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        <identifier>oai:drops-oai.dagstuhl.de:27570</identifier>
        <datestamp>2026-09-10T05:38:43Z</datestamp>
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          <dc:title>Learning a Map Under Positive Emotions: How Self-Reported Arousal and Individual Differences Relate to Route and Survey Knowledge (Short Paper)</dc:title>
          <dc:creator>Muffato, Veronica</dc:creator>
          <dc:creator>Miola, Laura</dc:creator>
          <dc:creator>Pazzaglia, Francesca</dc:creator>
          <dc:creator>Meneghetti, Chiara</dc:creator>
          <dc:subject>map</dc:subject>
          <dc:subject>emotions</dc:subject>
          <dc:subject>arousal</dc:subject>
          <dc:subject>route knowledge</dc:subject>
          <dc:subject>survey knowledge</dc:subject>
          <dc:subject>spatial cognition</dc:subject>
          <dc:description>Digital map learning is a common everyday activity requiring the encoding of landmarks and their spatial relations, and may be related to individual differences. The present study investigated how individual positive emotional states differing in arousal (high vs. low) relate to route and survey knowledge after spatial learning from maps. A total of 156 participants (ongoing data collection) completed an online within-subject procedure including emotionally induced scenarios, map study, and recall tasks assessing route (landmark order) and survey (landmark location task) knowledge. Results showed no direct effect of arousal condition on performance; however, individual increases in arousal predicted lower route knowledge accuracy, while survey knowledge was unaffected. Importantly, trait positive affect positively predicted both route and survey performance. Age negatively predicted both, gender differences emerged only for survey knowledge, whereas spatial anxiety impaired route knowledge. These findings suggest a selective role of arousal in route processing and highlight the importance of considering individual differences in spatial learning from maps.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Veronica Muffato and Laura Miola and Francesca Pazzaglia and Chiara Meneghetti</dc:contributor>
          <dc:date>2026</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 393, 17th International Conference on Spatial Information Theory (COSIT 2026)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.COSIT.2026.26</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-275701</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2026.26</dc:identifier>
          <dc:language>eng</dc:language>
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