The global population is aging rapidly, presenting challenges and opportunities. The proportion of individuals aged 65 and above is projected to rise significantly by 2050, necessitating efforts to combat ageism and promote active aging. Active aging emphasizes optimizing opportunities for health, lifelong learning, participation, and security to enhance quality of life. Universities of the Third Age and 60+ Refreshment Universities have emerged to foster active aging through educational programs. The increasing reliance on technology during the COVID-19 pandemic highlighted the importance of technology literacy among older adults. This study focuses on understanding the attitudes of Refreshment students towards technology use, examining the relationships between perceived usefulness, perceived ease of use, gerontechnology self-efficacy, and attitude towards technology usage. A gap in the literature exists regarding the attitudes of older adults actively engaged in learning, a group that can help dispel stereotypes about aging.

The Technology Acceptance Model (TAM) posits that perceived usefulness and perceived ease of use significantly influence attitudes and intentions toward technology use. Existing research shows varied results on the relationship between perceived usefulness and attitude toward using technology. Some studies have shown that the perceived usefulness and ease of use of technology are important factors that influence older adults' attitudes and behaviors towards using technology. Other studies have found that self-efficacy plays a key role in technology adoption among older adults. Gerontechnology self-efficacy, specifically, refers to an older adult's belief in their ability to use technology effectively to enhance their independence and social participation. This study investigates how perceived usefulness, perceived ease of use, and gerontechnology self-efficacy interact to influence attitudes toward using technology among Refreshment students, a demographic largely understudied in this context.

This quantitative study employed a survey method with closed-ended questions. Convenience sampling was used to select 318 participants from three Refreshment Universities in Turkey and North Cyprus. Ethical approval was obtained, and a pilot test was conducted to ensure survey clarity. The sample size of 318 was determined to be sufficient using Bartlett et al.'s (2001) formula, ensuring representativeness of the larger population of 1517 refreshment students. Data were collected over four weeks. Validated scales were used to measure perceived usefulness (5-item scale), perceived ease of use (4-item scale), attitude towards usage (4-item scale), and gerontechnology self-efficacy (2-item scale), all using a 5-point Likert scale. Control variables included age, gender, and education. Data were analyzed using AMOS 21.0 and SPSS 26.0 to assess the fit of the research model through confirmatory factor analysis (CFA) and structural equation modeling (SEM). The normality of the data, multicollinearity, convergent validity, and discriminant validity were assessed. The hypotheses were tested using mediation and moderated mediation analysis.

The average age of participants was 67.33, with a majority being female (65%), married (63.8%), holding a bachelor's degree (50.6%), and retired (86.6%). Correlation analysis showed significant positive relationships between PU and PEOU, PU and ATUT, PU and GTSE, PEOU and ATUT, and PEOU and GTSE. Confirmatory factor analysis supported the four-factor model (PU, PEOU, ATUT, and GTSE). Structural equation modeling results confirmed Hypothesis 1 (PU positively influences ATUT), Hypothesis 2 (PEOU mediates the relationship between PU and ATUT), and Hypothesis 3 (GTSE plays a moderating mediating role in the relationship between PU and ATUT via PEOU). The direct effect of PU on ATUT was significant (β = 0.612, p < 0.001). The indirect effect of PU on ATUT through PEOU was also significant (β = 0.293, p < 0.001). The moderated mediation analysis showed that the mediating effect of PEOU on the relationship between PU and ATUT was stronger for participants with low GTSE than those with high GTSE (β = -0.066, p = 0.007). Predictors of PEOU explained 47% of its variance, while predictors of ATUT explained 78% of its variance.

The findings align with the TAM, suggesting that older adults are more likely to adopt technology if they find it useful and easy to use. The mediating role of PEOU highlights the importance of user-friendliness in technology adoption. The moderating role of GTSE emphasizes the importance of building confidence and self-efficacy in older adults. These results suggest that interventions aimed at enhancing the perceived usefulness and ease of use of technology, especially for older adults with lower GTSE, are likely to be effective in promoting technology adoption. The significant variance explained by the model underscores the model's predictive power in understanding technology adoption among active learning older adults.

This study provides strong support for the TAM and extends the model by demonstrating the crucial role of GTSE in the technology acceptance process of older adults. The findings have practical implications for the design and implementation of gerontechnology interventions. Future research could compare attitudes across different Refreshment programs or contrast refreshment students with non-active learning seniors to better understand active learning's impact on technology adoption. Further investigation into the specific factors influencing GTSE would also be valuable.

The convenience sampling method may limit the generalizability of the findings. The study focused solely on Refreshment students, potentially limiting the applicability of the findings to other older adult populations. Future studies could use more diverse sampling techniques to enhance generalizability.