Through the last decades, Artificial Intelligence (AI) has revolutionized the field of education and transformed traditional teaching approaches. This study aimed to examine how university students adopt AI tools in their learning processes and the role of digital literacy (DL) in this process through the lens of the Technology Acceptance Model (TAM). In this context, this study measured the impact of DL on university students' acceptance of AI technologies and their intention to use such technologies in the future. The data was collected from university students (N = 154) at a university in Western Türkiye during the fall semester of 2023. Data collection was conducted using two separate online forms; the first form included items adapted from the Digital Literacy Scale developed by Bayrakçı and Narmanlıoğlu (2021) to measure digital literacy levels, while the second form included items adapted from the UTAUT study by Venkatesh et al. (2003). The hypothesis testing results showed that students with higher levels of DL perceived the usefulness and ease of use of AI tools more positively, which positively affected their intention to adopt AI-based tools. The study also found that perceived usefulness and ease of use were important in shaping students' attitudes and behavioural intentions towards AI. When students perceive AI as a valuable tool for learning and find it easy to interact with, they are more willing to use it. This study suggests that DL plays a significant role in the acceptance of AI-based tools among university students, and accordingly, the TAM is a practical and accurate model to explore students’ potential engagement with AI in the learning process.
{"title":"Exploring The Role of Digital Literacy in University Students' Engagement with AI through the Technology Acceptance Model","authors":"Caner Börekci, Özgür Çelik","doi":"10.19126/suje.1468866","DOIUrl":"https://doi.org/10.19126/suje.1468866","url":null,"abstract":"Through the last decades, Artificial Intelligence (AI) has revolutionized the field of education and transformed traditional teaching approaches. This study aimed to examine how university students adopt AI tools in their learning processes and the role of digital literacy (DL) in this process through the lens of the Technology Acceptance Model (TAM). In this context, this study measured the impact of DL on university students' acceptance of AI technologies and their intention to use such technologies in the future. The data was collected from university students (N = 154) at a university in Western Türkiye during the fall semester of 2023. Data collection was conducted using two separate online forms; the first form included items adapted from the Digital Literacy Scale developed by Bayrakçı and Narmanlıoğlu (2021) to measure digital literacy levels, while the second form included items adapted from the UTAUT study by Venkatesh et al. (2003). The hypothesis testing results showed that students with higher levels of DL perceived the usefulness and ease of use of AI tools more positively, which positively affected their intention to adopt AI-based tools. The study also found that perceived usefulness and ease of use were important in shaping students' attitudes and behavioural intentions towards AI. When students perceive AI as a valuable tool for learning and find it easy to interact with, they are more willing to use it. This study suggests that DL plays a significant role in the acceptance of AI-based tools among university students, and accordingly, the TAM is a practical and accurate model to explore students’ potential engagement with AI in the learning process.","PeriodicalId":487001,"journal":{"name":"Sakarya University Journal of Education","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141815270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigates prospective teachers' perspectives on the present status of artificial intelligence (AI) and their predictions regarding its future development. The study utilized a case study approach to select a group of 64 prospective teachers from the faculty of education at a state university in Türkiye. The study participants comprised 34 female and 30 male prospective teachers. The researchers employed a purposive sampling technique, specifically the criterion sampling approach, to select the prospective teachers included in the study. The researchers collected data for the study using the "AI Perception Interview Form" and the "AI Future Foresight Determination Form," and then analyzed the data using descriptive and content analysis techniques. The results showed that prospective teachers obtained information about AI primarily from social media, internet/news websites, and applications. Analyzing the definitions and explanations provided by the prospective teachers revealed that they particularly emphasized the uploading of human intelligence to computer systems, the acquisition of human-like abilities by machines, and the ability of AI to learn independently. Additionally, prospective teachers identified health, education, accounting, and finance as domains with significant potential for the advancement of AI. In education, the initial applications prospective teachers thought AI could be used for included determining students' mental states, assessing student levels, and providing personalized content. The data obtained from the study indicate that prospective teachers produced both utopian and dystopian content regarding the future of AI. This production of varied content reveals that prospective teachers have diverse perspectives on the future of AI.
{"title":"Present and Future of Artificial Intelligence: A Case Study on Prospective Teachers","authors":"Mehmet Uymaz","doi":"10.19126/suje.1466052","DOIUrl":"https://doi.org/10.19126/suje.1466052","url":null,"abstract":"This study investigates prospective teachers' perspectives on the present status of artificial intelligence (AI) and their predictions regarding its future development. The study utilized a case study approach to select a group of 64 prospective teachers from the faculty of education at a state university in Türkiye. The study participants comprised 34 female and 30 male prospective teachers. The researchers employed a purposive sampling technique, specifically the criterion sampling approach, to select the prospective teachers included in the study. The researchers collected data for the study using the \"AI Perception Interview Form\" and the \"AI Future Foresight Determination Form,\" and then analyzed the data using descriptive and content analysis techniques. The results showed that prospective teachers obtained information about AI primarily from social media, internet/news websites, and applications. Analyzing the definitions and explanations provided by the prospective teachers revealed that they particularly emphasized the uploading of human intelligence to computer systems, the acquisition of human-like abilities by machines, and the ability of AI to learn independently. Additionally, prospective teachers identified health, education, accounting, and finance as domains with significant potential for the advancement of AI. In education, the initial applications prospective teachers thought AI could be used for included determining students' mental states, assessing student levels, and providing personalized content. The data obtained from the study indicate that prospective teachers produced both utopian and dystopian content regarding the future of AI. This production of varied content reveals that prospective teachers have diverse perspectives on the future of AI.","PeriodicalId":487001,"journal":{"name":"Sakarya University Journal of Education","volume":"63 S289","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141835177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The process that enables students to achieve objectives while performing mathematical tasks is defined as an activity. The task creation process is a lengthy and challenging journey involving many complex stages. Artificial intelligence technologies can facilitate this process. For instance, ChatGPT can assist teachers on various issues and help them create tasks. This study aimed to evaluate the tasks prepared for the Grade 7 ratio concept using ChatGPT, focusing on cognitive demand levels. It employed a case study design to examine the cognitive demand levels of tasks created with ChatGPT 3.5 and ChatGPT 4, identifying any potential deficiencies. The content analysis was performed to analyze the data. It was concluded that the created tasks could be used with necessary improvements, allowing teachers to enrich their course content while saving time and energy.
{"title":"Examination of Grade 7 Ratio Concept Tasks Designed by ChatGPT Based on Cognitive Demand Levels","authors":"Merve Koçyiğit Gürbüz, Kübra Alan, B. Yıldız","doi":"10.19126/suje.1429781","DOIUrl":"https://doi.org/10.19126/suje.1429781","url":null,"abstract":"The process that enables students to achieve objectives while performing mathematical tasks is defined as an activity. The task creation process is a lengthy and challenging journey involving many complex stages. Artificial intelligence technologies can facilitate this process. For instance, ChatGPT can assist teachers on various issues and help them create tasks. This study aimed to evaluate the tasks prepared for the Grade 7 ratio concept using ChatGPT, focusing on cognitive demand levels. It employed a case study design to examine the cognitive demand levels of tasks created with ChatGPT 3.5 and ChatGPT 4, identifying any potential deficiencies. The content analysis was performed to analyze the data. It was concluded that the created tasks could be used with necessary improvements, allowing teachers to enrich their course content while saving time and energy.","PeriodicalId":487001,"journal":{"name":"Sakarya University Journal of Education","volume":"34 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141845509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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