Evaluating Model Fit

This study examined whether the simple view of reading framework is consistently applicable among high school Korean EFL learners. In addition, it was investigated whether an oral reading fluency component is an efficient predictor for reading comprehension on top of decoding skills and linguistic comprehension skills. Thirty tenth-grade students in Korean high school were selected as participants in this research, and their decoding skills, listening comprehension, oral reading fluency, and reading comprehension in English were assessed. The data demonstrated that decoding was not an important component in predicting English reading proficiency, which does not support the original version of the simple view of reading. Instead, it was revealed that oral reading fluency had a strong predictive power of reading comprehension. Furthermore, it was found that the model should be modified as an additive model (listening comprehension + fluency) instead of a productive one. The result is discussed with respect to reading comprehension, taking into account learners’ grade level and EFL learners’ English education circumstances.

The Simple View of Reading

The primary goal was to expand our understanding of text reading fluency (efficiency or automaticity)-how its relation to other constructs (e.g., word reading fluency and reading comprehension) changes over time and how it is different from word reading fluency and reading comprehension. We examined (1) developmentally changing relations among word reading fluency, listening comprehension, text reading fluency, and reading comprehension; (2) the relation of reading comprehension to text reading fluency; (3) unique emergent literacy predictors (i.e., phonological awareness, orthographic awareness, morphological awareness, letter name knowledge, vocabulary) of text reading fluency vs. word reading fluency; and (4) unique language and cognitive predictors (e.g., vocabulary, grammatical knowledge, theory of mind) of text reading fluency vs. reading comprehension. These questions were addressed using longitudinal data (two timepoints; Mean age = 5;24 & 6;08) from Korean-speaking children (N = 143). Results showed that listening comprehension was related to text reading fluency at time 2, but not at time 1. At both times text reading fluency was related to reading comprehension, and reading comprehension was related to text reading fluency over and above word reading fluency and listening comprehension. Orthographic awareness was related to text reading fluency over and above other emergent literacy skills and word reading fluency. Vocabulary and grammatical knowledge were independently related to text reading fluency and reading comprehension whereas theory of mind was related to reading comprehension, but not text reading fluency. These results reveal developmental nature of relations and mechanism of text reading fluency in reading development.

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Developmental, Component-Based Model of Reading Fluency: An Investigation of Predictors of Word-Reading Fluency, Text-Reading Fluency, and Reading Comprehension.

Learning mathematics has been considered as a great challenge for many students. The advancement of computer technologies, in particular, artificial intelligence (AI), provides an opportunity to cope with this problem by diagnosing individual students’ learning problems and providing personalized supports to maximize their learning performances in mathematics courses. However, there is a lack of reviews from diverse perspectives to help researchers, especially novices, gain a whole picture of the research of AI in mathematics education. To this end, this research aims to conduct a bibliometric mapping analysis and systematic review to explore the role and research trends of AI in mathematics education by searching for the relevant articles published in the quality journals indexed by the Social Sciences Citation Index (SSCI) from the Web of Science (WOS) database. Moreover, by referring to the technology-based learning model, several dimensions of AI in mathematics education research, such as the application domains, participants, research methods, adopted technologies, research issues and the roles of AI as well as the citation and co-citation relationships, are taken into account. Accordingly, the advancements of AI in mathematics education research are reported, and potential research topics for future research are recommended.

https://www.mdpi.com/2227-7390/9/6/584/pdf

Roles and Research Trends of Artificial Intelligence in Mathematics Education: A Bibliometric Mapping Analysis and Systematic Review

Scholars have indicated the importance of providing guidance and support for individual learners. In the past decades, most studies have developed adaptive learning systems to address this issue mainly based on students’ cognitive status, such as their learning achievements. However, several educators have pointed out the need to take learners’ affective status into account. Therefore, this study proposed an expert system approach by taking into account both the affective and cognitive status of individual learners. An adaptive learning system was implemented based on the proposed approach. In addition, an experiment was conducted in a fifth-grade Mathematics course to compare the learning performances and perceptions of the students who learned with the adaptive learning system with affective and cognitive status analysis, a cognitive-status-based adaptive learning system, and a conventional learning system. The ANCOVA results revealed that the adaptive learning model with the affective and cognitive performance analysis mechanism outperformed the other two approaches in terms of improving the students’ learning achievement (F ​= ​3.12, p ​

A fuzzy expert system-based adaptive learning approach to improving students’ learning performances by considering affective and cognitive factors

The present study aims to examine the pedagogical effectiveness of a Chinese mathematical dialogue-based intelligent tutoring system used for teaching mathematics. The mathematical unit ‘multiplica...

An application of Chinese dialogue-based intelligent tutoring system in remedial instruction for mathematics learning

The current study explores students’ collaboration and problem solving (CPS) abilities using a human-to-agent (H-A) computer-based collaborative problem solving assessment. Five CPS assessment unit...

Computer-Based Collaborative Problem-Solving Assessment in Taiwan.

This study aimed to investigate the structure and the validity of the cognitive components of reading in Thai, which is a language with a high degree of grapheme–phoneme correspondence. The participants were 1181 fourth-grade students in 29 schools in Thailand, divided into two subsamples for data analysis. Phoneme isolation, rapid colour naming, rapid number naming, rapid word segmentation, morphological structure and morphological production were developed based on the cognitive theories involved in reading. The reliabilities of the tests ranged from .81 to .98. The structure of the cognitive components of reading in Thai was examined using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). With subsample 1 (N = 590), the results of EFA support a three-factor structure, measuring morphological awareness, decoding-related and rapid naming skills. With subsample 2 (N = 591), the results of CFA are consistent with the findings of EFA. These findings indicate that the three-fa...

Exploratory and confirmatory factor analyses in reading-related cognitive component among grade four students in Thailand

This study aims to identify the predictors of Chinese reading and literacy skills among Chinese school children in Taiwan. Participants recruited in the study were 182 Grade 1 elementary school stu...

Predictors of Chinese reading and literacy skills among Chinese school children: a 3-year longitudinal study

Automated scoring by means of Latent Semantic Analysis (LSA) has been introduced lately to improve the traditional human scoring system. The purposes of the present study were to develop a LSA-based assessment system to evaluate children’s Chinese sentence construction skills and to examine the effectiveness of LSA-based automated scoring function by comparing it with traditional human scoring. Twenty-seven fourth graders and thirty-one six graders were assessed on single-character sentence making test (subtest 1) and two-character words sentence making test (subtest 2). The outcomes of LSA-based automated scoring methods in three Chinese semantic spaces generated from three type weighting functions were compared to the traditional human scoring. The results showed that LSA-based automated scoring in three different Chinese semantic spaces and traditional human scoring were highly correlated in single-character sentence making test and moderately correlated in two-character words sentence making test. The Chinese semantic space generated from Log-IDF outperformed the other two types of weighting function in the present study.

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Chen-Huei Liao

Papers

An application of Chinese dialogue-based intelligent tutoring system in remedial instruction for mathematics learning

Computer-Based Collaborative Problem-Solving Assessment in Taiwan.

Exploratory and confirmatory factor analyses in reading-related cognitive component among grade four students in Thailand

Predictors of Chinese reading and literacy skills among Chinese school children: a 3-year longitudinal study

Effectiveness of Automated Chinese Sentence Scoring with Latent Semantic Analysis