hkdse-chinese-evaluation

Compute rank-based metrics and generate DOCX reports for HKDSE Chinese AI grading.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/AKCqhzdy/dse-subject-grading --skill hkdse-chinese-evaluation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hkdse-chinese-evaluation
Source: https://github.com/AKCqhzdy/dse-subject-grading/tree/main/skills/hkdse-chinese-evaluation
Command: npx skills add https://github.com/AKCqhzdy/dse-subject-grading --skill hkdse-chinese-evaluation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Evaluates HKDSE Chinese Language AI grading results for year 2025 against ground truth levels (1–5). Computes Spearman ρ, Kendall τ, exact/adjacent match rates, generates evaluation figures and DOCX reports for 10 students.

Core Features & Use Cases

  • Automates evaluation workflow aligning AI grades with ground truth levels for HKDSE Chinese.
  • Calculates rank-based metrics (Spearman ρ, Kendall τ) and per-student/class-level reports, plus visualization figures.
  • Produces DOCX evaluation reports for class-wide assessment and audit trails.

Quick Start

Set YEAR to the target year and run the evaluation workflow to process grading outputs and ground-truth mappings.

Frequently Asked Questions about hkdse-chinese-evaluation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I evaluate HKDSE Chinese AI grading against ground truth levels?▼

To evaluate HKDSE Chinese AI grading, compare AI predicted scores against ground-truth levels 1–5. The workflow computes Spearman ρ, Kendall τ, exact match rates, and adjacent match rates to quantify grading accuracy.

What metrics are used for HKDSE Chinese grading evaluation?▼

HKDSE Chinese grading evaluation uses rank-based metrics including Spearman ρ and Kendall τ. It also calculates exact match rates and adjacent match rates to measure alignment between AI predictions and ground-truth levels.

How to generate DOCX reports for HKDSE Chinese class-level evaluation?▼

Generate DOCX evaluation reports by running the workflow with the YEAR variable set to the target year. The system processes grading outputs and ground-truth mappings to produce per-student and class-level reports with visualization figures.

Can I use this evaluation workflow for a different year of HKDSE Chinese grading?▼

You can evaluate a different year of HKDSE Chinese grading by setting the YEAR variable to your target year. The workflow requires corresponding AI grading outputs and ground-truth level mappings for that specific year.

What data do I need to prepare for HKDSE Chinese AI grading evaluation?▼

You need AI grading prediction outputs and ground-truth level mappings ranging from 1 to 5. The evaluation workflow aligns these datasets to calculate rank-based metrics and generate per-student reports for 10 students.