Yumus Melike, Stuhr Christina, Meindl Marlene, Leuschner Haug, Jungmann Tanja
Department of Special Needs Education and Rehabilitation, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany.
Faculty of Philosophy, Institute for Sports Science, University of Rostock, Rostock, Germany.
Front Psychol. 2025 Apr 25;16:1522740. doi: 10.3389/fpsyg.2025.1522740. eCollection 2025.
Ample evidence indicates that assessing children's early literacy skills is crucial for later academic success. This assessment enables the provision of necessary support and materials while engaging them in the culture of print and books before school entry. However, relatively few assessment tools are available to identify early literacy skills, such as concepts of print, print awareness, phonological awareness, word awareness, alphabet knowledge, and early reading. The digital landscape presents new opportunities to enhance these assessments and provide enriching early literacy experiences. This study examines the psychometric properties of an adaptive assessment tool, EuLeApp©, focusing on its reliability and concurrent validity.
Data involved 307 German kindergarten children (M = 64 months old, range = 45-91). A Computerized Adaptive Testing (CAT) method, grounded in Item Response Theory (IRT), was employed to develop an adaptive digital tool for assessing early literacy competencies. We utilized an automatic item selection procedure based on item difficulty and discrimination parameters for the 183-item pool to ensure a precise and efficient assessment tailored to each child's ability level.
The 4-parameter Logistic (4PL) model was identified as the best-fitting model for adaptive assessment, providing the highest precision in estimating children's abilities within this framework.
The findings support the idea that the adaptive digital-based assessment tool EuLeApp© can be used to assess early literacy skills. It also provides a foundation for offering individualized and adaptable learning opportunities embedded in daily routines in daycare centers.
大量证据表明，评估儿童的早期读写能力对其日后的学业成功至关重要。这种评估能够在儿童入学前让他们接触印刷品和书籍文化的同时，提供必要的支持和材料。然而，用于识别早期读写能力（如印刷概念、印刷意识、语音意识、单词意识、字母知识和早期阅读）的评估工具相对较少。数字领域为加强这些评估并提供丰富的早期读写体验带来了新机遇。本研究考察了一种自适应评估工具EuLeApp©的心理测量特性，重点关注其信度和同时效度。
数据涉及307名德国幼儿园儿童（平均年龄M = 64个月，范围 = 45 - 91个月）。采用基于项目反应理论（IRT）的计算机自适应测试（CAT）方法，开发了一种用于评估早期读写能力的自适应数字工具。我们针对183个项目库，利用基于项目难度和区分度参数的自动项目选择程序，以确保根据每个孩子的能力水平进行精确而高效的评估。
四参数逻辑斯蒂（4PL）模型被确定为最适合自适应评估的模型，在此框架内对儿童能力的估计具有最高精度。
研究结果支持这样一种观点，即基于数字自适应的评估工具EuLeApp©可用于评估早期读写能力。它还为在日托中心的日常活动中提供个性化和适应性强的学习机会奠定了基础。
