AI in Assessment
Learn to use AI for Digital Assessment and Evaluation, ensuring fair, efficient, and meaningful feedback, including MCQ item writing and Learning Analytics.
Study Format
100% Online, Instructor Guided
Duration
8 Weeks
Category
Technology & AI
Tuition
PKR 10,000
MENTISERA Institute
AI in Assessment
Programme Specification and Weekly Outline
Course URL: /courses/ai-in-assessment
Category
Technology & AI
Duration
8 Weeks
Mode
Online
Tuition
PKR 10,000
Target Audience
Teachers, Assessment Coordinators, & Curriculum Developers
Prerequisite
Basic understanding of assessment principles.
Overview
Learn to use AI for Digital Assessment and Evaluation, ensuring fair, efficient, and meaningful feedback, including MCQ item writing and Learning Analytics.
Learning Outcomes
- Leverage AI to automate grading and provide instant, targeted feedback.
- Design robust assessments that measure higher-order thinking in the AI era.
- Analyze student performance data to identify learning gaps and inform instruction.
- Understand and mitigate the ethical implications of using AI in student evaluation.
- Reduce administrative workload related to assessment and grading.
Weekly Outline
Week 1: Rethinking Assessment in the AI Era
Objectives
- Analyze the impact of generative AI on traditional assessment methods.
- Distinguish between assessing learning process vs. final product.
- Understand the ethical imperative for changing assessment practices.
Topics
- The End of the Traditional Essay?
- Academic Integrity in the Age of AI
- Process vs. Product: A New Assessment Paradigm
- Foundational Ethics of AI in Evaluation
Activity: Critique a traditional assessment task and identify its vulnerabilities to AI.
Week 2: Designing AI-Resilient Assessments
Objectives
- Design assessment tasks that require higher-order thinking skills.
- Incorporate in-class activities, oral presentations, and group work.
- Focus on unique, personalized prompts that require critical self-reflection.
Topics
- Higher-Order Thinking: Beyond Bloom's Taxonomy
- The Power of In-Class, Time-Bound Tasks
- Designing for Oral Defense and Presentation
- Crafting Prompts that Elicit Personal Voice and Experience
Activity: Redesign a traditional research paper assignment to be 'AI-resilient'.
Week 3: AI for Automated and Efficient Feedback
Objectives
- Evaluate various AI tools for providing instant formative feedback.
- Use AI to analyze writing for grammar, style, and structure.
- Develop strategies for teaching students to use AI feedback effectively.
Topics
- The Role of AI in Formative vs. Summative Feedback
- Grammar and Style Checkers on Steroids
- Tools for Analyzing Argument Structure and Cohesion
- Teaching Students to be Critical Consumers of AI Feedback
Activity: Use an AI tool to provide feedback on a sample piece of student writing and evaluate the quality of the feedback.
Week 4: Creating Rubrics and Grading with AI
Objectives
- Use AI to generate detailed, task-specific rubrics.
- Train AI tools to assist in applying rubrics to student work.
- Understand the limitations and biases of AI-assisted grading.
Topics
- AI as a Rubric Co-designer
- Fine-tuning AI for Consistent Grading Assistance
- The 'Human-in-the-Loop' Principle
- Bias and Fairness in Automated Scoring
Activity: Generate a rubric with an AI tool and then refine it based on pedagogical principles.
Week 5: Data Analysis and Performance Insights
Objectives
- Use AI to analyze class-wide assessment data to identify common misconceptions.
- Track individual student progress and identify at-risk learners.
- Generate reports and visualizations to share insights with stakeholders.
Topics
- From Grades to Insights: AI-Powered Learning Analytics
- Identifying Patterns in Student Performance
- Early-Warning Systems for Student Support
- Visualizing Data for Departmental and Parent Meetings
Activity: Analyze a sample dataset of student scores to identify a class-wide learning gap and propose an intervention.
Week 6: AI in Peer and Self-Assessment
Objectives
- Structure peer assessment activities that are scaffolded by AI.
- Guide students in using AI for self-assessment and goal setting.
- Facilitate reflective practices on the learning process.
Topics
- AI as a 'Third Reviewer' in Peer Feedback
- Tools for AI-Facilitated Self-Reflection
- Setting SMART Goals with an AI Coach
- Metacognition and Learning How to Learn
Activity: Design a peer review activity where students use an AI tool to help them provide structured feedback.
Week 7: Specialized Assessments: Portfolios and Performance Tasks
Objectives
- Explore how AI can assist in the creation and evaluation of digital portfolios.
- Design complex performance tasks that integrate AI tools.
- Assess collaborative projects and individual contributions.
Topics
- AI for Curating and Reflecting on Portfolio Artifacts
- Assessing Complex, Multi-Step Projects
- Evaluating Collaboration and Teamwork with AI-supported tools
- Simulations and Game-Based Assessment
Activity: Outline a capstone project that requires students to use AI as a tool and submit a portfolio of their process.
Week 8: Developing a Future-Ready Assessment Strategy
Objectives
- Synthesize course learnings into a coherent assessment philosophy.
- Develop an institutional policy on the use of AI in assessment.
- Create a plan for professional development to support colleagues.
Topics
- Crafting Your Personal Assessment Philosophy
- Drafting an Institutional AI & Academic Integrity Policy
- Leading Assessment Change in Your Organization
- The Future of Assessment: Credentials, Badges, and Lifelong Learning
Activity: Present a comprehensive plan for transforming assessment practices at a departmental or institutional level.
This document is generated from the live MENTISERA course record and reflects administrator-managed programme content.
Next Steps
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About This Course
Programme Specification
Formal academic summary of the programme configuration.
- Programme
- AI in Assessment
- Category
- Technology & AI
- Duration
- 8 Weeks
- Mode
- Online
- Tuition
- PKR 10,000
- Target Audience
- Teachers, Assessment Coordinators, & Curriculum Developers
- Prerequisite
- Basic understanding of assessment principles.
Audience & Entry Requirements
Target Audience: Teachers, Assessment Coordinators, & Curriculum Developers
Focus Area: Assessment & AI
Prerequisite: Basic understanding of assessment principles.
Fee & Completion
Programme Fee: PKR 10,000
Key Learning Outcomes
- Leverage AI to automate grading and provide instant, targeted feedback.
- Design robust assessments that measure higher-order thinking in the AI era.
- Analyze student performance data to identify learning gaps and inform instruction.
- Understand and mitigate the ethical implications of using AI in student evaluation.
- Reduce administrative workload related to assessment and grading.
Weekly Course Outline
Navigate week by week to understand objectives, topics, and applied learning activities.
Week 1: Rethinking Assessment in the AI Era
Practical outcomes, focus topics, and weekly application activity.
Learning Objectives
- Analyze the impact of generative AI on traditional assessment methods.
- Distinguish between assessing learning process vs. final product.
- Understand the ethical imperative for changing assessment practices.
Key Topics
- The End of the Traditional Essay?
- Academic Integrity in the Age of AI
- Process vs. Product: A New Assessment Paradigm
- Foundational Ethics of AI in Evaluation
Practice Focus
Critique a traditional assessment task and identify its vulnerabilities to AI.
Thematic Course Structure
This chart provides a visual breakdown of the program's core themes.
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