How to develop curriculum using AI

New technology brings significant opportunities for educators to improve their processes and the student experience. Think of how the internet and cloud computing allow students to learn from anywhere they like. If educational institutions ignore these advances, they impact their ability to meet student demands. Today, the industry is abuzz with news of artificial intelligence (AI), and there’s still plenty of time to get on board.

Course design is a particular area of interest for AI implementation. While designing a course is a complex process, getting it right is imperative for student and institutional success. AI can’t replace a subject matter expert’s skills, but it can significantly improve course design efficiency and effectiveness.

Read on to discover exactly how your institution can leverage AI for course design to empower faculty and provide the best education to students. You’ll also learn about the challenges of AI and the best practices you can implement to overcome them.

How to improve course design with AI

AI brings multiple opportunities for improvement in course design if you use it correctly. Not sure where to start? Here are 12 ways educational institutions are using AI for course design today:

1. Resource allocation

Higher education courses require a careful balance of resources to ensure their effectiveness. Course designers must evaluate which resources — like faculty, technology, books, software, and lab equipment — have the largest impact on student outcomes. Resource allocation can be difficult and time-intensive, but AI can speed up and simplify the process.

By gathering and analyzing student performance data, AI technology can highlight the most effective resources in a course. It can also identify which resources students use least so you can replace them or allocate them elsewhere. Using predictive analytics, AI can also predict course demands so your institution can allocate sufficient resources to courses in time.

2. Course objectives

Objectives are a critical component of course design because they indicate the desired student outcomes upon completion. Course designers then work backward from objectives to decide on learning material, teaching strategies, and assessments. Each decision must align with the overall course objectives. However, developing relevant objectives that meet both student and institutional goals isn’t easy.

Your institution can implement AI to inspire course objectives. With faculty guidance, AI can come up with ideas for course objectives as a starting point. AI can also refine existing course objectives and identify gaps in learning outcomes. Additionally, faculty can use AI to easily organize objectives into the correct sequence and align course content to them.

3. Content creation

Course designers and faculty spend significant time creating course content for students. This content can include presentations, quizzes, assignments, learning material, lesson plans, and activities. Content creation eats up the time they have to dedicate to their other responsibilities, like research and teaching. AI can streamline content creation and allow faculty to spend more time on other high-impact areas.

Educators shouldn’t rely solely on AI for creating content, as it lacks the creativity and subject matter expertise faculty have. However, it’s a fantastic tool for creating content outlines, generating ideas, and summarising content. It can also take existing content and develop teaching materials, like presentations and quizzes. AI can even save faculty time by updating course content to align with the latest information and industry standards.

4. Assessment questions

Educational assessments require students to apply their knowledge and showcase what they’ve learned. Faculty use assessment results to identify student weaknesses and assess course effectiveness. However, these results are only helpful if assessments contain the right questions. Questions should align with course objectives, which can be challenging.

With AI, faculty can quickly generate questions from course content and build a comprehensive question bank. They can also add further parameters to refine results, like creating questions around a specific topic or learning outcome. The generated questions may need editing and sorting, but having a place to start can make the process go much faster. AI can also take existing questions and adjust their difficulty level.

5. Assignment grading and feedback

Grading assignments is an essential but time-consuming task that often causes faculty to work overtime. However, grading and providing feedback are invaluable to students as they improve their performance. AI tools can help alleviate the burden of grading while still maintaining the educational quality students have come to expect.

While some assignments — like opinion essays — need a faculty member’s expertise and judgment, others have more straightforward answers. AI makes quick work of grading quizzes and exams with close-ended questions like multiple choice and true or false. AI tools can also use rubrics to grade short, open-ended questions. AI grading is often more unbiased and consistent than traditional methods.

AI can also help with assignments that require detailed feedback. Thanks to AI’s processing speed and availability, students can receive assignment feedback immediately. It can also provide recommendations for improvement specific to the student. When an assignment requires human consideration, faculty can use AI feedback as a starting point, making grading a quicker process.

6. Smart tutoring

Many students seek the support of tutors to aid in their educational journey. While faculty make time for one-on-one consults, they may have insufficient time to meet each student’s needs. Your institution can provide tutoring to students whenever they need it through smart tutoring, which involves AI-based intelligent tutoring systems (ITS).

An ITS is an advanced education platform that uses AI to simulate the one-on-one tutoring experience. It can:

  • Guide students through course content and offer instant guidance and feedback, just like a human tutor.
  • Break up complex problems into manageable steps to facilitate understanding.
  • Modify learning methods based on student action and performance, keeping them engaged.

7. Personalized learning

Every student has different goals, strengths, and interests. To cater to each student, some educators use a student-centered approach called personalized learning. Personalized learning involves tailoring curriculum and teaching methods to individual student needs. It’s an incredibly effective approach that can improve student engagement and performance.

What does personalized learning look like, and how can AI help? Examples of personal learning include allowing students to learn online, offering custom tutoring lessons, adapting course pace, and changing instructional methods. However, successful personalized learning relies on collecting sufficient data to understand each student’s needs. That’s where AI comes in — AI makes it easier for faculty to gather information about student performance and preferences, uncover actionable insights, and alter their learning experience accordingly.

8. Adaptive learning

Adaptive learning is part of personalized learning in that it customizes course design for each student. The approach uses AI to analyze student behavior and performance and automatically adjust the learning experience in real time. For example, when a student struggles to grasp a concept, the AI program can offer more content to boost their understanding. It can also increase course difficulty to challenge students who understand the content well.

9. Gamification

Educational institutions are constantly looking for new strategies to increase student engagement. One strategy that’s becoming increasingly popular is gamification, which is the incorporation of game design elements into learning environments. Think leaderboards, badges, levels, quests, rules, and interactivity.

Gamification aims to make learning fun and spark curiosity in students. Many young adults love to play video games in their spare time, so more game-like elements in coursework can motivate them to learn. Gamification platforms that utilize AI can capture student attention by personalizing and adapting elements to their preferences, making it more engaging.

10. Accessibility features

Another aspect of course design that benefits from AI is accessibility. One of the biggest challenges some students face is navigating education with disabilities. By incorporating AI tools into course design, your institution can improve access to education and help students of all abilities achieve their goals. AI accomplishes this by:

  • Converting text and visual content into speech.
  • Turning spoken words into text and controlling devices through voice commands.
  • Provide real-time captioning and sign language interpretation.
  • Translating course material and lectures into various languages.
  • Adapting content to suit an individual’s pace, ability, and learning style.

11. Predictive analytics

Some AI systems can collect and use data to predict future trends, a process called predictive analytics. Predictive analytics is an asset to higher education institutions, allowing them to stay ahead of industry changes and student needs. The technique has various use cases throughout education, including course design.

With predictive analytics, your institution can start monitoring student interaction with course content. Over time, the system identifies trends and patterns in learning behavior and performance. When a student begins struggling with the course, AI can notify faculty so they can intervene early and provide extra support. Early intervention is key to retaining students and ensuring their success.

12. Course improvement

Evaluating how students progress through your institution’s courses is vital for improvement. AI can make improving course design a breeze as it collects vast amounts of valuable data. It can record student engagement, completion rates, assessment results, and course feedback. Course designers can analyze this data and look for areas of improvement.

For example, you can identify and directly adjust the sections students struggle with. AI may help pinpoint the reason behind why they’re struggling, like whether its an issue with teaching methods, content, or platform design. It can also highlight which strategies work the best. By using AI to collect data and drive decision-making, you can continually improve course design and student outcomes.

Challenges facing AI-powered course design

AI can revolutionize course design, but it comes with challenges your institution may have to overcome. By understanding potential drawbacks and preparing for them in advance, you can ensure a seamless integration. Examples of AI-related challenges include:

  • Faculty resistance: Faculty may have read headlines about how AI can replace their jobs, making them apprehensive and fearful of it. Without addressing their concerns, your institution may struggle to get faculty on board with using AI for course design. Addressing concerns and educating faculty on AI is key.
  • Overreliance: Given how much AI can do, it’s easy for educators to become overreliant on it. However, this poses an ethical concern as students pay for and expect courses designed and taught by experts, not AI. AI lacks the knowledge, empathy, and intuition of real people, and using it too much can cause education quality and student experience to suffer.
  • Sustainability: AI is helping sustainability experts tackle some of the world’s biggest environmental emergencies, but it comes with a cost. The technology behind AI consumes large amounts of water and energy, negatively impacting the planet. Your institution must focus on only using AI when necessary, supporting eco-friendly AI providers, and increasing overall sustainability efforts.

Best practices for leveraging AI in course design

AI is the future of course design, but how your institution approaches it can impact your success. Here are some tips for overcoming challenges and achieving the best results with AI in course design:

  • Define clear objectives: Outlining objectives and an overall goal for using AI is essential. Objectives will help you measure the success of AI implementation and ensure that any use of AI aligns with your institution’s goals and values. They can also guide faculty when using AI, reducing the chance of overreliance.
  • Choose optimal tools: With your objectives defined, you can move on to choosing AI tools. The right tool for your institution is one that will help you achieve your goals and meet student needs. Evaluate each tool’s features, cost, support, scalability, and ease of integration with existing tools.
  • Establish and monitor KPIs: Along with objectives, you should establish key performance indicators (KPIs) for AI use. KPIs give you a clear metric for how well your institution uses AI and if it’s worth the cost and effort. Frequently gather feedback from students and faculty to investigate the effectiveness of AI for course design at your institution.
  • Prioritize data security: AI systems often access private and sensitive student and institutional data to provide the best results. However, this poses a security risk and requires sufficient protection. Ensure your chosen AI tool has adequate data security methods and complies with data protection regulations.

Streamline the course design process with Watermark

Before integrating AI, your current course design process should be consistent and straightforward. Having a strong foundation gives faculty the freedom to explore and harness AI with less stress. That’s why we created Watermark Curriculum Strategy, a simplified curriculum management system tailor-made for higher education.

This powerful tool lets faculty easily collaborate on curriculum development and catalog creation. It can also gather student feedback about course content to inform curricular changes. What’s more, Curriculum Strategy seamlessly integrates with Watermark’s Educational Impact Suite, an integrated hub of tools for higher education institutions.

Simplify your software solutions and make room for AI with Watermark. Want to see our tools in action? Request a demo today!

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Online Course Feedback 101: From the Physical to the Digital Classroom

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Positive Change During Challenging Times: How Six Leaders Transformed Higher Education During the Pandemic

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Continuing education evaluation guide

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Supporting working-class students: 7 ways to show support

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Building soft skills for future careers: Integrating professional development into your curriculum
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Building soft skills for future careers: Integrating professional development into your curriculum

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15 common challenges that first-year students face

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How to spot struggling first-year students and intervene

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12 tips to improve first-year college student performance
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Weighing legacy admissions: What to consider at your institution

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Key metrics for mid-semester program reviews: What to measure and why

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Supporting student success during midterms

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7 student engagement software trends to watch for in 2025

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7 innovative assessment practices to transform your institution

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Involving faculty in accreditation processes

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Leading causes of faculty burnout and how to spot it

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The impact of AI on institutional research 

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Essential strategies to support adjunct and part-time faculty

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What are guided career pathways for faculty?

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Separation of school and state: Can the Department of Education pull accreditation? No. Here’s why

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The importance of community colleges in 2025: A look back and forward

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Community college trends in 2025

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How community colleges can increase course demand by adding courses on AI

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Synchronous vs. asynchronous learning: How to measure success

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