AI-Human Collaboration: Extending the Frontiers of Education Content Development
AVP Content Development
Generative AI (GAI) has the potential to transform the task of educators by 54%, STEM professionals by 57%, and creators by 53%, says a 2023 McKinsey report. This only highlights the massive potential of GAI to transform pedagogy, learning, and authorship. AI is also driving us to re-examine how we deliver education, and, most fundamentally, why. This blog takes a deep dive into how a collaboration between humans and AI for Education (AIEd) can be instrumental in defining the future of learning.
UNESCO emphasizes that despite GAI’s ability to make quality education available in the remotest places, where schools have not yet reached, the role of educators and conducive environments remains paramount. Educators and policymakers need to define the trajectory and establish the norms for AI applications to ensure the achievement of learning outcomes.
Content curation involves careful congregation, compilation, and communication of value-added knowledge, pertinent to each learner’s goals. AI in education content development can thus study the diversity and multiplicity of effective learning approaches, and help educators evaluate the various education models to gain a broader understanding of what effective, meaningful engagement might look like across a variety of contexts. AIEd enables resource selection, contextualization, curriculum planning, design, and development of learning in multiple ways.
The curricular requirements have broadened to include creative thinking, problem solving, and soft skills in education. AI systems can be active even before education planning begins, to gather learner data and use it to assess student proficiency, learning preferences, and goals. These insights can be instrumental in curriculum planning, leveraging predictive AI to fill the gaps between current learner levels and future skill requirements.
The design phase is critical to ensuring the accessibility and inclusivity of learning materials. Content development with AI-powered tools can power education publishers to incorporate the needs of learners with special needs, ensure regulatory compliance, and drive curriculum-focused learning outcome achievement from the design stage itself. These tools can identify suitable templates and formats, such as interactive language exercises, simulations, and virtual laboratories, to deliver learning in ways students can assimilate it most effectively. This, in turn, can reduce the need for retroactive changes, saving both time and resources.
Data-driven student analysis, reinforced with predictive exploration of future learning requirements, can help educators develop unique learning paths that accommodate different learning styles, speeds, and preferences. Generative AI can divide learning modules into micro and nano-modules to create bite-sized learning available and enable content reusability. While educators can drive curriculum design, AI can assist by helping them link learning to emerging technologies, potential career pathways, and global challenges. Unique hints and suggestions for solving problems and real-time feedback instill ownership and confidence among learners, ensuring progress. This facilitates satisfying learning experiences and boosts learner engagement.
AI systems facilitate automated updates for regulatory or compliance changes, while ML-powered analytics help educators identify trends and patterns in the evolving learning practices. Such insights can also support education publishers and edtech providers in staying relevant in a rapidly changing landscape. Leveraging XR (AR/VR/ER) technologies can become instrumental in providing immersive learning experiences to students via both traditional and borderless classrooms.
With diverse evaluation formats, including dynamic and adaptive assessments, multimedia-based questions and video/audio-recorded responses, AI is helping transform student assessments. AIEd can enable more precise, effective, and efficient evaluations that support learning rather than merely evaluate knowledge retention.
Further, automated evaluations eliminate human bias and foster objectivity in scoring. Immediate feedback and reinforcement with micro-modules and individualized assessments can promote timely introspection and growth. This can be instrumental in democratizing learning into a learner-driven paradigm.
The US Bureau of Labor Statistics’ Employment Projections Program projects that the demand for instructional coordinators will grow by 7% between 2021 and 2031. During the same timeframe, AI will evolve manifold. While multimedia-rich approaches can make the learning experience engaging and realistic, GAI can be instrumental in creating such learning materials, saving time and effort for education publishers and educators.
Given how quickly generative AI is proliferating, AI-literacy among educators needs to snowball to catch up with technology use. All stakeholders in the education sector need to understand why and how AI tools can be leveraged for accelerated and targeted content development and delivery. The use of AI in education content development presents diverse channels of friction-free communication among participants to offer the most impactful learning experiences. Analytics can further support policymakers in making strategic decisions, aligned with evolving education needs, keeping accessibility and individual learner needs at the fore.
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