scientific-research
آموزش از دور
Nazila Khatib Zanjani
Abstract
The present study was conducted with the aim of identifying the dimensions, components, and indicators of hyper-Personalized education using artificial intelligence. The type of research was qualitative in terms of data type, which included meta synthesis and Delphi stages in terms of nature. The statistical ...
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The present study was conducted with the aim of identifying the dimensions, components, and indicators of hyper-Personalized education using artificial intelligence. The type of research was qualitative in terms of data type, which included meta synthesis and Delphi stages in terms of nature. The statistical population in the qualitative section and meta synthesis stage included all theoretical foundations and relevant background from external databases, and in the Delphi stage, 15 participants (experts) were selected using purposive non-random sampling. The data collection method in the meta synthesis stage was a systematic literature review, and in the Delphi stage, a worksheet, and validity and reliability were examined, and the results indicated that the research tools were valid and reliable. The data analysis method in the meta synthesis stage was systematic analysis, and in the Delphi stage, the Kendall agreement coefficient was used with Maxqda-V2018 and Spss-V23 software. The findings showed that hyper-Personalized education using artificial intelligence included a cognitive dimension with the components of prior knowledge level analysis (5 indicators), individual learning style (6 indicators), cognitive adaptation (6 indicators), memory and memorization (6 indicators), and problem solving and critical thinking (6 indicators); an affective dimension with the components of identifying emotional states (6 indicators), intrinsic motivation (6 indicators), learner self-efficacy (6 indicators), learner satisfaction (6 indicators), and emotional involvement in learning (6 indicators); a behavioral dimension with the components of interaction patterns with the system (6 indicators), participation in group activities (6 indicators), learning discipline and pursuit (5 indicators), knowledge seeking behaviors (6 indicators), and interaction with feedback (6 indicators); and a contextual dimension with the components of learning environmental conditions (6 indicators), technology and tools used (6 indicators), cultural and linguistic adaptation (6 indicators), educational access and justice (6 indicators), and learning data analysis (6 indicators).
scientific-research
آموزش از دور
akbar jadidi
Abstract
The purpose of the study was to examine the mediating role of cognitive intelligence in the relationship between ICT and academic enthusiasm. This was a descriptive-correlational study. The statistical population consisted of all sixth-grade students studying in the 2023-2024 primary school year in Kerman ...
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The purpose of the study was to examine the mediating role of cognitive intelligence in the relationship between ICT and academic enthusiasm. This was a descriptive-correlational study. The statistical population consisted of all sixth-grade students studying in the 2023-2024 primary school year in Kerman City. 250 people were selected as the sample size using the total number sampling method. Data were collected through questionnaires made (ICT) by Islami (2018), a standard questionnaire of academic aspiration by Fredericks et al. (2004) Cattell Child Studies Form B 2 test. Hypotheses were analyzed using the correlation coefficient and modeling of old structural equations. The findings showed that the relationship between experience working with the Internet, Internet use, cognitive intelligence, and academic enthusiasm was insignificant. The relationship between cognitive intelligence and academic motivation is not significant. Also, the relationship between the use of educational software, the use of computers and Internet services, the ease and usefulness of working with computers and Internet services, and the ability to work with computers and Internet services with academic enthusiasm is positive and significant. The direct effect of ICT components (use of computers and Internet services, ease and usefulness of working with computers and Internet services) on academic motivation is positive and significant. The findings showed that the direct effect of ICT components such as (the ability to work with computers and Internet services) on cognitive intelligence is positive and significant. The direct effect of cognitive intelligence on students' academic enthusiasm is not significant. Cognitive intelligence does not have a significant mediating role in the relationship between ICT components and academic enthusiasm. As a result, it can be said that paying attention to ICT is effective in academic enthusiasm and cognitive intelligence.
