Unravelling the Impact of Generative AI in Education
General Manager- Marketing
The world woke up to the incredible power of ‘generative artificial intelligence’ with the launch of ChatGPT. It stirred up quite a storm, garnering one million users within 5 days of OpenAI releasing the tool for public use and 100 million users within 2 months of its release. More importantly, it has sparked our imagination regarding the transformative power of AI for education.
Given that innovation around generative AI could well be a game-changer for K-12 and higher education, UNESCO has already started a global dialogue with educational policymakers, academia, edtech firms, and society at large. The first meeting of Ministers of Education was held in May 2023 to discuss policy guidelines regarding the use of generative AI in education.
Generative AI has been defined as a technology that uses deep learning models to create human-like content in response to “complex and varied prompts,” such as questions or instructions. Generative AI goes beyond simply responding with existing data to generating new responses or content. In fact, ChatGPT already combines the capabilities of generative and conversational AI to conduct human-like interactions. This has fueled expectations regarding the real-world applications of generative AI in education.
Generative AI leverages machine and deep learning technologies to generate new content autonomously, including text, images, and even music. Imagine the opportunities this would provide educational publishers, edtech firms, and educators to improve educational quality and coverage.
Key areas where generative AI could be used across various real-world applications in education are:
An AI-first approach in educational publishing could lead to content development practices that promote individualized teaching based on each student’s learning style and pace. Generative AI could adjust course difficulty and content recommendations, depending on the student’s learning progress and performance. Assignments, practice exercises, and more could be curated for each learner, with generative AI automatically creating learning paths and suggesting resources aligned to individual needs.
Generative AI could also be leveraged to communicate with parents and educators, allowing them to better understand students’ learning performance and provide effective support.
Intelligent Tutoring Systems
Tutoring strategies and content could be generated using analytics to understand each student’s learning needs. Intelligent, generative AI -driven tutoring systems could also adapt to difficulty levels, as mentioned earlier, generating best-fit practice questions and tutoring tasks. Learning strategies could be developed based on each individual’s learning habits, style, and needs for better comprehension and retention.
AI-driven intelligent speech recognition, in combination with student data analysis, could foster voice-based interactions in the preferred language of the learner. Such speech interactions is beneficial in speech assessment and providing feedback in real-time, which proves invaluable, especially for language learning.
Adaptive Assessment and Feedback
Another area where generative AI could have immense potential is the creation and implementation of individual and group assignments, as well as formative and adaptive assessments. Multiple question types can be included to better assess knowledge acquisition, while generative AI -powered grading can ensure immediate feedback to promote self-directed learning. In fact, generative AI can go a step further by suggesting ways to improve student performance while arming educators with efficient assignment and assessment management tools. This can transform assessments into tools for evaluating learning to tools that promote learning.
Real-time scoring and feedback provide insights for students to regulate their learning style and better achieve learning goals. A review of 63 studies revealed that student performance improved with immediate, automatic feedback in 65.07% of the reviewed research.
AI-Powered Virtual Tutors and Learning Assistants
Generative AI and natural language processing (NLP) can together power virtual tutors and assistants to make learning truly accessible and inclusive. They can understand questions and generate responses in multiple languages, leading to more equitable learning opportunities. Student problems can be solved, learning resources recommended, and learning effectiveness improved without the need for human intervention.
The future could bring natural language interactions for intelligent tutoring, adapting the mode of interaction and content to each student’s preferences, needs, and goals.
An EDUCAUSE poll of 800 higher education respondents revealed that 54% were “optimistic or very optimistic” about the real-world applications of generative AI in education. Integrating AI throughout the academic value chain can not only benefit publishers and edtech providers but also the students. For businesses, it could improve digital rights protection, allow predictive market analytics, and provide strategic insights. For students, it would make content more discoverable, align offerings to individual needs, and free up time for educational institutions and educators to focus more on adding value for learners.
To garner all these benefits, companies in the education sector will need to adopt an AI-first approach to content development in publishing and technology innovation. Existing resources, in terms of both content and assessments, will also need to be transformed into AI-ready formats for easy integration with evolving technology.
A major challenge will be the initial investment required to build in-house IT infrastructure and align the currently siloed workflows. This is where leveraging the capabilities of an AI-powered digital platform could remove barriers to harnessing the power of AI. It would not just reduce costs and time-to-market for educational publishers and edtech firms but will also lead to lower costs for their customers, driving adoption.
Effectiveness of AI in education depends on the data used to train the system. For now, research shows that there are encoding biases and perpetuating stereotypes, which could threaten the progress toward achieving DEI goals in education. There have also been concerns regarding the originality of content and the potential for plagiarism in AI-generated content, violating copyrights.
There also are concerns regarding the reliance of generative AI on student data. Steps will need to be taken to protect personal, sensitive information and ensure privacy and confidentiality.
When used in combination with existing edtech tools and human educators, generative AI can transform learning experiences and academic outcomes. Generative AI tools, such as text-to-speech and vice versa, or recommendations of different content formats could prove especially useful for students with special needs and learning disabilities. Virtual tutors and assistants could provide 24/7 learning support and benefit students from underserved or remote areas.
By analyzing learning preferences and patterns, generative AI could adapt content to personalize learning, recommend teaching methods, benefitting both teachers and learners.
In the future, generative AI could not only transform the educational publishing and edtech sectors but would also alter the competitive landscape by enhancing productivity, reducing risks and operational costs, and adding value for all participants in the education sector.
At Integra, we support education and learning services providers experiment and innovate through our digital content development and AI/ML solutions. Our team of experts collaborate in design and development of innovative and impactful learning interventions varied learning needs. Contact us today to learn more about how we can support you with this transformation!
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