that perform the complex design work themselves. Users simply provide high-level requirements, and the system self-generates the detailed course structure, objectives, and content organization, making expert-level course design accessible to non-experts.
2Stability of the object's composition
If comprehensive course framework planning is performed before course delivery, then course structure and organization are improved, but the time and effort required for course preparation increases
Solution Approach 1:
The system performs preliminary automated generation of course frameworks, learning objectives, and content structures before the actual course development begins. By pre-generating these foundational elements based on user requirements, the system establishes a stable course structure that guides subsequent content creation, reducing overall preparation time despite the comprehensive planning approach.
Solution Approach 2:
The system allows users to adjust parameters such as course duration, difficulty level, and content depth, which automatically trigger regenerative algorithms to restructure the course framework. This dynamic parameter adjustment capability enables the system to optimize course structure organization while adapting preparation time based on specific course requirements, rather than requiring fixed comprehensive planning for all scenarios.
3Ease of operation
If traditional just-in-time material preparation is used, then flexibility in responding to student needs is improved, but the ability to accommodate varying student progression rates deteriorates
Solution Approach 1:
The system dynamically adjusts course frameworks and learning pathways based on real-time student performance data and progression rates. Rather than using static just-in-time material preparation, the system continuously regenerates and reorganizes course content to match individual student needs, enabling simultaneous accommodation of multiple progression rates while maintaining operational flexibility through automated content delivery.
Data Source
AI summary
According to some embodiments, a system for providing guided instructional design. The system includes at least one processing device and at least one data storage device in communication with the at least one processing device. The at least one data storage device is configured to store information about at least one course. For each course, the at least one processing device is configured to present at least one predetermined course component to a first user, and for the at least one course component: present at least one course parameter, receive at least one first input from the first user in relation to the at least one course parameter, based on the at least one first input and at least one educational design element, present at least one modified course parameter to the first user; and receive at least one second input from the first user in relation to the at least one modified course parameter.