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Artificial intelligence in content personalisation and adaptation

Site: Loomen za stručna usavršavanja
Course: Artificial Intelligence in Education
Book: Artificial intelligence in content personalisation and adaptation
Printed by: Gost (anonimni korisnik)
Date: Tuesday, 28 July 2026, 8:16 AM

Table of contents

1. An introduction to the personalisation and adaptation of content using artificial intelligence

Personalisation in education involves adapting teaching content and methods to the individual needs, interests, and pace of each student. Artificial intelligence (AI) can significantly enhance this process by analysing large amounts of student data and automatically adjusting content to their abilities and preferences based on the insights gained.

AI-driven content personalisation and adaptation create a dynamic educational environment in which teaching activities, materials, and difficulty levels are continuously tailored to each student's abilities, interests, and progress, promoting deeper, more effective, and more meaningful learning.

For example, AI systems can recommend additional materials to students who need extra support, while offering more complex tasks and challenges to those progressing more quickly. AI can also continuously monitor student progress and engagement, providing real-time feedback that enables rapid and effective adaptation of teaching activities to individual needs.

Some of the main ways AI contributes to the personalisation and adaptation of educational content include:

  • Automatically adjusting task difficulty according to the learner's abilities and pace

  • Recommending additional resources and materials based on interests and previous achievements

  • Generating customised quizzes, exercises, and tasks

  • Analysing educational behaviour and predicting areas where learners need additional support.

By using such systems, AI becomes a key factor in shaping personalised and adaptive learning, allowing each learner to progress at their own pace with content that is credible, reliable, and aligned with their educational needs.

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2. Selected tools and artificial intelligence systems for personalisation and content adaptation

The development of generative artificial intelligence has created numerous opportunities to improve how educational content is created, organised, and adapted. Educational stakeholders now have access to various digital tools that use artificial intelligence to design, analyse, and personalise teaching materials, enabling students to learn according to their individual needs, interests, and pace of progress.

The tools listed below are among the most commonly used in higher education and have proven relevant for creating and adapting educational content. They were selected based on criteria such as pedagogical applicability, availability, and the potential for integration into digital educational environments. Each tool is presented with a brief description, an explanation of its relevance to the educational context, and links to official pages and tutorials to support independent research and use.

It is important to note that not all of the listed tools are completely free. Most offer basic functionality through free plans, while advanced features – such as extended content generation, collaboration tools, or integration with other systems – are typically available by subscription. Therefore, teachers should evaluate the capabilities of each tool in relation to their own needs, technical requirements, and institutional resources before use.

2.1. List of tutorials: AI tools and systems for personalisation and adaptation of content

The following AI tools and systems are designed for the personalisation and adaptation of educational content, selected based on their availability, pedagogical value, and applicability in higher education. The attached tutorials allow users to explore their capabilities and understand how they can enhance the creation and adaptation of teaching materials.

1. ChatGPT (OpenAI)

Description: A generative artificial intelligence model that enables the creation of customised educational materials, assistance with essay writing, explanations of complex topics, and interactive dialogues with students.
Uses: Creating personalised tasks, providing learning support, and assisting with research work.

Relevance: ChatGPT is the most widely used tool in higher education due to its flexibility and ability to adapt content to various levels of complexity and learning styles.

Links:

2. Google Gemini (formerly Bard)

Description: Google’s advanced AI model that combines text, image, and multimedia capabilities.
Uses: Creating personalised modules, visuals, and interactive teaching materials.

Relevance: Integrated with Google Workspace, it is a practical tool for higher education instructors, allowing easy implementation within existing Google environments (Docs, Slides, Classroom).

Link:

3. Claude (Anthropic)

Description: A generative model developed with an emphasis on ethics, accuracy, and transparency.
Uses: Academic writing, content analysis, and automated summarisation of scientific articles.

Relevance: Claude is well-suited for academic contexts because it reduces the risk of bias and misinformation, contributing to the quality of educational materials.

Link:

4. Jasper AI

Description: A tool for generating educational texts and teaching materials with the ability to adjust tone and writing style.
Uses: Creating teaching units, seminar texts, project descriptions, and educational guides.

Relevance: Jasper AI provides a high level of control over text style and tone, distinguishing it from other tools and making it suitable for academic writing and communication.

Link:

5. Writesonic

Description: A generative tool that enables rapid creation of educational texts, explanations, and tasks.
Uses: Adapting content to different knowledge levels, creating test questions, and creating didactic materials.

Relevance: Known for its speed and ability to adapt content to target student groups, Writesonic is useful for teachers seeking to personalise materials effectively.

Link:

6. Copy.ai

Description: A tool for automatically generating shorter educational texts, summaries, and questions.
Uses: Creating short teaching units, summaries, and quiz questions.

Relevance: Easy to use and enables quick creation of micro-content to supplement core teaching materials.

Link:

7. Curipod

Description: A platform powered by artificial intelligence to create interactive presentations and quizzes with elements of collaboration and active learning.
Uses: Creating dynamic lessons, surveys, and quizzes that adapt to student needs.

Relevance: Curipod uses artificial intelligence to automatically generate content and question suggestions, simplifying lesson preparation and encouraging active participation.

Links:

8. Khan Academy AI Tutor

Description: A virtual assistant that monitors learning and provides personalised recommendations.
Uses: Individualised support for students through additional materials and assignments.

Relevance: AI Tutor enables personalised learning in real time and helps students master content independently.

Link:

9. Microsoft 365 Copilot and Designer

Description: Tools integrated into the Microsoft environment, using artificial intelligence to create textual and visual educational materials.
Uses: Automating the preparation of presentations, work materials, and educational documents.

Relevance: The main advantage is full integration with tools teachers already use, allowing quick implementation in higher education without the need to learn new systems.

Links:

10. Synthesia

Description: An artificial intelligence tool for creating video lessons with avatars that speak and adapt content to the target audience.
Uses: Creating video materials that replace traditional lectures.

Relevance: Enables simple and affordable creation of professional video lessons without technical equipment, increasing student accessibility and engagement.

Link:

11. Pixverse UI

Description: A platform that enables the generation of visual content using artificial intelligence, helping instructors and teachers create engaging and personalised graphic materials for education.

Uses: Creating illustrations, infographics, and graphic elements for educational content.

Relevance: Provides teachers with the ability to quickly create visually appealing materials that enhance understanding and help retain student attention.

Link: 

12. DALL-E (OpenAI)

Description: A generative tool that creates images based on users' text descriptions.

Uses: Creating illustrations and visuals to accompany and enrich educational content.

Relevance: DALL·E opens new possibilities in visual expression and supports the creation of creative, customised materials that aid in understanding complex concepts.

Link: 

Note:

Most of the tools listed offer basic functionality for free, with advanced features available by subscription. While reading and studying the tutorials, it is recommended to explore the appearance and functionality of each tool to better understand how artificial intelligence contributes to the personalised and adaptive creation of educational content.

There are many artificial intelligence tools available today for creating, adapting, and improving educational content. Their functionalities vary according to purpose, complexity, and level of integration into educational systems. When choosing, it is important to consider pedagogical goals, technical capabilities, and the reliability of the source.

For an additional overview of more than 50 tools currently most commonly used in education and enabling creative design of teaching materials, the recommended source is:

Note: For most of the listed artificial intelligence tools and systems, additional video tutorials and guides can be found on the official YouTube channels of the manufacturers or user communities. Following these channels is recommended to gain insight into the latest instructions, examples, and best practices for applying artificial intelligence in education.

2.2. Examples of successful use of AI in the creation of educational content

This lesson focuses on higher education institutions that have successfully implemented artificial intelligence (AI) tools in creating and adapting educational content. Each example demonstrates how a particular institution uses a specific tool, why that tool was chosen, its advantages compared to other options, and the results and value achieved for teachers and students. The goal is to promote understanding of best practices and provide inspiration for applying similar solutions in your own educational context.

1. University of Oslo (Norway)

  • AI tools and systems used: ChatGPT and its adapted institutional version, GPT AiO
  • Reasons for choosing the tool: ChatGPT is one of the most advanced and widely used generative AI models in higher education. Its key value lies in its ability to generate, summarise, and adapt educational content according to students’ prior knowledge and interests. Compared to other AI tools, ChatGPT offers an interactive interface that enables dynamic dialogue, fosters critical thinking, and develops metacognitive skills. Its flexibility and ability to process complex tasks in real time make it especially suitable for teaching and research contexts.
  • Application description: The University of Oslo has developed its own secure version of this tool – GPT AiO. This version operates within a closed institutional environment and fully complies with Norwegian and European data protection standards (GDPR). GPT AIO is used as a digital assistant in various educational contexts, including teaching, mentoring, and research projects.
    Teachers use it to design lesson plans, create didactic scenarios, formulate problem tasks, and develop educational texts. Students use the tool during independent learning phases, such as analysing texts, writing essays, formulating research questions, and checking their understanding of complex theoretical concepts. The tool also encourages reflective learning, as students can review their own answers and compare them with system-generated feedback.
  • Best practices and results: Implementing the GPT AiO system at the University of Oslo has led to increased student engagement, greater autonomy in learning, and higher-quality, more well-argued academic papers. The introduction of the tool was accompanied by training on the ethical and responsible use of AI, ensuring academic integrity and transparency in the use of generative technologies. This example illustrates a model of institutional integration of AI in higher education, connecting technological innovation with pedagogical purpose and ethical principles. Unlike commercial versions, GPT AiO is integrated into the University of Oslo’s security system and upholds the principles of academic freedom and responsible technology use. The quality of teaching materials has improved, and teachers receive support in developing didactic scenarios tailored to different learning styles. This example shows how institutions can develop their own AI-based tools, maintaining full control over data protection and academic ethics.
  • Link: GPT AiO – University of Oslo

2. Arizona State University (USA)

  • Tools used: 
    • ChatGPT Edu — a generative model within a secure institutional environment that enables the creation of personalised teaching materials, academic support for students, and the development of digital literacy,
    • Google Workspace AI (Gemini integration) — allows teachers to generate texts, visual summaries, and activity suggestions within familiar Google tools, increasing efficiency and creativity in teaching,
    • Question Generator — automates the creation of quizzes, tests, and questions aligned with learning outcomes, making knowledge assessment easier for teachers,
    • ClipGist — generates summaries and guides from video lectures and creates content-based quizzes, helping students follow and review material,
    • Image Accessibility Tool — automatically generates descriptions and alt-texts for images in educational materials, increasing content accessibility for all students,
    • Rubric Generator — enables the creation of rubrics and assessment criteria for defined tasks, ensuring transparency and consistency in student assessment,
    • Learning Objective Creator — helps teachers formulate learning objectives and generates questions and tasks that support the development of desired competencies,
    • Script Voiceover Tool — converts text into professional-quality voiceover, making it easy to create video lessons and multimedia materials.
  • Application description:
    Arizona State University is one of the most innovative universities in applying generative artificial intelligence in higher education. In 2024, ASU became the first institution to officially implement ChatGPT Edu in its academic programmes in partnership with OpenAI (OpenAI, 2024). By integrating the Google Gemini model into Google Workspace AI tools (Docs, Sheets, Slides, and Meet) and developing its own AI Tool Suite, ASU has created a system that enables the creation, adaptation, and evaluation of educational content in real time, with a high level of ethics, security, and pedagogical compliance.
  • Good practice and results:

    Through the “AI Innovation at ASU” initiative, ASU has established a systematic framework for using artificial intelligence in teaching and research. The application of these tools at ASU has resulted in a significant increase in efficiency in preparing and personalising teaching materials and greater student engagement. Teachers emphasise the reduction of administrative burden, faster adaptation of content to different groups of students, and better alignment between digital tools and pedagogical goals.

    ASU's model of integrating artificial intelligence into education is recognised as an example of a balanced approach between innovation, ethics, and quality of learning, setting the standard for other higher education institutions.

  • Links:

3.  University College London (UCL)

  • AI tools and systems used: 
    • ChatGPT (OpenAI), Microsoft Copilot, Turnitin AI Detection (key tools used are listed)
    • University College London (UCL) is recognised as a leading university in the responsible and pedagogically sound use of AI in higher education. The selected tools address key aspects of the teaching process: content generation and adaptation (ChatGPT, Microsoft Copilot), assessment (Gradescope), and ensuring academic integrity (Turnitin AI Detection). These tools offer advantages over other solutions due to their integration with the university’s existing digital ecosystem, interoperability, and the ability to operate within an institutionally controlled, secure environment.
  • Description of the application:
    • UCL is systematically developing frameworks for the ethical and transparent use of AI through the Generative AI Hub initiative, which provides teachers and students with resources, guidance, and examples of good practice.
      ChatGPT is used in digital literacy and academic skills courses, where students learn about the potential and limitations of generative models. Microsoft Copilot is integrated into work tools (Word, Excel, PowerPoint) and assists teachers in creating, editing, and adapting teaching materials, thereby increasing the productivity and quality of didactic content.
      Gradescope, which uses AI to analyse student responses, enables automated assessment and faster feedback to students, especially in high-volume STEM fields. Turnitin's AI Detection is used to verify similarity and identify generated content, ensuring compliance with academic standards and ethical principles.
  • Good practice and results:
    • UCL has developed the concept "Three categories of GenAI use in assessment," which categorises the ways generative artificial intelligence can improve the assessment of student work. This approach allows teachers to systematically include AI tools in assessment while respecting the principles of academic fairness and transparency.
      Evaluations conducted within UCL's Digital Education Futures Lab show that the use of AI tools reduces the administrative burden on teachers, speeds up the assessment process, and encourages students to learn more actively and reflectively.
      This example illustrates a balanced institutional approach that connects technological innovation with pedagogical purpose and ethical responsibility.
  • Links:

4.  University of Edinburgh (UK)

  • AI tools and systems used:
    • ChatGPT (OpenAI), Microsoft Copilot, Gradescope, Turnitin AI Detection
  • Reasons for choosing the tools:
    • The University of Edinburgh is one of the first in Europe to systematically integrate generative AI into teaching, learning, and assessment processes. ChatGPT and Microsoft Copilot are used to support the design of teaching materials, the creation of educational texts, and communication with students, while Gradescope and Turnitin AI Detection were introduced to improve the assessment process and ensure academic integrity. This approach combines generative tools for content creation with analytical tools that monitor the quality and authenticity of student work.
  • Description of the application:
    • Gradescope is the main platform for digital assessment in more than 500 courses at the University of Edinburgh, covering over 200,000 student submissions per year (Digitisation Assessment at the University of Edinburgh).
    • The tool enables automated grading, collaborative work among teachers, and the provision of feedback in a significantly shorter time. ChatGPT and Copilot support the creation of teaching content and learning scenarios, while Turnitin AI Detection is the standard tool for checking the authenticity of texts and detecting AI-generated content.
    • Within the AI for Teaching Innovation initiative, the University is also exploring the development of its own models (ELM – Edinburgh Language Models) to enable the safe use of generative AI in an academic context.
  • Good practice and results:

    • The implementation of Gradescope has significantly reduced administrative burden and increased grading accuracy, with a positive impact on transparency and student satisfaction. The AI for Teaching Innovation project has further contributed to the development of pedagogical models that combine human assessment with automated analysis systems.

    • The University of Edinburgh has set an example of how to integrate generative AI into learning and teaching processes responsibly, ethically, and pedagogically.

  • Links:

5.  Maryville University (USA)

  • Artificial intelligence tool and system used:
    • Synthesia – an artificial intelligence platform for creating personalised video lessons, simulations, and educational content with virtual avatars and automatic speech synthesis.
  • Application description:

    • Maryville University uses Synthesia in its online and hybrid degree programmes, particularly in business, educational technology, and health sciences. Instructors use the tool to create personalised video lessons in which AI avatars deliver customised teaching content, present study assignments, or conduct dialogues with real lecturers. This provides students with an interactive and accessible learning experience in an asynchronous environment.

      For example, Maryville University created more than 85 video lessons within eight months, reducing the time required to produce a single video by 35%. The tool is also used to develop educational scenarios in which AI avatars explain theoretical concepts or introduce students to new teaching units.

  • Good practice and results:
    • The use of Synthesia has enabled Maryville University to increase efficiency in creating multimedia educational content, improve material accessibility, and boost student engagement in the online environment. Evaluations show that students respond positively to personalised video lessons, as they foster a sense of closeness and individual support, even in a digital context. This example demonstrates how higher education institutions can effectively integrate generative AI tools into their educational practices while maintaining pedagogical quality and professional standards in multimedia production.
  • Link:

6.   Harvard University (USA)

  • Artificial intelligence tool and system used:
    • Gradescope, Turnitin AI Detection, ChatGPT Edu (experimental application)
  • Application description:

    • At Harvard, artificial intelligence-based tools are used within the officially supported Academic Technology for FAS (Faculty of Arts and Sciences). Gradescope is integrated into Harvard’s digital education ecosystem and is especially useful in science, technology, engineering, and mathematics (STEM) courses, where it facilitates the analysis of handwritten and digital assignments. Combined with the Turnitin AI Detection system, it provides comprehensive support to instructors in assessing the authenticity and quality of student work.

      Experimentally, some departments (e.g., Harvard Graduate School of Education) are also exploring the potential of ChatGPT Edu to support learning and prepare materials, with clear ethical guidelines.

  • Good practice and results:

    • The implementation of artificial intelligence tools at Harvard has increased efficiency in grading and providing feedback to students, especially in large courses with several hundred students. The use of Gradescope has reduced the average time for grading exams and assignments by more than 50%, allowing instructors to focus more on qualitative analysis of student work and personalised comments. At the same time, students receive faster and clearer feedback, which contributes to greater transparency and motivation for learning. Additionally, the use of Turnitin's AI Detection tool has helped establish clear standards of academic integrity in the era of generative artificial intelligence, while research on ChatGPT Edu highlights opportunities for developing metacognitive skills and independent learning, with the need for ongoing supervision and user education.

    • The example of Harvard University illustrates a balanced approach to introducing artificial intelligence in higher education, combining technological innovation with ethical standards and pedagogical effectiveness. Systems like Gradescope and Turnitin AI Detection not only improve grading processes but also contribute to a culture of responsible and transparent use of artificial intelligence in the academic context.

  • Links:

7.  Massachusetts Institute of Technology (MIT, USA)

  • Artificial intelligence tools and systems used:
    • Generative AI models (primarily ChatGPT and related large language models), the Gradescope tool for automated grading and feedback, and other tools defined by institutional AI guidelines developed through the Teaching + Learning Lab (TLL) initiative.
  • Application description:
    • Through the Generative AI & Your Course initiative, MIT systematically empowers teachers to apply generative artificial intelligence in education ethically, creatively, and pedagogically. According to a report by MIT News, faculty members and students are experimenting with ChatGPT and similar models to explore ways to integrate AI tools into materials preparation, data analysis, and personalised student support. Additionally, MIT uses the Gradescope tool as a standardised solution for digital grading. This tool enables faster, more consistent, and more transparent evaluation of student work, and is integrated into teaching across several departments and courses.
  • Good practice and results:
    • According to the study "Gradescope: a Fast, Flexible, and Fair System for Scalable Assessment of Handwritten Work” (Berkeley, 2017), the use of Gradescope led to savings of 30% or more in the assessment process compared to traditional methods. At MIT, the results of using the tool showed increased consistency in grading and improved quality of feedback to students. The use of generative AI tools, according to MIT Open Learning, has encouraged the development of innovative learning approaches and increased student engagement. This example demonstrates how MIT integrates artificial intelligence into teaching through a combination of generative and evaluative tools, with an emphasis on ethics, efficiency, and scientific validity.
  • Link:

8. Tsinghua University (Beijing, China)

  • Artificial intelligence tools and systems used:
    • iFlytek Spark Cognitive Model, Baidu ERNIE Bot, and the institutionally developed AI Teaching Assistant system within the Tsinghua Laboratory for Educational AI.
  • Application description:
    • Tsinghua University is one of the world's leading institutions in integrating artificial intelligence into educational processes. As part of the Institute for AI Education and the Laboratory for Educational AI, an advanced AI Teaching Assistant System has been developed to provide students with personalised learning support. The system uses generative AI models to analyse learning styles, monitor progress, and identify areas requiring additional support, enabling the recommendation of tailored content, exercises, and resources. Tsinghua also collaborates with leading Chinese technology companies, iFlytek and Baidu, in applying the iFlytek Sparki cognitive model and the Baidu ERNIE Bot generative system. These tools are used to create educational materials, check student understanding, and automate the analysis of written assignments.
  • Good practice and results:
    • According to reports published on the official websites of Tsinghua University – Tsinghua University News (“The five best things about Tsinghua’s new AI teaching assistant”) and Tsinghua University Library (“AI Service New Experience”) — the introduction of the AI teaching assistant system and related tools has significantly improved the efficiency and quality of teaching. The use of AI has enabled teachers to assess student progress more accurately and allowed students to receive personalised learning and faster feedback. The results of the pilot program showed increased student engagement, reduced time spent on individual mentoring, and greater clarity in understanding complex concepts. The university has also established an ethical framework for the use of AI in education, emphasising transparency, privacy, and responsible use of generative technologies.
  • Links:

9.  Columbia University (USA)

  • AI tools and systems used:
    • ChatGPT (educational and institutional version available through the Columbia University system)
    • Google Gemini – a generative model integrated into academic tools
    • NotebookLM – an AI-based tool supporting research, analysis, and content summarisation

  • Application description:

    • Columbia University uses generative AI systems to enhance the educational process and assist faculty in content creation. Tools such as ChatGPT and Google Gemini enable more efficient creation, customisation, and visualisation of educational materials, while NotebookLM helps analyse complex texts and research sources. Their advantage over other available tools lies in their integration with the university’s existing digital ecosystems and in security standards that protect academic integrity and data privacy.
    • Through the Department of Information Technology (Columbia University Information Technology – CUIT), Columbia University provides students and faculty with institutional access to ChatGPT Education, Google Gemini generative models, and the NotebookLM system.
    • The University also develops and publishes practical guides, such as Considerations for AI Tools in the Classroom, to help educators use AI  in teaching and learning responsibly and purposefully.

  • Good practices and results:

    • Columbia University has established a comprehensive framework for the ethical and responsible use of AI in academia through its Generative AI Policy. This policy clearly defines guidelines for data protection, copyright, academic integrity, and transparent use of generative systems. Faculty apply these guidelines across disciplines, adapting curricula and teaching activities in line with the principles of transparency and responsible innovation.

      This approach has been recognised as a model of good practice for institutional integration of AI in higher education, ensuring a balance between innovation, ethics, and teaching quality.

  • Links:

10. University of Sydney (Australia)

3. Conclusion

Examples of AI applications in higher education at universities worldwide – from the University of Oslo and the University of Arizona to University College London and Harvard, to Tsinghua University and the University of Sydney – demonstrate how technological innovation can be successfully combined with pedagogical purpose and ethical responsibility. Although the approaches differ, common goals are evident in all cases: increasing student engagement, fostering the development of digital competencies, and creating flexible, customised, and experiential forms of learning.

These examples clearly demonstrate that AI, when used thoughtfully and with clear institutional guidelines, can help improve the quality of teaching, assessment, and learning support. The key to successful integration lies not in the technology itself, but in its meaningful inclusion in the pedagogical context, with ongoing monitoring of its effects, professional development for teachers, and adherence to the principles of ethics, transparency, and privacy protection.

AI does not replace the human element in education – it complements it. As a partner in the teaching and learning process, it allows teachers to focus more on the creative and analytical aspects of their work and provides students with opportunities for deeper, more independent, and more reflective learning. The future of education is therefore not only about technology, but also about how we apply it responsibly and purposefully.

Reflective questions:

  1. What are the similarities and differences in approaches to integrating AI among the universities analysed?

  2. How could you apply some of the presented examples of good practice in your own teaching or research context?

  3. What are the potential challenges and risks of over-reliance on automated systems in education, and how can they be mitigated?

  4. How can ethical and pedagogical principles guide the future development and use of AI in higher education?

  5. What does the idea of AI as a partner in the teaching and learning process mean to you personally?

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