Search results for: reading method classification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20558

Search results for: reading method classification

20468 Moving from Practice to Theory

Authors: Maria Lina Garrido

Abstract:

This paper aims to reflect upon instruction in English classes with the specific purpose of reading comprehension development, having as its paradigm the considerations presented by William Grabe, in his book Reading in a Second Language: Moving from theory to practice. His concerns regarding the connection between research findings and instructional practices have stimulated the present author to re-evaluate both her long practice as an English reading teacher and as the author of two reading textbooks for graduate students. Elements of the reading process such as linguistic issues, prior knowledge, reading strategies, critical evaluation, and motivation are the main foci of this analysis as far as the activities developed in the classroom are concerned. The experience with university candidates on postgraduate courses with different levels of English knowledge in Bahia, Brazil, has definitely demanded certain adjustments to this author`s classroom setting. Word recognition based on cognates, for example, has been emphasized given the fact that academic texts use many Latin words which have the same roots as the Brazilian Portuguese lexicon. Concerning syntactic parsing, the tenses/verbal aspects, modality and linking words are included in the curriculum, but not with the same depth as the general English curricula. Reading strategies, another essential predictor for developing reading skills, have been largely stimulated in L2 classes in order to compensate for a lack of the appropriate knowledge of the foreign language. This paper presents results that demonstrate that this author`s teaching practice is compatible with the implications and instruction concerning the reading process outlined by Grabe, however, it admits that each class demands specific instructions to meet the needs of that particular group.

Keywords: classroom practice, instructional activities, reading comprehension, reading skills

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20467 The Impact of an Interactive E-Book on Mathematics Reading and Spatial Ability in Middle School Students

Authors: Abebayehu Yohannes, Hsiu-Ling Chen, Chiu-Chen Chang

Abstract:

Mathematics reading and spatial ability are important learning components in mathematics education. However, many students struggle to understand real-world problems and lack the spatial ability to form internal imagery. To cope with this problem, in this study, an interactive e-book was developed. The result indicated that both groups had a significant increase in the mathematics reading ability test, and a significant difference was observed in the overall mathematics reading score in favor of the experimental group. In addition, the interactive e-book learning mode had significant impacts on students’ spatial ability. It was also found that the richness of content with visual and interactive elements provided in the interactive e-book enhanced students’ satisfaction with the teaching material.

Keywords: interactive e-books, spatial ability, mathematics reading, satisfaction, three view

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20466 Instruction High-Leverage Practices in Reading Instruction for Adolescents

Authors: Nicole Pyle, Daniel Pyle, Christa Haring, Marty Hougen

Abstract:

Effective special education teachers utilize evidence-based practices for adolescent reading instruction and target the skills needed to improve the reading of older struggling readers. High-Leverage Practices (HLPs) are critical to helping students with disabilities learn important content. Therefore, special education teachers are encouraged to implement HLPs to maximize the learning of students with disabilities, including students with reading difficulties. Teachers’ implementation of HLPs in reading comprehension instruction should aim to develop adolescents’ understanding of grade-level narrative texts and informational texts, including content area texts. Instruction High-Leverage Practices (11-22) that ensure effective implementation of evidence-based practice in reading comprehension instruction for adolescents are presented. Effective reading comprehension activities within the 12 Instruction HLPs are illustrated.

Keywords: high-leverage practices, adolescent, instructional activities, students with disabilities

Procedia PDF Downloads 51
20465 Classification of Construction Projects

Authors: M. Safa, A. Sabet, S. MacGillivray, M. Davidson, K. Kaczmarczyk, C. T. Haas, G. E. Gibson, D. Rayside

Abstract:

To address construction project requirements and specifications, scholars and practitioners need to establish a taxonomy according to a scheme that best fits their need. While existing characterization methods are continuously being improved, new ones are devised to cover project properties which have not been previously addressed. One such method, the Project Definition Rating Index (PDRI), has received limited consideration strictly as a classification scheme. Developed by the Construction Industry Institute (CII) in 1996, the PDRI has been refined over the last two decades as a method for evaluating a project's scope definition completeness during front-end planning (FEP). The main contribution of this study is a review of practical project classification methods, and a discussion of how PDRI can be used to classify projects based on their readiness in the FEP phase. The proposed model has been applied to 59 construction projects in Ontario, and the results are discussed.

Keywords: project classification, project definition rating index (PDRI), risk, project goals alignment

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20464 Class Size Effects on Reading Achievement in Europe: Evidence from Progress in International Reading Literacy Study

Authors: Ting Shen, Spyros Konstantopoulos

Abstract:

During the past three decades, class size effects have been a focal debate in education. The idea of having smaller class is enormously popular among parents, teachers and policy makers. The rationale of its popularity is that small classroom could provide a better learning environment in which there would be more teacher-pupil interaction and more individualized instruction. This early stage benefits would also have a long-term positive effect. It is a common belief that reducing class size may result in increases in student achievement. However, the empirical evidence about class-size effects from experimental or quasi-experimental studies has been mixed overall. This study sheds more light on whether class size reduction impacts reading achievement in eight European countries: Bulgaria, Germany, Hungary, Italy, Lithuania, Romania, Slovakia, and Slovenia. We examine class size effects on reading achievement using national probability samples of fourth graders. All eight European countries had participated in the Progress in International Reading Literacy Study (PIRLS) in 2001, 2006 and 2011. Methodologically, the quasi-experimental method of instrumental variables (IV) has been utilized to facilitate causal inference of class size effects. Overall, the results indicate that class size effects on reading achievement are not significant across countries and years. However, class size effects are evident in Romania where reducing class size increases reading achievement. In contrast, in Germany, increasing class size seems to increase reading achievement. In future work, it would be valuable to evaluate differential class size effects for minority or economically disadvantaged student groups or low- and high-achievers. Replication studies with different samples and in various settings would also be informative. Future research should continue examining class size effects in different age groups and countries using rich international databases.

Keywords: class size, reading achievement, instrumental variables, PIRLS

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20463 MhAGCN: Multi-Head Attention Graph Convolutional Network for Web Services Classification

Authors: Bing Li, Zhi Li, Yilong Yang

Abstract:

Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

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20462 An Investigation into Slow ESL Reading Speed in Pakistani Students

Authors: Hina Javed

Abstract:

This study investigated the different strategies used by Pakistani students learning English as a second language at secondary level school. The basic premise of the study is that ESL students face tremendous difficulty while they are reading a text in English. It also purports to dig into the different causes of their slow reading. They might range from word reading accuracy, mental translation, lexical density, cultural gaps, complex syntactic constructions, and back skipping. Sixty Grade 7 students from two secondary mainstream schools in Lahore were selected for the study, thirty being boys and thirty girls. They were administered reading-related and reading speed pre and post-tests. The purpose of the tests was to gauge their performance on different reading tasks so as to be able to see how they used strategies, if any, and also to ascertain the causes hampering their performance on those tests. In the pretests, they were given simple texts with considerable lexical density and moderately complex sentential layout. In the post-tests, the reading tasks contained comic strips, texts with visuals, texts with controlled vocabulary, and an evenly distributed varied range of simple, compound, and complex sentences. Both the tests were timed. The results gleaned through the data gathered corroborated the researchers’ basic hunch that they performed significantly better than pretests. The findings suggest that the morphological structure of words and lexical density are the main sources of reading comprehension difficulties in poor ESL readers. It is also confirmed that if the texts are accompanied by pictorial visuals, it greatly facilitates students’ reading speed and comprehension. There is no substantial evidence that ESL readers adopt any specific strategy while reading in English.

Keywords: slow ESL reading speed, mental translation, complex syntactic constructions, back skipping

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20461 Teaching Attentive Literature Reading in Higher Education French as a Foreign Language: A Pilot Study of a Flipped Classroom Teaching Model

Authors: Malin Isaksson

Abstract:

Teaching French as a foreign language usually implies teaching French literature, especially in higher education. Training university students in literary reading in a foreign language requires addressing several aspects at the same time: the (foreign) language, the poetic language, the aesthetic aspects of the studied works, and various interpretations of them. A pilot study sought to test a teaching model that would support students in learning to perform competent readings and short analyses of French literary works, in a rather independent manner. This shared practice paper describes the use of a flipped classroom method in two French literature courses, a campus course and an online course, and suggests that the teaching model may provide efficient tools for teaching literary reading and analysis in a foreign language. The teaching model builds on a high level of student activity and focuses on attentive reading, meta-perspectives such as theoretical concepts, individual analyses by students where said concepts are applied, and group discussions of the studied texts and of possible interpretations.

Keywords: attentive reading, flipped classroom, literature in foreign language studies, teaching literature analysis

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20460 Teaching Reading in English: The Neglect of Phonics in Nigeria

Authors: Abdulkabir Abdullahi

Abstract:

Nigeria has not yet welcomed phonics into its primary schools. In government-owned primary schools teachers are functionally ignorant of the stories of the reading wars amongst international scholars. There are few or no Nigerian-authored phonics textbooks, and there has been no government-owned phonics curriculum either. There are few or no academic journal articles on phonics in the country and there is, in fact, a certain danger of confusion between phonics and phonetics among Nigerian publishers, authors, writers and academics as if Nigerian teachers of English and the educational policy makers of the country were unaware of reading failures/problems amongst Nigerian children, or had never heard of phonics or read of the stories of the reading wars or the annual phonics test in the United Kingdom, the United States of America and other parts of the world. It is on this note that this article reviews and examines, in the style of a qualitative inquiry, the body of arguments on phonics, and explores the effectiveness of phonics teaching, particularly, in a second-language learning contexts. While the merit of the paper is, perhaps, situated in its supreme effort to draw global attention to reading failures/problems in Nigeria and the ways the situation may affect English language learning, international academic relations and the educational future of the country, it leaves any quantitative verification of its claims to interested quantitative researchers in the world.

Keywords: graphemes, phonics, reading, reading wars, reading theories, phonemic awareness

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20459 Comparative Analysis of Spectral Estimation Methods for Brain-Computer Interfaces

Authors: Rafik Djemili, Hocine Bourouba, M. C. Amara Korba

Abstract:

In this paper, we present a method in order to classify EEG signals for Brain-Computer Interfaces (BCI). EEG signals are first processed by means of spectral estimation methods to derive reliable features before classification step. Spectral estimation methods used are standard periodogram and the periodogram calculated by the Welch method; both methods are compared with Logarithm of Band Power (logBP) features. In the method proposed, we apply Linear Discriminant Analysis (LDA) followed by Support Vector Machine (SVM). Classification accuracy reached could be as high as 85%, which proves the effectiveness of classification of EEG signals based BCI using spectral methods.

Keywords: brain-computer interface, motor imagery, electroencephalogram, linear discriminant analysis, support vector machine

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20458 The Social Media, Reading Culture and Vocabulary Expansion: Three Universities from Northern Nigeria

Authors: Nasir Umar Abdullahi

Abstract:

The social media profoundly causes the reading culture to decline in Nigeria, where the English language is a second language (SL), a language of instruction (LI), as well as the target language (TL). This is because the university students have, over the years, failed to make extensive reading their closest companion, with much emphasis on reading the European novels, newspapers, magazines, etc., so as to learn language from its original or native speakers for linguistic competence. Instead, they squander the most part of their day and nocturnal hours, sending and receiving messages through social media. The end result is their vocabulary become stagnant or ebbs, and that they cannot acquire the Cox head’s 570 vocabulary, let alone the Nation’s 2000 vocabulary to use the language fluently in writing, reading, listening, and speaking and to further compete with the native speaker in varying degrees of language usages. Be that as it may, if the social media is a monster in worsening the decline in reading culture, which degenerates in the Northern part of the country in contradistinction to the Southern part, it boosts it as well, for aside the social media language, slangs, cliché, for instance, students improve their vocabulary power, and at the same time it allows the students to privately and leisurely put the language into use, by using practically some of the vocabulary they have acquired to chart, to comment, socialize to adjudge, etc. This is what this paper tries to explore in Umaru Musa Yar’adua University Al-qalam University and the Federal University Dutin-ma.

Keywords: social media, reading, vocabulary, universities

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20457 The Results of Reading Test on Movement Staff Notation System

Authors: Sonay Ödemiş

Abstract:

Movement Staff Notation System (MSNS) is a movement transcription, analyzing method, and it's been constantly improved since it was first developed in 2005. This method is based on human anatomy, is being used and applied in the lessons at The Department of Turkish Folk Dances in Istanbul Technical University, nowadays. In this research, it is aimed to discover, how MSNS can help to participants about learning the basic movements of lower extremity. This experiment has six volunteers who were randomly selected. Each volunteer has been graded for their dance backgrounds and all the volunteers have been studied for six weeks. Each week has included different topic and examples such as contacts on foot, jumps, timing, directions and basic symbols of MSNS. Examples have changed from easy to hard. On conclusion, 6 volunteer subjects were tested in final test. The tests were recorded with the camera. In this presentation, it will be explained and detailed the results of the reading test on MSNS. Some of important video records will be watched and interpreted after the test. As a conclusion, all the scores will be interpreted and assessed from different perspectives.

Keywords: dance notation, Turkish dances, reading test, Education

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20456 Review and Comparison of Associative Classification Data Mining Approaches

Authors: Suzan Wedyan

Abstract:

Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

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20455 Meta-Learning for Hierarchical Classification and Applications in Bioinformatics

Authors: Fabio Fabris, Alex A. Freitas

Abstract:

Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

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20454 Teachers’ and Students’ Reactions to a Guided Reading Program Designed by a Teachers’ Professional Learning Community

Authors: Yea-Mei Leou, Shiu-Hsung Huang, T. C. Shen, Chin-Ya Fang

Abstract:

The purposes of this study were to explore how to establish a professional learning community for English teachers at a junior high school, and to explore how teachers and students think about the guided reading program. The participants were three experienced English teachers and their ESL seventh-grade students from three classes in a junior high school. Leveled picture books and worksheets were used in the program. Questionnaires and interviews were used for gathering information. The findings were as follows: First, most students enjoyed this guided reading program. Second, the teachers thought the guided reading program was helpful to students’ learning and the discussions in the professional learning community refreshed their ideas, but the preparation for the teaching was time-consuming. Suggestions based on the findings were provided.

Keywords: ESL students, guided reading, leveled books, professional learning community

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20453 Developing Students’ Academic Writing Skills through Scientific Reading: Using Questions and Answer Activities

Authors: Makhim Artikova, Shavkat Duschanov

Abstract:

So far, there have been a plethora of attempts to improve learners’ academic writing skills. However, this issue remains to be a real concern among the majority of students, especially those who are standing on their academic life threshold. The purpose of this research is improving students’ academic writing skills through 'Questions and Answer Reading' activities. Using well-prepared and well-chosen reading materials (from textbooks, scientific journals, or magazines) and applying questions and answer activities in the classroom facilitate learners to become great critical readers. Furthermore, it boosts their writing skills, which are the most crucial part of students’ personal and academic developments. In this activity, the class is divided into small groups of four. Then, the instructor will give students whether one section of the text or full text asking them to read and to find unfamiliar words within the group. After discovering the meaning of unknown words, each group has to share their findings with the class. In the next stage of the activity, students should be asked to create questions in a group based on the given reading material. Follow by each group should ask the other groups their questions which are an excellent opportunity to challenge leads to improve critical thinking skills. In the last part, the students are asked to write the text or article summary, which is the activity core that pilots to the writing skills perfection. This engaging activity highlights the effectiveness of incorporating reading materials into the classroom when it comes to improving students’ composition writings. Structural writing after every reading activity resulted in improving students’ coherence and cohesion in writing well-organized essays. Having experimented with high school 9th and 11th-grade students, implementing reading activities into the classroom is proved to be a productive tool to enhance one’s academic writing skills. In the future, this method planning to be implemented among university students.

Keywords: academic writing, coherence and cohesion, questions and answer activities, scientific reading

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20452 A Study of Flipped Classroom’s Influence on Classroom Environment of College English Reading, Writing and Translating

Authors: Xian Xie, Qinghua Fang

Abstract:

This study used quantitative and qualitative methods to explore the characteristics of flipped classroom’s influence on classroom environment of college English reading, writing, and translating, and to summarize and reflect on the teaching characteristics of college English Reading, writing, and translating. The results of the study indicated that after the flipped classroom applied to reading, writing, and translating, students’ performance was improved to a certain extent, the classroom environment was improved to some extent, students of the flipped classroom are generally satisfied with the classroom environment; students showed a certain degree of individual differences to the degree of cooperation, participation, self-responsibility, task-orientation, and the teacher leadership and innovation. The study indicated that the implementation of flipped classroom teaching mode can optimize College English reading, writing, and translating classroom environment and realize target-learner as the center in foreign language teaching and learning, but bring a greater challenge to teachers.

Keywords: classroom environment, college English reading, writing and translating, individual differences, flipped classroom

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20451 A Hybrid Feature Selection and Deep Learning Algorithm for Cancer Disease Classification

Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

Abstract:

Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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20450 Students’ Attitudes towards Reading as a Determinant of Performance in O’ Level English in Oyo State Secondary Schools, Nigeria

Authors: Adebimpe Olubunmi Adebanjo

Abstract:

This study observed students’ attitudes towards reading as a determinant of performance in O’ Level English in Oyo state secondary schools. Random sampling technique was used to select two schools from each of the five geo-political zones of the state while stratified sampling technique was used to select twenty students from each of the ten schools. A researcher designed questionnaire was used to gather information on students’ attitudes while a prepared test based on O’ Level syllabus was stapled to each of the questionnaire to ascertain their level of achievement in O’ Level English. The Percentage, Mean, Standard Deviation, Chi-square and Pearson Contingency Coefficient were used to answer and test the research questions and hypotheses raised. The findings showed that the general attitude of students towards reading was ambivalent; the general level of achievement was also low. The findings also revealed that there was a significant difference in the attitudes of students to reading on the basis of gender and home background. Students from educated homes also had better attitudes towards reading than their counterparts from illiterate homes. The findings also showed that there was a significant relationship between students’ attitudes to reading and their performance in O’ Level English. Students with positive attitude to reading had better grades in O’ Level English than students with ambivalent and negative attitudes. Based on the findings, it was recommended that students should change their attitudes to reading; the school and the home were also advised to always encourage students to read.

Keywords: positive, ambivalent, negative attitudes, o' level English

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20449 Comparison of Various Classification Techniques Using WEKA for Colon Cancer Detection

Authors: Beema Akbar, Varun P. Gopi, V. Suresh Babu

Abstract:

Colon cancer causes the deaths of about half a million people every year. The common method of its detection is histopathological tissue analysis, it leads to tiredness and workload to the pathologist. A novel method is proposed that combines both structural and statistical pattern recognition used for the detection of colon cancer. This paper presents a comparison among the different classifiers such as Multilayer Perception (MLP), Sequential Minimal Optimization (SMO), Bayesian Logistic Regression (BLR) and k-star by using classification accuracy and error rate based on the percentage split method. The result shows that the best algorithm in WEKA is MLP classifier with an accuracy of 83.333% and kappa statistics is 0.625. The MLP classifier which has a lower error rate, will be preferred as more powerful classification capability.

Keywords: colon cancer, histopathological image, structural and statistical pattern recognition, multilayer perception

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20448 Effects of Computer-Mediated Dictionaries on Reading Comprehension and Vocabulary Acquisition

Authors: Mohamed Amin Mekheimer

Abstract:

This study aimed to investigate the effects of paper-based monolingual, pop-up and type-in electronic dictionaries on improving reading comprehension and incidental vocabulary acquisition and retention in an EFL context. It tapped into how computer-mediated dictionaries may have facilitated/impeded reading comprehension and vocabulary acquisition. Findings showed differential effects produced by the three treatments compared with the control group. Specifically, it revealed that the pop-up dictionary condition had the shortest average vocabulary searching time, vocabulary and text reading time, yet with less than the type-in dictionary group but more than the book dictionary group in terms of frequent dictionary 'look-ups' (p<.0001). In addition, ANOVA analyses also showed that text reading time differed significantly across all four treatments, and so did reading comprehension. Vocabulary acquisition was reported as enhanced in the three treatments rather than in the control group, but still with insignificant differences across the three treatments, yet with more differential effects in favour of the pop-up condition. Data also assert that participants preferred the pop-up e-dictionary more than the type-in and paper-based groups. Explanations of the findings vis-à-vis the cognitive load theory were presented. Pedagogical implications and suggestions for further research were forwarded at the end.

Keywords: computer-mediated dictionaries, type-in dictionaries, pop-up dictionaries, reading comprehension, vocabulary acquisition

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20447 A Study on the Performance of 2-PC-D Classification Model

Authors: Nurul Aini Abdul Wahab, Nor Syamim Halidin, Sayidatina Aisah Masnan, Nur Izzati Romli

Abstract:

There are many applications of principle component method for reducing the large set of variables in various fields. Fisher’s Discriminant function is also a popular tool for classification. In this research, the researcher focuses on studying the performance of Principle Component-Fisher’s Discriminant function in helping to classify rice kernels to their defined classes. The data were collected on the smells or odour of the rice kernel using odour-detection sensor, Cyranose. 32 variables were captured by this electronic nose (e-nose). The objective of this research is to measure how well a combination model, between principle component and linear discriminant, to be as a classification model. Principle component method was used to reduce all 32 variables to a smaller and manageable set of components. Then, the reduced components were used to develop the Fisher’s Discriminant function. In this research, there are 4 defined classes of rice kernel which are Aromatic, Brown, Ordinary and Others. Based on the output from principle component method, the 32 variables were reduced to only 2 components. Based on the output of classification table from the discriminant analysis, 40.76% from the total observations were correctly classified into their classes by the PC-Discriminant function. Indirectly, it gives an idea that the classification model developed has committed to more than 50% of misclassifying the observations. As a conclusion, the Fisher’s Discriminant function that was built on a 2-component from PCA (2-PC-D) is not satisfying to classify the rice kernels into its defined classes.

Keywords: classification model, discriminant function, principle component analysis, variable reduction

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20446 Classification of Red, Green and Blue Values from Face Images Using k-NN Classifier to Predict the Skin or Non-Skin

Authors: Kemal Polat

Abstract:

In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

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20445 Transitivity Analysis in Reading Passage of English Text Book for Senior High School

Authors: Elitaria Bestri Agustina Siregar, Boni Fasius Siregar

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The paper concerned with the transitivity in the reading passage of English textbook for Senior High School. The six types of process were occurred in the passages with percentage as follows: Material Process is 166 (42%), Relational Process is 155 (39%), Mental Process is 39 (10%), Verbal Process is 21 (5%), Existential Process is 13 (3), and Behavioral Process is 5 (1%). The material processes were found to be the most frequently used process type in the samples in our corpus (41,60 %). This indicates that the twenty reading passages are centrally concerned with action and events. Related to developmental psychology theory, this book fits the needs of students of this age.

Keywords: transitivity, types of processes, reading passages, developmental psycholoy

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20444 Using Eye-Tracking to Investigate TEM Validity and Design

Authors: Cao Xi

Abstract:

This paper reports a study which used eye-tracking to examine the cognitive validity of TEM 8(Test for English Majors, Band 8). The study investigated test takers' reading patterns on four -item types using eye-tracking, and interviews. Thirty participants completed 22 items on a computer, with the Tobii X2 Eye Tracker recording their eye movements on screen. Eleven students further participated in a recall interview while viewing video footage of their gaze patterns on the test. The findings will indicate that first, different reading item types will employ different cognitive processes; then different reading patterns for stronger and weaker test takers’on each item types. The implication of this study is to provide recommendations for the use of eye tracking technology in language research.

Keywords: eye tracking, reading patterns, test for english majors, cognitive validity

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20443 Hong Kong Chinese-Speaking Adolescents Diagnosed with Dyslexia: What Is and Is Not Improved?

Authors: Kevin Kien Hoa Chung

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The present study was to investigate cognitive-linguistic skills that might distinguish the improved dyslexics from the non-improved dyslexics. Twenty-eight improved dyslexics and 28 non-improved dyslexics were selected from a pool of 254 students diagnosed as dyslexics in Grade 1 to 2. These students were administered measures: morphological skills, visual-orthographic skills, rapid naming skills, working memory, reading comprehension, writing, word reading, word dictation, and one-minute word reading. Findings showed that the improved dyslexics performed better than the non-improved dyslexics in visual-orthographic skills, word reading, one-minute reading, writing, and reading comprehension. Furthermore, the improved dyslexics showed fewer cognitive-linguistic deficits compared with the non-improved dyslexics. Among the 4 cognitive-linguistic measures, morphological skills and visual-orthographic skills showed the greatest power in discriminating the improved and non-improved dyslexics. Results underscore the importance of cognitive-linguistic skills underlying the manifestations of the improved and non-improved dyslexia in Chinese adolescents.

Keywords: adolescents, chinese language, improved dyslexics, non-improved dyslexics

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20442 An Examination of Self-Mentions and Engagement Markers on the Academic IELTS Reading Exam

Authors: Hilda Freimuth

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This study examined the interactional resources of self-mentions and engagement markers in twenty official IELTS reading exam passages to determine the passages’ similarity to academic research papers. Although the findings revealed a variation ranging from zero to 22 instances for any given passage, the study found the average number of markers (5.5) per passage in line with those found on research papers. This finding confirms that the IELTS exam’s reading passages mirror the academic nature of research papers in this regard.

Keywords: IELTS exam, IELTS reading, interpersonal resources, self-mentions, engagement markers

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20441 The Appropriate Number of Test Items That a Classroom-Based Reading Assessment Should Include: A Generalizability Analysis

Authors: Jui-Teng Liao

Abstract:

The selected-response (SR) format has been commonly adopted to assess academic reading in both formal and informal testing (i.e., standardized assessment and classroom assessment) because of its strengths in content validity, construct validity, as well as scoring objectivity and efficiency. When developing a second language (L2) reading test, researchers indicate that the longer the test (e.g., more test items) is, the higher reliability and validity the test is likely to produce. However, previous studies have not provided specific guidelines regarding the optimal length of a test or the most suitable number of test items or reading passages. Additionally, reading tests often include different question types (e.g., factual, vocabulary, inferential) that require varying degrees of reading comprehension and cognitive processes. Therefore, it is important to investigate the impact of question types on the number of items in relation to the score reliability of L2 reading tests. Given the popularity of the SR question format and its impact on assessment results on teaching and learning, it is necessary to investigate the degree to which such a question format can reliably measure learners’ L2 reading comprehension. The present study, therefore, adopted the generalizability (G) theory to investigate the score reliability of the SR format in L2 reading tests focusing on how many test items a reading test should include. Specifically, this study aimed to investigate the interaction between question types and the number of items, providing insights into the appropriate item count for different types of questions. G theory is a comprehensive statistical framework used for estimating the score reliability of tests and validating their results. Data were collected from 108 English as a second language student who completed an English reading test comprising factual, vocabulary, and inferential questions in the SR format. The computer program mGENOVA was utilized to analyze the data using multivariate designs (i.e., scenarios). Based on the results of G theory analyses, the findings indicated that the number of test items had a critical impact on the score reliability of an L2 reading test. Furthermore, the findings revealed that different types of reading questions required varying numbers of test items for reliable assessment of learners’ L2 reading proficiency. Further implications for teaching practice and classroom-based assessments are discussed.

Keywords: second language reading assessment, validity and reliability, Generalizability theory, Academic reading, Question format

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20440 Contextual Variables Affecting Frustration Level in Reading: An Integral Inquiry

Authors: Mae C. Pavilario

Abstract:

This study employs a sequential explanatory mixed method. Quantitatively it investigated the profile of grade VII students. Qualitatively, the prevailing contextual variables that affect their frustration-level were sought based on their perspective and that of their parents and teachers. These students were categorized as frustration-level in reading based on the data on word list of the Philippine Informal Reading Inventory (Phil-IRI). The researcher-made reading factor instrument translated to local dialect (Hiligaynon) was subjected to cross-cultural translation to address content, semantic, technical, criterion, or conceptual equivalence, the open-ended questions, and one unstructured interview was utilized. In the profile of the 26 participants, the 12 males are categorized as grade II and grade III frustration-levels. The prevailing contextual variables are personal-“having no interest in reading”, “being ashamed and fear of having to read in front of others” for extremely high frustration level; social environmental-“having no regular reading schedule at home” for very high frustration level and personal- “having no interest in reading” for high frustration level. Kendall Tau inferential statistical tool was used to test the significant relationship in the prevailing contextual variables that affect frustration-level readers when grouped according to perspective. Result showed that significant relationship exists between students-parents perspectives; however, there is no significant relationship between students’ and teachers’, and parents’ and teachers’ perspectives. The themes in the narratives of the participants on frustration-level readers are existence of speech defects, undesirable attitude, insufficient amount of reading materials, lack of close supervision from parents, and losing time and focus on task. Intervention was designed.

Keywords: contextual variables, frustration-level readers, perspective, inquiry

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20439 SNR Classification Using Multiple CNNs

Authors: Thinh Ngo, Paul Rad, Brian Kelley

Abstract:

Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

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