Online learning support is a crucial tool to enhance quality in education for this digital era. The online courses, applications, and learning resources (OCALR) play a critical role in expanding educational opportunities across diverse contexts, particularly when courses are well designed and supported by interactive learning materials (Peltola et al., 2025). By emphasizing flexibility in time and place through digital technologies, Artificial Intelligence (AI) (Wang, 2025), online learning enables meaningful and interactive learning experiences beyond traditional classroom boundaries and has become especially important during periods of disruption and in response to evolving learner needs (Bamrungsin & Khampirat, 2022; Karo & Petsangsri, 2021). Accessible and interactive learning materials further enhance student engagement and motivation by supporting active participation in the learning process (Hu & Xiao, 2025). To support these learning experiences, various online platforms and resources such as open educational resources (OER), open courseware (OCW), and massive open online courses (MOOCs) (Goshtasbpour et al., 2024), have been developed to broaden access to high-quality educational content and enhance learning skills (Cho & Permzadian, 2024). These approaches operate within distributed learning environments enabled by internet-based platforms and communication technologies. Effective online learning environments require the interaction of teaching presence, cognitive presence, and social presence, which together foster meaningful engagement, knowledge construction, and sustained learning (Alshammari & Alrehaili, 2025). In addition, the concept of academic optimism highlights the role of high academic expectations, supportive learning environments, and confidence in students’ learning capacity in enhancing learning effectiveness in online contexts. Accordingly, effective online teaching emphasizes instructional clarity, learner interaction, timely feedback, reliable access to digital learning resources, and a supportive learning environment (Bamrungsin & Khampirat, 2022). Recognizing the potential of online learning and digital resources, the Ministry of Education (MOE) of Thailand has promoted them as a key national strategy to enhance students’ competencies and ensure more equitable access to education, particularly for learners in remote and underserved areas (MOE, 2026). However, despite these initiatives, higher education institutions in remote regions continue to face significant challenges related to geographic isolation, limited digital infrastructure, and unequal access to digital educational resources (KC et al., 2025). These barriers restrict students’ full participation in higher education and underscore the urgent need for innovative instructional approaches, including distance and online learning and the effective use of information and communication technologies (ICT), to support both teaching and educational management in remote contexts  (Norman et al., 2022). Moreover, the effectiveness of OCALR is not determined by course design, interaction, or technology usability alone (Goshtasbpour et al., 2024). Contextual factors such as internet connectivity, geographic location, and the availability of digital devices play a critical role in shaping students’ learning experiences, particularly for learners in remote areas where disparities in digital access between urban and rural regions remain substantial (Enciso-Huamani et al., 2025; Jiang et al., 2024). To address these gaps, this quantitative study investigates the effectiveness of OCALR for college students in a remote area near the Khao Phu Luang mountain region in Nakhon Ratchasima Province, Thailand. The findings are expected to provide evidence-based insights to support effective online teaching practices, inform institutional decision-making, and promote more equitable learning opportunities in remote higher education contexts.

Data for this study were collected in 2023 from undergraduate students and alumni enrolled in a female equal-opportunity education college offering programs aimed at expanding access to higher education for women in a mountainous area of Nakhon Ratchasima Province, Thailand. A total of 74 respondents participated in the study, all of whom were female, reflecting the institutional context. First-year students represented the largest proportion of the sample (n = 23), followed by fourth-year students (n = 21), while second-year students, third-year students, and alumni each accounted for 10 respondents. This distribution ensured representation across different stages of academic progression. In terms of access to online learning, the majority of respondents (86.5%) reported using personal laptops as their primary learning device. Smaller proportions of students shared computers with peers (8.1%) or used tablets and desktop computers (2.7% each). Regarding learning time, more than half of the respondents (52.7%) spent approximately 3–4 hours per day engaged in online learning activities, followed by 27.0% who reported spending 5–6 hours per day. Fewer students spent 1–2 hours (14.9%) or 7–8 hours (2.4%) per day on online learning. Students’ learning effectiveness was assessed using an adapted and validated survey instrument measuring Online Courses, Applications, and Learning Resources (OCALR). The instrument comprised 10 items across three factors: online learners, online teachers, and online resources. The online learner factor included motivation, satisfaction, access ability, and learning-related happiness. The online teacher factor focused on online interaction, use of online media, and learning support. The online resources factor assessed the effective provision of learning materials, recommendations of learning sources, and opportunities for collaboration. All items were measured using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The study aimed to examine how OCALR factors contributed to students’ perceived learning effectiveness. Multiple Linear Regression (MLR) analysis using the stepwise method was employed to identify the relative contribution of each predictor variable. Missing data were handled using listwise deletion. Regression coefficients (β), t-values, and p-values were used to interpret predictor effects, while model performance was evaluated using the coefficient of determination (R²), adjusted R², and the F-statistic. Assumptions of regression analysis, including multicollinearity and residual normality, were examined using variance inflation factors (VIF), tolerance values, and residual diagnostics, following established statistical guidelines (Field, 2009). All analyses were conducted using SPSS version 29.0.

This quantitative study examined the effectiveness of OCALR for female college students in a remote mountainous area of Nakhon Ratchasima Province, Thailand, using Multiple Linear Regression (MLR) analysis. Data were collected through a validated OCALR survey instrument and analyzed using a stepwise MLR approach to identify the most significant predictors of students’ perceived learning effectiveness in online learning environments. The MLR results indicated that three factors were statistically significant at the .05 level: effective access to the internet for learning, quality teacher-student interaction in online teaching, and the recommendation of online learning resources. The final regression model explained 29.3% of the variance in students’ learning effectiveness (Adjusted R² = 0.293), reflecting a moderate level of explanatory power. Among the predictors, teacher-student interaction demonstrated the strongest positive effect, underscoring the critical role of instructional presence, timely feedback, and meaningful interaction in supporting effective online learning, particularly in geographically remote contexts. Effective internet access also showed a positive and significant contribution, highlighting the importance of reliable digital infrastructure in enabling students’ participation, engagement, and learning continuity. In contrast, the recommendation of multiple online learning resources exhibited a negative relationship with learning effectiveness. This finding suggests that excessive or insufficiently guided exposure to online platforms may overwhelm learners and reduce perceived learning outcomes, emphasizing the need for structured and pedagogically guided integration of digital resources rather than an overabundance of platforms. Overall, the MLR findings confirm that the effectiveness of OCALR in remote higher education settings is fundamentally driven by reliable internet accessibility, high-quality instructional interaction, and intentional management of learning resources. These results offer important implications for strengthening internet support and digital infrastructure, as well as for curriculum design, instructional planning, and educational policy, particularly for institutions seeking to promote effective, equitable, and sustainable online learning opportunities in remote regions.

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