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Master 14 AI-integrated assessment methods and design authentic, effective assessment tasks. Integrate Quiz and Survey tools to support your teaching assessment needs in all aspects.
Overview of AI-Integrated Assessment
As generative AI becomes widespread, traditional assessment methods face major challenges. Students can easily use AI to complete assignments, forcing us to rethink: What constitutes a genuinely valuable learning outcome?
AI-integrated assessment is not about banning AI; it is about designing assessment tasks that can demonstrate Students’ real abilities. These 14 methods are divided into two main categories:
Using AI as a tool to support traditional assessment, with the focus still on evaluating subject knowledge and skills
AI itself becomes central to learning and assessment, evaluating Students’ AI literacy
Six AI Competencies
These six core competencies are the foundation of AI-integrated assessment; each assessment method cultivates one or more of them:
Critically evaluate the accuracy, bias and applicability of AI-generated content
Design effective prompts to obtain the AI output you need
Identify bias and limitations in AI systems
Effectively integrate AI into workflows
Understand and apply the ethical principles of AI use
Reflect on your own use of AI and the decisions you made
AI to Enhance Traditional Assessment (8 Methods)
Students use AI as a reflective partner, exploring their learning process through dialogue and identifying strengths and areas for improvement. AI provides guiding questions to help students deepen their self-understanding.
After completing a project report, students have a reflective dialogue with AI: "What did I learn from this project? Which parts did I do well? If I were to do it again, how would I improve it?" AI provides follow-up questions to help students reflect in depth.
Students first use AI to generate a draft, then critically review, revise and improve the AI output. The assessment focuses on the Student's editing skills, critical thinking and reasons for improvement.
Students use AI to generate an essay outline, then need to: (1) identify issues in the AI output, (2) revise it and explain the reasons, and (3) submit a tracked-changes version to show the improvement process.
Students complete the work independently first, then use AI to review and improve it. The focus is on how the Student uses AI feedback, selectively adopts suggestions, and explains the decision-making process.
Students write the code independently and then use AI for code review. Students must submit: the original code, the AI feedback, the final version, and an explanation of which suggestions were accepted or rejected, and why.
The instructor or students use AI to generate learning materials (cases, data, scenarios), and students analyse these materials. The focus is on analytical ability rather than material creation.
Business course: AI generates financial data and market scenarios for a fictional company, and students must analyse the challenges faced by the company and propose strategic recommendations. Each student receives a different AI-generated case.
AI plays a specific role (client, patient, negotiating counterpart, and so on), and Students interact with it for practice. Students’ performance and response ability in simulated situations are assessed.
Nursing Course: AI acts as a patient with specific symptoms, and the Student practises taking a history. AI gives consistent responses based on the Student's questions, assessing the Student's history-taking skills and clinical reasoning ability.
Use AI to create immersive learning experiences, such as interactive stories, simulated environments or gamified learning. Students demonstrate their knowledge and skills in these environments.
Historical course: AI creates an interactive historical scenario in which the Student plays a historical figure and must make decisions based on the social context and knowledge of the time; AI responds with the consequences of those decisions.
Students complete both a manually produced version and an AI-assisted version of the work, then compare and analyse the differences, strengths and weaknesses, and reflect on the value and limitations of AI.
Writing course: Students first complete a short essay independently, then use AI to help write another short essay on the same topic. They then analyse and compare the two versions, discussing the impact of AI on writing style, creativity and efficiency.
Allow students to use AI as an assistant in complex tasks, but require them to record and reflect on how AI is used. Assess both students' overall work and their ability to use AI effectively.
Research methods course: Students conduct a literature review project and may use AI to assist with searching, summarising and organising the literature. Students must submit an AI usage log explaining how they verified the information provided by AI.
AI as the Key Object of Study (6 Methods)
Students assess the quality, accuracy, bias and applicability of AI-generated content. The focus is on developing the ability to critically evaluate AI outputs.
Journalism course: Students receive multiple AI-generated news summaries and need to assess each summary's accuracy, whether it contains bias, what important information has been omitted, and propose improvements.
Students learn and demonstrate the ability to design effective prompts, analyse how different prompting strategies affect AI output, and optimise human-AI interaction workflows.
Information Science course: students design multiple versions of prompts for a specific task, record the results of each iteration, analyse which prompting strategy is most effective, and write a best-practice report on prompt engineering.
The Student studies and discusses ethical issues, policy frameworks and social impact of AI, developing a broader understanding of AI's impact and critical thinking.
For law or public policy courses: students analyse the application of AI in the justice system (for example, sentencing recommendation algorithms), discuss issues of fairness, transparency and accountability, and propose policy recommendations.
Students explore AI vulnerabilities and limitations in a controlled environment, using methods such as "red teaming" to understand how AI systems may be misused or manipulated.
Cybersecurity course: Students attempt to use various prompt strategies to induce AI to generate inappropriate content or misinformation, record successful and unsuccessful attempts, and analyse AI's safety mechanisms and vulnerabilities.
The Student studies practical application cases of AI in specific fields or contexts, analysing their impact, challenges and opportunities.
Medical management course: students study a case of introducing an AI diagnostic system into a hospital, analysing the implementation process, challenges encountered, the impact on doctor-patient relationships, and methods for evaluating effectiveness.
Students analyse the AI system itself from technical, design, or humanities perspectives — how it is built, what values its design choices reflect, and how it shapes user behaviour.
Human–computer interaction course: Students analyse the interface design, personality settings, and dialogue strategies of different chatbots, discussing how these design choices affect user experience and trust.
Assessment Tools in Uedu Platform
In addition to the 14 AI-integrated assessment methods above, the Uedu platform also provides complete Quiz and Survey tools to support your teaching assessment needs:
An AI-driven intelligent quiz system supporting multiple question types, automatic marking and learning analytics.
Please use the Quiz function on your course page
A complete survey tool, supporting multiple question types, anonymous responses and statistical analysis.
Please use the Survey function on your course page
Combining 14 AI-integrated assessment methods with Quiz/Survey tools can create a richer assessment experience. For example:
• Use Survey to collect Students' reflections on AI collaboration experiences (paired with A1, A8)
• Use Quiz to assess Students' ability to identify AI bias (paired with B1, B3)
• Use Survey's pre- and post-test functions to track growth in AI literacy