教師著作
Permanent URI for this collectionhttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/37072
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Item A Chinese word segmentation and POS tagging system for readability research(2012-11-15) Chang, T. H.; Sung, Y. T.; Lee, Y. T.In recent years, readability research has relied on applications of natural language processing techniques to analyze documents. However, Chinese sentences consist of characters and with no blanks between words. Therefore, a mistake on word segmentation and/or part-of-speech tagging for Chinese sentences will result in many errors in the follow-up analysis. CRF model,is recently the most popular and successful method for Chinese word segmentation. However, due to such problems as reiterative locution, unknown words and incomplete sentences, many readings for children cannot be processed accurately by CRF model. This study aims to develop a Chinese word segmentation and POS tagging system called WeCan. This system is composed of bigram model, SPLR algorithm, unknown words extraction and rule bases. WeCan has been applied to the preprocessing procedure of CRIE. In preliminary experiments, it also worked well on the elementary school textbook in Taiwan.Item Classifying Chinese text based on readability indices: comparing the machine learning and statistical approaches(2012-08-01) Lee, Y. S.; Chen, J. L.; Chang, T. H.; Chang, K. E.; Chen, H. C.; Sung, Y. T.Item Constructing a novel Chinese readability classification model using principal component analysis and genetic programming(2012-07-06) Lee, Y. S.; Tseng, H. C.; Chen, J. L.; Peng, C. Y.; Chang, T. H.; Sung, Y. T.The studies of readability aim to measure the level of text difficulty. Although traditional formulae such as the Flesch-Kincaid formula can properly predict text readability, they are only effective for English text. Other formulae with very few features may result in inaccurate text classification. The study takes into account multiple linguistic features, and attempts to increase the level of accuracy in text classification by adopting a new model which integrates Principal Component Analysis (PCA) with Genetic Programming (GP). Empirical data are used to demonstrate the performance of the proposed model.Item The Construction of Readability Formula for Chinese Text Using SVM: the Preliminary Study(2012-05-01) Chen, J. L.; Tseng,H. C; Cha,J. H.; Chang, T. H.; Sung, Y. T.Item CRIE: A tool for analyzing Chinese text characteristics(2012-11-15) Chen, J. L.; Cha, J. H. Cha; Chang, T. H.; Sung, Y. T.; Hsieh, K. S.Studies focusing on language analyses of alphabetic writing systems have been researched for more than 40 years. Abundant and advanced research outcomes and practical needs have made automated text analyzing tools possible; however, such tools designed for Chinese writing system are insufficient and scarce. Following the latest trend of multi-level analyses of text features (Graesser et al., 2004), we develop a tool called Chinese Readability Indices Explorer, CRIE, which can extract 90 features based on features of Chinese characters, words, syntax, and cohesion. The modules used in CRIE include lexicons, segmentation, syntactic parsers, corpora, latent semantic analysis, and other components that are widely used in computational linguistics. Not only does CRIE provide multi-level linguistic feature analyses, CRIE is also able to deal with literary Chinese and domain-specific texts. CRIE provides outputs on measures of individual linguistic features as well as providing formulas for different text domains , age groups.Item Evaluation of the feasibility of online readability application(2012-11-15) Tseng, H. C.; Chang, T. H.; Sung, Y. T.Readability refers to the extent to which a text can be understood. Reading materials of high readability can facilitate reading comprehension, learning, and information retention. With the development of Cloud computing, it has become important to assess the readability of online texts. However, previous readability research focuses only on the accuracy of text classification but fails to comprehensively take into account the formulae accuracy, time complexity, and feature diversity. Currently readability formulae used in evaluating online documents are time-consuming and low in accuracy. Therefore, to enhance the online utilization of readability formulae, we propose a standardized framework for evaluating the feasibility of online readability formulae, based on the three major factors: (a) user waiting time, (b) text classification accuracy, and (c) feature diversity. We also verified the feasibility of this framework by comparing several readability models under such framework.Item How many heads are better than one? The reliability and validity of teenagers' self- and peer assessments(ELSEVIER, 2010-02-01) Sung, Y. T.; Chang, K. E.; Chang, T. H.; Yu, W. C.Self- and peer assessments are becoming more popular in classrooms, but there are few data on the reliability and validity of such assessments performed by school children. Because these factors are greatly affected by the number of raters, we conducted two studies to determine the rating behaviours of teenagers in self- and peer assessments, and how the number of raters influences the reliability and validity of self- and peer assessments. The first study involved 116 seventh graders (the first grade of middle school), where students individually playing musical recorders were subject to self- and peer assessments. The second study involved 110 eighth graders, with Web pages constructed by students being subject to self- and peer assessments. Generalizability theory and criterion-related validity were used to obtain the reliability and validity coefficients of the self- and peer ratings. Analyses of variance were used to compare differences in self- and peer ratings between low- and high-achieving students. The coefficients of reliability and validity increased with the number of raters in both studies, reaching the acceptable levels of 0.80 and 0.70, respectively, with 3 or 4 raters in the first study (involving assessments of individual performance) and with 14–17 raters in the second study (involving assessments of group work). Furthermore, low- and high-achieving students tended to over- and underestimate the quality of their work in self-assessment, respectively. The discrepancy between the ratings of students and experts was higher in group-work assessments then in individual-work assessments. The results have both theoretical and practical implications for researchers and teachers.Item Supporting teachers' reflection and learning through structured digital teaching portfolios(John Wiley & Sons Ltd, 2009-08-01) Sung, Y. T.; Chang, K. E.; Yu, W. C.; Chang, T. H.Digital teaching portfolios have been proposed as an effective tool for teacher learning and professional development, but there is a lack of empirical evidence supporting their effectiveness. This study proposed the design of a structured digital portfolio equipped with multiple aids (e.g. self-assessment, peer assessment, discussion and journal writing) for the professional development of teachers. This study also empirically evaluated the reflection and professional development as demonstrated in digital teaching portfolios with multiple supporting measures. Forty-four in-service substitute teachers participated in a course of classroom assessment and used a Web-based portfolio system. Based on the framework of teacher reflective thinking developed by Sparks-Langer et al., we found that most teachers demonstrated moderate levels of reflection in their journals but only one-third of them showed the highest level of reflection. We also found that the professional knowledge of teachers about classroom assessment – as shown by their implementation of it – improved significantly during the construction of portfolios. The above findings also represent good evidence that digital portfolios with multiple aids are beneficial to teacher reflection and professional development.Item Teachers' reflection and learning in digital teaching portfolios: An empirical evaluation(2004-04-16) Sung, Y. T.; Chang, K. E.; Chang, T. H.