Department of Psychology, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
Department of Psychology, California State University, Los Angeles, Los Angeles, CA, 90032, USA.
Behav Res Methods. 2024 Oct;56(7):7849-7871. doi: 10.3758/s13428-024-02458-5. Epub 2024 Aug 2.
This paper introduces A Library for Innovative Category Exemplars (ALICE) database, a resource that enhances research efficiency in cognitive and developmental studies by providing printable 3D objects representing 30 novel categories. Our research consists of three experiments to validate the novelty and complexity of the objects in ALICE. Experiment 1 assessed the novelty of objects through adult participants' subjective familiarity ratings and agreement on object naming and descriptions. The results confirm the general novelty of the objects. Experiment 2 employed multidimensional scaling (MDS) to analyze perceived similarities between objects, revealing a three-dimensional structure based solely on shape, indicative of their complexity. Experiment 3 used two clustering techniques to categorize objects: k-means clustering for creating nonoverlapping global categories, and hierarchical clustering for allowing global categories that overlap and have a hierarchical structure. Through stability tests, we verified the robustness of each clustering method and observed a moderate to good consensus between them, affirming the strength of our dual approach in effectively and accurately delineating meaningful object categories. By offering easy access to customizable novel stimuli, ALICE provides a practical solution to the challenges of creating novel physical objects for experimental purposes.
本文介绍了创新类别范例库（ALICE）数据库，这是一个资源库，通过提供 30 个新颖类别的可打印 3D 对象，提高了认知和发展研究的效率。我们的研究包括三个实验来验证 ALICE 中对象的新颖性和复杂性。实验 1 通过成年参与者对物体主观熟悉度的评价以及对物体命名和描述的一致性，评估了物体的新颖性。结果证实了物体的总体新颖性。实验 2 使用多维尺度分析（MDS）来分析物体之间的感知相似性，揭示了仅基于形状的三维结构，表明其复杂性。实验 3 使用两种聚类技术对物体进行分类：k-均值聚类用于创建不重叠的全局类别，层次聚类用于允许全局类别重叠并有层次结构。通过稳定性测试，我们验证了每种聚类方法的稳健性，并观察到它们之间存在中等至良好的一致性，这证实了我们在有效和准确划定有意义的物体类别方面的双重方法的有效性。通过提供易于访问的可定制新颖刺激，ALICE 为实验目的创建新颖物理对象提供了一种实用的解决方案。
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