Intelligent Learning Management Systems (ILMS): Implications for teaching and learning

Traditional learning management systems (LMS) have been used in higher education for a quarter-century and support online course management, administration, and learner assessment, while intelligent learning management systems (ILMS) extend the capabilities of traditional LMS with integrated interactive features powered by artificial intelligence (AI) [1]. AI-powered features are integrated applications, or apps, in ILMS that extend the capabilities of existing LMS such as Canvas, Blackboard, and Moodle. For example, AI chatbots (i.e., Ivy.ai) are currently integrated into the Canvas LMS to provide 24/7 student support. GradeOn is integrated into Canvas to assist with automated grading and feedback. Proctorio is integrated into Canvas and Blackboard to facilitate proctored grading. Packback, integrated into Canvas, Blackboard, and Moodle, enhances student discussion platforms with AI coaching to assist students in writing better questions and responses; it also offers automated grading of writing assignments linked to an instructor-designed rubric.

Several systematic reviews [2–4] have detailed multiple categories of AI use in ILMS:

• AI-computer-assisted content analysis to conduct student online assessments.
• Assistive technology to simulate conversation among students.
• Intelligent analytics and classification systems to detect students’ readiness to progress.
• Image analytics, including facial recognition, to take attendance.
• Support for collaborative learning.
• Academic support, institutional, and administrative services.

ILMS platforms’ capabilities include automating and streamlining content management, personalized curricula and learning, enhanced student engagement, improved content accessibility, immediate user communication and knowledge assessment, and sophisticated and curated content. While AI applications facilitate teachers’ classroom work by automating and reducing repetitive tasks, AI provides students with rapid, automated feedback using chatbots and customized tutoring systems. Educators should be aware of the functions of algorithms, AI, and machine learning to understand complex educational challenges [5]. This article explores eight features of ILMS platforms and provides examples for each feature.

A Closer Look at ILMS

Curriculum automation, customized content, gamification, virtual and augmented reality, real-time student support, individualized tutoring, personalized learning, and automated assessment are the principal features of ILMS that can mitigate teacher workload, predict learner behavior, and provide personalized learning tasks. Described below are each feature alongside examples of ILMS in higher education.

1. Curriculum automation. ILMS platforms reduce the human labor needed to design online content and activities. Traditional LMS platforms require constant updating, especially in disciplines in which knowledge changes or updates rapidly. ILMS can alleviate this time-consuming task for educators as AI can independently develop course content and activities. ILMS can curate and aggregate content by sorting through vast sources of information to identify, organize, and present the most suitable content. An ILMS platform increases content consistency across disciplines or institutions, thereby improving the consistency of the learners’ experience. Additionally, multiple curriculum generator platforms are available that use AI to aid in developing and organizing curricula for online courses [6].

For example, one university's engineering department implemented ILMS to automate the creation of course content for the rapidly evolving field of computer science. The ILMS platform continuously scans the latest research papers, industry reports, and academic journals to curate up-to-date and relevant materials. It generates interactive modules, quizzes, and assignments, ensuring the content remains current without requiring constant manual updates from faculty. Professors then review and customize the ILMS-generated content to match the course objectives and students’ learning levels [7]. Human teachers are still required to evaluate the content’s suitability and determine the level of knowledge learners should achieve within the course and semester.

2. Customized content. ILMS can automatically assess and curate content most relevant to each learner’s journey and their preferred media, learning format, and style. ILMS allow students to choose how content is presented (such as text, infographics, audio, or video) and their preferred language for learning. They can access information in multiple formats or repeat the lesson as often as needed to reinforce learning. With mobile apps, HTML5 sites, and other mobile functionality, learners can select where, when, and how to learn. ILMS platforms are responsive to learners’ speed of processing information and make learning more efficient [6]. 

In a university psychology course, the ILMS platform customizes content delivery based on each student's learning preferences and pace. Students can engage with the course material through text, podcasts, or video lectures. The ILMS platform offers interactive elements like quizzes and discussion forums to reinforce learning and provide feedback on areas where students need to improve. The system adapts the presentation of new concepts based on the student’s speed of processing information, ensuring that slower learners receive additional explanations and quicker learners are presented with more challenging material. The mobile-friendly platform allows students to access their coursework from any location, making it easier to integrate learning into their daily routines [8, 9].

3. Gamification. Some attributes of gamification include social engagement, competition, instant feedback, and the recognition of accomplishments. The ILMS platform supports varied game features, including allocating points for performance, levels, badges, progress bars, and leaderboards. Gamification makes learning feel more fun and less like work. The game features can increase learners’ enjoyment, retention of information, ability to transfer learning, and learning activity [10, 11]. 

At a university in Kazakhstan, a language learning app integrated within an ILMS platform uses gamification to enhance the learning experience. Users earn points for completing daily lessons, practicing vocabulary, and participating in conversation exercises. The app features levels that unlock new challenges and content as users progress. Badges are awarded for milestones like a perfect lesson streak or mastering a set number of words. A leaderboard displays users’ rankings, allowing them to see how they compare to their peers. Social engagement features, such as the ability to form study groups and compete in language challenges, further motivate users to stay active and engaged in their learning journey [12].

4. Virtual and augmented reality. Educators have turned to virtual reality (VR) and augmented reality (AR) as effective teaching tools for adults. VR offers immersive experiences through computer-generated simulations and sensory stimuli, enhancing proactive learning by engaging multiple senses. AR merges real-life environments with digitally enhanced elements, creating interactive experiences without requiring specialized headsets. Both technologies enrich learning experiences, foster greater engagement, and alter users' perceptions of reality [13, 14].

For example, a medical school integrated VR into its ILMS platform to provide students with immersive, hands-on training. They can practice complex surgical procedures using VR headsets in a simulated operating room. The VR environment replicates real-life scenarios with high fidelity, including the need to respond to patient responses and potential complications. This immersive experience allows students to gain practical skills and confidence in a controlled setting, enhancing their learning and preparation for real-world medical situations. The sensory engagement provided by VR helps reinforce knowledge retention and procedural proficiency [14, 15]. Similarly, an architecture program adopted AR to enhance the learning experience for its students [16]. Using AR-enabled tablets or smartphones, students can overlay digital models of buildings onto real-world environments. This technology allows them to visualize their designs in context, examining how structures interact with existing landscapes and urban settings. Students can walk around their AR models, experiencing different perspectives and scales. This interactive approach helps students better understand spatial relationships, design feasibility, and the impact of their work on the surrounding environment without the need for specialized headsets.

5. Real-time student support. ILMS can provide immediate feedback to learners, saving time and optimizing the learning process [6, 17]. In this case, chatbots are important in increasing learning efficiency, quality, and speed. Using natural language processing, ILMS platforms can give learners real-time responses to common questions and provide rapid assessment results. It is available when students need access in a way that human teachers are not. Receiving immediate feedback supports learning. These time-saving processes reduce learner frustration and optimize learning. The ILMS platform also tracks student’s learning progress and sends reminders about what learning activities students have completed and have yet to complete. Automated knowledge checks make learning processes more accurate and efficient. 

In an online university mathematics course, the ILMS platform uses chatbots to provide immediate feedback on problem sets and quizzes [18]. When a student submits an answer, the chatbot instantly analyzes it and provides detailed feedback on any mistakes, including step-by-step solutions and explanations. This real-time support helps students understand where they went wrong and learn the correct methods without waiting for a human teacher to review their work. Additionally, the ILMS platform tracks each student’s progress and sends personalized reminders about upcoming assignments and areas needing improvement, ensuring students stay on track.

6. Individualized tutoring. Using chatbots, ILMS can simulate voice conversations and be programmed to present an avatar that uses gestures, tone of voice, and facial expressions to make the relationship between learner and tutor realistic. Virtual tutoring is effective because the ILMS platform learns about a student’s knowledge, learning preferences, and preferred method of consuming information [6]. Intelligent tutoring systems can monitor students’ attention, performance, and emotions by noting the force and frequency of keystrokes and mouse manipulation [19]. When first developed, virtual tutors had to be programmed by hand, a laborious process requiring an investment of 200 development hours for each hour of tutoring. Later, that was reduced by approximately 75%. ILMS has reduced the time to a 1:1 relationship, meaning one hour of development equals one hour of instruction that benefits multiple students. This allows teachers to reduce the time spent answering repetitive questions, provide students with timely information to reinforce learning, and automate training delivery. 

In an advanced university language learning platform, the ILMS platform includes chatbots that simulate voice conversations with lifelike avatars. These virtual tutors adjust their teaching strategies based on the student's emotional state, gauged by analyzing keystroke dynamics and mouse movements. For instance, if a student appears frustrated due to frequent backspacing or slow responses, the tutor offers encouragement and simpler tasks to rebuild confidence. The ILMS platform tracks progress and adapts lessons to fit the student's pace, ensuring that learning remains effective and enjoyable. This system significantly reduces the development time for creating engaging and supportive tutoring sessions [20]

7. Personalized learning. A personalized course in the ILMS platform can appeal more to learners than a generalized course because it is relevant to their knowledge, responsibilities, interests, and proficiency. ILMS platforms can track individual learning patterns and adapt the curriculum to students’ needs. It can track students’ prior content learning and present new material based on each learner's pattern of knowledge and course performance. This function can detect learner weaknesses in understanding and present suitable content and tasks to meet students’ learning needs. ILMS can identify when a student is more advanced and automatically skips tasks to adapt the content to the learners’ knowledge level. Because of its personalization capabilities, ILMS can provide intuitive content and increase engagement. Learners may feel the course was tailored to their needs because it avoids repeating content and learning tasks students have mastered. In addition, by using ILMS, the allocation of resources saves time and simplifies and automates the task of analysis for the educator [6, 21].

A university business school offers an online business management course through an ILMS platform that tracks each student's professional background, previous coursework, and performance. For example, for a student with extensive experience in marketing but limited knowledge in finance, the ILMS platform adjusts the curriculum to focus more on financial management topics, skipping introductory marketing modules. This personalized approach ensures that the students are not spending time on areas they already understand but are instead gaining proficiency in new and relevant subjects. The platform provides real-time feedback and adaptive assessments, making the learning experience more engaging and efficient [22, 23].

8. Automated assessment. ILMS assessment can be a labor- and time-saving device for educators, but human oversight is still required. Due to individual students’ characteristics and needs, caution must be used when implementing algorithmic-based automatic grading. Educators can use formative assessment to analyze data on students’ learning. ILMS platforms can evaluate learner behavior over different modules and provide insights about the effectiveness of the course, areas of the learning content retained by learners, and content areas that need more work. This information can improve the course content and enhance learning activities [6].

An online university mathematics course employs an ILMS platform to handle automated assessments. The ILMS platform grades assignments and quizzes based on predefined algorithms, providing immediate feedback to students. The course instructor regularly reviews a sample of the graded assessments to ensure the accuracy and fairness of the automated grading. The ILMS platform collects and analyzes data on student performance across different modules, identifying areas where students struggle the most. This insight allows the instructor to adjust the curriculum, provide additional resources, and improve learning activities to address those challenging topics [24].

Implications for Teaching and Learning

With the advancement of ILMS, the practice of creating online learning experiences is evolving [25]. The benefits of ILMS platforms include customized content, curriculum automation, real-time student support, personalized learning, gamification, virtual tutoring, and enhanced learning assessments. ILMS platforms can significantly improve the quality of learning experiences by tailoring content and skill development based on learner progress, which helps achieve educational goals. Automation within the ILMS platform can reduce students' time on tasks and personalize their learning, leading to increased motivation. 

However, ILMS platforms can influence human decision-making. The values embedded in AI and machine-learning algorithms may impact outcomes unless they are actively managed and corrected by humans. Educators might not always be aware of the intricacies of the code that drives these systems. ILMS platforms should be designed to be safe and effective, include protections against discrimination, ensure user privacy, provide clear notice that AI is being used, and offer human alternatives when needed.

Reliable systems with risk mitigation. A collaborative approach is essential for ILMS platforms to be reliable and safe, involving diverse communities, stakeholders, and domain experts. During the development phase, these groups should collaborate to identify potential concerns, risks, and broader impacts of the system. Before deployment, pre-testing is crucial in risk identification and mitigation, and ongoing, dynamic monitoring ensures that emerging issues are addressed in real time. Independent evaluations should be embedded into the oversight process to validate the safety and effectiveness of the system. Transparency in this process is key, and findings from these evaluations should be published to inform the public and other stakeholders. This ensures that ILMS platforms are built on sound foundations and continuously improved through evidence-based practices and risk mitigation strategies. These practices foster accountability, safety, and effectiveness, aligning with best practices for ensuring that ILMS platforms operate reliably and ethically [6, 26].

Protection from algorithmic discrimination. Educators must take proactive and ongoing steps to shield learners from algorithmic discrimination and ensure the equitable design and use of ILMS platforms. Algorithmic discrimination can be based on the data used to train the system based on race, color, ethnicity, gender, sexual identity, religion, age, national origin, disability, veteran status, genetic information, and other legally protected characteristics. Educators should develop equitable systems and conduct regular evaluations to protect individuals and communities from discrimination. Bias detection and mitigation can be achieved through inclusive data collection and augmentation, regular internal audits, fairness metrics to ensure demographic parity, and continuous monitoring. Regularly performing and, whenever possible, publishing algorithmic impact assessments, including disparity identification and mitigation measures, is essential [6, 26].

Respect for privacy. Protecting privacy in ILMS platforms is paramount, especially as they collect sensitive information about students' progress and performance. ILMS platforms must prioritize safeguarding student data from the outset, with clear mechanisms in place for data protection throughout the system's lifecycle. Data collection should be strictly limited to the minimum necessary to support educational outcomes, and informed consent must be secured for all data-related activities, including collection, use, transfer, or deletion of data. The potential risks of surveillance should be mitigated by avoiding continuous monitoring of students or communities, thus preserving their autonomy and dignity. Students should be provided tools to verify that their data preferences have been upheld, particularly in educational settings where privacy concerns are heightened. Reports should not only focus on technical details but also assess the impact of data storage on fundamental human rights, equal opportunities, and equitable access to education. This approach will ensure that privacy protections in ILMS extend beyond technical safeguards, including ethical considerations and respect for students' rights in the digital age [6, 26].

Information dissemination regarding data privacy. Ensuring the ethical dissemination of information regarding data privacy within ILMS platforms safeguards learners against exploitative data practices. Learners must maintain full control over how their personal information is used, shared, and disseminated. To achieve this, privacy protections should be embedded into the core architecture of ILMS platforms, focusing on user autonomy and consent at every stage. Educational institutions must adopt a rights-centered approach, where privacy concerns are addressed without compromising students' educational experiences or future careers. These practices ensure a more responsible, ethical, and learner-centered approach to data privacy in educational environments [6, 26].

Reporting of drawbacks. To foster trust and effectiveness in ILMS platforms, users must be fully informed that they are engaging with automated systems and educated on how these systems can complement their teaching and learning experiences. Clear communication is vital, especially in areas as sensitive as education, where the role of automation must be carefully managed. Users should be able to choose human intervention whenever they feel it is necessary or beneficial. Students and educators should be able to escalate issues to a human reviewer, especially for decisions with significant personal or academic implications. Appeals and reviews of system decisions should follow a structured, transparent process to ensure fairness and accountability. ILMS platforms should be custom-designed to meet the specific needs of the educational context in which they are used, accounting for the unique challenges of automated decision-making in sensitive areas like education [6, 26].

The Future of ILMS

ILMS platforms can potentially revolutionize the online learning experience in educational environments. They are highly efficient at automating laborious tasks. They can increase the efficiency, quality, and speed of learning; facilitate the allocation of resources by saving time and automating task analysis; optimize learning and reduce learner frustration; assess learner progress during the course; and evaluate course effectiveness upon completion. Table 1 summarizes ILMS platform features and their benefits for teaching and learning.

Table 1. ILMS Platform Features and Their Benefits for Teaching and Learning.

Integrating AI into traditional LMS, resulting in ILMS, offers significant advancements in eLearning. ILMS platforms automate repetitive tasks, provide personalized learning experiences, and enhance student engagement through features like curriculum automation, customized content, gamification, virtual and augmented reality, real-time student support, individualized tutoring, personalized learning, and automated assessment.

Adopting ILMS brings new challenges, particularly in confronting privacy issues, algorithmic discrimination, and system reliability. Ongoing training is essential for individuals interacting with these systems, ensuring they remain proficient and aware of best practices as technology evolves. Human oversight is crucial for high-risk or critical decisions, with personnel equipped to handle safety, security, and ethical concerns. Safeguarding learners' privacy and ensuring data protection are paramount. The development and deployment of ILMS platforms should involve diverse stakeholders to identify and mitigate risks, with continuous monitoring and independent evaluation to maintain safety and effectiveness.

To protect against algorithmic discrimination, educators must design equitable systems and regularly assess their impact. Transparent reporting on data practices, respect for privacy, and the operation of automated systems is essential. This ensures that users are informed and can access human alternatives when needed.

By addressing these concerns and leveraging ILMS' capabilities, educators can create a more efficient, engaging, and personalized learning environment that enhances learning outcomes while respecting the rights and dignity of all learners. To maximize ILMS's benefits, it is essential to implement robust safeguards, involve diverse stakeholders in their development, and ensure ongoing monitoring and evaluation. As ILMS technologies continue to evolve, they have the potential to create more dynamic, responsive, and effective learning environments, ultimately transforming the educational landscape.

References

About the Authors

Dr. Lillian H. Hill is Professor Emerita at the University of Southern Mississippi School of Education. Her work experiences included program and conference management, faculty development, and academic appointments. Dr. Hill is an award-winning professor and 2018 inductee into the International Adult and Continuing Education Hall of Fame.

Dr. Simone C. O. Conceição is Professor Emerita in the Department of Administrative Leadership at the University of Wisconsin-Milwaukee. She is also a learning design consultant and owner of SCOC Consulting. Her areas of interest include artificial intelligence in education, distance education, adult learning, the impact of technology on teaching and learning, learning design, and staff development and training. In 2018, Dr. Conceição was inducted into the International Adult and Continuing Education Hall of Fame.