By Larry G. Martin
In the 21st century, digital technology is a beacon of unprecedented access to smart, personalized tools for building learning hubs that can actively assist adults in enhancing and accelerating the achievement of their lifelong learning goals. By strategically adopting and integrating these tools into convenient and accessible hubs, adults can more effectively improve their knowledge, skills, and competencies (Yen et al., 2019). These digital learning hubs can proactively personalize learning pathways through LLM AI chatbots and adaptive learning platforms, which analyze individual learner data and tailor content to meet their unique needs. Accessibility and flexibility to pursue learning are afforded through mobile learning platforms and IoTs, which provide on-demand access and enable learners to fit learning smoothly into their demanding schedules. Extensive learner engagement is provided through immersive learning environments that transform abstract concepts into interactive experiences, enhancing understanding and retention. Lastly, trustworthy, portable, and secure credentials can be stored via blockchain ledgers that allow learners to own and transparently manage verifiable records of their achievements.
This constellation of independent technologies not only empowers learners but, when integrated with others, they evolve dynamically to meet adults’ lifelong needs. For example, to keep adults engaged and on task, continuous feedback loops can be created through IoTs and big data, which enable real-time monitoring of progress, thus allowing learners to self-correct as they advance and for educators/trainers to provide timely interventions. Therefore, to fully optimize these hubs, each learner should strategically build them by adopting the appropriate digital tools to address their distinctive formal, non-formal, and informal learning needs and goals.
Different Pathways for Propositional and Procedural Knowledge
Adults pursuing propositional (i.e., fact-based) knowledge via formal learning goals should focus heavily on digital tools (such as, AI online digital learning platforms, big data and adaptive learning, LLM AI chatbots, and blockchain digital ledgers). These adults typically seek learning opportunities from hierarchically structured formal educational and training systems (such as university-based education, organizational training, etc.) (Johnson & Majewska, 2022). Through highly defined roles for educators and trainers, these systems rely on sequentially structured learning goals and grading systems (Johnson & Majewska, 2022). Although formal learning is important in lifelong learning, non-formal and informal learning are estimated to constitute 70-90% of lifelong learning (Yen et al., 2019).
Several digital tools (such as, LLM AI chatbots, mobile learning, immersive learning environments, IoTs, and wearables) often support non-formal learning of procedural (skill-based) knowledge involving real-world problems. Encouraging self-directed learning through organized and systematic instructional activity, it tends to occur outside the framework of formal educational systems (Johnson & Majewska, 2022). These tools provide access to non-direct teaching behaviors (e.g., facial expressions, tone of voice, gestures, etc.) that often occur in authentic, highly motivating, and engaging contextual environments. Many of these tools can also support informal learning by providing access to meaningful unstructured activities and unsystematic processes through which adults can acquire and accumulate knowledge, skills, attitudes, and insights to address perceived needs (Johnson & Majewska, 2022). These types of learning should be top-of-mind as adults build interdependent and interconnected learning hubs. However, they should first adopt the core technologies to anchor the system.
Core Technologies to Anchor Personal Learning Hubs
Adults should consider adopting a robust, independent AI-powered personalized learning management system (LMS) to anchor their learning hub. An independent LMS can be a transformative tool that synergistically creates a learning ecosystem that evaluates their learning needs and preferences; tracks their progress; recommends courses and learning opportunities; adapts to their learning pace; identifies personalized formal, non-formal, and informal learning pathways; and allows design flexibility to upgrade and change technologies in accordance with changing learning needs.
Ideally, the system will incorporate AI features for personalized feedback and assessments while providing access to teaching and learning resources (e.g., MOOCs, tutorials, and multimedia tools). Therefore, learners should consider prioritizing systems with robust application programming interface (API) capacities for educational tools that allow strong LMS integration abilities and allow adopted third-party educational tools, platforms, and technologies to work seamlessly together. Also, reports issued by LMSs can provide comprehensive accounts of learners’ subject matter progress and inform adults at different stages and phases of their learning efforts about how well their learning needs are being accomplished. With the vast number of options available, adults should adopt an AI-powered system with the most desirable attributes to address their lifelong learning needs.
Adopting an AI-Powered Personalized LMS
Several different LMS platforms can be personalized as a central hub for formal, nonformal, and informal learning experiences. The OpenLMS platform is a robust blockchain-based LMS with highly flexible API access that integrates with various LMS platforms and educational tools to access multiple courses from universities and companies. For learners anticipating formal and informal learning opportunities, Coursera, LinkedIn Learning, and Skillsoft Percipio, should be considered. They are highly versatile AI-powered platforms that offer strong API capabilities (e.g., interoperability with chatbots and some immersive technologies). Through adaptive content and assessments, peer grading, and personalization, they can suggest the most relevant courses based on a learner’s past behavior and learning goals.
Similarly, WileyPLUS with ORION can be integrated with the LMSs employed by higher education and training organizations to provide adaptive practice learning paths, real-time analytics, and personalized study recommendations. Altoura should be considered for adults prioritizing experiential learning. Through AI-powered virtual simulations and immersive learning content, it simulates real-world scenarios. Through IoT integration, it leverages advanced wearable technology (such as VR headsets and smart devices) to deliver skill development in a variety of learning and educational settings.
Case Examples: Creating Integrated Digital Learning Hubs
Based on their applied knowledge of digital learning tools and technology affordability, learners should select digital tools to optimize the achievement of their learning goals. Below are two hypothetical examples of learning hubs built to respond to job- and employment-related challenges.
Case 1: Customer Service Representative to Technical Support Specialist
Maria is a 25-year-old high school graduate and single mother living in an urban community. She is among the 1,554,799 customer service representatives currently employed in the United States. However, key customer service functions are now being replaced by AI-driven chatbots and virtual assistants (Phudech, 2024). At lower costs, these technologies can provide 24/7 service, answer inquiries, and successfully troubleshoot customers’ problems without human intervention (Phudech, 2024). Although she has a laptop computer, smartphone, and home Internet connection, Maria is among 31% of Americans who are “cautious clickers” (Horrigan, 2016) with limited eLearning experience. To upskill for her job in the service economy, she developed an affordable integrated digital learning hub to pursue certification as a technical support specialist. This new certification builds on her work experiences and prepares her to assist customers with technical issues related to a company’s products or services.
With limited digital technology experience and a low budget, Maria created a rudimentary and accessible learning hub on her computer. She focused primarily on formal learning and anchored her hub with the highly versatile Coursera LMS. By integrating with a local college LMS platform, she gained access to a variety of free and paid self-paced courses and assessments that led to a technical support specialist certification upon completion. This type of integration enabled personalized learning paths, real-time insights, and tailored feedback while allowing her to maintain control over her learning data within a personal system. Mobile learning apps from the campus LMS enhanced Maria’s access to formal courses, allowing her to complete assignments and access educational resources anytime.
For the non-formal and informal learning technologies in her hub, she integrated Chat GPT-4o with Coursera to gain access to a wealth of knowledge across various topics. Acting as a virtual assistant, it provided immediate coursework support and guidance through instant conversational responses; accessed her course progress, performance data, and learning history to provide automated tutoring and support; and created personalized content by dynamically generating personalized quizzes, summaries, and feedback tailored to her learning progress.
Case Study 2: Manufacturing Worker to Robotics Technician
Jamerson is a 40-year-old manufacturing worker with an associate degree in manufacturing technology. A father of three, he has spent the last 15 years in assembly line production. However, with the rise of automation and smart manufacturing technologies, including robotics capable of performing repetitive tasks faster and more precisely than humans, he is among the 13 million manufacturing workers faced with job displacement due to increasing automation on the assembly line (Moseman & McKittrick, 2024). For employment security, Jamerson aspires to upskill by becoming a robotics technician. Among17% of Americans who are “digital ready” (Horrigan, 2016) he has a strong Internet service, highly capable computer, and a proficient smartphone. He thereby developed a highly integrated and connected digital learning hub that offers speed, scalability, and seamless experiences to assist his transition.
For formal learning activities, he anchored his hub with the Altoura LMS. Through robust API capabilities, he was able to link Altoura to a variety of digital technologies to support his learning journey. Connecting it to his company’s training LMS platform gave him access to company-related training sources. By integrating with college LMS platforms like Udemy, he consulted with academic advisors and enrolled in courses focused on robotics, Industrial Internet of Things (IIoTs), automation technologies, and programming languages such as Python and C++. These courses also exposed him to data analytics in manufacturing through the use of big data software applications (such as Netstock and Delmia Works) that he linked to Altoura to understand how companies collect, store, analyze, and interpret massive amounts of data generated from various sources like machine sensors, digital twins, and automated production lines and supply chains.
For the non-formal and informal learning technologies in his hub, he integrated Chat GPT-4o with Altoura to gain access to a highly knowledgeable virtual academic advisor and coach to assist his transformation. As an experiential learner, James integrated several immersive technology tools (such as Oculus for Business and STRIVR) with Altoura. This integration allowed him to experience complex robotic mechanisms, troubleshoot common machinery issues, and enhance his technical skills in a safe environment by simulating real-world interactive scenarios with virtual robots in manufacturing settings (Brynjolfsson & McAfee, 2014).
Conclusion
The individual technologies in learning hubs can provide personalized learning pathways, on-demand access to knowledge and information, interactive experiences, and secure storage and access to credentials. The above two hypothetical cases demonstrate how, when these technologies are integrated, digital learning hubs can create gestalt effects through which adult learners in highly varied life situations can receive unprecedented access and assistance in formal, nonformal, and informal learning situations. Consequently, well-designed hubs can provide transformational learning opportunities to adult learners when the tumult of technology innovations signals an urgent need to keep learning throughout the life course.
References
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & company.
Horrigan, John B. “Digital Readiness Gaps.” Pew Research Center, September 2016. Available at: http://www.pewinternet.org/2016/09/20/2016/Digital-Readiness-Gaps/
Johnson, M., & Majewska, D. (2022). Formal, Non-Formal, and Informal Learning: What Are They, and How Can We Research Them? Research Report. Cambridge University Press & Assessment.
Moseman, M. & McKittrick, S. (2024). How Automation Can Help Overcome Labor Shortages in Manufacturing. https://develop-llc.com/insights/how-automation-can-help-overcome-labor-shortages-in-manufacturing/
Phudech, P. (2024). AI and Smart Customer Services: Revolutionizing the Customer Experience. Journal of Social Science and Multidisciplinary Research (JSSMR), 1(3), 1-20.
Yen, C. J., Tu, C. H., Sujo-Montes, L. E., Harati, H., & Rodas, C. R. (2019). Using personal learning environment (PLE) management to support digital lifelong learning. International Journal of Online Pedagogy and Course Design (IJOPCD), 9(3), 13-31.
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