Factors that Influence Communication in eMentoring with Urban Alternative High School Students

Edward Wilson Jr., Ph.D., The University of Kansas, 2013.


School-based mentoring has emerged as a means of improving academic outcomes for many disadvantaged youth. Particularly, school-based eMentoring has been utilized to eliminate barriers of distance and time, while covering academic content. This mixed methods study investigated the factors that influence communication in eMentoring.

A convergent parallel mixed methods design (Creswell, 2010) was utilized. Participants were 17 eMentoring pairs for the quantitative analysis and five of the eMentors were the source of the qualitative data. The eMentoring pairs were classified into multiple groups based on match rationale (intentional or arbitrarily matched), pair classification (managers or non-managers paired with high school juniors or seniors), and pair gender(all male pair or all female pair). Email response time and communication frequency were analyzed using Independent t-tests, One-Way ANOVAs, and a Repeated Measures ANOVA. A thematic analysis of the qualitative interview data revealed detailed information regarding perceptions of communication frequency, relationship quality, and mentor engagement. The separate findings were then merged for a final interpretation.

Results indicated that female eMentoring pairs (M=18.63) had a higher average number of emails exchanged at the end of the program than those that were male eMentoring pairs (M=12.88); (t(14) = -1.190, p = .254), and Cohen’s effect size (d=.60) was moderate to large. The Manager and High School Senior group (M=28) had a significantly higher difference in total number of emails than the Manager & Junior group (M=6.75); (f=4.898, p=.017). There was a statistically significant difference in email response time in days among all pairs between time period 1 (M=4.220) and time period 2(M=15.570); (f=5.300, p=.015). Intentionally matched (based on career paths and known interests) pairs (M=19.6) had a higher average number of email exchanges than arbitrarily matched pairs (M=12.3); (t(15) = -1.647, p = .120) and Cohen’s effect size (d=.80) was large. There was a statistically significant difference in average number of emails exchanged within both groups between time period 1 (M=7.065) and time period 3(M=4.368); (f=5.178, p = .012). Additionally, the flexibility of the program and ability to set goals with mentees engaged the mentors. Being able to relate to the mentee, having face-to-face visits, using interaction strategies and removing limitations on communication were cited as positive influences on relationship quality. Communication frequency may be influenced by gender, face-to-face visits, and unexpected personal events. Making adjustments to the program structure based on pair preferences may be the key to effective eMentoring.

To maximize the academic and social impact, eMentoring programs should explore methods to capture mentor and mentee perceptions of the relationship over time to ensure matches are progressing. Using personal information to match pairs, working to achieve short and long-term goals, and monitoring outcomes are of critical importance to ensure efficient and effective eMentoring. Reducing the programmatic limitations to maintain the flexibility to communicate using multiple methods may be the key to ensure an effective communication frequency and positive relationship development in eMentoring programs.