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JournalISSN: 2010-3689

International Journal of Information and Education Technology 

International Journal of Information and Education Technology
About: International Journal of Information and Education Technology is an academic journal published by International Journal of Information and Education Technology. The journal publishes majorly in the area(s): Computer science & Mathematics education. It has an ISSN identifier of 2010-3689. It is also open access. Over the lifetime, 1753 publications have been published receiving 10300 citations. The journal is also known as: IJIET.


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Journal ArticleDOI
TL;DR: This study uses the Moodle system to make up for the shortcomings of learning in a large class, and find out the difference of learning performance and acceptance between traditional learning and digital learning.
Abstract: —With the rapid development of the Internet, constructing the e-learning system has been an integral part of many educational institutions. This study uses the Moodle system to make up for the shortcomings of learning in a large class, and find out the difference of learning performance and acceptance between traditional learning and digital learning. The study is experimented with the students in the Calculus course. There are two part of research design in the study. The first part corresponds to learning performance, which uses the quasi-experimental method to compare the difference of the experimental group, and the control group. The second part refers to technology acceptance, where the unified theory of acceptance use of technology (UTAUT) is used. With two dimensions: Outcome Expectation and Attainment Value, a new hybrid technology acceptance model is proposed to investigate the students' intentions to use Moodle systems. Data Analysis of this study shows a great promising in providing new academic research evidence in e-learning teaching.

219 citations

Journal ArticleDOI
TL;DR: In this paper, a project-based curriculum for the vocational high school students who majored in food and beverages was developed, and the effect of the curriculum on students' learning motivation and ability of problem solving by means of quasi-experimental method and qualitative analysis.
Abstract: Due to pay too much attention to pencil-and-paper test, lacking of learning motivation and problemsolving ability are quite popular for the vocational high school students in Taiwan. This study developed a project-based curriculum for the vocational high school students majored in food and beverage, and examine the effect of the curriculum on students’ learning motivation and ability of problem solving by means of quasi-experimental method and qualitative analysis. The objects of this study are the students majored in food and beverage from two vocational high schools in Taiwan, divided into treatment group and control group. The treatment-group students are given project-based teaching method and control group students are given traditional teaching method during four week period of courses. Research questionnaires consist of learning motivation scale and problem-solving ability questions and answers. The questionnaires, “Learning motivation of vocational high school students” and “Problem-solving ability of vocational high school students”, were conducted to both treatment and control group students. The research results showed project-based learning not only could enhance vocational school students’ learning motivation, but facilitate their problem-solving ability. The contribution of the research is to the vocational education, especially to give the teachers a real exemplar of PBL.

184 citations

Journal ArticleDOI
TL;DR: The results show that applying KNN could achieve higher accuracy than neural network ensemble in the diagnosis of heart disease patients and that applying voting could not enhance the KNN accuracy.
Abstract: Heart disease is the leading cause of death in the world over the past 10 years. Researchers have been using several data mining techniques to help health care professionals in the diagnosis of heart disease. K-Nearest-Neighbour(KNN) is one of the successful data mining techniques used in classification problems. However, it is less used in the diagnosis of heart disease patients. Recently, researchers are showing that combining different classifiers through voting is outperforming other single classifiers. This paper investigates applying KNN to help healthcare professionals in the diagnosis of heart disease. It also investigates if integrating voting with KNN can enhance its accuracy in the diagnosis of heart disease patients. The results show that applying KNN could achieve higher accuracy than neural network ensemble in the diagnosis of heart disease patients. The results also show that applying voting could not enhance the KNN accuracy in the diagnosis of heart disease.

149 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
2023141
2022202
202190
2020146
2019156
2018149