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'gifted and talented students' Search Results



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This study aims to describe achievement motivation on outstanding students in learning to write at the fifth grade  primary schools students. The research method used is descriptive qualitative. Subjects in this study were 18 achieving students. The data were collected through questionnaire, interview and observation. Analytical techniques used are interactive analysis consisting of data collection, data reduction, data presentation and conclusion. The results of this study indicate that the achievement motivation on outstanding students in learning writing is good, this happens because of several factors that support outstanding students in learning writing have good achievement motivation. There are factors of individuals (intern) and environmental factors (external), an individual factor which consists of 1) the competence of students; 2) belief to succeed, while environmental factors consists of 1) the competitive situation; 2) support from parents, 3) schools, including how to teach teachers.

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10.12973/ijem.4.3.133
Pages: 133-139
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This study aimed to develop an instructional design that focuses on programming teaching for gifted and talented students and to investigate its effects on the teaching process. During the development of the instructional design; the steps of Morrison, Ross and Kemp Instructional Design Model were followed. Embedded experimental design, one of the mixed-method research designs, was used in the modeling of the study. The participants consisted of students studying at the Science and Art Center (BILSEM) (experimental group: 13 girls and 12 boys, control group: 10 girls and 15 boys). While the instructional design developed by the researchers was applied to the gifted and talented students in the experimental group, the standard activities used in Information Technologies and Software Courses at BILSEM were applied to the gifted and talented students in the control group. “Computational Thinking Scale (CTS)”, “Torrance Creative Thinking Test (TCTT-Figural)” and “Computer Programming Self-Efficacy Scale (CPSES)” were used to collect the data of the quantitative phase of the study. Qualitative data were gathered by using interview form, observation forms, and design thinking rubric. Two-Factor ANOVA Test, Bonferroni Adjustment Multiple Comparisons Test, and interaction graphs were used to analyze quantitative data while qualitative data were analyzed by content analysis. The quantitative results of the research showed that the instructional design was effective on students' computational thinking and creative thinking skills, but not on programming self-efficacy. Qualitative findings revealed that the instructional design helped the students learn the computational concepts, use computational applications, and develop computational-perspectives. Also, students improved their design thinking skills to a certain level and expressed that they enjoyed the design thinking process, learned the course content, and experienced some difficulties.

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10.12973/ijem.6.1.161
Pages: 161-183
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The study's goal was to examine the correlation between the computer programming self-efficacy and computational thinking skills of gifted and talented students. The capacity of the computer programming self-efficacy of gifted and talented students to predict their computational thinking skills were also examined. The relational screening model has been implemented in the research. The participants of the study were composed of 106 secondary school gifted and talented students studying the Individual Ability Recognition Program (IAR) at the Science and Art Center in the city center. Typical case sampling was applied for the student identification of the participants, 46 are female and 60 are male. Gifted and talented students' computational thinking skills were assessed using the "Computational Thinking Skills Scale” and the computer programming self-efficacy was measured by using the "Computer Programming Self-Efficacy Scale". Data were analysed by Pearson correlation analysis and simple linear regression analysis in statistical software SPSS 22. Research results found that there was a positive and high correlation between the computer programming self-efficacy and computational thinking skills. The gifted and talented students' computer programming self-efficacy demonstrated 31.5% of the total variance in computational thinking skills. This finding supports the claim which is present in the literature that self-efficacy in computer programming is the affective aspect of computational thinking skills. To predict computational thinking skills, it may be recommended to build multiple models for cognitive and affective skills of gifted and talented students.

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10.12973/ijem.6.2.259
Pages: 259-270
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This research aims to examine the effect of coding education on the analytical thinking skills of gifted students. The participants are 18 students, 11 to 12 years old. An embedded experimental mixed design was used in the research. The data collection was carried out with the Analytical Thinking Skill Scale to determine the difference in the analytical thinking skills of the study group before and after the coding training; the Analytical Thinking Skill Observation Form to determine the analytical thinking skill levels during the implementation process; and the semi-structured interview form to get their opinions on the coding training. The data were analyzed with a pre-test-post-test quasi-experimental design, descriptive analysis, and content analysis. The results show that coding education developed the participants' analytical thinking skills. The difference in the analytical thinking skills of the study group was not statistically significant in terms of gender. According to the students' views on the coding education application process, there was an improvement in the sub-dimensions of sorting, classification, comparison, and evaluation in analytical thinking skills; coding education developed problem-solving and thinking skills, was useful, encouraged students to choose a profession, and was entertaining, as well as negative opinions such as being difficult, boring, and requiring a lack of time.

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10.12973/ijem.9.1.95
Pages: 95-106
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The purposes of this research are (a) to make an instrument to measure the achievement of project-based digitalpreneurship learning in students; (b) to describe the quality of the project-based digitalpreneurship learning achievement assessment instrument for vocational high school students; (c) to measure the competence and skills. This study employed to research and development as its methodology, using a combination procedure between Oriondo and Antonio and, Mardapi. The development procedure includes three stages: instrument design, instrument testing, and measurement. A total of 795 students who participated in the study at 5 vocational high schools in Yogyakarta's special region served as responders. Data analysis in this development uses the content validity of the formula Aiken V Index, confirmatory factor analysis establishes the construct's validity, and construct reliability. Measurement instrument development. Research findings that (a) the instrument is ready to be used in the measurement; (b) the quality of the project-based digitalpreneruship learning achievement assessment instrument for vocational high school students is well tested. This is evidenced by the validity test which has a high score >.8; The proof of construct validity in this study using CFA > .5; GOF chi-square value with a critical value of df = 289, X2 = 323, p-value with a critical value of .079, RMSEA with a critical value of RMSEA .019 (≤ .08), SMRM with a critical value of SRMR 0.030 (≤ .05), CFI with a critical value of CFI .990 (> .97), and an NFI with a critical value of NFI .989 ( > .90); (c) the measurement results are identified in the process that needs to be improved again regarding the digitalpreneurship skills of vocational high school students.

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10.12973/ijem.9.1.283
Pages: 283-295
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Knowledge-based economy is an economic model students need to be prepared for a future economic model that uses knowledge as its main resource. Therefore, this study developed and validated instruments for constructing knowledge-based economy readiness among undergraduate students. This study used an online questionnaire with 120 respondents of economic education students in educational universities in East Java, Indonesia, for exploratory factor analysis and 417 respondents for confirmatory factor analysis. Then, statistical analysis was conducted using exploratory factor analysis in SPSS and confirmatory factor analysis in AMOS. This study first developed five factors of knowledge of economics, readiness for economic challenges, readiness for education, readiness for infrastructure, and readiness for innovation, consisting of 27 items. However, one item was removed because the loading factor was below .50. Consequently, 26 items were retained because the loading factor was significantly greater than .50. The Cronbach's alpha value for each item of the knowledge-based economy readiness construct was >.60 and met all goodness of fit index criteria, which means that it meets the requirements and can measure the construct of knowledge-based economy readiness. Since this study meets the validity and reliability requirements of the constructs leading to knowledge-based economy readiness, these results will help students prepare for the current and future knowledge-based economy. They can be used in developing economic education curricula in higher education.

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10.12973/ijem.9.4.697
Pages: 697-710
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Computational Thinking Through the Engineering Design Process in Chemistry Education

computational thinking engineering design process chemistry

Norhaslinda Abdul Samad , Kamisah Osman , Nazrul Anuar Nayan


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This study investigated the influence of CThink4CS2 Module on computational thinking (CT) skills of form four chemistry students. The CThink4CS2 Module integrated CT with the Engineering Design Process (EDP) in chemistry class. This study utilized quantitative research methods and quasi-experimental design. Quantitative data were collected using the Computational Thinking Skill Test (CTST) which consisted of algorithmic reasoning, abstraction, decomposition, and pattern recognition constructs. A total of 73 students were in the treatment group (n=39) and control group (n=34). Experimental data were described by means of descriptive analysis and inferential analysis employing two-way MANOVA analysis. The results of the analysis indicated significant differences in CT skills between groups; students in the treatment group demonstrated better results compared to those in the control group. The paper provides insight into the integration of CT and EDP as effective pedagogical strategies for inculcating CT skills.

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10.12973/ijem.9.4.771
Pages: 771-785
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