Pickren Sage E, Stacy Maria, Del Tufo Stephanie N, Spencer Mercedes, Cutting Laurie E
Vanderbilt University, Nashville, Tennessee, USA.
Southern Illinois University, Carbondale, USA.
Read Res Q. 2022 Apr-Jun;57(2):649-667. doi: 10.1002/rrq.431. Epub 2021 Jun 28.
In the current study, we examined relations between text features (e.g., word concreteness, referential cohesion) and reading comprehension using multilevel logistic models. The sample was 158 native English-speaking students between 8 years 8 months and 11 years 2 months of age with a wide range of reading ability. In line with the simple view of reading, decoding ability and language comprehension were associated with reading comprehension performance. Text characteristics, including indices of word frequency, number of pronouns, word concreteness, and deep cohesion, also predicted unique variance in reading comprehension performance over and above the simple view's components. Additionally, the emotional charge of text (i.e., lexical ratings of arousal) predicted reading comprehension beyond traditional person-level and text-based characteristics. These findings add to a small but growing body of evidence suggesting that it is important to consider emotional charge in addition to person-level and text-based characteristics to better understand reading comprehension performance.
在本研究中，我们使用多层逻辑模型检验了文本特征（如单词具体性、指代衔接）与阅读理解之间的关系。样本为158名以英语为母语的学生，年龄在8岁8个月至11岁2个月之间，阅读能力范围广泛。与阅读的简单观点一致，解码能力和语言理解与阅读理解表现相关。文本特征，包括词频指数、代词数量、单词具体性和深层衔接，也预测了阅读理解表现中超出简单观点组成部分的独特方差。此外，文本的情感负荷（即唤醒的词汇评级）预测了超越传统个体水平和基于文本特征的阅读理解。这些发现增加了一小部分但不断增长的证据，表明除了个体水平和基于文本的特征外，考虑情感负荷对于更好地理解阅读理解表现很重要。
