Factors Linked to AI Literacy in University Students
- Conditions
- Technology LiteracyReading HabitsSmartphone AddictionInternet AddictionAcademic Acheivement
- Registration Number
- NCT06689319
- Lead Sponsor
- Nagihan Acet
- 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.
Recruitment & Eligibility
- Status
- NOT_YET_RECRUITING
- Sex
- All
- Target Recruitment
- 184
- Being between 18-35 years of age.
- Willingness to participate after receiving detailed information about the study's purpose and methodology.
- Missing responses in questionnaires.
- Illiteracy.
- Inability to cooperate.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Assessment of reading habits Day 1 Assessment of reading habits The Self-Report Habit Index will be used to assess reading habits . The Reading Habits Questionnaire is a 12-item instrument designed to assess individuals' reading habits, covering dimensions such as reading frequency, duration, preferred materials (books, magazines, online content, etc.), reading purpose, and reading environment. The questionnaire allows participants to respond on a 5-point Likert scale (1: Never, 5: Always). The total score obtained is used to interpret an individual's reading habits: low scores indicate infrequent reading, moderate scores represent regular but not intensive reading habits, and high scores reflect frequent reading of diverse materials. This assessment helps determine the level of an individual's reading habits and identify areas for potential improvement.
Assessment of smartphone addiction Day 1 Smartphone addiction will be assessed using the Smartphone Addiction Scale - Short Form. This is a 10-item scale used to evaluate individuals' smartphone usage habits.Each item is scored from 1 (Strongly Disagree) to 6 (Strongly Agree), with a minimum total score of 10 and a maximum of 60. Higher scores indicate a greater risk of addiction and provide a quick assessment.
Assessment of internet addiction Day 1 Internet addiction will be assessed using the Internet Addiction Scale - Short Form, an instrument designed to evaluate individuals' internet usage habits. Originally developed by Young (1998), the scale has been adapted as a short form consisting of 6 items for a quick assessment of internet addiction \[14\]. The Turkish version will be used \[15\]. Each item is rated from 1 (Never) to 5 (Always), with a total score ranging from 6 to 30. Higher scores indicate an increased risk of internet addiction.
Assessment of academic achievement Day 1 The level of academic achievement will be assessed based on the cumulative grade point average (GPA) from the previous semester. This measure provides an objective indicator of students' overall academic performance, capturing their sustained efforts and intellectual engagement in coursework.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Atılım University
🇹🇷Ankara, Turkey