Hearing-impaired students learning new words from written context

1992 ◽  
Vol 13 (4) ◽  
pp. 409-431 ◽  
Author(s):  
Peter A. De Villiers ◽  
Sarah B. Pomerantz

AbstractNormally hearing students acquire most of their reading vocabulary from printed context, but little is known about this process in hearing-impaired students. Two studies, therefore, investigated hearing-impaired students' ability to derive lexical and syntactic information about unknown words embedded in short passages of text. The passages varied in their informativeness about the meaning of the unknown words. Ability to derive at least a partial meaning for a word in context was determined both by the type of context and the reading comprehension levels of the students. However, there was no relationship between reading comprehension scores and ability to determine the form class of the words in context. The results are related to the importance of integrating semantic information into a meaning schema for the passage in order to acquire new meanings for unknown words and to the local strategies adopted by poorer readers when attempting to answer comprehension questions. Implications for explaining, and trying to ameliorate, the well-documented vocabulary limitations of hearing-impaired students are discussed.

2018 ◽  
Vol 2 (1) ◽  
pp. 19-27
Author(s):  
Abdul Rahim Razalli ◽  
Renate Olga Thomas ◽  
Nordin Mamat ◽  
Noreha Yusuf

2020 ◽  
Vol 26 (2) ◽  
pp. 278-282
Author(s):  
Maria-Miruna Ciocoi-Pop

AbstractIn an ever-increasing competitive academic setting, university students are striving for proficiency in their skills of foreign languages. This paper aims to highlight the significance of reading comprehension for students of English as a second language. Reading comprehension is a cognitive process, in other words, reading a text means processing and decoding it. Reading proficiency is linked to numerous aspects, such as age, cognitive processes, abilities, knowledge of the foreign language, etc. It goes without saying that the experience of reading a text, be it literary or non-literary, is more enjoyable without the need to constantly look up unknown words. This brief study also tries to show whether there is a direct connection between finding contentment in reading and comprehending the texts itself. Since reading is a key-skill verified in all major language exams, it is crucial for the ESL class, and not only, to include reading comprehension processes. Like any other skill, reading comprehension can be trained, as long as it is perceived as a procedure which requires the student’s commitment. Reading comprehension is a mechanism of phrase and concept identification, as well as of decoding meanings. Thus, this paper tries to emphasize the implications of reading comprehension and of teaching reading comprehension methods in the overall linguistic knowledge of ESL learners.


2020 ◽  
Vol 44 (3) ◽  
Author(s):  
Scott Gardner

Words change. We use new words to describe old things, and we put new meanings on old words. Take “beddum and bolstrum” for example. For some of you that phrase might conjure up warm memories of spending the night at grandmother’s house after a day of frolicking with cousins in the meadow, and at bedtime hearing her call from the top of the staircase, “Beddum and bolstrum, kiddies!” . . . or it might not. In fact, beddum ond bolstrum (bedding materials) is made up of old Anglo-Saxon words that haven’t been used much since the late 1000s. Whatever grandma was shouting down the stairs, you must have heard it wrong.


Author(s):  
Sheng Zhang ◽  
Qi Luo ◽  
Yukun Feng ◽  
Ke Ding ◽  
Daniela Gifu ◽  
...  

Background: As a known key phrase extraction algorithm, TextRank is an analogue of PageRank algorithm, which relied heavily on the statistics of term frequency in the manner of co-occurrence analysis. Objective: The frequency-based characteristic made it a neck-bottle for performance enhancement, and various improved TextRank algorithms were proposed in the recent years. Most of improvements incorporated semantic information into key phrase extraction algorithm and achieved improvement. Method: In this research, taking both syntactic and semantic information into consideration, we integrated syntactic tree algorithm and word embedding and put forward an algorithm of Word Embedding and Syntactic Information Algorithm (WESIA), which improved the accuracy of the TextRank algorithm. Results: By applying our method on a self-made test set and a public test set, the result implied that the proposed unsupervised key phrase extraction algorithm outperformed the other algorithms to some extent.


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