Research Article
Sawanan Dangprasert
CONT ED TECHNOLOGY, Volume 18, Issue 3, Article No: ep681
ABSTRACT
The rapid emergence of generative artificial intelligence (GenAI) necessitates a robust and validated framework for digital competency in higher education. This study developed and validated the artificial intelligence-augmented digital competency framework (AIDCF) to address the gap between general digital literacy and artificial intelligence (AI)-specific operational requirements. The research was conducted at a public technological university in Thailand. Employing a developmental mixed-methods design, the primary instrument, a 24-item questionnaire, was reviewed by nine experts, yielding a mean content validity ratio (CVR) of 0.861, with item-level CVRs ranging from 0.778 to 1.000. Exploratory factor analysis with a sample of 300 participants supported a five-factor structure: (1) AI awareness & ethics, (2) prompting & tool proficiency, (3) critical thinking with AI, (4) AI-integrated learning design, and (5) reflective digital practice. These factors collectively explained 65.12% of the total variance, with factor loadings ranging from 0.682 to 0.884 and an overall Cronbach’s alpha of 0.87. The framework’s pedagogical utility was examined through a five-week instructional intervention utilizing the collecting, reviewing, analyzing, framing, and tailoring (CRAFT) model with 36 graduate students. Results revealed high levels of perceived competency (mean = 4.51, standard deviation = 0.53) and qualitative evidence of metacognitive development. The AIDCF provides a theoretically grounded and empirically validated roadmap for fostering advanced AI literacy in the GenAI era.
Keywords: AI literacy, digital competency, critical thinking with AI, technology integration, exploratory factor analysis, CRAFT framework
Research Article
Roza Sh. Akhmadieva, Regina G. Sakhieva, Maria A. Khvatova, Natalya S. Erokhova, Zhanna M. Sizova, Natalya N. Shindryaeva
CONT ED TECHNOLOGY, Volume 18, Issue 2, Article No: ep644
ABSTRACT
This study aims to examine the relationship between university students’ attitudes towards artificial intelligence (AI) and AI literacy levels. A quantitative research method was used using the relational survey model to determine whether students’ attitudes of AI, both positive and negative, were related to their understanding and application (literacy) of AI concepts. The data were collected with the AI attitude scale and the AI literacy scale. The data were analyzed using descriptive statistics, comparative analyses, correlation analysis, and multinominal logistic regression analysis to determine the strength and nature of the relationship between AI attitudes and literacy. The results of the research determined that the students generally had a moderate level of AI literacy, their positive attitudes were high and their negative attitudes were moderate. It was determined that male students and upper-grade students had higher AI literacy and positive attitudes, while engineering and social sciences students had more positive perspectives among disciplines. Correlation analyses show that there are significant positive relationships between AI literacy and positive attitude, and negative relationships between negative attitudes. The model explains the AI literacy level with a rate of 38.6%. According to the findings of the research, it is recommended that university administrations offer course contents, workshops and certificate programs that will increase AI literacy by considering discipline-based differences. It is recommended to disseminate informative and guiding activities, especially in areas where negative attitudes are high, such as health sciences. On the other hand students should make individual efforts to learn not only the user level, but also the technical, ethical and social dimensions of AI. It is important for them to evaluate technology in line with the principles of critical thinking, ethical awareness and digital responsibility.
Keywords: artificial intelligence, AI literacy, attitudes, university students, technology in education, digital competency