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	<title>KDD Cup 2015 &#8211; BIOENGINEER.ORG</title>
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		<title>Hybrid AI spots MOOC students at risk of dropping out within days</title>
		<link>https://bioengineer.org/hybrid-ai-spots-mooc-students-at-risk-of-dropping-out-within-days/</link>
		
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		<pubDate>Sun, 18 Oct 2026 05:18:49 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[balancing]]></category>
		<category><![CDATA[BiLSTM]]></category>
		<category><![CDATA[CNN]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[detection]]></category>
		<category><![CDATA[early]]></category>
		<category><![CDATA[early warning systems]]></category>
		<category><![CDATA[Educational Technology]]></category>
		<category><![CDATA[KDD Cup 2015]]></category>
		<category><![CDATA[MOOC dropout prediction]]></category>
		<category><![CDATA[performance]]></category>
		<category><![CDATA[time series analysis]]></category>
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					<description><![CDATA[A hybrid deep learning model combining CNN and bidirectional LSTM networks can identify MOOC students at risk of dropping out with 93.11 percent accuracy from just one day of interaction data, and reaches 95.34 percent accuracy using an average of 19.24 days, cutting the required observation period by 35.9 percent.]]></description>
		
		
		
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