Thresholds, Text Coverage, Vocabulary Size, and Reading Comprehension in Applied Linguistics
Thresholds, Text Coverage, Vocabulary Size, and Reading Comprehension in Applied Linguistics
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应用语言学中的阈值、文本覆盖范围、词汇量和阅读理解
DOI：
10.26686/wgtn.17057906
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发表时间：
2017
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影响因子：
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通讯作者：
Myq Larson
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作者：
Myq Larson
词汇知识与阅读理解之间的必然联系是毋庸置疑的。然而，关于互动的性质仍有问题。一个尚未解决的问题是，是否存在最佳的文本覆盖率，或者文本中已知词与未知词的比率，使得未知词对阅读理解的任何有害影响最小化。与此相关的一个问题是，读者需要多大的词汇量才能达到最佳的文本覆盖率。首先，进行了一项关键研究（Hu & Nation，2000）1的复制和扩展。在这项研究中，98%的文本覆盖率被认为是最佳的充分阅读理解短篇小说文本时，阅读的乐趣。为了重复这项研究，从泰国北方一所大学的一组更同质的参与者（n = 138）中收集了阅读理解的等效措施，在更严格的条件下，随机分配到三个文本覆盖条件之一，以验证结果的普遍性。最初的研究还通过测量被认为有助于阅读理解的读者特征，如词汇量，l1和l2读写能力，以及阅读态度来扩展，以努力提高可解释的阅读理解方差。为了更准确地计算读者对特定文本的文本覆盖率，必须尽可能精确地知道文本的词汇简档和读者的词汇量。因此，为了解决词汇量的问题，对VST（P. Nation & Beglar，2007）进行了诸如测量项目完成时间和改变项目呈现顺序等更改，以提高其灵敏度和准确性。这可能最终导致使用文本覆盖率预测阅读comprehensions.Finally，l2英语词汇量的规范建立，以补充VST的诊断有用性时，增加精度。数据收集通过一个在线版本的VST创建本论文从主要是自我选择的参与者（n 1：31 105）位于世界各地的国家（n 100）代表几个l1和年龄groups.Analysis收集的数据为本论文表明，文本覆盖率解释的阅读理解的差异比以前报道的少得多，而词汇量可能是一个更强大的预测。Hu和Nation（2000）的一项内部复制研究发现，在计算最佳文本覆盖率和报告的阅读理解效果大小方面存在错误。对阅读理解的文本覆盖模型的理论基础进行了批判性的回顾，发现其在结构操作和研究设计上存在严重缺陷。由于这些缺陷，大多数研究声称测量文本覆盖对阅读理解的影响，实际上测量了一个中介变量的影响：读者的词汇量。词汇量标准来自于通过VST在线版本收集的数据，似乎是可靠的和有代表性的。不同的项目呈现顺序似乎增加了测试的敏感性。尽管对l1英语使用者有中等程度的影响，但项目完成时间似乎并不能解释l2英语学习者词汇量得分的任何差异。基于词汇量可以解释阅读理解和文本覆盖的发现，文本覆盖预测阅读理解的假定能力受到了挑战。然而，另一种可以提供更大的预测阅读理解能力的方法，VST，已经被修改并在网上提供。此版本的VST可能比离线纸质版本提供更高的灵敏度和易用性。
The inextricable link between vocabulary knowledge and reading comprehension is incontrovertible. However, questions remain regarding the nature of the interaction. One question which remains unresolved is whether there is an optimum text coverage, or ratio of known to unknown words in a text, such that any deleterious effects of the unknown words on reading comprehension are minimised. A related question is what vocabulary size would a reader need to have in order to achieve the optimum text coverage for a given text or class of texts. This thesis addresses these questions in three ways. First, a replication and expansion of a key study (Hu & Nation, 2000)1 was performed. In that study, 98% text coverage was found to be optimal for adequate reading comprehension of short fiction texts when reading for pleasure. To replicate that study, equivalent measures of reading comprehension were collected from a more homogeneous group of participants at a university in northern Thailand (n = 138), under stricter conditions and random assignment to one of three text coverage conditions, to verify the generalisability of the results. The original study was also expanded by measuring reader characteristics thought to contribute to reading comprehension, such as vocabulary size, l1 and l2 literacy, and reading attitudes, in an effort to improve the explainable reading comprehension variance. In order to more accurately calculate the text coverage a reader experiences for a particular text, both the vocabulary profile of the text and the vocabulary size of the reader must be known as precisely as possible. Therefore, to contribute to the question of vocabulary size, changes such as measuring item completion time and varying the order of item presentation were made to the VST (P. Nation & Beglar, 2007) to improve its sensitivity and accuracy. This may ultimately lead to increased precision when using text coverage to predict reading comprehension. Finally, l2 English vocabulary size norms were established to supplement the diagnostic usefulness of the VST. Data were collected through an online version of the VST created for this thesis from primarily self-selected participants (n 1:31 105) located in countries (n 100) around the world representing several l1 and age groups. Analysis of the data collected for this thesis suggest that text coverage explains much less reading comprehension variance than previously reported while vocabulary size may be a more powerful predictor. An internal replication of Hu and Nation (2000) found errors in the calculation of optimum text coverage and in the reported size of the effect on reading comprehension. A critical review of the theoretical foundations of the text coverage model of reading comprehension found serious flaws in construct operationalisation and research design. Due to these flaws, most research which has purported to measure the effect of text coverage on reading comprehension actually measured the effect of an intervening variable: readers’ vocabulary size. Vocabulary size norms derived from data collected through an online version of the VST appear to be reliable and representative. Varying item presentation order appears to increase test sensitivity. Despite a moderate effect for l1 English users, item completion time does not seem to account for any variance in vocabulary size scores for l2 English learners. Based on the finding that vocabulary size may explain both reading comprehension and text coverage, the putative power of text coverage to predict reading comprehension is challenged. However, an alternative measure which may offer greater power to predict reading comprehension, the VST, has been modified and made available online. This version of the VST may provide greater sensitivity and ease of use than the offline, paper-based version.