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The Knowledge-Gap in e-learning often leaves learners without essential context or in-depth information on critical topics, requiring them to seek additional knowledge outside the course. This disrupts the flow of learning, leads to frustration, and may reduce learner engagement. Learners might abandon the course, or worse, settle for incomplete or inaccurate information found through independent searches, impacting their overall understanding of the subject.
Learners face several challenges when addressing Knowledge-Gaps, such as the time-consuming nature of searching for supplementary information, evaluating the credibility of various sources, and determining which information is most relevant. Without sufficient prior knowledge, learners may struggle to differentiate between reliable and misleading information, resulting in confusion or misinformation. These challenges can diminish the learning experience and slow down knowledge acquisition.
Knowledge-Gaps in online courses can lead to reduced engagement by creating obstacles to understanding key concepts. Learners may become frustrated by incomplete explanations or a lack of depth in course material, prompting them to disengage or lose interest. The additional effort required to fill in gaps independently can also demotivate learners, particularly when they struggle to find credible and relevant information. This ultimately decreases satisfaction and retention rates in e-learning.
BubbleAI™ bridges the Knowledge-Gap by using AI-driven Bubbles that contain relevant extra information embedded directly into the video. This allows the user to access the knowledge needed to close gaps without leaving the video session or wasting time searching through external sources. The interactive interface powered by machine learning enables users to seamlessly explore and find the information they need within the video itself.
BubbleAI™ allows content creators to embed a transparent layer of Bubbles filled with extra information directly into their videos using an AI-based web-application interface. This innovative feature ensures that any Knowledge-Gap can be addressed in real time, providing viewers with immediate access to additional content without interrupting their video experience. Using the “Bubbles Concept”, BubbleAI™️ enables course creators enrich any short course with ample knowledge
BubbleAI™ is the first AI platform that enables knowledge acquisition directly through video by embedding a transparent layer of AI-driven Bubbles packed with extra knowledge. Its unique ability to predict knowledge demand and calculate knowledge trends using big data models sets it apart from traditional methods. This seamless integration of AI-driven knowledge mining directly within videos provides a new, innovative way to solve the Knowledge-Gap issue across all video types and platforms.
BubbleAI™ enables medical universities to easily embed new knowledge bubbles into existing courses, allowing them to update course content in real-time. This ensures that learners always have access to the most current medical information without requiring complete course redesigns. By using the “Bubbles Concept,” course creators can enrich their content with the latest research and clinical practices, keeping pace with the rapidly evolving medical field.
Medical universities often struggle to create interactive and engaging online learning experiences, which can lead to lower student engagement and retention. BubbleAI™ addresses this by providing a knowledge mining dashboard that allows e-learners to interact with content-rich bubbles within the course material. This interactive approach helps students dive deeper into topics of interest, increasing engagement and making the learning experience more dynamic and personalized.
BubbleAI™’s Knowledge Center provides powerful real-time assessment and analytics tools that help medical universities monitor student progress and identify areas where learners may be struggling. By analyzing student interactions with knowledge bubbles, universities can pinpoint missing areas of knowledge in their courses, enabling more targeted interventions to support learners. This real-time insight helps improve student outcomes and ensures that gaps in medical education are addressed promptly.
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