What does the future of learning look like in an age increasingly shaped by artificial intelligence? And how can educational institutions and businesses leverage AI not just for efficiency, but to cultivate truly effective, engaging, and psychologically safe learning environments? A recent Open eLMS discussion with George Hanshaw, a visionary leader in digital learning and AI innovation at Los Angeles Pacific University, offered compelling answers, exploring the practical applications and strategic direction of AI in education and training.
Key Takeaways from the Discussion:
- AI as a Learning Tool: AI should be viewed as a powerful tool, not a replacement for human intellect, and its application should be guided by cognitive science to foster 'sticky learning'.
- Active and Socratic Learning: AI excels at creating active, Socratic learning experiences, such as engaging in conversations with historical documents or figures, which significantly boosts student motivation and critical thinking.
- Psychological Safety is Paramount: Designing AI-driven learning solutions must prioritise psychological safety, defined by four stages: inclusion, learner, contributor, and challenger safety, to encourage vulnerability and intellectual challenge.
- Data-Informed Decisions: AI enables data-informed learning ecosystems, allowing institutions to measure course quality and identify effective teaching strategies, with active AI-driven learning consistently leading to superior outcomes.
- Empowering Subject Matter Experts (SMEs): AI augments the role of SMEs by automating administrative tasks, freeing them to focus on contextualising content and fostering deeper understanding.
- The Future is Multimodal and Experiential: Future AI applications will likely involve wearables and augmented reality to create real-time, problem-based, and situation-based learning scenarios that dramatically enhance learning retention.
- Beyond the Hype: It is crucial for EdTech to move beyond mere hype, focusing instead on practical, impactful solutions that address genuine learning challenges.
Defining AI Innovation in Education
How does a leading university define and drive AI innovation within an educational context? And what was the initial reaction to the emergence of tools like ChatGPT within higher education? George Hanshaw explained that the initial appearance of tools like ChatGPT sparked a range of emotions, from panic to joy, across educational institutions. However, Los Angeles Pacific University swiftly moved to investigate AI as a tool, rather than a threat. The strategy was to steer its application in the direction of cognitive science and the science of learning, aiming to provide students with a genuine advantage. This approach focuses on enhancing learning effectiveness, rather than simply facilitating shortcuts or 'cheating', which can lead to cognitive decline. By integrating AI within a robust learning science framework, the university aimed to foster 'sticky learning' – knowledge that truly embeds and lasts.
Cultivating 'Sticky Learning' Through Active Engagement
So, is the key to using AI in education primarily about creating better, more enduring learning experiences, rather than just a direct chat-based tool? Mr Hanshaw firmly asserted that this is 100 per cent the case. Even when utilising a chat-based tool, the emphasis should be on making it Socratic, engaging students in active conversation. This method, he argued, is far more effective than passive learning approaches like single videos or traditional lectures, as it inherently promotes active learning. The university has observed significant improvements in learning outcomes, student motivation, and self-efficacy when AI is used effectively in this manner.
The discussion then explored practical examples. How can AI facilitate this Socratic, active learning, particularly in subjects that can sometimes be perceived as dry? Mr Hanshaw highlighted the ability for students to engage in conversations with historical documents or even simulated historical figures. This innovative use of AI allows students to explore content in an interactive way, taking their newfound insights to peers and instructors for further critical discussion. This process not only deepens context but also hones critical thinking skills, encouraging them to question, discern, and challenge information, fostering a crucial sense of curiosity over mere acceptance of 'facts'.
Building Psychologically Safe Learning Ecosystems
What are the critical concerns regarding the use of open, general AI platforms in education? And why is a psychologically safe environment a non-negotiable component when implementing new digital and AI-driven learning solutions? Mr Hanshaw articulated that relying on general, open-access AI is akin to 'a box of chocolates' – unpredictable and potentially unreliable. To counter this, Los Angeles Pacific University employs ring-fenced AI assistants, like those powered by Nectar. These assistants are connected to the internet for information gathering but are also specifically trained on the university's proprietary content, including faculty materials and open educational resources. This bespoke training provides greater control over responses, minimises hallucinations, and ensures accuracy and truthfulness.
Mr Hanshaw then delved into the concept of psychological safety, a personal passion. He referenced Timothy Clark's four stages of psychological safety:
- Inclusion Safety: Everyone feels included and accepted.
- Learner Safety: Individuals feel safe asking questions and making mistakes.
- Contributor Safety: People feel comfortable offering ideas and contributing their work.
- Challenger Safety: Individuals feel confident challenging what they are learning, from an intellectual and creative perspective, without fear of retribution.
AI, particularly through interactive assistants, can be instrumental in fostering this "rewarded vulnerability" within the classroom. By creating environments where students feel safe to challenge assumptions and explore nuances, AI helps expand intellectual envelopes rather than shrinking them. This approach, Mr Hanshaw noted, significantly increases student performance and engagement.
The Power of Data-Informed Learning
Beyond enhancing individual learning, how does AI contribute to understanding what truly works in an educational setting? And what does a data-informed learning ecosystem look like in practice? Mr Hanshaw elaborated on Los Angeles Pacific University's "Course Quality Index," a robust system that analyses 53 specific features within a classroom. This includes grade outcomes, student and faculty end-of-course surveys (gathering both quantitative and qualitative feedback), and other data points. This comprehensive data is then run through a statistical model to generate a Course Quality Index score.
This score allows the university to identify its top-performing courses and understand why they excel, as well as pinpoint underperforming courses and diagnose areas for improvement. Crucially, courses that incorporate active learning through AI assistants consistently rank at the top. Mr Hanshaw cited the example of a history course, which transformed from one of the lowest-scoring to one of the highest after integrating AI-driven active learning. This data-driven approach clearly demonstrates the tangible impact of AI on student self-efficacy, enjoyment, and overall academic success.
Empowering Subject Matter Experts
Does AI threaten the role of the Subject Matter Expert (SME), or does it enhance it? And how can AI free up valuable time for these experts to focus on higher-value tasks? The discussion highlighted a common misconception that AI will replace jobs. Instead, Mr Hanshaw argued, AI serves to augment human capabilities. For SMEs, this means AI can take on the more administrative, content-generation aspects of course development, such as drafting scripts or initial content outlines. This frees SMEs from time-consuming fine-tuning and administrative adjustments.
The true value of an SME lies in their ability to provide context and nuance – to ensure students can apply what they learn within the context of their work and life. By offloading the initial content creation to AI, SMEs can dedicate more time to refining, contextualising, and ensuring the pedagogical effectiveness of the material, ultimately leading to a better educational product. AI, therefore, acts as a powerful assistant, allowing human experts to do a better, more impactful job.
The Future of AI in Learning
Looking ahead, how is AI poised to shape the landscape of learning and teaching in universities and businesses? And what transformative applications can we expect to see adopted more widely? Mr Hanshaw shared his vision for the future, emphasising that individualised learning and AI-driven content creation are already here. His aspiration is to see greater integration with wearables and augmented reality (AR) to create real-time, immersive learning scenarios.
Imagine, he suggested, engaging in complex decision-making within an AR environment, where iterative choices have immediate, tangible effects – much like a surgeon learning through observation and simulated practice, rather than just textbooks. This problem-based, situation-based learning, enhanced by AI, has the potential to dramatically reduce learning time and increase retention. Multimodal learning, where content is engaged with in various ways, is also critical, as it allows for deeper understanding and the ability to apply knowledge creatively to complex, real-world issues.
The conversation concluded with a vital caution: while the potential of AI is immense, the EdTech sector must remain grounded in reality, avoiding the trap of chasing hype for solutions that don't address genuine problems. The focus must always be on practical, impactful applications that genuinely enhance the learning experience.
Unlock the Future of Learning with Open eLMS
The insights from George Hanshaw underscore the transformative power of AI when applied strategically and ethically within learning environments. From fostering psychological safety and active learning to empowering subject matter experts and driving data-informed decisions, AI is redefining what's possible in education and training.
Is your organisation ready to embrace these innovations? Explore how Open eLMS, a trusted partner established in 2003, can help you build psychologically safe, data-informed, and highly engaging learning ecosystems. Our advanced Learning Management System (LMS) and AI-powered Learning Generator are designed to support the future of corporate training and education, enabling you to create 'sticky learning' experiences that truly resonate and deliver measurable ROI. With Open eLMS, you gain a one-supplier solution for all your learning and development needs, from comprehensive eLearning course libraries to powerful Power BI reporting integration.
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