The state of education in the US is a contentious subject due to the continuous decline of student performance in nearly all states. Texas shows some of the worst results since at least 2017, scoring poorer than the last year for 4 years in a row in nearly every subject except for mathematics, which managed to remain on a relatively stable level throughout these years (Sharpes, 2020). The failing of students could be attributed to many factors, including teacher negligence, the lack of funding, the overall increases in standards of education, and other factors (Sharpes, 2020). While they require a systemic approach, there is a need to improve student preparation for STAAR exams here and now. The purpose of this paper is to present a mentorship intervention for 8th-graders with the intent of increasing their readiness and their knowledge levels to effectively pass the required state exam.
Modern education in Texas and other parts of the US is associated with an increasing workload on teachers. In addition to managing significant amounts of after-class activity in order to account for individual differences of pupils, connections with parents, and all kinds of paperwork, they are required to manage classes with many children in it (Sharpes, 2020). The average class size for Texas is 22-24 students, whereas the recommended size for optimal learning experience is 17 (Sharpes, 2020). These factors may have contributed to the increasingly poor performance of students throughout 2017-2020 (Sharpes 2020).
Students in schools are not getting enough time with teachers one-on-one due to the overloading with assignments and increased numbers of children in class demanding attention. While a systemic solution is sought and implemented, other measures have to be implemented to increase the success rates of students getting ready for STAAR tests. Failure to do so would result in the continuing degradation of grades with far-reaching consequences for graduation and college attendance.
Rationale for Study
One-on-one mentoring has the potential to make up for the lack of in-depth understanding of the subjects as well as the absence of focused educational attention on individual students’ learning process. It would help individuals stuck behind everyone else to catch up faster and increase their chances of succeeding in STAAR tests. The effectiveness of mentoring as a method would show if it is feasible to use as a long-term solution for students lagging behind.
Mentoring and Knowledge Transfer
Mentoring has several strong sides in comparison to typical class-based studies. According to Johnson and Lamprey (2010), mentoring achieves good results in sharing knowledge in connection to the life experiences of the mentor. It relies heavily on forming and maintaining a trusting relationship between the students and the mentors, the importance of which increases with at-risk learners. According to Robinson (2014), a mentoring learning process relies on several events that achieve reliable transfer of knowledge in skills. As the process progresses and the child sees success, their relationship with the mentor further strengthens, forming the base for present and future academic achievement.
Effectiveness of Mentoring in Improving Academic Performance
Mentoring is widely accepted as a solid practice to improve individual performance. Hagen-Hall and Verhaart (2008) report that mentoring programs help determine the main issues of personal education, as well as highlight the predictors for personal and academic success. These results are mirrored by Ismail, Jui, and Kho (2014), who maintain that mentoring programs allow for utilizing more effective communication and support methods tailored to a specific student. This improves academic performance by ensuring the better absorption of the learning material.
School-Based Mentoring Programs
School-based mentoring programs are some of the most available in contemporary educational practice, with many teachers engaging in mentoring their tutors. According to Gordon, Downey, and Bangert (2013), school-based mentoring programs not only achieve positive educational outcomes for students on their own, but also improve the quality of class-based education associated with the same teacher. In addition, SBMPs allow for matching students with non-parental adult figures, which could lead them by example, acting as role models and providing a positive influence for the youth (Schnautz, 2014).
School-based mentoring programs are the optimal medium of improving student performance. They allow for a connection with class-based studies and enable pinpointing the issues in the learning process that individual students have. In addition, they enable the pair to construct a meaningful relationship with one another, with the mentor acting as a role-model for the mentee. The transfer of knowledge is also improved as a result of a personalized approach.
The study will include up to 10 students that are lagging behind the rest in terms of academic performance. The selection of individuals will be based upon the teachers’ recommendations, in order to ensure that the ones struggling the most receive mentoring. The number of students is justified by the fact that one-on-one tutoring requires a significant number of staff members involved. Children will be selected to equally represent both genders and racial makeup percentages, to achieve maximum representability.
The study will follow a mixed-methods design due to the necessity of combining quantitative and qualitative methods of research to understand the effectiveness of mentoring in a chosen school setting. Surveys will be used as a means of determining which teachers and students are the most suited to be involved in the study. Interviews with open-ended questions will be the primary instrument of qualitative data retrieval.
Qualitative and quantitative data would be collected through several means, including STAAR test scores, surveys, report cards and progress reports, journal reflections and logs, as well as evaluations and interviews. Additional data would be collected from peer-reviewed literature sources, in order to provide an overarching framework and inform the study. The availability of various sources of data would ensure a holistic response and reduce the chances of bias associated with the inherently qualitative topic.
Data will be analyzed utilizing standard means of statistical significance. Triangulation would allow relating quantitative data with literature findings as well as with interviews and journal reflection logs. The primary criterion of success or failure would be the comparison of STAAR test scores of students with previous years’ results, with the increases attributed to the mentoring program. Additionally, an internal consistency analysis will be made in comparison with the student’s overall test scores in disciplines of interest, meant to ensure that the overarching progress is indeed present. Qualitative analysis of logs and interviews would help gouge the perceptions of the program, providing important insights on how the intervention is perceived.
- Gordon, J., Downey, J., & Bangert, A. (2013). Effects of a school-based mentoring program on school behavior and measures of adolescent connectedness. School Community Journal, 23(2), 227-250.
- Hagen-Hall, K., & Verhaart, M. (2008, July). Mentoring students to improve academic performance. In Proceedings of the 21st Annual Conference of the National Advisory Committee on Computing Qualifications Conference, Auckland, New Zealand (pp. 4-7).
- Ismail, A., Jui, K., & Kho, M. (2014). The role of mentoring program in enhancing mentees’ academic performance. Journal of Education and Learning, 8(1), 13-22.
- Johnson, K. C., & Lampley, J. H. (2010). Mentoring at-risk middle school students. SRATE Journal, 19(2), 64-69.
- Robinson, J. (2014). Mentoring program guidance and program plan. Washington, DC.
- Schnautz, B. M. (2014). The effects of school-based mentoring on student achievement for junior high school students (Doctoral dissertation).
- Sharpes, D. K. (2020). Education and the US Government. Routledge.