Scientific visualization (SciVis) has become an essential means for exploring, understanding, and communicating complex scientific phenomena. However, the field still lacks a validated instrument assessing how well people read, understand, and interpret them. We present a scientific visualization literacy assessment test (SVLAT) that measures the general public's SciVis literacy. Covering a range of visualization forms and interpretation demands, SVLAT comprises 49 items grounded in 18 scientific visualizations and illustrations spanning eight visualization techniques and 11 tasks. Instrument development followed a staged, psychometrically grounded pipeline. We defined the construct and blueprint, followed by item generation, and expert review with five SciVis experts using the content validity ratio (mean CVR = 0.79). We subsequently administered a pilot test (30 participants) and a large-scale test tryout (485 participants) to evaluate the instrument's psychometric properties. For validation, we performed item analysis and refinement using both classical test theory (CTT) and item response theory (IRT) to examine item functioning and overall test quality. SVLAT demonstrates high reliability in the tryout sample (McDonald's omega_t = 0.82, Cronbach's alpha = 0.81). The assessment materials are available at https://osf.io/hr3nw/.

翻译：科学可视化已成为探索、理解与传播复杂科学现象的重要手段。然而，该领域仍缺乏经过验证的标准化工具来评估人们阅读、理解及解读科学可视化内容的能力。本文提出一套科学可视化素养评估测试（SVLAT），用于衡量公众的科学可视化素养。该测试涵盖多种可视化形式与解读需求，包含49道题目，其内容基于18个科学可视化实例及插图，涉及8种可视化技术与11类任务。测试开发遵循分阶段的心理测量学框架：首先界定构念与蓝图，随后生成题目，并由五位科学可视化专家采用内容效度比（平均CVR=0.79）进行评审。接着开展试点测试（30名被试）和大规模测试（485名被试）以评估工具的心理测量学特性。为验证有效性，我们结合经典测试理论（CTT）与项目反应理论（IRT）进行题目分析与优化，检验题目功能及整体测试质量。SVLAT在试测样本中展现出高可靠性（McDonald's ωt=0.82，Cronbach's α=0.81）。评估材料见https://osf.io/hr3nw/。