Effects of Textual Enhancement and Explicit Instruction on Grammar Learning and Reading Comprehension : Comparison of Differences according to Learners’ Level of Prior Knowledge of a Target Form

2016 ◽  
Vol 79 ◽  
pp. 355
Author(s):  
Yunkyoung Cho
2020 ◽  
Author(s):  
Kshema Jose

<p>This study observed how two hypertext features – absence of a linear or author-specified order and availability of multiple reading aids – influence reading comprehension processes of ESL readers. Studies with native or highly proficient users of English, have suggested that readers reading hypertexts comprehend better than readers reading print texts. This was attributed to (i) presence of hyperlinks that provide access to additional information that can potentially help overcome comprehension obstacles and (ii) the absence of an author-imposed reading order that helps readers exercise cognitive flexibility. An aspect that remains largely un-researched is how well readers with low language competence comprehend hypertexts. This research sought to initiate research in the area by exploring the question: Do all ESL readers comprehend a hypertext better than a print text?</p> <p>Keeping in mind the fact that a majority of readers reading online texts in English can be hindered by three types of comprehension deficits – low levels of language proficiency, non-availability of prior knowledge, or both – this study investigated how two characteristic features of hypertext, viz., linking to additional information and non-linearity in presentation of information, affect reading comprehension of ESL readers. </p> <p>Two types of texts that occur in the electronic medium – linear or pre-structured texts and non-linear or self-navigating texts, were used in this study. Based on a comparison of subjects’ comprehension outcomes and free recalls, text factors and reader factors that can influence hypertext reading comprehension of ESL readers are identified. </p> Contradictory to what many researchers believe, results indicate that self-navigating hypertexts might not promote deep comprehension in all ESL readers.


2020 ◽  
Vol 8 ◽  
pp. 141-155
Author(s):  
Kai Sun ◽  
Dian Yu ◽  
Dong Yu ◽  
Claire Cardie

Machine reading comprehension tasks require a machine reader to answer questions relevant to the given document. In this paper, we present the first free-form multiple-Choice Chinese machine reading Comprehension dataset (C3), containing 13,369 documents (dialogues or more formally written mixed-genre texts) and their associated 19,577 multiple-choice free-form questions collected from Chinese-as-a-second-language examinations. We present a comprehensive analysis of the prior knowledge (i.e., linguistic, domain-specific, and general world knowledge) needed for these real-world problems. We implement rule-based and popular neural methods and find that there is still a significant performance gap between the best performing model (68.5%) and human readers (96.0%), especiallyon problems that require prior knowledge. We further study the effects of distractor plausibility and data augmentation based on translated relevant datasets for English on model performance. We expect C3 to present great challenges to existing systems as answering 86.8% of questions requires both knowledge within and beyond the accompanying document, and we hope that C3 can serve as a platform to study how to leverage various kinds of prior knowledge to better understand a given written or orally oriented text. C3 is available at https://dataset.org/c3/ .


1985 ◽  
Vol 20 (4) ◽  
pp. 497 ◽  
Author(s):  
R. Scott Baldwin ◽  
Ziva Peleg-Bruckner ◽  
Ann H. McClintock

2017 ◽  
Vol 55 (7) ◽  
pp. 1022-1048 ◽  
Author(s):  
Kausalai (Kay) Wijekumar ◽  
Bonnie J. F. Meyer ◽  
Puiwa Lei ◽  
Weiyi Cheng ◽  
Xuejun Ji ◽  
...  

Reading and comprehending content area texts require learners to effectively select and encode with hierarchically strategic memory structures in order to combine new information with prior knowledge. Unfortunately, evidence from state and national tests shows that children fail to successfully navigate the reading comprehension challenges they face. Schools have struggled to find approaches that can help children succeed in this important task. Typical instruction in classrooms across the country has focused on procedural application of strategies or content-focused approaches that encourage rich discussions. Both approaches have achieved success but have limitations-related transparency and specificity of scaffolds and guidance for the teacher and learner in today’s diverse and complex classroom settings. The text structure strategy combines content and strategy to provide pragmatic, transparent, and scaffolded instruction addressing these challenges. A web-based intelligent tutoring system for the text structure strategy, named ITSS, was designed and developed to provide consistent and high-quality instruction to learners in Grades 4 and 5 about how to read, select main ideas, encode strategic memory structures, make inferences, and monitor comprehension during reading. In this article, we synthesize results from two recent large-scale randomized controlled studies to showcase how the ITSS supports selection and encoding of students’ strategic memory structures and how prior knowledge affects the memory structures. We provide greater depth of information about such processing than examined and reported in extant literature about overall increases in reading comprehension resulting from students using ITSS.


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