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		<title>AI That Explains Itself: New Framework Reveals What Really Makes a Classroom Lesson Work</title>
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				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Borda count]]></category>
		<category><![CDATA[classroom teaching quality evaluation]]></category>
		<category><![CDATA[cross-modal attention fusion]]></category>
		<category><![CDATA[educational AI]]></category>
		<category><![CDATA[Explainable AI]]></category>
		<category><![CDATA[feature importance ranking]]></category>
		<category><![CDATA[Human-AI Collaboration]]></category>
		<category><![CDATA[LIME]]></category>
		<category><![CDATA[multimodal learning]]></category>
		<category><![CDATA[SHAP]]></category>
		<category><![CDATA[teacher professional development]]></category>
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					<description><![CDATA[A new multimodal AI framework ranks classroom features by importance with 88.6 percent prediction accuracy, identifying linguistic coherence, student engagement, and speech clarity as the top drivers of teaching quality.]]></description>
		
		
		
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