THE ROLE OF TECHNO-ETHICAL CLASSROOM BEHAVIOR AND METACOGNITIVE EXPERIENCES OVER TIME IN STUDENTS’ ARTIFICIAL INTELLIGENCE ADDICTIONS

İbrahim Durmus

Makale detayları

THE ROLE OF TECHNO-ETHICAL CLASSROOM BEHAVIOR AND METACOGNITIVE EXPERIENCES OVER TIME IN STUDENTS’ ARTIFICIAL INTELLIGENCE ADDICTIONS

Yazarlar:

İbrahim Durmus

Yayıncı:

Anadolu University

Ana Başlıklar:

Classroom Measurement Practices

Dergi:

Turkish Online Journal of Distance Education Vol.26 Issue 4, pp.36-54

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001360004

pISSN:

1302-6488

Anahtar kelimeler:

Özet:

 The study aims to identify the factors that may influence university students artificial intelligence addiction in educational activities. The study sample consists of 415 students currently studying at Bayburt University. The snowball sampling method was used in the research. In the study, an electronic survey was conducted with university students. The research surveys were distributed to students attending face-to-face education at various departments of Bayburt University by academic staff or educators. Students participated in the study voluntarily. In the research application, statistical analysis programs such as SPSS, SPSS Process Macro, and AMOS were utilized. The study was designed using Structural Equation Modeling SEM. The analyses revealed relational outcomes of the research variables, along with the demographic information of the students. In the analyses, results for both direct effect hypotheses and moderator effect hypotheses were also presented. The study explores the relationships between negative classroom behavior from a technoethical perspective, positive and negative metacognitive experiences related to the passage of time, and artificial intelligence addiction. The results of the study indicate that negative classroom behavior from a techno-ethical perspective increases students artificial intelligence addiction. The students negative techno-ethical classroom behavior reduced their positive metacognitive experiences related to the passage of time. At the same time, increased their negative metacognitive experiences related to the passage of time. Students positive and negative metacognitive experiences associated with time also increased their artificial intelligence addiction. It was observed that many students dedicated more than two hours, or between two and one hour, to artificial intelligence and its applications in their daily activities. In the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction, the daily usage time of artificial intelligence played a moderating role. The daily usage time of artificial intelligence strengthened the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction. There was also a moderating effect of positive metacognitive experiences related to the passage of time in the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction. The students educational status and gender were found to have moderating effects on the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction.

 The study aims to identify the factors that may influence university students artificial intelligence addiction in educational activities. The study sample consists of 415 students currently studying at Bayburt University. The snowball sampling method was used in the research. In the study, an electronic survey was conducted with university students. The research surveys were distributed to students attending face-to-face education at various departments of Bayburt University by academic staff or educators. Students participated in the study voluntarily. In the research application, statistical analysis programs such as SPSS, SPSS Process Macro, and AMOS were utilized. The study was designed using Structural Equation Modeling SEM. The analyses revealed relational outcomes of the research variables, along with the demographic information of the students. In the analyses, results for both direct effect hypotheses and moderator effect hypotheses were also presented. The study explores the relationships between negative classroom behavior from a technoethical perspective, positive and negative metacognitive experiences related to the passage of time, and artificial intelligence addiction. The results of the study indicate that negative classroom behavior from a techno-ethical perspective increases students artificial intelligence addiction. The students negative techno-ethical classroom behavior reduced their positive metacognitive experiences related to the passage of time. At the same time, increased their negative metacognitive experiences related to the passage of time. Students positive and negative metacognitive experiences associated with time also increased their artificial intelligence addiction. It was observed that many students dedicated more than two hours, or between two and one hour, to artificial intelligence and its applications in their daily activities. In the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction, the daily usage time of artificial intelligence played a moderating role. The daily usage time of artificial intelligence strengthened the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction. There was also a moderating effect of positive metacognitive experiences related to the passage of time in the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction. The students educational status and gender were found to have moderating effects on the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction.

 The study aims to identify the factors that may influence university students artificial intelligence addiction in educational activities. The study sample consists of 415 students currently studying at Bayburt University. The snowball sampling method was used in the research. In the study, an electronic survey was conducted with university students. The research surveys were distributed to students attending face-to-face education at various departments of Bayburt University by academic staff or educators. Students participated in the study voluntarily. In the research application, statistical analysis programs such as SPSS, SPSS Process Macro, and AMOS were utilized. The study was designed using Structural Equation Modeling SEM. The analyses revealed relational outcomes of the research variables, along with the demographic information of the students. In the analyses, results for both direct effect hypotheses and moderator effect hypotheses were also presented. The study explores the relationships between negative classroom behavior from a technoethical perspective, positive and negative metacognitive experiences related to the passage of time, and artificial intelligence addiction. The results of the study indicate that negative classroom behavior from a techno-ethical perspective increases students artificial intelligence addiction. The students negative techno-ethical classroom behavior reduced their positive metacognitive experiences related to the passage of time. At the same time, increased their negative metacognitive experiences related to the passage of time. Students positive and negative metacognitive experiences associated with time also increased their artificial intelligence addiction. It was observed that many students dedicated more than two hours, or between two and one hour, to artificial intelligence and its applications in their daily activities. In the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction, the daily usage time of artificial intelligence played a moderating role. The daily usage time of artificial intelligence strengthened the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction. There was also a moderating effect of positive metacognitive experiences related to the passage of time in the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction. The students educational status and gender were found to have moderating effects on the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction.

 The study aims to identify the factors that may influence university students artificial intelligence addiction in educational activities. The study sample consists of 415 students currently studying at Bayburt University. The snowball sampling method was used in the research. In the study, an electronic survey was conducted with university students. The research surveys were distributed to students attending face-to-face education at various departments of Bayburt University by academic staff or educators. Students participated in the study voluntarily. In the research application, statistical analysis programs such as SPSS, SPSS Process Macro, and AMOS were utilized. The study was designed using Structural Equation Modeling SEM. The analyses revealed relational outcomes of the research variables, along with the demographic information of the students. In the analyses, results for both direct effect hypotheses and moderator effect hypotheses were also presented. The study explores the relationships between negative classroom behavior from a technoethical perspective, positive and negative metacognitive experiences related to the passage of time, and artificial intelligence addiction. The results of the study indicate that negative classroom behavior from a techno-ethical perspective increases students artificial intelligence addiction. The students negative techno-ethical classroom behavior reduced their positive metacognitive experiences related to the passage of time. At the same time, increased their negative metacognitive experiences related to the passage of time. Students positive and negative metacognitive experiences associated with time also increased their artificial intelligence addiction. It was observed that many students dedicated more than two hours, or between two and one hour, to artificial intelligence and its applications in their daily activities. In the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction, the daily usage time of artificial intelligence played a moderating role. The daily usage time of artificial intelligence strengthened the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction. There was also a moderating effect of positive metacognitive experiences related to the passage of time in the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction. The students educational status and gender were found to have moderating effects on the relationship between negative techno-ethical classroom behavior and artificial intelligence addiction.

Makale detayları

THE ROLE OF TECHNO-ETHICAL CLASSROOM BEHAVIOR AND METACOGNITIVE EXPERIENCES OVER TIME IN STUDENTS’ ARTIFICIAL INTELLIGENCE ADDICTIONS

Yazarlar:

İbrahim Durmus

Yayıncı:

Anadolu University

Ana Başlıklar:

Classroom Measurement Practices

Dergi:

Turkish Online Journal of Distance Education Vol.26 Issue 4, pp.36-54

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001360004

pISSN:

1302-6488

Artificial intelligence addiction

techno-ethical classroom behavior

metacognitive level related to the passage of time

university students

Sayı

Makale detayları

THE ROLE OF TECHNO-ETHICAL CLASSROOM BEHAVIOR AND METACOGNITIVE EXPERIENCES OVER TIME IN STUDENTS’ ARTIFICIAL INTELLIGENCE ADDICTIONS

Yazarlar: İbrahim Durmus

Yayıncı: Anadolu University

Ana Başlıklar: Classroom Measurement Practices

Dergi: Turkish Online Journal of Distance Education Vol.26 Issue 4, pp.36-54

Belge Tipi: Makale

Yayın Tarihi: 1/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001360004

pISSN: 1302-6488

Artificial intelligence addiction

techno-ethical classroom behavior

metacognitive level related to the passage of time

university students

Sayı

Yazarlar:

İbrahim Durmus

Yayıncı:

Anadolu University

Ana Başlıklar:

Classroom Measurement Practices

Dergi:

Turkish Online Journal of Distance Education Vol.26 Issue 4, pp.36-54

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001360004

pISSN:

1302-6488