Explainable_Scoring/usage.html at main · DataScience-ArtificialIntelligence/Explainable_Scoring · GitHub

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<!DOCTYPE html>
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    <title>Usage Guide — How to use ExplainGrade</title>
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        <span class="badge">Usage Guide</span>
        <h1 class="hero-title">How to Use ExplainGrade</h1>
        <p class="hero-subtitle">Two ways to use the system: Directly in your browser or locally for high-accuracy
            workloads.</p>

        <div style="display: grid; grid-template-columns: 1fr 1fr; gap: 4rem; margin-top: 4rem;">
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                <h3 class="mb-4">🌐 Option 1: Browser-Based</h3>
                <p style="color: var(--text-dim); margin-bottom: 2rem;">No setup required. Perfect for grading
                    individual answers or small batches offline. Zero data leaves your computer.</p>

                <div style="display: grid; gap: 1.5rem;">
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                        <h4 style="margin-bottom: 0.5rem;"><span class="text-primary">01</span> Live Demo</h4>
                        <p style="font-size: 0.88rem; color: var(--text-muted);">Paste a reference and student answer.
                            Get scores instantly with XAI dashboard.</p>
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                    <div class="glass-card" style="padding: 1.5rem;">
                        <h4 style="margin-bottom: 0.5rem;"><span class="text-primary">02</span> Batch CSV</h4>
                        <p style="font-size: 0.88rem; color: var(--text-muted);">Upload a CSV file for multi-row grading
                            without any manual effort.</p>
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                        <h4 style="margin-bottom: 0.5rem;"><span class="text-primary">03</span> Class Eval (XLSX)</h4>
                        <p style="font-size: 0.88rem; color: var(--text-muted);">Grade student summaries vs a teacher's
                            script. Requires .docx for transcript and .xlsx for student summaries.</p>
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                <h3 class="mb-4">🖥️ Option 2: Local Runner</h3>
                <p style="color: var(--text-dim); margin-bottom: 1.5rem;">Uses a high-performance
                    **sentence-transformers** model (`all-MiniLM-L6-v2`) for better semantic accuracy than browser-based
                    proxies.</p>

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                    <p style="color: var(--text-muted);"># Clone and setup</p>
                    <span style="color: var(--accent2);">git clone</span> repo_url<br>
                    <span style="color: var(--accent2);">cd</span> repo_folder<br>
                    <span style="color: var(--accent2);">pip install</span> -r requirements.txt<br><br>

                    <p style="color: var(--text-muted);"># Run the grader</p>
                    <span style="color: var(--accent2);">python</span> local_grader.py \<br>
                    &nbsp;&nbsp;--docx transcript.docx \<br>
                    &nbsp;&nbsp;--xlsx summaries.xlsx \<br>
                    &nbsp;&nbsp;--max-score 10
                </div>

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                    <h4 style="margin-bottom: 1rem;">Expected Column Headers</h4>
                    <p style="font-size: 0.85rem; color: var(--text-dim);">The .xlsx file should contain these headers
                        (or similar):</p>
                    <div style="display: flex; gap: 0.5rem; margin-top: 1rem;">
                        <span class="badge" style="margin:0;">emailAddress</span>
                        <span class="badge" style="margin:0;">name</span>
                        <span class="badge" style="margin:0;">summary</span>
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