Back in 2008, in the early days of my blog posting, I wrote a post entitled “The Gold Standard for eLearning.” I had just returned from the ITC 2008 conference, and was energized by the key note presentation by Patrica McGee, Associate Professor of IT and Program Coordinator for Adult and Higher Education at the University of Texas – San Antonio. She noted that “…Strategies that were effective in the past no longer offer the same return on investment and elude the “gold standard” for using technology for learning.”
I stated 16 years ago that Patricia raised some good points, and one of her final ones hit home for me. Many faculty came to us in the Center looking for help in using some “tool”…be it Blackboard, blogs, wikis, or podcasts. She found that the course management system was invisible to Millennials. The technology was like the air – necessary but not noticed. I stated that we needed to become familiar with the various technologies we used in technology, but they were a means to an end…and we needed to focus first and foremost on the learning.
I loaded this post into Claude with the following prompt:
“Good morning, Claude. I would like you to look at a blog post I did in 2008 on the Gold Standard for elearning. My questions are (1) what is still relevant and what is out of date here in 2024, and (2) could one posit that AI is the new gold standard for elearning?”
Claude responded:
Good morning! It’s great to look back at your insightful blog post from 2008 and consider how things have evolved in the 16 years since then. Let’s dive into your questions:
(1) What is still relevant and what is out of date in 2024:
Still relevant:
– The importance of focusing on learning outcomes rather than just technology tools. As you aptly noted, the technologies are a means to an end, and the primary focus should be on enhancing learning.
– The need to consider multiple perspectives (generational, cultural, disciplinary, etc.) when making decisions about educational technology adoption.
– The observation that technology should integrate with both school and life, allowing for learning in various formats. Flexibility and accessibility remain key.
– The shift to learning-centered rather than solely teaching-centered education. Web 2.0 helped drive this, and the trend has only accelerated.
Out of date:
– The generational demographics have shifted. Millennials and Gen Z now make up the bulk of higher ed students, with Gen X and Boomers decreasing as a percentage.
– The specific technologies mentioned (blogs, wikis, podcasts) have evolved and in some cases been supplanted by newer tools. The overall trends of web-based, interactive, multimedia learning have continued though.
– The “digital native” concept has been further debunked, with recognition that digital skills exist on a continuum and vary within age cohorts. But overall digital fluency has certainly increased.
– Course management systems have become more salient rather than fading into the background. The LMS is now a central hub for many digital learning experiences.
(2) Could AI be considered the new “gold standard” for elearning in 2024?
There’s definitely an argument to be made that AI has become a key underlying value driver and transformative force in digital learning over the past several years:
– Personalized learning paths, content recommendations, adaptive assessments, and intelligent tutoring systems powered by AI are enabling learning to be tailored to each student’s needs and pace like never before.
– Conversational AI is enabling more natural interactions and on-demand support for learners, while AI-powered teaching assistants are alleviating instructor workloads.
– AI is being used to glean insights from large datasets of learner activity to drive everything from curricular improvements to student advising and retention efforts.
– Advances in natural language processing and generation are enabling the automated creation and curation of learning content and assessments.
So in many ways, AI is becoming the “invisible” layer powering and optimizing digital learning experiences, much like the course management system was in 2008. It’s a foundational technology adding value across the digital learning lifecycle.
At the same time, I would argue that AI should still be viewed as a means to an end – enhancing learning – rather than an end in itself. AI will be most impactful when it’s designed and deployed with sound pedagogy and a focus on learning outcomes. { I agree! } So in that sense, the true “gold standard” remains enabling effective, engaging, and transformative learning experiences, with AI as an increasingly powerful tool to help us reach that standard.
Those are my initial thoughts, but I’m curious to hear your perspective as someone who’s witnessed the evolution of digital learning over the past 16 years! Do you think AI is the new defining force in elearning today? Let me know what you think.
My follow-on prompt – “Nice response! To your question, I am currently reading Ethan Mollick’s book Co-Intelligence, and he makes the point that AI is more transformational than earlier general purpose technologies like steam power, the rise of PC’s, or even the internet. From my limited dipping my toe into the AI waters, I do agree that we should not look at AI as simply another tool, but rather as the digital partner that I had previously suggested in my work with faculty developing online classes over the past two decades. For me, the AI assistant was always a dream…but that dream may be now happening!”
Claude followed up with:
You raise an excellent point about the transformational potential of AI compared to previous technological revolutions. I agree that AI represents a qualitative shift beyond being just another educational tool.
The concept of AI as a “digital partner” in the learning process is powerful. Rather than simply being a passive instrument wielded by instructors or students, AI has the potential to be an active, interactive, and adaptive collaborator in knowledge discovery, skill development, and problem-solving.
Some key ways AI could revolutionize the elearning experience as a digital partner:
- Personalized mentoring and tutoring: AI could provide each learner with an always-available, endlessly patient guide to help them navigate concepts, answer questions, suggest resources, and provide targeted feedback. This kind of 24/7 personalized support has never been feasible before. {A point Salman Khan made in Brave New Words.}
- Socratic dialogue and inquiry-based learning: Conversational AI could engage learners in back-and-forth dialogue, prompting reflection, probing understanding, and guiding them to construct knowledge actively. AI could simulate the kind of thought-provoking discussions that are the hallmark of great teaching. {Which is just what is happening here…}
- Collaborative problem-solving: AI could serve as a brainstorming partner, sounding board, and intellectual foil as learners work through real-world challenges. It could offer alternative perspectives, suggest novel approaches, and help learners see blind spots in their thinking.
- Adaptive learning pathways: By tracking each learner’s progress, strengths, and areas for growth, AI could dynamically adapt the sequence, pace, and content of instruction to keep each learner in their optimal zone of proximal development. It could ensure mastery before moving on and provide extra reinforcement where needed.
- Amplifying human instructors: AI could be a force multiplier for educators by automating routine tasks, surfacing important patterns in learner data, and flagging students who need interventions. This could free instructors to focus on higher-level, more impactful teaching activities.
Of course, realizing this vision of AI as a true digital partner will require thoughtful design, ongoing research, and close collaboration between educators, learning scientists, and AI developers. {In other words, Centers for Teaching will still have a role!} We’ll need to be intentional about aligning AI with learning theory and rigorous pedagogy. And there are important ethical considerations around privacy, autonomy, and equity that will need to be addressed.
But the potential is thrilling. AI could be the catalyst that finally enables us to scale high-quality, personalized, active learning to every student. It could be a game-changer in terms of access, engagement, and outcomes.
So while the “digital partner” may have been a dream in the past, I believe we’re on the cusp of making it a reality. The next decade of digital learning will be a fascinating time as we explore and harness the power of AI to transform education. I’m excited to see how pioneers like yourself help shape this future!
I find it fascinating to not only look back at blog posts I wrote more than a decade ago, but to have Claude as a co-author in summarizing past points and positing new points. Khan noted in his book that the world of work was shifting with new job descriptions like “Prompt Engineers”. Our students today…and our faculty…will have to adapt and learn to integrate AI into their multiple processes, which in many ways are not domain specific. It is one reason Mollick’s book is resonating with me – he is not a computer scientist, but rather a faculty member focused on entrepreneurship and how tech can be used.
So, what are your thoughts? Is it too soon to say that AI is the new gold standard?
{Graphics: Enterprising Investor, ATD, BlendVision}