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			<titleStmt><title level='a'>Spatial Exploration Behavior in XR Learning: Toward Passive Assessment of Embodied Engagement</title></titleStmt>
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				<publisher>IEEE</publisher>
				<date>03/21/2026</date>
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				<bibl> 
					<idno type="par_id">10688221</idno>
					<idno type="doi">10.1109/VRW70859.2026.00051</idno>
					
					<author>Yiyin Gu</author><author>Yiqun Zhang</author><author>Miguel A Feijoo-Garcia</author><author>Alejandra J Magana</author><author>Bedrich Benes</author><author>Voicu Popescu</author>
				</bibl>
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			<abstract><ab><![CDATA[Not AvailableExtended Reality (XR) learning environments generate rich behavioral data through embodied interaction—head movements, gazepatterns, and spatial navigation—that could enable passive assessment without interrupting the learning experience. We investigatespatial exploration behavior in ACHIEVE, an XR environment forneural network visualization learning. In a between-subjects study(N = 56), XR participants exhibited significantly different spatialbehavior than desktop users: over 14 times greater pointer movement (M = 132.5 m vs. M = 9.5 m), extensive head rotation(M = 9,818◦), and M = 22.5 m of head translation during the learning session. We visualize individual exploration patterns throughhead and pointer trajectory traces, revealing substantial variation inhow learners navigate the 3D content. These spatial metrics, automatically captured during learning, represent a promising avenuefor passive assessment of embodied engagement—enabling educators to identify struggling learners, provide personalized feedback,and adapt content delivery without intrusive testing. Full learningoutcomes and user experience metrics are reported in companionpublications; here we focus on spatial behavior as a novel contribution toward spatialized learning analytics in education]]></ab></abstract>
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