Computer Assisted Learning System Research Articles

Effects of Computer-Assisted Reading Learning System on Chinese Reading Comprehension

Effects of Computer-Assisted Reading Learning System on Chinese Reading Comprehension

Comparison of template-based and multilayer perceptron-based approach for automatic question generation system

Intelligent tutoring systems are computer-assisted learning systems with adaption to students using artificial intelligence tools. An intelligent tutoring system can drastically improve education efficiency as it provides solutions to many issues that now plague the educational industry. One important component in education is questioning learners to assess and reinforce learning. This research compares two approaches for automatic question generation, a template-based question generation strategy and the phrase-Level automatic question generation system utilizing the Multilayer perceptron model. A template-based technique is a baseline for automatic question generation that uses templates taken from the training set to generate questions by filling certain templates with specific topic items. We utilize question-answer sentence composition datasets and manually constructed datasets for our experiments and comparison of the Multilayer perceptron training model. We used both human and automatic evaluation metrics to assess the efficiency of our suggested methods. Regarding automatic metrics, we selected the BLEU-n gram and ROUGE-N methodologies. The evaluation results demonstrate that the phrase-level Multilayer perceptron-based strategy dominates the template-based approach and has a promising score in both ROUGE automatic and human evaluation metrics.

ADDRESSING DIFFICULTIES IN TEACHING MATHEMATICS TO STUDENTS WITH MATHEMATICAL LEARNING DISABILITIES

The essence and reason for the inability to master mathematics are described as a lack of working memory. This paper describes two main approaches to solving the problem of teaching mathematics to students with learning difficulties in mathematics (MLD): (1) training working memory and (2) reducing the load on working memory in the instructional process. It was found that the results of the first approach are ambiguous: Training working memory leads to its improvement, which is confirmed by the test results but may not lead to improvement of the mathematical learning process associated with the student’s working memory. This justifies the primacy of the second approach. Both previously known methods for reducing the load on working memory in mathematics instruction are presented. A computer-based mathematics learning system developed by the author aims at automating basic computational skills (arithmetics, trigonometry, geometry). It is explained how to work with the developed computer-assisted learning system, which is based on the method of interval repetitions, and empirical data on the results of the system implementation are given.

A Qualitative Systematic Literature Review on Phonological Awareness in Preschoolers Supported by Information and Communication Technologies

This review is a systematic literature review (SLR) with the aim of advancing the state of the art in Phonological Awareness in preschoolers (4–6 years) by means of Information and Communication Technologies (ICT). The SLR provides an important guide to newcomers to this domain and researchers who seek a structured body of knowledge in the subject for gaining new, important insights. Searches were carried out in the indexed database Scopus© between June and July 2020. Among the inclusion and exclusion criteria were studies reported in English, Spanish and Portuguese, updated electronic documents from the last ten years and studies cited by others at least once, except for those with publication acknowledgement after 2017. To complete the task, a triangulation assessment was made among three researchers using the same tool developed in Microsoft Excel©, in which the search terms, the search strings, inclusion and exclusion criteria and the study collection process were systematized along with a word cloud of keywords to improve the systematic feature of the SLR. Fifty-nine (59) scientific articles were selected and from those, 24 articles met the experts’ criteria. The method included: (1) search and selection of terms; (2) inclusion and exclusion criteria; (3) the searching process; and (4) reporting study collection. The SLR synthesis reported in this paper is a novel contribution built on two conceptual categories: Computer assisted learning systems (CAL) and Computer assisted instruction systems (CAI) which frame works on Phonological Awareness processes with Preschoolers and provide an appraisal of the results to advance knowledge of systematic reviews of preschoolers’ phonological awareness strictly supported by ICT.

Graph-based knowledge tracing: Modeling student proficiency using graph neural networks

Recent advancements in computer-assisted learning systems have caused an increase in the research in knowledge tracing, wherein student performance is predicted over time. Student coursework can potentially be structured as a graph. Incorporating this graph-structured nature into a knowledge tracing model as a relational inductive bias can improve its performance; however, previous methods, such as deep knowledge tracing, did not consider such a latent graph structure. Inspired by the recent successes of graph neural networks (GNNs), we herein propose a GNN-based knowledge tracing method, i.e., graph-based knowledge tracing. Casting the knowledge structure as a graph enabled us to reformulate the knowledge tracing task as a time-series node-level classification problem in the GNN. As the knowledge graph structure is not explicitly provided in most cases, we propose various implementations of the graph structure. Empirical validations on two open datasets indicated that our method could potentially improve the prediction of student performance and demonstrated more interpretable predictions compared to those of the previous methods, without the requirement of any additional information.

A new QoE-based prediction model for evaluating virtual education systems with COVID-19 side effects using data mining.

Today, emerging technologies such as 5G Internet of things (IoT), virtual reality and cloud-edge computing have enhanced and upgraded higher education environments in universities, colleagues and research centers. Computer-assisted learning systems with aggregating IoT applications and smart devices have improved the e-learning systems by enabling remote monitoring and screening of the behavioral aspects of teaching and education scores of students. On the other side, educational data mining has improved the higher education systems by predicting and analyzing the behavioral aspects of teaching and education scores of students. Due to an unexpected and huge increase in the number of patients during coronavirus (COVID-19) pandemic, all universities, campuses, schools, research centers, many scientific collaborations and meetings have closed and forced to initiate online teaching, e-learning and virtual meeting. Due to importance of behavioral aspects of teaching and education between lecturers and students, prediction of quality of experience (QoE) in virtual education systems is a critical issue. This paper presents a new prediction model to detect technical aspects of teaching and e-learning in virtual education systems using data mining. Association rules mining and supervised techniques are applied to detect efficient QoE factors on virtual education systems. The experimental results described that the suggested prediction model meets the proper accuracy, precision and recall factors for predicting the behavioral aspects of teaching and e-learning for students in virtual education systems.

Synthesizing a Japanese-language functional expression learning system with Chinese-speaking learners’ cultural interests and backgrounds

This piece is a short response to Liu, Shindo, and Matsumoto’s (2019) Development of a computer-assisted Japanese functional expression learning system for Chinese-speaking learners for the special issue: Shifting to Digital: Informing the rapid development, deployment, and future of teaching and learning. Key ideas, value, and future implications are culturally addressed in relation to a computer-assisted language learning system entitled Jastudy meant for Chinese learners of Japanese language.

TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources

The recent advances in computer-assisted learning systems and the availability of open educational resources today promise a pathway to providing cost-efficient high-quality education to large masses of learners. One of the most ambitious use cases of computer-assisted learning is to build a lifelong learning recommendation system. Unlike short-term courses, lifelong learning presents unique challenges, requiring sophisticated recommendation models that account for a wide range of factors such as background knowledge of learners or novelty of the material while effectively maintaining knowledge states of masses of learners for significantly longer periods of time (ideally, a lifetime). This work presents the foundations towards building a dynamic, scalable and transparent recommendation system for education, modelling learner's knowledge from implicit data in the form of engagement with open educational resources. We i) use a text ontology based on Wikipedia to automatically extract knowledge components of educational resources and, ii) propose a set of online Bayesian strategies inspired by the well-known areas of item response theory and knowledge tracing. Our proposal, TrueLearn, focuses on recommendations for which the learner has enough background knowledge (so they are able to understand and learn from the material), and the material has enough novelty that would help the learner improve their knowledge about the subject and keep them engaged. We further construct a large open educational video lectures dataset and test the performance of the proposed algorithms, which show clear promise towards building an effective educational recommendation system.

Development of a computer-assisted Japanese functional expression learning system for Chinese-speaking learners

Because a large number of Chinese characters are commonly used in both Japanese and Chinese, Chinese-speaking learners of Japanese as a second language (JSL) find it more challenging to learn Japanese functional expressions than to learn other Japanese vocabulary. To address this challenge, we have developed Jastudy, a computer-assisted language learning (CALL) system designed specifically for Chinese-speaking learners studying Japanese functional expressions. Given a Japanese sentence as an input, the system automatically detects Japanese functional expressions using a character-based bidirectional long short-term memory with a conditional random field (BiLSTM-CRF) model. The sentence is then segmented and the parts of speech (POS) are tagged (word segmentation and POS tagging) by a Japanese morphological analyzer, MeCab ( http://taku910.github.io/mecab/ ), trained using a CRF model. In addition, the system provides JSL learners with appropriate example sentences that illustrate Japanese functional expressions. The system uses a ranking system, which gives easier sentences a higher rank, when selecting example sentences. A support vector machine for ranking (SVMRank) algorithm estimates the readability of example sentences, using Japanese-Chinese common words as an important feature. A k-means clustering algorithm is used to cluster example sentences that contain functional expressions with the same meanings, based on part-of-speech, conjugation form, and semantic attributes. Finally, to evaluate the usefulness of the system, we have conducted experiments and reported on a preliminary user study involving Chinese-speaking JSL learners.

Language Learning in Computer-assisted Collaborative Learning (CACL) Environment

Does computer helps learners improve their cognition? If yes, then what are the theories support such improvement? The different computer-assisted system will be used in the different purpose and needs of the education. Besides discussing the theories and some basic computer-assisted learning environment, this paper is trying to find the answers of the following questions as well: In which way do Computer-assisted Collaborative Learning (CACL) systems help learner improve the cognition? Will CACL help students in language (both first language and second language) learning?

学習者制御型簡易CALシステム「かきつばた」の設計と開発

学習者制御型簡易CALシステム「かきつばた」の設計と開発

An English Learning Method Based on Computer-assisted System

Computer terminology is studied by unit, professional computer knowledge and lexical features, etc. in this paper. An effective game-based learning pattern is generated combined with the characteristics of computer English terms. The computer-assisted English learning system is studied to help students memorize terminology. This learning system could also examine the learning effect after study. The relevant question bank is available to users for game-based examination. The examination result and the statistic score could be kept in the question bank for analysis of the learning effect.

Using a Touch-Based, Computer-Assisted Learning System to Promote Literacy and Math Skills for Low-Income Preschoolers

The use of touch-based technologies by young children to improve academic skills has seen growth outpacing empirical evidence of its effectiveness. Due to the educational challenges low-income children face, the stakes for providing instructional technology with demonstrated efficacy are high. The current work presents an empirical study of the use of a touch-based, computer-assisted learning system by low-income preschoolers. A description of the system’s design is provided with attention to young children’s interaction with touch devices, learner engagement, and pedagogically-based delivery of academic content. Children in 18 low-income child-care preschool classrooms were assessed on literacy and math skills in the fall and again in the spring. Target children used the iStartSmart learning system throughout the academic year, while control children did not have access to the system. Compared to controls, children using the learning system made significant gains on external standardized measures of literacy and math. Children who spent more time using the system and those who reached the upper levels of skill understanding showed the strongest improvement in test scores. The findings contribute to the currently sparse literature by illuminating that for at-risk early learners, touch-based, computer-assisted instructional technology shows promise as an educational tool.

A SCIENCE, TECHNOLOGY, ENGINEERING AND MATHEMATICS COURSE WITH COMPUTER-ASSISTED REMEDIAL LEARNING SYSTEM SUPPORT FOR VOCATIONAL HIGH SCHOOL STUDENTS

One of the significant and distinguishing curriculum characteristics of STEM compared to other subjects domains is hands-on skill development. Hands-on training enables the enhancement of learning because it parallels with the concrete-to-abstract nature of cognitive development, providing additional sources of brain activation via kinaesthetic involvement and elevating students’ motivation and engagement. To bridge the gap between theory and practice, and advance unprepared students’ hands-on skills, this research proposed and implemented an innovative STEM course with the computer-assisted remedial learning system (CARLS) in the vocational high school experience in Taiwan. The effects of STEM course were examined through an experiment with learning performances hypotheses. A total of 32 students in a vocational high school in Taiwan voluntarily participated in this research and a one-group pre-test and post-test pre-experimental design was adopted. The results of this experimental course demonstrated that CARLS is effective and contributed in enhancing students’ knowledge, achievement and hands-on skill performance in this STEM course. Suggestions and implications for STEM education is also made for practitioners and educators. Key words: hands-on activities, STEM, Computer-Assisted Remedial Learning System, vocational high school.

An application of adaptive games-based learning based on learning style to teach SQL

The fact that each student has a different way of learning and processing information has long been recognised by educationalists. In the classroom, the benefits derived from delivering learning content in ways that match the student's learning style have also been identified. As new modes of delivery of learning content such as computer-assisted learning systems (e.g. eLearning) have become increasingly popular, research into these has also identified the benefits of tailoring learning content to learning styles. However, in games-based learning (GBL), the adaptation based on learning style to enhance the educational experience has not been well researched. For the purpose of this research, a game with three game modes has been developed: 1) non-adaptivity mode; 2) a mode that customises the game according to the student's learning style identified by using a learning style questionnaire; and 3) a mode that has an in-game adaptive system that dynamically and continuously adapts its content according to the student's interactions in the game.This paper discusses the term adaptivity in a GBL context and presents the results of an experimental study investigating the differences in learning effectiveness of the different game modes compared to a paper-based learning. The study was performed with 120 Higher Education students learning the database language SQL (Structured Query Language). The results show that the game developed, regardless of mode, produced better learning outcomes than those who learned from a textbook while adaptive GBL was better in terms of allowing learners to complete the tasks faster than the other two game versions.

CALEE: A computer-assisted learning system for embedded OS laboratory exercises

With the popularity of embedded systems and the consequently rising demand in the job market for professionals well-versed in them, embedded operating systems (EOSs) have become one of the core courses in computer science studies across the world. The objective of EOS courses is to develop students' ability to port, modify, and customize an embedded operating system through a series of laboratory exercises. However, our teaching experience has revealed that beginners require a considerable amount of time to familiarize themselves with the development environment and the relevant processes, such as operating in a command line interface, setting environment variables, and kernel configurations. Furthermore, students need to constantly handle compiler error messages, malfunctions of the target EOS, and incompatibility issues related to development tools. These problems may frustrate and discourage students. A common strategy to address this problem is to dedicate more hours to teaching or to hire more teaching assistants to help students progress. However, none of these methods is suitable for institutions with limited resources. Therefore, in this paper, we develop a computer-assisted learning system called the Computer-assisted Learning Environment (CALEE) to assist students with their assignments and thus motivate them. CALEE consists of two parts: a self-learning assistant (SLAT) and a collaborative learning website (CLW). SLAT is a software application that provides a set of useful functions to help students perform EOS laboratory exercises, whereas the collaborative learning website seeks to encourage greater interaction among students. Our experiments show that CALEE expedites learning, improves students' motivation, and reduces the teaching load.

Interdisciplinary project-based learning: technology for improving student cognition

The article studies a way of enhancing student cognition by using interdisciplinary project-based learning (IPBL) in a higher education institution. IPBL is a creative pedagogic approach allowing students of one area of specialisation to develop projects for students with different academic profiles. The application of this approach in the Ural State University of Economics resulted in a computer-assisted learning system (CALS) designed by IT students. The CALS was used in an analytical chemistry course with students majoring in Commodities Management and Expertise (‘expert’ students). To test how effective the technology was, the control and experimental groups were formed. In the control group, learning was done with traditional methods. In the experimental group, it was reinforced by IPBL. A statistical analysis of the results, with an application of Pearson χ2 test, showed that the cognitive levels in both IT and ‘expert’ experimental groups improved as compared with the control groups. The findings demonstrated that IPBL can significantly enhance learning. It can be implemented in any institution of higher or secondary education that promotes learning, including the CALS development and its use for solving problems in different subject areas.Keywords: higher education; learning technology; computer-assisted learning; cognitive level(Published: 17 November 2015)Citation: Research in Learning Technology 2015, 23: 27577 - http://dx.doi.org/10.3402/rlt.v23.27577

Courseware development with animated pedagogical agents in learning system to improve learning motivation

The addition of animated pedagogical agents (APAs) in computer-assisted learning (CAL) systems could successfully enhance students' learning motivation and engagement in learning activities. Conventionally, the APA incorporated multimedia materials are constructed through the cooperation of teachers and software programmers. However, the thinking and technical gap between two roles, a concept/content provider (teacher) and an implementer (software programmer), may lead to the concept distortion and loss in the final teaching material implementations. This often results in preventing a teacher from preparing his or her own APA-based multimedia learning systems. This study aims to develop a courseware to facilitate the CAL through the combination of the two roles into a single one and then teachers can use it freely by themselves. The courseware can help teachers to develop appropriate multimedia instructional materials incorporating APAs, which attracts students' attention and enhances their interest in learning. Furthermore, in this study two separate trial experiments were conducted to measure the teachers' satisfaction with the courseware and students' learning motivation after using APA-based multimedia learning systems. The results show that the participating teachers were satisfied with the courseware and would like to apply it in their instruction. Moreover, the participating students were strongly motivated by the customized APA-based multimedia learning systems. Therefore, the proposed courseware could give teachers a good opportunity to add pedagogical value to the curriculum, so that students' learning interest and motivation could be enhanced.

A Design of a Speech Conversion System from PuTongHua to Cantonese Based on iFLY MSP 2.0

The paper analyzes the working theory of a Speech Conversion System from PuTongHua to Cantonese based on iFLY MSP 2.0. In the system, QISR interface is chosen to complete speech recognition function which is the key technology to convert the voice information into the corresponding text information. Moreover, the QTTS interface is chosen to complete the text to speech function which is the key technology to transform the text which is the result of the speech recognition into the spoken information in Cantonese and then output. Finally, the computer assisted learning system is designed successfully in the environment of Visual C++ 6.0.

Effects of an intelligent web‐based English instruction system on students' academic performance

AbstractThis research conducted quasi‐experiments in four middle schools to evaluate the long‐term effects of an intelligent web‐based English instruction system, Computer Simulation in Educational Communication (CSIEC), on students' academic attainment. The analysis of regular examination scores and vocabulary test validates the positive impact of CSIEC, and in most cases, the positive impact is statistically significant. The reliability is ensured by the spectrum of the students from Grade 1 to Grade 3 in three junior high schools and from Grade 1 to Grade 2 in one senior high school, and of the teachers with or without blended learning experience, as well as by the various school locations from rural to urban areas in four provinces of China. The learning content‐oriented design and the instant feedback feature of the web‐based system, as well as its regular integration into the English class, contributed to its reliable positive effect on students' learning performance in ordinary examinations. This is the research's implication for instructional design. The conclusion of this paper could serve as a reference to the technical feasibility and pedagogical benefit of regular usage of appropriate Computer Assisted Learning system in the mainstream subject of middle schools. The multiple quasi‐experiments in divergent school settings to ensure the results' reliability distinguish this research from previous ones that just implemented one single experiment in one school.