Standards for Developing Digital Educational Content

Introduction

This document outlines the role of artificial intelligence (AI) in supporting the implementation of the standards for developing digital educational content and illustrates how AI-driven tools can be leveraged to ensure the delivery of high-quality effective learning content. Recognizing the need to keep pace with AI advancements in digital learning, the National eLearning Center (NeLC) has established comprehensive standards for content development. These standards build upon NeLC’s previous frameworks that have significantly contributed to elevating the quality of digital learning across various dimensions. This initiative also aims to facilitate beneficiaries’ access to these standards. The standards are classified into four main pillars:

• Digital Content Quality
• Structure and Design Quality
• Technological Quality
• Technical Quality

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01 First Pillar: Scientific Content Quality

Standards for Developing Digital Educational Content

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Standard AI Applicability

1. Compliance with national laws, regulations and policies.

• AI tools and solutions can be utilized to analyze content and verify compliance with applicable laws and policies.

2. Application of intellectual property principles, copyright, and legal requirements.

• AI tools and solutions can be used to detect potential copyright infringements.

3. Commitment to maintaining integrity when using digital educational content.

• AI tools and solutions can be employed in examining content to maintain integrity; however, human intervention is required in some cases, as integrity relies on human values and to assess content sources accurately.

4. Accuracy and integrity of the scientific content, ensuring it is free of linguistic errors.

• AI tools and solutions can be employed through various proofreading tools to ensure linguistic accuracy and that the content is error free.

5. Regular content review and update.

• AI tools and solutions can be utilized to analyze data and identify content that needs updating based on current changes or emerging trends.

6. Ensuring diversity, inclusivity, and cultural alignment in the digital educational content.

• AI tools and solutions can be employed in examining content to ensure cultural diversity and inclusivity; however, human intervention is required to ensure cultural appropriateness and alignment.

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02 Second Pillar: Structure and Design Quality

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1. Providing a multidisciplinary team for building and developing digital educational content. AI tools and solutions can be utilized to support content creation and development; however, the presence of a specialized team across various fields is essential to ensure the quality, effectiveness, and achievement of the intended learning objectives.

2. Analyzing the needs of the target audience, objectives, and requirements of the digital educational content to guide the design process. AI tools and solutions can be employed in analyzing learners’ data to identify their needs and design appropriate content.

3. Providing accurate, realistic, and measurable learning objectives for the digital educational content, and clearly communicating them to the learner.

• AI tools and solutions can be employed through:
• 1- Learner performance analysis: Using performance analytics to identify new data-driven learning objectives.
• 2- Generating objectives: Using AI tools to generate learning objectives based on the analysis of lessons and previous assessments.
• 3- Measuring achievement of objectives: Using adaptive assessment platforms to automatically measure the extent to which learning objectives are achieved. Despite AI’s ability to contribute to the formulation and assessment of objectives, human intervention remains essential to ensure that learning objectives are realistic and pedagogically appropriate.

4. Designing content that considers learners’ preferences, interests, experiences, and levels of knowledge.

• AI tools and solutions can be employed to personalize content based on learners’ preferences and needs through adaptive learning.

5. Aligning the digital educational content with the learning objectives.

• AI tools and solutions can be employed to assess the alignment of content with the learning objectives based on educational data analysis.

6. Applying Universal Design for Learning (UDL) standards in digital educational content to promote equitable learning opportunities.

• AI tools and solutions can support the design of content that meets the needs of diverse learners; however, human supervision remains essential.

7. Chunking digital content into smaller units to reduce cognitive load.

• AI tools and solutions can be utilized to automatically chunk content based on its type, complexity, and learners’ needs.

8. Sequencing topics/units within digital educational content logically to support learning objectives.

• AI tools and solutions can be used to suggest a logical sequence of topics based on data analysis and learner behavior.

9. Providing diverse educational activities that align with the objectives of the digital educational content and meet learners' needs.

• AI tools and solutions can be used to create and deliver advanced educational activities tailored to learners' preferences.

10. Providing an overview of the delivered digital educational content, the target audience, and the required level of expertise and skills, and highlighting it in the introduction.

• AI tools and solutions can be utilized to generate automated content summaries and analyze the required knowledge level.

11. Providing self-assessment that enables the learner to monitor their progress and receive immediate feedback.

• AI tools and solutions can be employed to provide immediate feedback to learners based on their performance in automated assessments.

12. Designing assessments and ensuring their alignment with the learning objectives.

• AI tools and solutions can be employed to personalize and deliver assessments based on learning objectives and learners’ current levels.

13. Selecting appropriate assessment technologies and ensuring their accuracy and reliability periodically.

• AI tools and solutions can be utilized to analyze assessment performance and determine the most suitable technology based on available data.

14. Diversifying digital teaching and learning strategies to align with the digital educational content and learners’ needs and build engaging and effective learning experiences that help learners acquire the required knowledge and skills.

• AI tools and solutions can be utilized to suggest personalized teaching strategies based on learners’ data and behavior in the learning environment, however, human involvement is required.

15. Utilizing learner performance data to evaluate the effectiveness of teaching, educational technologies, materials, and assessment methods.

• AI tools and solutions can be employed in analyzing performance data to improve the effectiveness of the used educational tools.

16. Implementing ongoing training and qualification programs for digital educational content providers, covering the latest technologies, pedagogical strategies, eLearning delivery methods, and more.

• AI tools and solutions can support the development of qualification and training programs; however, they cannot replace human-led education, as the development of training programs fundamentally relies on human-centered pedagogical strategies and ongoing human guidance.

17. Developing the skills of instructional designers and content developers in designing and creating digital educational content, and collaborating with local and international experts in the field. Skill development requires direct human supervision, making the use of AI insufficient to achieve this independently.

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03 Third Pillar Technological Quality

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1. Providing systems, tools, and applications that support the delivery of various types of digital educational content.

• AI tools and solutions can be used to select appropriate systems and analyze data to choose the best learning tools.

2. The ability to browse and use digital educational content from various types of devices with different operating systems and screen sizes.

• AI tools and solutions can be utilized to enhance the browsing experience across different devices.

3. Digital learning systems support the customization of digital educational content according to the learner's preferences and needs.

• AI tools and solutions can be employed to personalize content based on learners' needs using adaptive learning systems.

4. Systems support accessibility for individuals with disabilities and consider the diverse needs of learners.

• AI tools and solutions can be employed to improve access to content, but it requires human supervision to meet the needs of all categories.

5. Providing systems or technologies for data collection and analysis to support decision-making in the development of digital educational content.

• AI tools and solutions can be utilized to analyze data and provide insights and recommendations to support decision-making; however, the final decision requires human supervision.

6. Ensuring the privacy and protection of beneficiaries' data. Data protection requires legal and regulatory human supervision and cannot rely solely on AI to ensure compliance.
7. Employing modern technologies such as AI and others in building and developing digital educational content in line with the objectives, nature of the content, and learners' needs.

• AI tools and solutions can be utilized to improve the process of building educational content by designing interactive and advanced content.

8. availability of tools that measure beneficiaries' satisfaction with digital educational content.

• AI tools and solutions can be used in automated analytics to collect and measure beneficiaries' satisfaction based on their feedback and behavior.

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04 Fourth Pillar Technical Quality

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1. Guidelines for beneficiaries to interact with digital educational content and optimize its benefits.

• AI tools and solutions can be employed to create smart and interactive guidelines for beneficiaries.

2. Applying Mayer’s 12 Principles when designing digital educational content.

• AI tools and solutions can be utilized to analyze content design and suggest improvements based on Mayer’s Principles.

3. Providing a consistent and unified design for all elements of the digital educational content.

• AI tools and solutions can be utilized to maintain a consistent design style across automated design tools.

4. Using appropriate language level for the target learners.

• AI tools and solutions can be employed to improve the language of the content based on the target audience level using text analysis tools.

5. Clarity and accuracy of metadata for digital educational content to preserve, reuse, and support the learning process.

• AI tools and solutions can be used to organize the metadata of the content, facilitate its reuse, and improve access to it.

6. Displaying the starting point for the learner's navigation "Start here".

• AI tools and solutions can be used to design user interfaces that facilitate navigation and clarify the starting point for the learner.

7. Displaying the digital educational content in an organized manner to facilitate navigation.

• AI tools and solutions can be utilized to analyze content flow and suggest improvements for organizing navigation between its sections.

8. Alignment of the digital educational content design with the Experience API (xAPI).

• AI tools and solutions can be employed to ensure compliance with xAPI.

9. Compliance with the Web Content Accessibility Guidelines (WCAG) to provide accessible content that can be used by all beneficiaries.

• AI tools and solutions can be employed to analyze the content's compliance with WCAG and suggest improvements for inclusive access.

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