Speculative Future of the Learning Management System

Through future analysis, we can identify potential challenges and discover new opportunities for growth and innovation. This paper applies this methodology to examine the critical software of educational technology (EdTech), the Learning Management System (LMS), from the context of the defence industry. Through an analysis of the LMS’s past, present, and potential futures, we will explore the Total Learning Architecture (TLA) (Advanced Distributed Learning Initiative, 2020) and modern data standards like the Experience Application Programming Interface (xAPI) (xAPI.com, n.d.-a). In doing so, this paper offers insights into the potential future of the LMS or its permutation by 2030.

Learning Management System

The Learning Management System (LMS) is a software solution at the heart of most digital learning environments, facilitating the distribution and management of training materials. The LMS gained prominence in 2002 (Weller, 2020, Chapter 2002) as a unified solution that replaced the integration challenges of using multiple third-party tools. While the LMS may not provide best-in-class capabilities, it often offers a “good enough” solution, a critical attribute that drives mass adoption in edTech, as highlighted by Weller (2020, Chapter 2002). The LMS’s primary functions include distributing, facilitating, assessing, and reporting of education in digital learning environments (Advanced Distributed Learning Initiative, 2020, p. 6; Watson, 2007). Critics argue that the LMS can be restrictive, lacks capabilities, and is limited by users’ digital literacy skills (Gibbs et al., 2021, 1:50, 4:10, 20:20; Weller, 2020, Chapter 2002) while also requiring significant resources to maintain and manage. Despite these challenges and critiques, the LMS market continues to grow, with a compound annual growth rate of 19.6% from 2018 to 2023 (Bouchrika, 2024). 

The LMS faced its ultimate test during the COVID-19 pandemic in 2020 when the education industry shifted to online learning due to necessity due to a worldwide social lockdown to mitigate the spread of Coronavirus. During the COVID-19 pandemic, studies demonstrated the LMS’s effectiveness in maintaining learning continuity (Raza et al., 2020; Alturki & Aldraiweesh, 2021). This evidence shows that while the LMS may not excel in every feature, its ease of use and access to essential educational functions in the digital space has driven its ongoing growth and relevance. While the LMS has proven its value during the pandemic, its limitations are more pronounced in specialized sectors like defence, where lifelong learning and adaptability are critical.

Challenges and Limitations of Defence Industry LMS

Assessing the limitations of critical capabilities of the defence industry LMS is challenging as these systems may be proprietary or adapted from consumer-based platforms and not made publicly available (Department of National Defence, n.d.-a). While addressing software gaps is necessary, the LMS’s ability to support a life-long learning continuum is crucial in the defence sector. This is key for continuous training and development throughout the long military careers, spanning 20-25 years, at multiple training schools, as seen in the Canadian Armed Forces (Department of National Defence, 2022; Canadian Armed Forces, n.d.-a, Education & Training section; Department of National Defence, n.d.-b). Consequently, the LMS must facilitate course management, ongoing professional growth, and adaptability throughout a service member’s career.

Advancements in technology have significantly enhanced the distribution and accessibility of training content in the digital space. Learners can now access training from their mobile devices, shifting the education paradigm away from predefined spatial and time-based constraints (ADL Initiative, 2020; Kearney et al., 2012). This evolution allows training to be more flexible, on-demand, and personalized to the learner’s schedule and environment. As our access to technology changes, so does how we can conduct training to meet the needs of students. In response to these needs, the Advanced Distributed Learning (ADL) organizations— which are distinct entities located in Canada, the United States and other countries, reporting to their respective defence industries, aim to enhance training and professional development by leveraging advanced technologies to support lifelong learning, adaptability, and readiness (ADL Initiative, n.d.-a; ADL Initiative, n.d.-b). 

Advanced Distributed Learning Initiative (2020) states that the Total Learning Architecture (TLA) is the digital framework solution that guides and ensures the interoperability of education technologies powered by data and process standards driven by critical strategies. These strategies include integrating learning experiences to facilitate the exchange of student performance data and shifting from a one-size-fits-all model to a personalized, adaptive learning experience. The initiative also emphasizes improving data collection, encompassing formal, informal, and historical data, and using this data to automate and align training distribution with institutional goals. Subsequently, it calls for the transition from rigid, vendor-locked digital architectures to decentralized, modular infrastructures, allowing for the insertion of technology capabilities when and where needed. These strategies will foster adaptive learning, training anywhere, and data-driven education solutions.

The ADL’s proposed TLA breaks down the LMS into its core functions and defines integration processes and data standards developed by industry and the Institute of Electrical and Electronics Engineers (IEEE, n.d.), which aim to ensure adaptability, scalability, and modularity for the future learning ecosystem. Decoupling the core capabilities of the LMS may seem like a regression to the pre-LMS era, reintroducing the complexities of integrating third-party systems. However, advancements in technology—such as cloud computing, high-speed internet, and software design methodologies like microservices (ADL, 2020; Pachghare, 2016)—significantly reduce the complexities associated with integrating software solutions in ways that were not feasible in the past, mitigating past challenges.

Integration of training content in the LMS relies heavily on the Shareable Content Object Reference Model (SCORM), which enables the exchange of student performance data (SCORM.com, n.d.). While effective in LMS environments, SCORM cannot accommodate training conducted in external or third-party systems (xAPI.com, n.d.-b). To address this limitation, the Experience Application Programming Interface (xAPI) offers a more versatile data model, providing the same functionality as SCORM while expanding its capabilities. xAPI allows student performance data collection in physical and digital domains, regardless of whether they are connected to the LMS or not, enabling training to be tracked anywhere (xAPI.com, n.d.-a).

The rationale behind the TLA is supported by extensive research, tools, standards, processes, and established maturity pathways (ADL Initiative, 2020). Now, it falls to governments and the broader education industry to adopt and implement these technologies and strategies to drive the modernization of learning ecosystems, and this has begun to happen as outlined by the Canadian Armed Forces in the Ready Forces plan (Department of National Defence, 2024). 

As the defence industry begins aligning its training strategies toward a Total Learning Architecture, it is worth employing speculative methodology—considering a fictional future shaped by these trends and technological advancements—to bring these concepts into focus (Ross, 2017, Introduction, para. 5). The following vignette explores a potential vision of a TLA future in 2030 through the lens of fictional writing.

2030: Total Learning Architecture Vignette

As Cpl. Saunders boarded the bus to her base as an Aviation Systems Technician; her phone chimed with a micro-learning task. These quick training sessions had become part of her routine, and she looked forward to each one as they introduced new types of training. Last week, she interacted with an AI chatbot for a complex troubleshooting scenario.

Today’s task came from a third-party tool specializing in 3D Simulations for technical assessments. Cpl. Saunders appreciated how seamlessly these tools integrated. She returned all performance data to the base, which she will review later today. After a quick interaction with the learning activity, her data was automatically uploaded, and her training profile was updated, all before the first stop on the bus route.

Sgt. DeCoste received a prompt notifying him of Cpl. Saunders’s successful completion. “That was fast!” he remarked, impressed by how smoothly the adaptive learning system used internal and external training tools. The adaptive learning system then recommended pairing Cpl. Saunders, with two service members based on their rank, role, skills, and career aspirations, identified them as the ideal team to maintain the new fleet of aircraft. Sgt. DeCoste assigned the three recommended service members a collective training exercise they will conduct in a virtual reality environment to validate the systems.

Conclusion

The LMS has been at the forefront of education technology for over two decades, showing consistent growth and proving its capabilities during the COVID-19 pandemic. While the LMS has long provided a “good enough” solution, this contextual statement will change with the rise of new technologies. Mobile technology has removed traditional constraints of time and space in education, enabling institutions to enhance training efficiencies in the digital realm. The Advanced Distributed Learning Initiative, backed by extensive research, has provided guidelines, processes, standards, and a roadmap for how institutions can evolve their educational strategies to leverage these advancements. These solutions support using key LMS functionalities within a decentralized learning architecture, enabling technology insertion and reducing vendor lock-in. This flexibility allows institutions to adopt new technologies that support evolving pedagogies, shifting the LMS from a “good enough” solution to “the best.”

References

ADL Initiative. (n.d.-a). Canada ADL Partnership Center. Retrieved October 23, 2024, from https://adlnet.gov/partnership-network/canada-adl/

ADL Initiative. (n.d.-b). About the ADL Initiative. Retrieved October 23, 2024, from https://adlnet.gov/about/

Advanced Distributed Learning Initiative. (2020, April). 2019 total learning architecture report (Publication No. 2020-04). https://adlnet.gov/publications/2020/04/2019-Total-Learning-Architecture-Report/

Alturki, U., & Aldraiweesh, A. (2021). Application of Learning Management System (LMS) during the COVID-19 pandemic: A sustainable acceptance model of the expansion technology approach. Sustainability, 13(19), 10991. https://doi.org/10.3390/su131910991

Bouchrika, I. (2024, June 11). 51 LMS statistics: 2024 data, trends & predictions. Research.com. https://research.com/education/lms-statistics

Canadian Armed Forces. (n.d.). Life in the military. Retrieved October 23, 2024, from https://forces.ca/en/life-in-the-military/

Department of National Defence. (2022, October 06). Annex E: Data and Details – CAF Retention Strategy. Government of Canada. Retrieved October 23, 2024, from https://www.canada.ca/en/department-national-defence/corporate/reports-publications/caf-retention-strategy/annex-e-data-details.html

Department of National Defence. (2024). Ready Forces – Departmental Plan 2024-25. Government of Canada. Retrieved October 23, 2024, from https://www.canada.ca/en/department-national-defence/corporate/reports-publications/departmental-plans/departmental-plan-2024-25/planned-results/ready-forces.html

Department of National Defence. (n.d.-a). Defence Learning Network. Government of Canada. Retrieved October 23, 2024, from https://www.canada.ca/en/department-national-defence/services/benefits-military/education-training/professional-development/defence-learning-network.html

Department of National Defence. (n.d.-b). Establishments – Education and Training. Government of Canada. Retrieved October 23, 2024, from https://www.canada.ca/en/department-national-defence/services/benefits-military/education-training/establishments.html

Dlalisa, S. F. & Govender, D. W., (2020), Challenges of Acceptance and Usage of a Learning Management System Amongst Academics, International Journal of eBusiness and eGovernment Studies, 12 (1): 63-78. https://www.researchgate.net/publication/338374514_CHALLENGES_OF_ACCEPTANCE_AND_USAGE_OF_A_LEARNING_MANAGEMENT_SYSTEM_AMONGST_ACADEMICS

Gibbs, L., Clarke Gray, B., & Kuhn, C. (2021, January 7). Between the chapters: The Learning Management System (LMS) [Audio podcast episode]. In M. Weller (Host), 25 years of ed tech. https://25years.opened.ca/2021/01/07/between-the-chapters-the-lms/

IEEE. (n.d.). About IEEE. Retrieved October 23, 2024, from https://www.ieee.org/about/index.html

Kearney, M., Schuck, S., Burden, K., & Aubusson, P. (2012). Viewing mobile learning from a pedagogical perspective. Research in Learning Technology, 20. https://doi.org/10.1016/j.compedu.2012.03.016

OpenAI. (2024). Modern, decentralized learning environment with seamless, mobile training on-the-go. https://chat.openai.com/

Pachghare, V. (2016, April). Microservices architecture for cloud computing. Journal of Information Technology and Sciences, 2(1). Retrieved from https://www.researchgate.net/profile/Vinod-Pachghare/publication/317637883_Microservices_Architecture_for_Cloud_Computing/links/5b62eeaca6fdccf0b2078870/Microservices-Architecture-for-Cloud-Computing.pdf

Raza, S. A., Qazi, W., Khan, K. A., & Salam, J. (2020). Social isolation and acceptance of the learning management system (LMS) in the time of COVID-19 pandemic: An expansion of the UTAUT model. Journal of Educational Computing Research, 58(8), 1733–1756. https://doi.org/10.1177/0735633120960421

Ross, J. (2017). Speculative method in digital education research. Learning, Media and Technology, 42(2), 214-229. https://doi.org/10.1080/17439884.2016.1160927

SCORM.com. (n.d.). What is SCORM? Retrieved October 24, 2024, from https://scorm.com/

Selwyn, N., Pangrazio, L., Nemorin, S., & Perrotta, C. (2020). What might the school of 2030 be like? An exercise in social science fiction. Learning, Media and Technology, 45(1), 90-106. https://www.tandfonline.com/doi/full/10.1080/17439884.2020.1694944

Watson, William. (2007). An Argument for clarity: What are Learning Management Systems, what are they not, and what should they become. TechTrends. 51. 28-34. https://www.researchgate.net/publication/261177582_An_Argument_for_clarity_What_are_Learning_Management_Systems_what_are_they_not_and_what_should_they_become

Weller, M. (2020). 25 years of ed tech. Athabasca University Press. https://doi.org/10.15215/aupress/9781771993050.01

xAPI.com. (n.d.-a). Overview of xAPI. xAPI. Retrieved October 23, 2024, from https://xapi.com/overview/

xAPI.com. (n.d.-b). SCORM vs the Experience API (xAPI). Retrieved October 24, 2024, from https://xapi.com/scorm-vs-the-experience-api-xapi/