How AI Is Pushing the Boundaries of Education: The Use of AI in E-Learning and Innovations in LMS iTutor

Summary: AI is gradually being adopted across many areas of e-learning. The article summarizes commonly cited ways AI is used in e-learning and describes the practical implementation of AI for Just-In-Time and Micro-Learning. In conclusion, it outlines the implementation of AI in LMS, showing that AI in corporate education can go beyond merely assisting with human resource training.

Use of AI in E-Learning

Artificial intelligence (AI) is finding ever-increasing use in e-learning. Typically, AI is gradually being adopted in the following areas:

Content Creation

One of the bottlenecks of e-learning is content creation. The original vision of e-learning—that employees would gain access to a large number of engaging, interactive, multimedia e-courses containing the company's specific know-how—encounters long and costly production cycles with high didactic and technical demands on creators. AI is expected to fundamentally assist with the creation of e-courses, and many authoring tools already have some AI features implemented. In multilingual companies, AI can handle the translation and localization of materials into other languages.

Virtual Assistants

AI can be used to create chatbots that provide immediate answers to students' questions about study material, help with navigation within the LMS, assist with learners' technical issues, and remain available 24/7, thereby increasing support availability and student engagement.

Automated Assessment

AI automatically evaluates open-ended responses in tests or assigned tasks, provides students with instant feedback, performs plagiarism checks, and more.

Data Analysis, Adaptive Learning

AI analyzes learner behavior data captured by the LMS, such as time spent in learning units, number of lesson or SCO (Shareable Content Objects) launches, and errors in test responses. Based on this, AI offers students supplementary materials, repeats content tailored to their weaknesses, identifies engaged and at-risk students for instructors, recommends tutor interventions, or, conversely, flags problematic content for revision.

Virtual Reality (VR) and Augmented Reality (AR)

Combined with AI, this enables the creation of complex intelligent simulations—for instance, for medicine, technical fields, or language courses—where AI controls, for example, the behavior of characters and simulated environments.

Implementation of AI in LMS iTutor for JIT Learning, Micro-Learning, and Human Resource Substitution

At Kontis, we have been developing e-learning systems for the corporate sector for over 25 years, and throughout this time, we have aimed to set trends in this field. We have long focused on implementing AI in e-learning and learning management systems (LMS) across all the areas mentioned above. Below, you will find possibilities for using AI in areas beyond those commonly cited—such as JIT, micro-learning, and human resource replacement (HR)—including a description of the concrete implementation of such AI in an LMS.

If we imagine an LMS as a platform containing all company training materials and know-how, which the company uses to educate its employees and provide them with information needed to perform their job duties, the role of AI in an LMS can be divided into two basic areas:

Just In Time Learning and Micro-Learning

Modern workers rarely have time to spend several hours studying long e-courses to acquire knowledge that they will only need in the distant future. They prefer learning "Just in Time" (JIT)—when they need specific information to solve a current task. Alongside JIT, micro-learning is often cited—studying in short intervals (typically a few minutes) focused on a narrow topic. AI in LMS iTutor makes it possible to generate answers on demand to specific student inquiries based on company documentation and courses, delivering instant micro-learning exactly when needed.

Human Resource Substitution

Corporate education is not just about training employees; it is about transferring corporate know-how so that employees can perform tasks according to company procedures. In many routine situations—such as answering repetitive internal or customer queries—AI connected to corporate training data can directly act on behalf of human personnel, functioning as an automated virtual colleague or customer-facing advisor.

Centralization of Educational Documents

LMS iTutor includes an integrated document management system (iTutor Documents / DMS). This module allows storing all company guidelines, manuals, regulations, and educational materials in a structured manner, with version control and granular access permissions based on user roles and positions.

Conversion of E-Courses to Documents

Interactive e-courses are great for human learners, but LLMs cannot directly read proprietary interactive SCORM packages. LMS iTutor therefore automatically parses and converts the text and multimedia transcript of e-courses into structured document formats, which are indexed alongside traditional documents.

iTutor AI for Handling Student Requests

iTutor AI connects to the corporate knowledge base and handles queries using a Retrieval-Augmented Generation (RAG) architecture:

Generates embeddings from all uploaded documents and converted e-courses. Embeddings capture the semantic meaning of the text, represented as multidimensional numerical vectors with thousands of dimensions that numerically reflect the semantic closeness (similarity) of individual texts.

Stores the created embeddings in a vector database. This is a repository of multidimensional vectors where mathematical search algorithms can find the vectors closest to one another.

Processes natural-language user learning requests by converting the request into an embedding and searching the vector database for the embeddings closest to the query. This retrieves links to the information most likely to resolve the query. It verifies whether the user has read permissions for the source texts corresponding to the retrieved embeddings. If not, it iteratively searches for other close embeddings where the user does have access rights. The text passages corresponding to the retrieved embeddings, together with the user's natural-language query, are then processed by iTutor AI using the most suitable LLM to produce an accurate answer in the user's native language, including citations and links to the source documents. The user can review the answer—a concise synthesis of study materials representing micro-learning delivered JIT. In addition, the user can follow the provided source links. If the source is a document, they can open or download it; if it is a web page, they can visit the URL; and if the source is an e-course, the user can launch that e-course directly in the LMS to study the material interactively.

The above description is simplified for the purposes of this article. The actual process incorporates mechanisms for maintaining conversation context, adjusting embedding similarity thresholds, selecting the optimal LLM, automatically translating source documents into the requester's language, and many other aspects that exceed the scope of this article.

iTutor AI Chatbots

iTutor AI enables the creation of automated AI chatbots that can be embedded into any HTML page. To create an iTutor AI chatbot, one simply creates a virtual user in iTutor LMS and assigns them the appropriate permissions to documents in iTutor Documents. The iTutor AI module generates the required chatbot widget, whose JavaScript code can be placed on any intranet or internet webpage.

For example, a virtual user in LMS iTutor can be assigned similar permissions to documents as human employees in the "Sales Representative" role. The chatbot generated for this user can then be deployed, for instance, on the company website, where it will answer questions about products and services for prospective visitors, just like a salesperson. Thanks to centralized rights management in iTutor Documents, the chatbot can be precisely fine-tuned regarding what it should and shouldn't know. Such a chatbot would typically not have access to proprietary wholesale price lists or contract drafting, leaving specific quote negotiation to human representatives, but it can explain pricing principles and direct inquiries to the proper sales contact.

iTutor AI features its own API; in addition to the automatically generated chatbots described above, developers can program custom complex chatbots supporting voice input/output, video, animated avatars, and any other advanced capabilities. iTutor AI provides administrators with complete logs of user queries and chatbot responses, complete with user feedback ratings. This enables continuous refinement of the underlying knowledge base and ongoing enhancement of chatbot response quality.

Practical Example

Finally, here is an example of a simple chatbot answering basic questions about our company, its products, and services based on information gathered directly from the website where the chatbot is embedded. The chatbot also has access to several supplementary background documents uploaded into iTutor Documents specifically for its operation. Creating such a chatbot in LMS iTutor takes just a few minutes.

https://www.kontis.net/