This study investigates interrelationships among nine dimensions of online learning readiness and their implications for distance education administration. Using a dataset of over 50,000 students from multiple higher education institutions, correlational and inferential analyses were conducted to examine associations among self-motivation, self-management, learning preferences, and technology-related competencies. Results revealed a strong correlation between Technology Skills and Course Management System Skills (r = .632), highlighting the synergy between general technical competence and platform-specific fluency. Moderate correlations were observed between Self-Motivation and Self-Management (r = .424), indicating behavioral and motivational interdependence. Additional analyses demonstrated statistically significant differences in readiness across both age and gender groups. Younger participants reported higher levels of Self-Motivation, Technology Skills, and Course Management competencies, whereas older participants scored higher in Self-Management, Social Interaction, and Reading/Visual dimensions. Gender analyses revealed small but significant effects, with females scoring higher in Self-Motivation, Self-Management, and Text-Based Learning Preferences, and males slightly outperforming females in Visual Learning dimensions. These findings underscore the value of readiness analytics for institutional decision-making, faculty development, and learner support strategies aimed at improving online learning outcomes. Keywords: online readiness, correlation analysis, technology skills, distance education management, gender differences, age differences, self-motivation, self-management, learning preferences
This article introduces the Engaging with Content Holistically Online (ECHO) instructional framework, designed to guide faculty and instructional designers in creating transformative, student-centered online courses in higher education. ECHO provides scaffolded templates, guiding questions, prompts for using AI as a thought partner, and practical strategies for course design and implementation grounded in the Community of Inquiry and Technological Pedagogical Content Knowledge (TPACK) models. This framework emphasizes structured pedagogy, reflective practice, and contextualized design, enabling institutions to build cohesive online programs that promote engagement, critical discourse, and transformative learning. Implications for online program administration and faculty development are discussed.
This action research study evaluated and enhanced the Program Curriculum Deep Dive (PCDD) process to improve a bachelor’s degree program in healthcare administration at a private online college. Using a mixed-methods approach combining document analysis and a stakeholder survey, researchers examined cross-functional collaboration between academic and industry experts to modernize course content. Analysis revealed four key findings: (1) participants valued structured process organization; (2) personalized, collaborative support contributed to meaningful stakeholder engagement; (3) faculty perceived their contributions as instrumental in enhancing industry-curriculum alignment; and (4) faculty believed their curriculum changes resulted in improved student career preparedness. The study's systems thinking framework emphasized the interconnected nature of curriculum elements, while the action research methodology facilitated continuous improvement through iterative cycles of planning, implementation, and reflection. This research addresses the critical need for healthcare administration programs to bridge the preparation-practice gap through authentic learning experiences while navigating the unique challenges of online education. Recommendations include maintaining collaborative structures, emphasizing real-world applications, diversifying assignments for skill development, and documenting successful processes for institutional replication. Keywords: curriculum development, course review, higher education, action research
Hiring online adjunct faculty in higher education continues to grow, encompassing nearly half of the overall faculty population. As four-year institutions rely on the benefits of adjunct faculty, they must also invest in their orientation and continuous development. Existing literature confirms the varied approaches to supporting adjunct faculty, the deficiency in coordinated programming, and reveals a lack of understanding in adjunct faculty's perception of training delivered. Using a qualitative phenomenological design, this study explored the gap between the onboarding and professional development an institution provides and the online adjunct faculty’s perception of its effectiveness. The research questions explored the lived experiences of adjunct faculty receiving and administrators managing the training. To better understand the barriers to developing comprehensive training, both perspectives contributed to the body of literature on this topic. The study was conducted with participants from two small liberal arts universities in the Midwest by conducting direct interviews with three administrators and 25 online adjunct faculty. The findings revealed eight themes about the phenomena of adjunct faculty onboarding and professional development, indicating that diverse perceptions among adjunct faculty highlight the challenge of creating effective training programs. However, academic leaders can overcome this by listening to adjuncts and improving processes. Adjuncts reported that receiving clear expectations, a thorough orientation to the LMS, and connecting with support staff can boost satisfaction and readiness. Results suggest that a structured approach to assessing training needs and effectiveness provides valuable insights into the most effective training program design. Keywords: Adjunct faculty onboarding and professional development, Adjunct faculty training, Adjunct faculty support, Designing comprehensive contingent faculty training, Higher education
With the development and availability of AI models there is concern about AI plagiarism in higher education. To help address this challenge, AI detectors such as Turnitin have been created to help faculty assess the presence of AI plagiarism in various assignments. This study aims to present faculty-student communication strategies that in combination with flexible use of Turnitin may help address AI plagiarism in higher education. To this end, this study involves an exploratory content analysis of a sample of 149 cases of AI-related plagiarism from 35 undergraduate social science course sections, with 901 enrolled students across three universities in the Southwest. Three instructors identified cases occurring in April 2023 through October 2025. All of these cases operated under the syllabus stipulation that AI should not be used to directly generate assignment text. Instructors used the Turnitin AI detector to help identify potential cases where the student used AI to compose major portions of a written assignment. Out of 149 cases of AI-plagiarism, only one case involved denial of misuse of AI. The 149 cases of AI-plagiarism were generated by 142 individual students. Students flagged generally did not repeat AI plagiarism in the classes taken with the instructors involved in this study. We present a basic statistical summary of characteristics of the cases identified. In addition, the content analysis identified five recurring themes reflective of various communication strategies that seem helpful when coupled with the flexible use of the Turnitin AI detector. Such strategies are illustrated via actual examples of instructor-student discussions. We conclude that utilizing the Turnitin AI detector, along with certain communication strategies, might be an effective way to detect and reduce the frequency of AI plagiarism in courses.
