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        <identifier>oai:figshare.com:article/33904064</identifier>
        <datestamp>2026-09-17T17:30:57Z</datestamp>
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        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>&lt;p&gt;Descriptive statistics.&lt;/p&gt;</dc:title>
          <dc:creator>Qiusu Wang (12334529)</dc:creator>
          <dc:subject>Environmental Sciences not elsewhere classified</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>Developmental Biology</dc:subject>
          <dc:subject>Cancer</dc:subject>
          <dc:subject>Science Policy</dc:subject>
          <dc:subject>using survey data</dc:subject>
          <dc:subject>teachers &amp;# 8217</dc:subject>
          <dc:subject>structural equation modeling</dc:subject>
          <dc:subject>reshaping higher education</dc:subject>
          <dc:subject>615 university teachers</dc:subject>
          <dc:subject>technology acceptance model</dc:subject>
          <dc:subject>significant direct association</dc:subject>
          <dc:subject>continue using genai</dc:subject>
          <dc:subject>based beliefs within</dc:subject>
          <dc:subject>different competency dimensions</dc:subject>
          <dc:subject>perceived genai competency</dc:subject>
          <dc:subject>whereas peou showed</dc:subject>
          <dc:subject>understanding continuance intention</dc:subject>
          <dc:subject>based beliefs</dc:subject>
          <dc:subject>different dimensions</dc:subject>
          <dc:subject>perceived ease</dc:subject>
          <dc:subject>robust association</dc:subject>
          <dc:subject>results showed</dc:subject>
          <dc:subject>proposed model</dc:subject>
          <dc:subject>continuance intention</dc:subject>
          <dc:subject>study examines</dc:subject>
          <dc:subject>professional practices</dc:subject>
          <dc:subject>professional engagement</dc:subject>
          <dc:subject>increasingly important</dc:subject>
          <dc:subject>homogeneous capability</dc:subject>
          <dc:subject>genai usefulness</dc:subject>
          <dc:subject>findings suggest</dc:subject>
          <dc:subject>findings highlight</dc:subject>
          <dc:subject>different tam</dc:subject>
          <dc:description>&lt;div&gt;&lt;p&gt;Generative artificial intelligence (GenAI) is reshaping higher education, and understanding teachers’ intention to continue using GenAI is increasingly important in this context. Grounded in the technology acceptance model (TAM), this study examines how different dimensions of teachers’ perceived GenAI competency are associated with perceived ease of use (PEOU), perceived usefulness (PU), and GenAI use continuance intention (GenAI-UCI). Using survey data from 615 university teachers in Qingdao, China, structural equation modeling was employed to examine the hypothesized relationships among perceived GenAI competency dimensions, TAM-based beliefs, and continuance intention. Results showed that perceived GenAI competency dimensions related to teaching, research, and professional engagement were positively associated with PU, whereas perceived basic understanding showed a small and non-robust association with PEOU. PU was positively associated with GenAI-UCI, whereas PEOU showed no significant direct association with GenAI-UCI. Overall, the findings suggest that perceived GenAI competency is not a homogeneous capability; rather, different competency dimensions were associated with different TAM-based beliefs within the proposed model. The findings highlight the importance of teachers’ perceptions of GenAI usefulness in their professional practices for understanding continuance intention in higher education.&lt;/p&gt;&lt;/div&gt;</dc:description>
          <dc:date>2026-09-17T17:30:49Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.1371/journal.pone.0358596.t003</dc:identifier>
          <dc:relation>https://figshare.com/articles/dataset/_p_Descriptive_statistics_p_/33904064</dc:relation>
          <dc:rights>CC BY 4.0</dc:rights>
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