The AI in Education Assessment course is designed to introduce educators, instructional designers, and education technologists to the transformative role of artificial intelligence in grading and assessment.
AI in Education Assessment
The AI in Education Assessment course is designed to introduce educators, instructional designers, and education technologists to the transformative role of artificial intelligence in grading and assessment. As digital classrooms evolve, the demand for scalable, accurate, and real-time evaluation methods is increasing. This course explores how Grading and Assessment with AI is revolutionizing education by automating grading, analysing essays, evaluating visual submissions, and delivering personalized feedback at scale.
From leveraging machine learning for objective tests to using natural language processing (NLP) to assess student essays, this course takes a hands-on, practical approach to implementing Assessment with AI in diverse learning environments. Whether you're curious about AI-powered feedback tools or exploring ethical concerns in automated grading systems, this course will equip you with the knowledge and skills to navigate the evolving landscape of digital assessment.
This course is ideal for educators, school administrators, instructional designers, and EdTech professionals who want to understand and apply AI in grading and educational assessment. It also suits data analysts, AI enthusiasts, and policy-makers interested in the future of education and automation. No prior programming or AI experience is required—just a passion for innovation in teaching and learning assessment.
Understand the fundamentals of AI in grading and assessment.
Explore machine learning techniques for automating grading processes.
Apply NLP tools to evaluate essays and written assignments.
Use AI-powered systems for objective test evaluation and instant feedback.
Analyse how computer vision can assess visual and creative student work.
Design personalized feedback mechanisms using AI tools.
Evaluate ethical and privacy implications of AI in educational settings.
Anticipate future trends and innovations in AI grading systems.
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Gain an overview of how artificial intelligence is being used to support grading, feedback, and learning evaluations.
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Learn how machine learning algorithms classify responses, predict scores, and adapt to grading patterns over time.
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Explore how NLP tools assess student essays for coherence, grammar, relevance, and critical thinking.
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Use AI-driven systems to create and grade multiple-choice, true/false, and short-answer questions instantly.
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Understand how computer vision evaluates diagrams, sketches, artwork, and STEM-related visuals.
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Design smart feedback systems that provide real-time insights and adaptive suggestions to improve student learning.
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Discuss fairness, transparency, data security, and bias in AI assessment tools.
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Discover the latest innovations in grading and assessment with AI, including predictive grading models and personalized learning analytics.
Earn a Professional Certificate
Earn a certificate of completion issued by Learn Artificial Intelligence (LAI), recognised for demonstrating personal and professional development.
Hudson
Diploma in AI in Edu...It shows how AI can make grading faster, fairer, and more efficient.
No, this course is designed for non-technical participants. The focus is on practical applications of AI in education rather than programming.
Yes, the course introduces various AI-based tools and platforms used for automated grading and feedback. You’ll explore their functionality and real-world use cases.
Through NLP and computer vision technologies, AI can analyse text for structure and clarity, and visuals for accuracy and creativity—helping standardize assessment.
AI is used to automate grading, analyse student responses, track learning progress, and deliver personalized feedback in real time—enhancing both efficiency and accuracy.
AI is applied in curriculum planning, virtual tutoring, classroom management, student support, and especially in assessment through smart evaluation systems.
Intelligence tests help gauge students' cognitive abilities. When powered by AI, these assessments can adapt in real time, offering a more personalized evaluation of learning potential.
Key Aspects of Course
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