This session shares findings from a study of 52,426 students on online learning readiness. Results reveal strong connections between technology skills and course management, along with notable demographic differences. Attendees will explore key readiness factors, practical implications, and strategies to empower diverse learners in online education.

Topic and Relevance

The global growth of online education continues to demand evidence-based insights into student readiness for digital learning environments. Our session presents results from a correlational and group-difference analysis of more than 52,000 students, exploring nine readiness factors—Self-Motivation, Self-Management, Need for Instructor Feedback, Peer Interaction, Text-Based Preferences, Visual Preferences, Auditory Preferences, Technology Skills, and Course Management System Skills—alongside demographic variables of Gender and Age.

This research contributes one of the largest empirical examinations of online learning readiness to date, providing original findings that are directly relevant to faculty, administrators, instructional designers, and technologists who aim to improve student success in online and blended learning contexts.

Key Findings

1. Strong correlations (|r| ≥ .50): Technology Skills (D8) and Course Management System Skills (D9) demonstrated a strong positive relationship (r = .632*), emphasizing the synergy between general technical competence and platform-specific fluency essential for online learning success.

2. Moderate correlations (.30 ≤ |r| < .50): Self-Motivation and Self-Management were moderately correlated (r = .424*), reflecting the interdependence between students' internal drive and their ability to organize learning behaviors (Lee, 2015; Horzum et al., 2015).

3. Weak but significant associations (.10 ≤ |r| < .30): Small but significant relationships were found between Age and Text-Based Preferences (r = .149*, Spearman's rho) and Gender and Text-Based Preferences (r = .100*, point-biserial) (Hergüner et al., 2020). A negative relationship between Need for Instructor Feedback and Technology Skills (r = –.195*), suggested that students with greater technological confidence tend to rely less on instructor intervention (Nguyen et al., 2022; Gupta, 2024).

4. Group differences by Age (ANOVA results):
One-way ANOVA analyses across seven age categories (Under 18 to 66+) revealed significant differences in all nine readiness dimensions (p < .001). Younger participants (Under 35) showed higher scores in Self-Motivation, Listening, Technology Skills, and Course Management, while older participants (36+) scored higher in Self-Management, Social Interaction, and Reading/Visual dimensions. Effect sizes (η² = .006–.030) were small to moderate, indicating practical yet modest group distinctions (Berkling et al., 2021; Hergüner et al., 2020).

5. Group differences by Gender (t-test results):
Independent samples t-tests indicated significant gender differences in seven of nine dimensions (p < .001). Females reported higher means in Self-Motivation, Self-Management, Text-Based Learning, and Listening, whereas males scored higher in Visual Learning dimensions. No significant gender differences emerged for Technology Skills and Course Management System Skills (p > .05), suggesting parity in technological readiness across genders (Yaseen et al., 2024; Gupta, 2024).

These categories of statistical findings will be discussed and interpreted in accessible language, showcasing the nuanced relationships between demographic and readiness variables. Both the initial Pearson matrix and adjusted interpretations will be shared to demonstrate transparency and best practices in statistical reporting.

Engagement Strategy

The session will actively involve participants by:

1. Using live polls to gauge perceptions of readiness at their institutions.

2. Facilitating small-group reflection on applying findings (e.g., technology–autonomy links, demographic patterns).

3. Displaying heatmaps and correlation tables, asking participants to interpret patterns before results are explained.

4. Extending a collaborative opportunity: Each participant will be offered 100 free student seats in the readiness tool if their institution chooses to collaborate in a follow-up study. This gives attendees both immediate data insights and a tangible resource for applied research.

Takeaways

1. Understand which readiness factors are most strongly interrelated and how they collectively influence online learning success.

2. Translate empirical findings into actionable strategies for learner support, advising, and instructional design interventions.

3. Reflect on institutional practices and develop readiness-informed action steps to strengthen student engagement and retention.

4. Gain access to 100 complimentary student seats for readiness assessment through participation in a follow-up institutional collaboration.

Contribution to the Field

This study offers large-scale empirical evidence on how student motivation, management, and technology competencies interact with demographic characteristics to shape online learning readiness. The results extend current research by demonstrating how readiness analytics can inform institutional strategy, faculty development, and student support systems. The combination of statistical rigor, demographic insights, and practical applications makes this session valuable to researchers, administrators, and practitioners alike.

References

Berkling, K., Saller, D., & Winter, C. (2021). Online learning readiness: Determining key factors that distinguish university students who feel comfortable with online studies. In L. Gómez Chova, A. López Martínez, & I. Candel Torres (Eds.), ICERI2021 Proceedings (pp. 6962–6970). IATED Academy. https://doi.org/10.21125/iceri.2021.1575

Gupta, S. (2024). The relationship between online learning readiness and cognitive load in college students. Frontiers in Health Informatics, 13(2), Article 415. https://doi.org/10.25259/FHI_13_2024

Hergüner, G., Son, S. B., Hergüner Son, S., & Dönmez, A. (2020). The effect of online learning attitudes of university students on their online learning readiness. Turkish Online Journal of Educational Technology-TOJET, 19(4), 102–110.

Horzum, M. B., Kaymak, Z. D., & Gungoren, O. C. (2015). Structural equation modeling towards online learning readiness, academic motivations, and perceived learning. Computers in Human Behavior, 49, 236–243. https://doi.org/10.1016/j.chb.2015.03.032

Lee, C. Y. (2015). Changes in self-efficacy and task value in online learning. Distance Education, 36(1), 59–79. https://doi.org/10.1080/01587919.2015.1019967

Nguyen, M. T., Tran, B. T., Nguyen, T. G., Phan, M. T., Luong, T. T. T., & Le, D. D. (2022). Self-control as an important factor affecting the online learning readiness of Vietnamese medical and health students during the COVID-19 pandemic: A network analysis. Journal of Educational Evaluation for Health Professions, 19, Article 22. https://doi.org/10.3352/jeehp.2022.19.22

Yaseen, S., Saeed, A., Kohan, N., Arif, S., Qureshi, S., & Ilyas, M. (2024). Assessment of online learning readiness among MBBS students: A correlational study. Annals of King Edward Medical University, 30(4), 402–408. https://doi.org/10.21649/akemu.v30i4.5683

Cheng-Yuan (Corey) Lee

Professor at Coastal Carolina University

Dr. Lee earned an M.S. degree in Instructional Technology from the University of Tennessee, Knoxville in 1999 and a Ph.D. in Curriculum and Instruction with an emphasis on Instructional System Design from the University of Central Florida. Since 2010, he has taught at Coastal Carolina University. Throughout his career in teaching, he developed strong interests in the areas of distance education, mobile learning, interactive multimedia, and graphic/website design. In his classes, he introduces a wide range of software applications and open-source packages to students, allowing them to master computer-based tools used in the design and creation of electronic media, such as electronic images, sounds, videos, text, and motion.

Dr. Lee also leads a research-based project (eLearnReady - https://elearnready.com/). eLearnReady is a free, web-based tool designed to analyze students’ preparedness for online learning. After students complete the survey, eLearnReady analyzes their responses to identify their strengths and areas for improvement for online learning. The survey results are then provided to students as a comprehensive report, complete with study tips and videos that demonstrate methods for being a successful online learner. Given its usefulness and ease of use, to date, over 94,000 students have completed the eLearnReady survey across multiple states since eLearnReady was first introduced at the Online Learning Consortium (OLC) Innovate in April 2017. Some institutions of higher education have embedded eLearnReady into college and transfer student orientation sessions, freshman seminar classes, and other online courses to support students.

Sherri Restauri

Faculty, Department of Psychology at Coastal Carolina University

Dr. Sherri Restauri is a faculty member in the Department of Psychology at Coastal Carolina University, where she teaches upper-level courses in Developmental Psychology, including special focus on Child Psychology, Adolescent Development, and Gerontology. In her role as a developmental psychologist, she advocates for enhanced understanding of short- and long-term impacts of trauma, as well as provides training and support to faculty, staff, and other professionals regarding a trauma-informed perspective in best supporting others. In addition to her role as a faculty member, Sherri previously served in Digital Learning administration in Higher Education for over 20 years, aiding universities in successfully launching and supporting successful digital learning as well as digital access and inclusion programs. Dr. Restauri received the 2021 OLC Gomory-Mayadas Leadership Award in Higher Education for her contributions and in recognition of her leadership in the online education community, including her work on digital equity, accessibility, and online best practices in teaching and learning. Serving now as a full-time educational consultant as well as a part-time faculty member, she is actively involved in assisting campuses and organizations across the globe with enhancing digital access, inclusion, and equity opportunities for learners of all ages, backgrounds, and neurotypes.