cross-sectional study

Conducting qualitative research in applied linguistics seems to have some challenges. Hence, this study aimed to investigate the challenges of applied linguists across different research abilities to conduct qualitative studies. To that end, the biographical narratives, authored by 13 applied linguists, were collected. Then, the narratives were analyzed through qualitative data analysis principles, including organizing and familiarizing, coding and reducing, and interpreting and presenting (Ary et al., 2014). The findings showed that applied linguists face four challenges: methodological issues, technical issues, ethical issues, and qualitative research dissemination while doing qualitative research. The findings also indicated similarities and differences among applied linguists' challenges across different research abilities. It can be concluded that teaching qualitative research is more than mere lecturing about qualitative concepts. Thus, there should be practice-based instruction on qualitative research for applied linguistics students. Moreover, there should be a community for addressing pedagogical dialogs among applied linguists about doing qualitative research.

This study aims to investigate the impact of R&D intensity on operational efficiency and strategic alliances in medium-sized companies. Specifically, it seeks to understand how these variables interact to influence a firm's commitment to research and development activities, ultimately affecting their innovation and market performance. A cross-sectional design was employed, with a sample of 230 participants drawn from medium-sized companies. The sample size was determined using the Morgan and Krejcie table. Data were collected through structured questionnaires assessing R&D intensity, operational efficiency, and strategic alliances. Pearson correlation analysis was conducted to examine the relationships between the dependent variable (R&D intensity) and each independent variable (operational efficiency and strategic alliances). Linear regression analysis was performed to explore the combined effect of the independent variables on R&D intensity. All analyses were conducted using SPSS version 27. Pearson correlation coefficients indicated significant positive relationships between R&D intensity and operational efficiency (r = 0.53, p = 0.001), and between R&D intensity and strategic alliances (r = 0.47, p = 0.002). The regression analysis showed that operational efficiency and strategic alliances together explain 40% of the variance in R&D intensity (R² = 0.40, F(2, 227) = 19.25, p = 0.000). Multivariate regression results confirmed that both operational efficiency (B = 0.07, β = 0.42, p = 0.001) and strategic alliances (B = 1.10, β = 0.35, p = 0.000) are significant predictors of R&D intensity. The study concludes that operational efficiency and strategic alliances significantly enhance R&D intensity in medium-sized companies. These findings suggest that improving operational processes and fostering strategic partnerships are critical for increasing a firm's investment in research and development. The results are consistent with previous research and provide valuable insights for both academia and industry practitioners. Future research should consider longitudinal designs and explore additional variables to further understand these relationships.

Purpose: Academic motivation is a critical driver of educational outcomes, influenced by various factors including attitudes toward education and civic knowledge. Despite abundant research on these factors independently, their collective impact on academic motivation remains underexplored. This study aims to fill this gap by examining how attitudes toward education and civic knowledge together predict academic motivation. Methodology: A cross-sectional study design was employed with a sample of 350 participants derived from high schools and universities, based on Morgan and Krejcie’s table for sample size. Data were collected using validated scales: the Academic Motivation Scale (AMS), Education Attitude Scale (EAS), and Civic Knowledge Assessment Test (CKAT). Pearson correlation and linear regression analyses were conducted using SPSS version 27 to explore the relationships between the study variables. Findings: Descriptive statistics indicated moderate levels of academic motivation (Mean = 4.21, SD = 1.05), positive educational attitudes (Mean = 3.89, SD = 0.78), and varied civic knowledge (Mean = 3.45, SD = 0.88). Pearson correlation showed significant positive relationships between academic motivation and attitudes toward education (r = .312, p < .001) and civic knowledge (r = .287, p < .001). Regression analysis revealed that both attitudes toward education (β = 0.32, p < .001) and civic knowledge (β = 0.27, p < .001) significantly predicted academic motivation, accounting for 20.9% of the variance (R² adjusted = .209). Conclusion: The findings confirm that both educational attitudes and civic knowledge are significant predictors of academic motivation. These results underscore the importance of integrating civic education into curricula and fostering positive educational attitudes to enhance academic motivation. Future educational policies and practices should consider these dimensions to effectively support academic engagement and achievement.