10 Top LMS Trends: Technologies Driving Learning Management Systems

10 Top LMS Trends: Technologies Driving Learning Management Systems
Imed Bouchrika, Phd by Imed Bouchrika, Phd
Chief Data Scientist & Head of Content

The rollout of one of the earliest Learning Management Systems (LMS) in the ’90s, FirstClass by SoftArc (United Kingdom), gave the educational sector an initial glimpse of the revolutionary way education could be deployed via the internet (Oxagile, 2016). FirstClass was used to deliver online learning across Europe up until the early 2000s.

Since then, LMS has evolved from merely administering student records and distributing course materials to today’s core system pulling together other technologies that are propelling education into the future. Modern LMS systems today do more than just host and deploy courses; they leverage analytics that brings with it a deeper understanding of, not just student performance, but the whole learning experience with 360-degree visibility. That is, from the perspectives of the administrator, instructor, and student.

This article presents the technologies that are driving LMS today, including analytics, interoperability, virtual reality (VR) and augmented reality (AR), mobile technology, and social networks. These technologies are pushing the envelope on the potential use of LMS to reach more students with more personalized learning courses and more equitable and better learning outcomes.

Technological Trends Driving LMS Today

  1. LMS Analytics Trends
  2. LXP: Next-Generation LMS
  3. Semantic Interoperability to Gain Traction
  4. xAPI Developments
  5. Virtual Reality in LMS
  6. Augmented Reality in LMS
  7. Mobile-first LMS
  8. Richer Device Responsiveness
  9. Rise of eLearning Ecosystems
  10. Social Learning Will Go Mainstream

LMS Analytics Trends

As a platform that links together data from various systems, content, records, and processes of an online learning environment, LMS leverages analytics to generate insights that will help administrators, educators and students make data-driven, hence, smarter decisions. In academic research, the benefits of data-driven decision making are proven conclusively, primarily resulting in better business performance (Provost & Fawcett, 2013). The same benefits can be harnessed in the academe, for instance, to improve student attainment and progress (Schildkamp et al., 2013) and operations as well.

Improve Student Performance

Able to drill down to the finer details of data and reach a wider range of processes, LMS today do more than monitor student performance. Among others, modern LMS can (Movchan, 2019):

  • Process enrollment metrics
  • Identify specific course parts that are most difficult or interesting to students
  • Run diagnostics to improve a course or process
  • Track learner’s engagement in a course
  • Cluster students based on key metrics, for instance, progress or score

In particular, Sujitha and Sridhar (2020) discussed how analytics can be generated using different methods like clustering, classification, prediction algorithm, data mining classification and 3D cubes classification. Today’s LMS solutions are more than capable of performing such data processing either as a standalone system or integrated with analytics software.

Personalized Learning

Learning analytics can also help schools to tailor courses and learning pace based on the needs of different students. An LMS can generate and mash-up different reports, such as learner’s activity report,  learner’s progress report, and problem report at the individual level, which enables educators to customize a “road map” of course materials for each student.

In the age of big data when learners are faced with an incessant barrage of content, analytics provide the lit path to help the learner sort the right materials for him. For example, one study presented a novel way of applying learning analytics to classify large video collections to support micro-learning. In the study (Danilo et al., 2019), researchers combined learning analytics with Speech-to-Text, Natural Language Processing, and Cognitive Computing, which, the researchers said, can help content managers facilitate micro-learning video collections down to the individual learner’s needs.

Improve School Operations

Able to leverage more powerful analytics, LMS brings with it benefits to running schools more efficiently. Modern LMS can generate analytics by pulling and consolidating large sets of financial and operational data. This enables administrators to run statistical and predictive modeling for smarter strategic decisions (LAMBDA Solutions, 2016). In one study (Ahmad et al., 2019), librarians were found to use large data sets to conduct library operations such as curation and analysis, acquisition and preservation of data.

Improve eLearning Delivery

Not the least, cloud-hosted LMS provides schools with an online infrastructure the better to reach students at a time when universities are locking down due to the pandemic. In particular, the use of web analytics in LMS is promising, able to solicit usage data, base improvements, and user feedback (Baron, 2018). These data aid administrators in improving their online learning services, for example, delivering the right courses to the right learner at the right learning pace.

In general, Baron 2020 put forward three web analytics methods that can be applied to evaluate one’s LMS-driven online learning program:

  • Learner web log analysis – helps determine the status of current learning activities
  • Learner life-cycle analysis – investigates KPIs of individual learner or learner group
  • Learning progression analysis – combines data derived from the web metrics-driven analysis of LMS and online learning outcomes.

By combining web analytics with LMS data, administrators are given a comprehensive data framework to assess their online learning program, which can result in more valid evaluation. A good baseline example is the analytics one can glean from an integrated Google Analytics and LMS. The former allows you to see key metrics, such as time spent on a course, rapid page exits, learner preferences, and elearning marketing effectiveness. On the other hand, an LMS can provide learner satisfaction rating, proficiency, personalized metrics, and learner progress.

Democratization of Analytics

Analytics is seen by more higher learning institutions (HEI) today as integral to all departments, no longer confined to the jurisdiction of data scientists. That means administration, finance, HR, faculty, and even the alumni body are staking their interest in analytics and that usually means relying on data churned by LMS (Ovum, 2018).

Many advanced LMS can digest key insights, such as user interaction statistics, completion rates, and session times. Insights on sessions vs. total users, device type, and other user statistics can also help school administrators make smarter business decisions.

Nevertheless, deploying analytics is another matter. A study by Ovum (2018), a technology research firm, showed that 67% of HEIs are still either planning or trialing the deployment of analytics across departments. Even in mature HEI areas where analytics is a historical component–managing enrollment data–only a third of institutions have deployed full analytics.

What is indicative though of the fact that HEIs recognize the importance of cross-departmental data analytics is the findings on institutions that are not planning to deploy full analytics. For example, only 6% do not consider fully deploying analytics for enrollment management and 14% for alumni management.

Being the primary data analytics platform for HEIs, LMS is poised to grow alongside the drive to apply more analytics in the conduct of higher learning.

LXP: Next-Generation LMS

The ability to personalize content and customize one’s learning pacing is giving rise to learning experience platforms (LXP), where users study lessons that fit their interests or needs and at their own pace.

LXP is more suited to corporate training where learning is less structured and on a needs-basis.  But there is no reason for the academe not to embrace LXP for its inherent benefit of making learning more engaging with the use of AI and machine learning. Consider the benefits:

  1. Learners can mix and match lessons to come up with their own coursework. This means students can focus their learning on matters that truly interest them.
    Through machine learning, LXP can curate an intelligent selection of course materials for the learner.
  2. AI-based LXP can generate microlearning, able to break down lessons into digestible bits that learners can more easily absorb and retain. Schools that plan to incorporate agile learning in their teaching modalities will benefit from this feature.
  3. LXP analytics can deep dive into user learning data and generate dashboards and reports that allow administrators to understand usage trends. This helps them make smarter decisions.
  4. Customized learning paths mean learners are directed towards personalized learning goals.

Semantic Interoperability to Gain More Traction

Many LMS systems today can integrate with other LMS systems and even with other key business applications like payment gateways, CRM and document management apps. However, the integration is often limited at the date field level (Haag, 2015). For instance, Experience API (xAPI or Tin Can API), the elearning specification that allows for the consistent collection of a learner’s data across multiple platforms, devices and technologies, mainly focuses on the structural interoperability. Data is shared and is compatible between LMS systems, but its interpretation may be inconsistent for lack of shared semantic specifications. xAPI.com admits that without semantic interoperability, “the Experience API has a limited future” (Miller, 2017).

Such a limited level of integration tends to make LMS a closed system even today, something highlighted by Tiropanis and colleagues (2009) more than a decade ago. They noted the need for different systems to agree on the definition of the concept of course, summary, class, and pedagogical resource to leverage a shared learning experience ecosystem.

But as learning providers and HEIs move towards leveraging big data, the interest in semantic interoperability, which provides a universal vocabulary so different systems can interpret data in the same context, may gain more traction in the coming years.

Already, a semantic web solution to enhance LMS interoperability has been proposed by Bakhouyi and co-researchers (2019). The study concluded that having content standards ensures interoperability between LMS systems, in particular, between their web and mobile versions. Their study used the JSON-LD mapping tool to transform JSON format declarations into RDF format. The study showed the potential of learners to have access to immense volumes of learning resources stored in different LMS systems. Likewise, educators can look forward to generating statistics and reports from no-SQL data and from IoT devices, the researchers suggested.

It can be recalled that another semantic web modelling idea of using a “univ” namespace for university-based LMS systems was suggested back in 2011 (Rashid et al., 2011). The idea is to have a semantic portal under the “univ” label grouping various elearning services and tools, including course documents, registration, and assignments. The “univ” namespace, the researchers said, could help learners find information on a university’s course materials quickly via a semantic search.

For sure, more studies are needed to explore the potential of semantic interoperability. In fact, Bakhouyi and colleagues (2019) noted this architecture is in development but is expected to progress as technologies in general advance and more learning providers realize the promise of big data analytics off the continuous tons of data being churned out by LMS systems worldwide.

Source: eLearning Trends 2019, Docebo

xAPI Developments

No doubt,  xAPI will play a major part in a future consolidated ecosystem of different LMS systems. xAPI builds on the capabilities of SCORM (Sharable Content Object Reference Model), which is still the compatibility standard for many LMS systems. But where SCORM can only collect four types of data in learning sessions—pass/failed, completed, time, single score—and cannot integrate other learning performance evaluation data, xAPI captures a wider scope of the learner’s activities from various technologies through the Learning Record Stores or LRS (xAPI.com, 2020). LRS acts as the “server” where learner data is stored and shared. As a result, different systems can capture and communicate learner data based on the LRS.

Ultimately, any undertaking towards a future LMS ecosystem needs to be kept abreast of the latest xAPI developments.

IEEE standardization underway

The Institute of Electrical and Electronics Engineers (IEEE), the world’s largest technical professional organization, is working on the latest xAPI specifications that will elevate its data model format and communication protocol to IEEE standard. This ensures xAPI is up to speed with the latest data-intensive learning technologies for greater interoperability between xAPI-enabled solutions (P92741.1 xAPI Work Group, 2020).

xAPI adoption by LMS vendors

The increasing number of xAPI-enabled LMS systems points to a long shelf-life of this compatibility format. As of June 2020, there are 80 LMS adopters of xAPI, as far as xAPI.org knows. They include known brands as Moodle, Talent LMS, Survey Gizmo, docebo, efront, iSpring and LearnUpon.

Similarly, a survey of 535 L&D professionals and providers showed that xAPI adopters “have leapfrogged” their organizations ahead of those of non-adopters (Torrance, 2019). The survey suggests a positive outlook by the industry towards xAPI. Tellingly, among the issues hounding the non-adopters is security and privacy concern over the ethics of capturing detailed human performance as sensitive as one’s learning data.

Different product vendors sharing xAPI statements

Another innovative xAPI feature is sharing statements. xAPI enables the migration of data out of LMS and into another system through LRSs. It is a groundbreaking development when one imagines the potential of sharing records not just between LMS systems, but between LMS and any product that generates statements (xAPI.com, 2020).

xAPI.com sees its API will allow sharing statements to extend beyond LMS vendors, authoring vendors and content vendors. For instance, in a future scenario, an IoT device like a smart TV acting as a learning channel extension is not difficult to imagine where LRS can be shared across different xAPI-compliant devices.

Source: Rustici Software

Virtual Reality in LMS

LMS for higher education has been adopting immersive technologies such as VR and AR to cater to the various needs of learners to keep them engaged in learning. Virtual Reality uses a head-mounted display, which completely changes a person’s vision, whereas Augmented Reality projects images either on a tablet or a computer screen.

Both VR and AR foster learning in greater depth. With the adoption of these advanced learning tools in an LMS system, students will be able to build knowledge and retain course content by utilizing sensory skills. They are instrumental in helping educators prepare the next generation for the challenges of a 21st-century world and are essential to the development of learning in the digital age.

For example, colleges and universities have put up research facilities to study on the topics of VR and AR (Schaffhauser, 2019). Academic conferences have been held using virtual reality such as in Lethbridge College in Alberta and Centennial College in Toronto for the last two years. Apparently, immersive technologies in the classroom have an immense impact on course design and delivery as these learning platforms help students interact with the world around them and help develop the students’ critical thinking and problem-solving skills.

VR in Higher Education

To keep up with the fast-paced 21st-century learners, higher education institutions can integrate VR to promote learning beyond traditional teaching method. For instance, San Diego State University Instructional Technological Services has been using virtual immersive teaching since 2017 (Hauze, 2019). 3D graphics in Virtual Reality help deliver a unique, environment setting where students can use their senses, such as vision, hearing, and touch. Students are immersed in what appears to be a real-world experience in an environment where they can interact with stimuli.

VR in Medical School

In medical school, part of learning is also done in VR. Medical students can now use virtual reality programs based on pictures from medical imaging technologies instead of studying anatomy by dissecting corpses of animals or bodies of people donated to science. These 3D programs let students examine and see body parts and organs, and make virtual cuts into them. The advantage of using these programs is that they can repeat the process as many times as they need to.

VR a Perfect Fit for Teaching Astronomy

An instructor in the astronomy department of San Diego State University Instructional Technological Services, Gur Windmiller, believes that VR is “a perfect fit” to introduce astronomy to students (Price, 2018). VR enables students to make meaning out of difficult postulations and theories presented in traditional teaching styles. He further explained in a university article that it is a very visual subject wherein students can just see astronomical objects and play with them as they discover and learn more about these objects.

VR in Architecture

A company called Sunrise VR has made an educational VR program that teaches architecture in its most natural form. Virtual Chicago lets students see and experience the development of modern architecture by hovering over Chicago and lets them survey the city’s buildings and architecture. The program also provides a demonstration of how a skyscraper is built and includes an introduction to architecture throughout history, famous architects, and a description of modern architectural designs, among others.

Interest in VR in Higher education

In support of VR programs, Morgan and Resnick (2017) recommended the use of virtual reality platforms in higher education which will help students acquire achievement and become better engaged in class. They further elaborated that from a higher education perspective, the interest in VR stems from factors such as its efficiency to enhance learning for students, its ability to help attract and retain students, and it prepares the students for their careers.

VR Tools Help Improve Communication Skills

The National Education Association or NEA has concluded that the modern technology of today demands for global competitiveness among team players that makes it necessary for the new graduates to be able to use different languages in a clear and effective way.

According to a 2018 survey on the future of work by the Association of American Colleges and Universities, employers across all industries also prefer applicants with strong oral and written communication skills when hiring.

For instance, VR apps for students such as VirtualSpeech are made to help students practice their stage performance and speaking skills. Jon Spike presented the app at IDEAcon 2020.  He is the coordinator of instructional technology integration services at the University of Wisconsin-Whitewater. The app immerses students in realistic virtual environments, including seminar rooms and auditoriums and students can practice giving speeches or presentations, after which they will be given feedback on their performance.

Benefits of VR to Businesses and Education Cost

VR programs in businesses and education are not yet widely used because they can be costly to create, but they can be a better alternative in the long run by decreasing expenses remarkably on costly real equipment and machinery in companies. In corporate training, simulation programs also reduce risk to the environment and human lives. In education, VR programs could be a better option to reduce costs in maintenance in laboratories where students carry out experiments or a possible substitute for the use of real equipment which could be more expensive than buying or creating these programs.

Augmented Reality in LMS

AR also plays a major role in the future of higher education. Although AR can only be seen on a device, it can set students in a distinctive learning environment wherever they are, be it a classroom, a facility, or even their home with the use of Google’s augmented reality programs. With a greater level of context and scale, AR is very useful as a visualization tool that can help students in higher education understand theoretical concepts more easily. AR apps address the difficulty of hard-to-grasp concepts of science by bringing it to life, thereby making it easier for students to learn, as well as improve their critical thinking and solving skills. In some universities, AR apps are utilized for historical and architectural reviews and campus tours.

Medical school

The integration of augmented reality in higher education is becoming more in demand and popular. As an example, Case Western Reserve University use an AR app called HoloLens and HoloAnatomy that first year medical students in their university can use to learn about the human body through 3D learning of a virtual human. It is created by Case Western Reserve University and Cleveland Clinic.

Art Objects and Historic Relics

Taking learning to the next level, researchers in the Department of Geography at Penn State University designed an AR app that provides details about the Obelisk, which is one of the most popular and oldest memorials on the campus built in 1896. It was made of minerals and rocks and what’s more fascinating is that a collection of data is linked to every 281 stones and when a stone is touched, it gives information as to where it came from, how old it is, and other information according to its geologic time period. A doctoral student in geography, Arif Masrur, stated that in addition, they also target to have 3D photos of where the rocks actually originated.

AR on Specializations

Another example of AR being incorporated in higher education is through the use an AR app developed by Deakin University’s School of Medicine and Eon Reality, called cARdiac ECG AR app which allows students to view the heart in 3D and learn about the mechanism and the basics of the heart in relation to ECG. The app immerses students to learn and explore the essential foundations and basic anatomy of the heart, including its physiology and pathophysiology as well.  

AR on STEM Labs

Augmented technology is already being used at the University of Rochester as a part of their learning curriculum in their science, technology, engineering and math (STEM) laboratories. The university used augmented reality to design a hands-on lab involving the sense of touch that students’ working on a chemical plant was made possible. Students could observe and examine chemical reactions by placing together multiple reactors with different temperatures.

AR in Online Education

To help students feel more connected with everyone in class even when they are located in different places, AR might be a potential tool for online education. A related technology is already being used to give students a better learning experience in distant classrooms, such as digitally improve projections of images of professors from one classroom to another.

Mobile-first LMS

Mobile technology is playing a more strategic role in course deployment, with almost all college students having a smartphone or tablet. In fact, in their study, Magda and Aslania (2018) found out that 87% of online students searched for online courses via a mobile device, while 67% even completed coursework from a mobile device. LMS vendors will do well to ensure their platforms are mobile-responsive, if not mobile-first designed, to capture this growing reliance on mobile access.

Richer Device Responsiveness

Remote access will go beyond smartphones and tablets. The Internet-of-Things, the general term for connected devices, thanks to more powerful and accessible hardware and an internet connection, can lead to more devices connected to LMS, such as smart TVs, electronic whiteboards, smartwatches, smart glasses, and other electronic devices. Coupled with a consolidated elearning ecosystem, you have a wider array of learning materials accessible to a wider range of devices than ever before.

Rise of eLearning Ecosystems

Many LMS vendors today offer a rich library of course materials for their subscribers. However, these are standalone libraries, meaning, users are limited to the vendor of their subscription. Driven by a growing customer base of school administrators, educators, and learners, the LMS industry is expected to consolidate their libraries, allowing for a shared, collaborative elearning ecosystem. This will open up more resources to more users and lend to learners more personalized courses given the wider horizon of choices.

Likewise, there is no stopping LMS vendors to collaborate with other software systems like CRM to further extend the software’s capabilities and enrich the learning experience.

Social Learning Will Go Mainstream

The same elearning ecosystem may spawn more collaboration between students belonging in the same school or are even miles apart. Collaboration leads to social learning, where learners share information and collaborate on projects on a regular basis utilizing blogs, forums, live events, social networks, chat apps, and other communication channels. Students and educators can discuss ideas, debate on issues, or provide feedback to each other, generating more knowledge and best practices on a scale never been seen before.


The technological advances above can only point to a next-generation breed of LMS solutions, one that is more efficient, streamlined, and powerful. No longer just the engine driving online learning, the future LMS is expected to be the “brains” consistently showing the stakeholders the way to better learning paths at the group and individual level, a more efficient way of managing the courses, and a streamlined channel to communicate.



  1. Bakhouyi, A., Dehbi, R., Banane, M., & Talea, M. (2019). A semantic web solution for enhancing the interoperability of e-learning systems by using next generation of SCORM specifications. International Journal of Emerging Technologies in Learning, 14 (11), 174. https://doi.org/10.3991/ijet.v14i11.10342
  2. Baron, M. (2018, June 13). LMS performance analysis: Using web analytics methods to improve elearning delivery. eLearning Industry.
  3. Case School of Engineering (2016). HoloAnatomy app wins top honors. Case Western Reserve University.
  4. Dessi, D., Fenu, G., Marras, M., & Recupero, D. (2019). Bridging learning analytics and cognitive computing for big data classification in micro-learning video collections. Computers in Human Behavior, 92, 468–477.  https://doi.org/10.1016/j.chb.2018.03.004
  5. Haag, J. (2015, July). xAPI Vocabulary – Improving semantic interoperability of controlled vocabularies. SlideShare.
  6. Hart Research Associates (2013). It takes more than a major: employer priorities for college learning and student success. Liberal Education, 99 (2). AACU
  7. Hauze, S. (2019, April 23). VITaL: The future of immersive learning at SDSU. Instructional Technology Services.
  8. Miller, B. (2020, May 14). Semantic interoperability. Picking the best verb for a statement. xAPI.com.
  9. Movchan, S. (2019, July 10). LMS Reporting: Why do we need data in digital learning process? RacoonGang.
  10. National Education Association (2012). Preparing 21st century students for a global society: An educator’s guide to “the four Cs.” Washington, DC: NEA.
  11. Oxagile (2016, April 12). History and trends of learning management system [Infographic]. Oxagile.
  12. P92741.1 xAPI Work Group (2020). P92741.1 XAPI Base Standard. IEEE
  13. Price, M. (2018, April 24). Making VR Learning a Reality. SDU NewsCenter.
  14. Provost, F. J., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1 (1), 51–59. https://doi.org/10.1089/big.2013.1508
  15. Rashid, S., Khan, R., & Ahmed, F. (2011). Towards E-Learning Management System using Semantic Web Technologies.: A great proposed model for E-LMS in Semantic web and a unique university namespace “univ” for developing this E-LMS. Saarbrücken, Germany: LAP LAMBERT Academic Publishing. ACM
  16. Resnick, M., & Morgan, G. (2017, August). Best practices for virtual reality in higher education. Gartner.
  17. Schaffhauser, D. (2019, May 15). 9 amazing uses for VR and AR in college classrooms. Campus Technology.
  18. Schildkamp, K., Lai, M.K., & Earl, L. (Eds). (2013). Data-Based Decision Making in Education: Challenges and Opportunities. New York, NY: Springer.
  19. Tiropanis, T., Davis, H., Millard, D., & Weal, M. (2009). Semantic technologies for learn-ing and teaching in the Web 2.0 era. IEEE Intelligent Systems, 24 (6), 49-53. https://doi.org/10.1109/MIS.2009.121
  20. Torrance, M. (2019, September). 2019: The state of xAPI adoption. The Learning Guild.
  21. xAPI.com (2020). Sharing Statements. London: Rustici Software.

Newsletter & Conference Alerts

Research.com uses the information to contact you about our relevant content. For more information, check out our privacy policy.