Ismail Celik
Biographic Data
| ID | 4633902 |
|---|---|
| NAME | Ismail Celik |
| GIVEN NAMES | Ismail |
| FAMILY NAME | Celik |
| SIGNATURE | CELIK I |
| AFFILIATIONS | University of Oulu |
| ORCID | 0000-0002-5027-8284 |
| VERIFIED | Yes |
| TOTAL WORKS | 13 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 13 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Teachers’ professional knowledge to prevent students’ overreliance on AI
Generative AI (GenAI) tools introduce the risk of student overreliance, in which learners bypass their cognitive effort and depend uncritically on GenAI outputs. Teachers have a crucial role in preventing students’ overreliance on GenAI. This paper suggests teachers’ knowledge for preventing GenAI overreliance based on the Intelligent-TPACK framework. This framework addresses GenAI-specific pedagogical and ethical knowledge with five dimensions: …
Knowledge construction with GenAI
Although generative artificial intelligence (GenAI) tools are increasingly integrated into education, limited attention has been paid to how prompt design mediates pedagogical alignment and instructional intent. This study addresses this gap by exploring the interplay between theory-informed prompt engineering and the coherence of generated content with curricular goals. We employ a theory-driven prompt engineering approach based on the Social Kn…
Co-constructing adaptive lesson plans with GenAI
Generative Artificial Intelligence (GenAI) technologies present new opportunities for teachers to design adaptive and student-centered instruction. However, the educational value of GenAI depends not only on technical usage but also on teachers’ ability to formulate pedagogically meaningful prompts. Prompting strategies are not isolated from teachers` prior knowledge and skills. Less is known about how pre-service teachers` AI-related knowledge i…
Longitudinal effects of learning analytics support for study planning and monitoring
Learning analytics (LA) can be an effective support for self-regulation of higher education students. Supporting different students on their academic paths requires considering students' self-efficacy beliefs and data-literacy skills as well as their varying uses and interpretations of LA. In this quasi-experimental study, we collected quantitative survey data on higher education students (N = 105) with and without access to a student-facing LA d…
Higher education students' value tensions and alignments with a learning analytics dashboard
Data and algorithm driven technologies designed to support teaching and learning activities have raised intense debate on ethics. Specifically, learning analytics (LA) have been criticized for the lack of students' involvement and disconnection from the learning context. The current study addresses this gap by investigating higher education students' ( N = 12) use of an LA dashboard from a value perspective. Semi‐structured interviews were conduc…
Teacher – Artificial Intelligence (AI) interaction
Despite the novel educational opportunities of chatbots, their integration into teaching and learning settings is still in the early stages. Understanding the interplay of teachers’ perceptions, attitudes, and intentions to use chatbots can provide insight into the sustainable integration of chatbots in K-12 education. However, little is known about teachers’ acceptance of chatbots in this context. This study proposes a framework to better unders…
The antecedents of pre-service teachers’ AI literacy
This study explores the relationships between pre-service teachers’ perceptions of AI tools, their attitudes towards AI, and their AI literacy competencies. Specifically, it examines how perceived characteristics of the GenAI Teachable Machine (GenAI TM) and attitudes towards AI influence key dimensions of AI literacy, including technical understanding, critical evaluation, and practical application. Findings indicate that technical understanding…
The affordances of artificial intelligence-based tools for supporting 21st-century skills
Twenty-first-century skills should be integrated into higher education to prepare students for complex working-life challenges. Artificial intelligence (AI)-powered tools have the potential to optimise skill development among higher education students. Therefore, it is important to conceptualise relevant affordances of AI systems for 21st-century skills development in higher education. This study aimed to present an overview of journal articles p…
Response of learning analytics to the online education challenges during pandemic
Emerging technological advancements can play an essential role in overcoming challenges caused by the COVID-19 pandemic. As a promising educational technology field, Learning Analytics (LA) tools or systems can offer solutions to COVID-19 pandemic-related needs, obstacles, and expectations in higher education. In the current study, we systematically reviewed 20 papers to better understand the responses of LA tools to the online learning challenge…
Towards Intelligent-TPACK
The affordances of artificial intelligence (AI) have not been totally utilized in education. To effectively integrate AI into education, teachers’ AI-specific technological and pedagogical knowledge is important. Furthermore, due to novel ethical issues caused by Al, teachers also must have the knowledge to assess AI-based decisions. None of the previous studies so far explored teacher knowledge to pedagogically and ethically use AI-based tools. …
Enerji Emtiaları Arasında Getiri ve Volatilite Yayılımı
Bu araştırmanın amacı enerji emtiaları arasında getiri ve volatilite yayılımı olup olmadığını incelemektir. Farklı makroekonomik gelişmeler neticesi varlık fiyatlarında meydana gelen getiri oynaklıkları emtialar arasında yayılım göstererek birbirlerinin getirilerini de etkileyebilmektedir. Enerji emtialarının fiyatlarını etkileyen unsurların ve aralarındaki yayılımın tespiti özellikle yatırım yapmak isteyenler ve enerji piyasası ile ilgilenenler …
The Promises and Challenges of Artificial Intelligence for Teachers
This study provides an overview of research on teachers’ use of artificial intelligence (AI) applications and machine learning methods to analyze teachers’ data. Our analysis showed that AI offers teachers several opportunities for improved planning (e.g., by defining students’ needs and familiarizing teachers with such needs), implementation (e.g., through immediate feedback and teacher intervention), and assessment (e.g., through automated essa…
Antidiabetic properties of lyophilized extract of acorn (Quercus brantii Lindl.) on experimentally STZ-induced diabetic rats
No prominent works on this page.
Antidiabetic properties of lyophilized extract of acorn (Quercus brantii Lindl.) on experimentally STZ-induced diabetic rats
Enerji Emtiaları Arasında Getiri ve Volatilite Yayılımı
Bu araştırmanın amacı enerji emtiaları arasında getiri ve volatilite yayılımı olup olmadığını incelemektir. Farklı makroekonomik gelişmeler neticesi varlık fiyatlarında meydana gelen getiri oynaklıkları emtialar arasında yayılım göstererek birbirlerinin getirilerini de etkileyebilmektedir. Enerji emtialarının fiyatlarını etkileyen unsurların ve aralarındaki yayılımın tespiti özellikle yatırım yapmak isteyenler ve enerji piyasası ile ilgilenenler …
The Promises and Challenges of Artificial Intelligence for Teachers
This study provides an overview of research on teachers’ use of artificial intelligence (AI) applications and machine learning methods to analyze teachers’ data. Our analysis showed that AI offers teachers several opportunities for improved planning (e.g., by defining students’ needs and familiarizing teachers with such needs), implementation (e.g., through immediate feedback and teacher intervention), and assessment (e.g., through automated essa…
Response of learning analytics to the online education challenges during pandemic
Emerging technological advancements can play an essential role in overcoming challenges caused by the COVID-19 pandemic. As a promising educational technology field, Learning Analytics (LA) tools or systems can offer solutions to COVID-19 pandemic-related needs, obstacles, and expectations in higher education. In the current study, we systematically reviewed 20 papers to better understand the responses of LA tools to the online learning challenge…
Towards Intelligent-TPACK
The affordances of artificial intelligence (AI) have not been totally utilized in education. To effectively integrate AI into education, teachers’ AI-specific technological and pedagogical knowledge is important. Furthermore, due to novel ethical issues caused by Al, teachers also must have the knowledge to assess AI-based decisions. None of the previous studies so far explored teacher knowledge to pedagogically and ethically use AI-based tools. …
The affordances of artificial intelligence-based tools for supporting 21st-century skills
Twenty-first-century skills should be integrated into higher education to prepare students for complex working-life challenges. Artificial intelligence (AI)-powered tools have the potential to optimise skill development among higher education students. Therefore, it is important to conceptualise relevant affordances of AI systems for 21st-century skills development in higher education. This study aimed to present an overview of journal articles p…
The antecedents of pre-service teachers’ AI literacy
This study explores the relationships between pre-service teachers’ perceptions of AI tools, their attitudes towards AI, and their AI literacy competencies. Specifically, it examines how perceived characteristics of the GenAI Teachable Machine (GenAI TM) and attitudes towards AI influence key dimensions of AI literacy, including technical understanding, critical evaluation, and practical application. Findings indicate that technical understanding…
Teachers’ professional knowledge to prevent students’ overreliance on AI
Generative AI (GenAI) tools introduce the risk of student overreliance, in which learners bypass their cognitive effort and depend uncritically on GenAI outputs. Teachers have a crucial role in preventing students’ overreliance on GenAI. This paper suggests teachers’ knowledge for preventing GenAI overreliance based on the Intelligent-TPACK framework. This framework addresses GenAI-specific pedagogical and ethical knowledge with five dimensions: …
Knowledge construction with GenAI
Although generative artificial intelligence (GenAI) tools are increasingly integrated into education, limited attention has been paid to how prompt design mediates pedagogical alignment and instructional intent. This study addresses this gap by exploring the interplay between theory-informed prompt engineering and the coherence of generated content with curricular goals. We employ a theory-driven prompt engineering approach based on the Social Kn…
Co-constructing adaptive lesson plans with GenAI
Generative Artificial Intelligence (GenAI) technologies present new opportunities for teachers to design adaptive and student-centered instruction. However, the educational value of GenAI depends not only on technical usage but also on teachers’ ability to formulate pedagogically meaningful prompts. Prompting strategies are not isolated from teachers` prior knowledge and skills. Less is known about how pre-service teachers` AI-related knowledge i…
Longitudinal effects of learning analytics support for study planning and monitoring
Learning analytics (LA) can be an effective support for self-regulation of higher education students. Supporting different students on their academic paths requires considering students' self-efficacy beliefs and data-literacy skills as well as their varying uses and interpretations of LA. In this quasi-experimental study, we collected quantitative survey data on higher education students (N = 105) with and without access to a student-facing LA d…
Higher education students' value tensions and alignments with a learning analytics dashboard
Data and algorithm driven technologies designed to support teaching and learning activities have raised intense debate on ethics. Specifically, learning analytics (LA) have been criticized for the lack of students' involvement and disconnection from the learning context. The current study addresses this gap by investigating higher education students' ( N = 12) use of an LA dashboard from a value perspective. Semi‐structured interviews were conduc…
Teacher – Artificial Intelligence (AI) interaction
Despite the novel educational opportunities of chatbots, their integration into teaching and learning settings is still in the early stages. Understanding the interplay of teachers’ perceptions, attitudes, and intentions to use chatbots can provide insight into the sustainable integration of chatbots in K-12 education. However, little is known about teachers’ acceptance of chatbots in this context. This study proposes a framework to better unders…
Online Learning and Analytics (7 works) · Mathematics education (4 works) · Psychology (4 works) · Analytics (3 works) · Computer Science (3 works) · Higher education (3 works) · Knowledge level (3 works) · Learning analytics (3 works) · Literacy (3 works) · Affordance (2 works)