Factors Linked to AI Literacy in University Students

NCT ID: NCT06689319

Last Updated: 2025-11-25

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 184 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2024-11-15
• Study Completion Date: 2025-04-15

Brief Summary

This study investigates the relationships between artificial intelligence (AI) literacy and factors such as academic achievement, reading habits, smartphone addiction, and internet addiction among university students. As AI technologies become increasingly integrated into daily life, AI literacy-necessary for understanding and evaluating AI-is emerging as a critical skill. While factors like academic success and regular reading habits may enhance AI literacy, behaviors like smartphone and internet addiction may have an adverse effect by promoting superficial information access over deeper critical engagement. This prospective, observational, and cross-sectional study will assess AI literacy using the Artificial Intelligence Literacy Scale and analyze its association with academic and behavioral factors. The study will be conducted among participants aged 18-35 in the Physiotherapy and Rehabilitation Department Laboratory at Atılım University. Data will be evaluated using descriptive statistics, correlation analyses (Pearson or Spearman, depending on distribution), and significance testing. The results may highlight the impact of academic and behavioral factors on AI literacy, offering insights for educational strategies aimed at fostering critical AI competencies.

Detailed Description

Artificial Intelligence (AI), a transformative force within information technology, is a subfield of computer science that involves creating intelligent machines and software that act and respond similarly to humans. With the introduction of ChatGPT, an OpenAI product released in November 2022, the concept of artificial intelligence has gained further popularity. Historically, a significant milestone for AI was the Turing Test, introduced by Alan Turing in 1950 to measure a machine's ability to exhibit human-like behaviors. Following this, the development of expert systems in the 1960s-70s, neural networks in the 1980s, machine learning and data mining in the 1990s, and deep learning in the 2000s each marked pivotal points in the AI timeline . Within the realm of computing, AI is often described as a "man-made homo sapiens" species . AI systems possess foundational skills such as learning, reasoning, self-improvement through experiential learning, language comprehension, and problem-solving, and are programmed as simulations of human intelligence. AI and its applications are utilized to address complex issues across diverse fields-including science, healthcare, education, engineering, business, defense, entertainment, and advertising-by means of expert systems.

The rapid integration of AI technologies into daily life has made it essential for individuals to acquire knowledge and skills related to these technologies. AI literacy represents an understanding and awareness of core artificial intelligence concepts. In this context, AI literacy is a fundamental competency that enables individuals to understand, utilize, and critically evaluate AI technologies, recognizing both their benefits and limitations. Having AI literacy can help individuals understand and manage AI technologies, offering an opportunity to become more informed and capable individuals. Therefore, it has become essential for everyone today to possess and enhance their AI literacy.

Factors such as reading habits and levels of academic achievement may positively influence the development of AI literacy. Individuals who have regular reading habits typically develop critical thinking and in-depth analysis skills, which facilitate understanding and critically evaluating AI technologies. Similarly, individuals with high academic performance are often experienced in accessing and applying knowledge, making them more adaptable to the foundational skills required for gaining AI literacy.

However, behaviors like internet addiction and smartphone addiction, while facilitating access to AI technologies, may have an adverse effect on AI literacy. Internet addiction reinforces a habit of accessing information rapidly and superficially, which can reduce critical thinking and focus. Likewise, smartphone addiction, due to its provision of constant and superficial access to information, may diminish interest in the deep thinking processes required for AI literacy. Therefore, internet and smartphone addiction could act as barriers in the processes requiring deep thought, analysis, and accumulation of knowledge essential for AI literacy.

To our knowledge, there is no comprehensive study that examines AI literacy among university students in relation to academic achievement, reading habits, smartphone addiction, and internet addiction from a multifaceted perspective.

The aim of this study is to reveal the relationships between university students' AI literacy and their levels of academic achievement, reading habits, internet addiction, and smartphone addiction.

Conditions

Technology Literacy; Reading Habits; Smartphone Addiction; Internet Addiction; Academic Acheivement

Study Design

• Observational Model Type: OTHER
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

The group to be evaluated in terms of AI literacy

Assessment of Artificial Intelligence Literacy

Intervention Type: BEHAVIORAL

The Artificial Intelligence Literacy Scale will be used to determine the level of AI literacy.. The scale is a 12-item instrument designed to measure individuals' knowledge and skills in AI awareness, usage, evaluation, and ethical considerations. Items are rated on a Likert scale from 1 to 7 (1: Strongly Disagree, 7: Strongly Agree), with some items reverse-coded (items 2, 5, and 11). The minimum possible score on the scale is 12, and the maximum score is 84; a higher score indicates a higher level of AI literacy. The Turkish version of the scale will be used in this study.

Interventions

Assessment of Artificial Intelligence Literacy

The Artificial Intelligence Literacy Scale will be used to determine the level of AI literacy.. The scale is a 12-item instrument designed to measure individuals' knowledge and skills in AI awareness, usage, evaluation, and ethical considerations. Items are rated on a Likert scale from 1 to 7 (1: Strongly Disagree, 7: Strongly Agree), with some items reverse-coded (items 2, 5, and 11). The minimum possible score on the scale is 12, and the maximum score is 84; a higher score indicates a higher level of AI literacy. The Turkish version of the scale will be used in this study.

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

• Being between 18-35 years of age.
• Willingness to participate after receiving detailed information about the study's purpose and methodology.

Exclusion Criteria

• Missing responses in questionnaires.
• Illiteracy.
• Inability to cooperate.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 35 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Nagihan Acet

OTHER

Sponsor Role: lead

Responsible Party

Nagihan Acet

Asst. Prof.

Responsibility Role: SPONSOR_INVESTIGATOR

Locations

Atılım University

Ankara, , Turkey (Türkiye)

Countries

Turkey (Türkiye)

References

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Reference Type: RESULT

Kutlu, M., et al., Turkish adaptation of Young's Internet Addiction Test-Short Form: A reliability and validity study on university students and adolescents/Young Internet Bagimliligi Testi Kisa Formunun Turkce uyarlamasi: Universite ogrencileri ve ergenlerde gecerlilik ve guvenilirlik calismasi. Anadolu Psikiyatri Dergisi, 2016. 17(S1): p. 69-77.

Reference Type: RESULT

Noyan, C.O., et al., Validity and reliability of the Turkish version of the Smartphone Addiction Scale-Short version among university students/Akilli Telefon Bagimliligi Olceginin Kisa Formunun universite ogrencilerinde Turkce gecerlilik ve guvenilirlik calismasi. Anadolu Psikiyatri Dergisi, 2015. 16(S1): p. 73-82.

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PMID: 24391787 (View on PubMed)

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Other Identifiers

Atılım University_5

Identifier Type: -

Identifier Source: org_study_id