Reading Progress now utilizes AI-generated reading passages to assist educators in creating personalized reading assignments for their students, enhancing online learning and digital education. These auto-generated passages can be created directly from the new reading assignment form or through the Education Insights Reading Progress report.

Educators can provide specific guidelines for generating passages, such as the topic, student age/reading level, passage length, required language, and key words for practice from previous assignments. Using Generative AI (Azure Open AI), new passages are crafted to help students practice their reading skills. Content moderation ensures that the generated passages are safe and appropriate for the students' reading level.

How does the passage generation technology work? 

Passage generation is powered by a machine learning model called GPT (Generative Pre-trained Transformer), which is essential for enhancing online learning and distance education. This model is trained on a vast array of text samples from the internet and generates new text that mimics human writing. Educators can specify the topic, student age, passage length, and language from a predefined list, and GPT creates customized reading passages.

The model also integrates selected practice words into the passage, ensuring that the text is tailored to the students' needs. This AI-driven tool supports virtual classrooms, blended learning, and hybrid learning environments by providing personalized and engaging digital education materials. It enhances online student engagement and interactive learning, making it a valuable asset in various e-learning platforms and remote learning settings.

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Once generated, educators have the flexibility to update the text and adjust its complexity using generative AI, making it ideal for online learning and digital education. Each passage is originally created, though it may not always be factual. To reduce the risk of inappropriate content, both the input word list and the AI-generated text undergo multiple content moderation steps.

To enhance the factual accuracy and engage students, some passages are grounded in Wikipedia content. However, these passages are intended to be engaging reading material rather than strictly factual learning content.

This AI-driven tool supports virtual classrooms, distance education, and various e-learning platforms by allowing educators to customize and refine reading materials. It is beneficial for blended learning, hybrid learning, and remote learning environments, ensuring that students receive tailored and engaging digital education experiences. By integrating generative AI in educational technology (EdTech), this feature enhances online student engagement, interactive learning, and self-paced learning.

The ability to modify text complexity makes it suitable for adaptive learning and online tutoring, supporting both asynchronous and synchronous learning environments. This innovative feature aligns with modern online education practices, contributing to the effectiveness of learning management systems (LMS) and virtual learning environments (VLE). By utilizing advanced AI, educators can create high-quality and relevant online resources, improving the overall online learning experience.

How should educators use the passage generation? 

Educators can utilize passage generation to quickly create practice opportunities for their students, enhancing online learning and distance education. This tool allows for the rapid creation of customized reading passages, providing valuable resources for virtual classrooms and digital education.

It is crucial for educators to review and edit the generated content for appropriateness and accuracy before assigning it to students. While various filters and safeguards are in place to limit questionable or inappropriate content, the AI technology behind passage generation is trained on a wide range of internet sources. Therefore, educators play a vital role in confirming the final passage's suitability.

This feature supports blended learning, hybrid learning, and various e-learning platforms, offering flexible and interactive learning opportunities. By leveraging AI in educational technology (EdTech), educators can enhance online student engagement and self-paced learning. This tool also supports adaptive learning and online tutoring, making it a valuable asset for modern online education practices.

What safeguards are employed while generating the passage? 

  • Educators are instructed to review and approve the passage before sharing with their students.

  • Passage generation output will be up to approximately 1,000 words.

  • Challenge words presented to the educator to select from are provided based on previous published assignments, all other parameters are taken from pre-defined closed lists. 

  • Content moderation is employed on the passage before presented to the educator.

  • Generated passages are only saved as part of the assignment and are not stored in other locations.

Model limitations 

  • From the Reading Progress creation form, only up to five challenge words are available to select from, and only when the selected language is English. 

  • From the Education Insights report, the passage generation is only available in English, and topic, age, and length can't be chosen. At least one practice word and up to 10 words must be selected to generate a passage. 

  • Age-appropriateness evaluation metrics are based on English texts and language statistics of native English speakers. For other languages, evaluation is done on the English version of the passage, which might create a less accurate readability score. Additionally, disparity between native speakers and second language learners should be taken into account. 

Data classification for the generated passage 

The text generated by the AI is owned by the educator using the functionality. For more information on the use limitations and data access and use terms, see the Microsoft Customer Agreement program under “Azure OpenAI Service." 

Learn more

Reading Progress Passage generation FAQ

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