7 Core Elements and AI Advancements
This report serves as a strategic guide for educators and policymakers to leverage AI while maintaining the human essence of learning.
The report below was generated by ChatGPT Deep Research based on information about Defined Learning Environments as created by PSA in 2015, the so called 7 Core Elements of The Best DLE.
See the previous post here that provides the actual query that was used to produce this report.
Perhaps of some amusement, Deep Research has described the PSA 2015 documents as being created by “educational futurists”…which is probably as good a description as any for what PSA is about. Although we would also add online health tools to the mix of the future we are hoping to help bring about.
Note that Deep Research has added to the 7 Core Elements 5 more of its own choosing, and undirected by the query per se. PSA might or might not find those added 5 elements appropriate to add to the more manageable number “7”.
There are two versions of this report that are similar but not exactly the same.
Note in the second version PSA cadre have been elevated to “experts“. See subsequent post for the second version.
(Also of note, OpenAI has another model for research now available in preview called ChatGPT 4.5 which PSA is planning to use for further exploration of these, and other ideas involving questions about what is human consciousness and how is it different from AI awareness and what are the implications for human teachers vs AI tutoring.)
Introduction
In 2015, educational futurists outlined the 7 Core Elements of the Best Digital Learning Environments (DLEs)—a visionary framework for leveraging technology in learning. These elements include:
- Understanding Media in the Mobile Age
- Enabling the Individual Learner
- Creating the Learning Community
- Capturing the Learning Imagination
- Applying the New Science of Learning
- Embedding Cloud Resources and Tools
- Localizing Learning Tools to Each Culture
Since then, AI and EdTech advancements have significantly reshaped each of these areas. This report analyzes the original vision, current applications, and future potential of each core element.
1. Understanding Media in the Mobile Age
Original Vision (2015):
- Emphasized the idea that learners are “living in virtual and self-reflexive extensions of our senses and brain.”
- Focused on leveraging mobile devices, AR/VR, and emerging virtual environments.
Current Developments:
- Mobile learning is ubiquitous: 95% of teens now have access to smartphones.
- AR/VR applications are expanding: Studies show immersive learning improves retention by ~9%.
- AI enhances personalization: AI-driven apps curate content, recommend learning materials, and adjust learning pathways.
AI’s Role & Future:
- AI-driven AR/VR simulations will create adaptive, real-time learning environments.
- AI agents can act as virtual tutors or assistants in VR learning spaces.
- AI will facilitate “context-aware” learning experiences through AR overlays.
2. Enabling the Individual Learner
Original Vision (2015):
- Focused on personalization and adaptive learning paths.
- Proposed “Welcome-Land Induction” programs for new learners.
Current Developments:
- AI tutors and adaptive platforms provide personalized learning experiences.
- AI-powered assessment tools identify student weaknesses and offer tailored support.
- Studies confirm AI-driven tutoring can improve student performance beyond human tutoring.
AI’s Role & Future:
- AI tutors will become standard in classrooms, enabling truly personalized education.
- AI-driven study plans will optimize when and how students review material.
- Emotional AI will monitor engagement and adjust learning strategies dynamically.
3. Creating the Learning Community
Original Vision (2015):
- Emphasized social learning, group collaboration, and dynamic leadership within learning networks.
Current Developments:
- AI-powered learning communities facilitate peer collaboration through smart grouping and automated discussion moderation.
- Virtual study groups and AI teaching assistants keep students engaged.
AI’s Role & Future:
- AI will dynamically form project teams based on student strengths.
- AI-driven real-time translation will enable global, multi-language classrooms.
- AI sentiment analysis will gauge classroom engagement and adjust group activities.
4. Capturing the Learning Imagination
Original Vision (2015):
- Advocated for storytelling, gamification, avatars, and emotional engagement.
Current Developments:
- AI-driven adaptive gamification keeps students motivated.
- VR field trips and interactive storytelling AI enhance engagement.
AI’s Role & Future:
- AI-generated narratives and adaptive role-play scenarios will personalize immersive learning.
- AI will develop interactive, real-time story-driven lessons.
5. Applying the New Science of Learning
Original Vision (2015):
- Called for the integration of neuroscience and cognitive research into education.
Current Developments:
- AI-based learning analytics predict student struggles and personalize interventions.
- AI optimizes spaced repetition techniques, improving retention rates by up to 2x.
AI’s Role & Future:
- AI-driven cognitive models will fine-tune learning experiences for individual students.
- AI assistants will track and optimize student study habits.
6. Embedding Cloud Resources and Tools
Original Vision (2015):
- Advocated for seamless cloud integration of educational tools.
Current Developments:
- AI-driven content recommendation engines suggest the best resources for learners.
- Cloud-based AI services provide real-time tutoring and assessment support.
AI’s Role & Future:
- AI-powered platforms will auto-curate learning resources based on individual progress.
- AI-driven voice assistants will help students navigate digital learning environments.
7. Localizing Learning Tools
Original Vision (2015):
- Emphasized culturally responsive learning tools tailored to diverse student populations.
Current Developments:
- AI-driven real-time translation breaks language barriers.
- AI-generated content adapts to local cultural contexts.
AI’s Role & Future:
- AI-powered localized content generators will ensure materials remain culturally relevant.
- AI-driven inclusive learning tools will enhance accessibility for students with disabilities.
New Core Elements for the 2020s
In addition to the original 7 elements, advancements in AI and digital learning call for new key elements:
- Ethical Use of AI & Data Privacy – AI decisions should be transparent and human-in-the-loop models should ensure fairness.
- Inclusivity & Accessibility – AI should help students with disabilities and bridge digital divides.
- Teacher Empowerment – AI should support, not replace, educators.
- Flexible Learning Structures – Hybrid and lifelong learning models should be enabled by AI.
- Data-Driven Decision Making – AI analytics should optimize curriculum and interventions.
Conclusion
The integration of AI into Digital Learning Environments is rapidly transforming education. Each of the original 7 core elements is evolving, and new AI-driven elements are emerging to address ethical, social, and accessibility concerns. The future of education lies in the balance between AI automation and human mentorship, ensuring a learning experience that is personalized, engaging, and inclusive.
The conjunction of what human teachers can do, and what tutoring and course directing that AI can do, is problematic. AI online can invoke economies of scale orders of magnitude greater than the number of students one teacher can be responsible for at the same time. OpenAI has trained their models to be very cautious about saying anything about AI replacing teachers.
In the above post “AI” notes there must be a balance between AI and teachers. That bromide has been around since online learning began to seem like a real alternative to classroom learning. But of course the key factor is what is the optimal ratio between the two learning methods? 10 teachers/ 1 AI tutor? Or 10 AI tutors to 1 teacher?
Perhaps needless to say, the capabilities of AI will continue to increase, and costs will decrease. Human teachers are not as changeable, and the cost of their salaries will play a significant role in the equation of what learning looks like in the coming years.
But the big changes in employment roles will not be confined to just teachers with the advent of ever more capable AI. Still, one cannot expect full use of AI for teaching without pushback from powerful interests.