Mentorship
and Tutoring: The effects of community members’ guidance on at-risk middle
school students
At Murphy Middle
School, half of the economically disadvantaged students were not proficient on
state testing, such as Texas Assessment of Knowledge and Skills (TAKS) and
Modality Assessment Profile (MAP) tests. To provide support to our economically
disadvantaged at-risk students, two programs were created, a peer tutoring and
mentorship program. Each program consisted of a partnership with the community.
The peer-tutoring utilized high school volunteers to assist with schoolwork,
and the mentorship program utilized community volunteers to discuss study
habits, organizational skills, goal setting, college preparation, and career.
The additional support, was created to increase academic achievement and
college readiness in our academically disadvantaged at-risk students.
Background
The
research study was conducted at Murphy Middle School, in Plano Independent
School District (PISD), which serves sixth through eighth grade students. The
school is located in Murphy, TX, which is east of Plano, Texas. In the 2011 to
2012 school year, the campus’ student population was 1010 students. The
demographics of the campus student population was 53.2% White, 21.5% Asian,
11.4% African American, 9.2% Hispanic, 2.7% limited English proficient
students, and 9.8% economically disadvantaged.
At
the beginning of the 2011 to 2012 school year, the campus’ Adequate Yearly
Progress (AYP) report card, TAKS and MAP scores were reviewed from the previous
year. While analyzing the data to determine the needs of the students, it was
noted that 50% of the economically disadvantaged students were not proficient
in at least one TAKS test and 10% were not proficient in a minimum of two TAKS
tests. Based on the data, a dual program, a mentorship and tutoring program,
was constructed to increase academic achievement and college readiness, which
would partner with community members, parents, high school students, and peer
tutors.
Involved
in the study were the assistant principal, art teacher, special education lead,
Parent and Teacher Association (PTA) president, community members, high school
students, and middle school students. In the study, the community members
provide guidance to the students by exploring occupational interests,
continuing educational options, and life skills. The school principal approved
the program and provided the appropriate contacts to begin the process of the
mentorship program.
The
objectives for the action research mentorship and tutoring program was
first that 80% of the economically
disadvantaged “high risk” students, who failed two or more state tests, were to
be matched with a mentor by November of 2011. The second objective was that the
student would participate in the weekly peer-tutoring program. The final
objective was that the economically disadvantaged students in grades six
through eight would meet a 90% passing rate on all the remaining 2011-2012 core
classes, over a duration of 30 weeks.
Prior
to this study, the middle school has never asked for academic or behavioral
support from community volunteers beyond the Parent-Teacher Association’s (PTA)
assistance in extra-curricular activities and office errands. The mentorship
and tutoring program was the first partnership with the community to provide
additional educational support to the students. When advertising the chance for
the community to participate in a mid-day program, 34 community members
volunteered to commit one day a week within the school year to mentor a student
“in-need”.
Literature
Review
In
Mentorship for Resiliency, Marc Freedman
(1992) described the current society in the United States as becoming
increasingly absent from children, making it difficult for children to spend
quality time with caring adults. Freedman (1992) stated that the number of
divorces, absent fathers-figures from children’s lives, and parents work hours
are all increasing. In schools, classroom sizes and school counselors’
caseloads were increasing, which made it hard for teachers and counselors to
spend quality time with their students. If children were not receiving support
at home or at school, the children were seeking acceptance elsewhere. In 1991,
Arthur Levine, from Columbia University, conducted a study of 24 young adults
who came from poverty to Ivy League universities (Freedman, 1992). The common
denominator between all the students was the presence of a caring adult. The
power in making a difference is not in making rules or regulations, but in the
time invested in connecting with a child (Freedman, 1992).
When
developing the curriculum for the mentorship program for economically
disadvantaged students, Ruby Payne’s (2001) A Framework for Understanding
Poverty was used to provide instruction on
the appropriate techniques for the mentors in the program to utilize. Payne
(2001) discussed techniques to improve academic achievement with generational
poverty, characteristics of cultural poverty, and how to become a support
system for those in poverty. By breaking the generational patterns, such as
beliefs in “bad luck,” family structure, time orientation, financial spending
patterns, and the sense of community, the mentorship program must provide a
support system, role models, successful behavior, and promotion of education to
prepare the students for life after school (Payne, 2001). As a mentor, one must
be aware of a cultural disconnect between the adult and the child. Each mentor
must understand that there are gaps in generational values, ideas, language,
expectations, attitudes, beliefs, and behaviors. Other areas of potential cultural
gaps are ethnic and social-economic. Not every student is able to be matched
with an adult of the same ethnicity or economic status. The best strategy for
an adult mentor is to identify the gaps, accept the differences, educate them
on the students’ backgrounds, and communicate through critical thinking instead
of emotional responses (Wynn, 1992).
In
“How to build a successful mentoring program using the elements for effective
practice” (MENTOR, 2005), the literature explains that each program needs to
consist of data driven interviews, surveys, and records to evaluate the types
of activities. Additionally, the quality of the activities, the length of the
mentor relationship, frequency and duration of the meetings, and the perception
of the relationship with the student and mentor all need to be evaluated
(MENTOR, 2005). Following these
recommendations, the middle school mentorship program gathered outcome data
from state testing scores, school records, and classroom grades to determine if
the student were improving their academic understanding.
When
constructing a peer-tutoring program, the goal was to use the most effective
and effortless educational resource as possible. Jackson, Johnson, and Askia (2010)
described a peer-teaching program for middle school students, which occurred in
the classroom. In the program, students became the teacher and presented the
self-prepared material to their peers. In the peer-teaching program, the
students were engaged and motivated during the teaching sessions. The cause of
the increase in student motivation and engagement was based on the
peer-teacher’s understanding of the youth culture, communications styles, and
the culture of empowerment, created by the teacher (Jackson et al., 2010). Ding and Harskamp (2011) believed that
students generated a negative perception of school based on the lack of
understanding of studying techniques. To prove their hypothesis, a study was
performed in a secondary school with eleventh grade students. The study
analyzed 96 chemistry students, who were divided into three different study
groups. The first study group was individual learners, the second group was
collaborative learning groups, and the third was a peer-tutoring study group.
The results of the study showed that the peer-tutoring groups produced higher
scores on chemistry tests, increased confidence in learning, created a stronger
interest in the subject matter, and constructed a higher value of the taught
material, compared to the collaborative learning and individual studying groups
(Ding & Harskamp, 2011).
Similar benefits have been shown in tutoring programs,
where the tutor is an adult. Diaz (2009) stated that a successful connection
must be created to engage the students. In working with youth, the tutor must
be flexible, interested in the student, and providing positive communication
(Diaz, 2009).
Action Research Design
Utilizing
the research on mentoring and peer-tutoring, and analyzed data from the middle
school’s most recent TAKS and MAP tests, eligible subjects were determined. The
programs were set initiated after partnering with the community for volunteers.
Data was analyzed at the end of the school year to determine efficiency of the
programs, and potential for further future developments.
Subjects
The
target population for the study was classified as economically disadvantaged,
at-risk, sixth to eighth grade students. The subjects were selected to
participate in the mentorship and tutoring programs due to low TAKS scores and
MAP test scores. Reading, mathematics, and science TAKS scores, and reading,
math, science, and language usage MAP scores were analyzed to determine
subjects’ needs.
The TAKS
Proficiency standards, from Texas Education Agency (TEA), for sixth grade
reading were a score of 644 and sixth grade math were 637. Proficiency scores
for seventh grade reading were 670, seventh grade math were 670. Eighth grade proficiency
scores were 700 for reading, 700 for math, and 2100 for writing.
To interpret the
MAP scores of the students, each MAP score was compared to a grade level
proficiency range. For the research study, the proficiency range for MAP
reading scores for sixth grade students were between 204 and 212, seventh grade
scores ranged from 208 to 216, and eighth grade scores were 212 to 220. The
proficiency range for MAP math scores for sixth grade students were 212 to 220,
seventh grade scores were 217 to 226, and eighth grade scores were 223 to 232.
The MAP science proficiency range for sixth grade students was 200 to 205,
seventh grade scores were 202 to 208, and eighth grade scores were 203 to 210.
The proficiency range for MAP language usage for sixth grade students were 202
to 209, seventh grade scores were 206 to 213, and eighth grade scores were 208
to 216.
Any TAKS or MAPS
score below the proficiency range qualified the student as an “at-risk”
subject. If a student had more than one “at-risk” subject, the student
qualified as “high-risk”. There are 99 economically disadvantaged students
enrolled at the middle school. Of the 99 students categorized as economically
disadvantaged, 42 students were defined as “at-risk” and, of the 42 “at risk”
students, 13 students were defined as “high risk”. Each of the 42 “at-risk”
students was invited to the tutoring program and the 13 “high-risk” students
were invited to both the mentorship and the tutoring programs. Of the 13 “high
risk” students, 8 participated only in the peer-tutoring program, 2
participated only in the mentorship program and 3 “high risk” students
participated in the mentorship and tutoring programs.
Procedure
In
creating the tutoring program, the local high school National Honor Society
(NHS), the campus National Junior Honor Society (NJHS), and the Peer Assistance
and Leadership (PAL) programs were contacted to gain peer tutors. Each
economically disadvantaged “at-risk” student was invited through both a written
letter and verbally to participate in the morning tutoring program. The
tutoring program occurred twice a week in 35-minute intervals. During each
tutoring session, the tutors or tutees were required to sign a piece of paper
indicting they attended the tutoring session. The tutees were asked to take out
their homework. Each “at-risk” student was required bring homework to the
tutoring session for the peer tutors to provide assistance. The goal for the
program was to match one tutor with one student at all times. Throughout the
school year, the economically disadvantaged students were never required to be
at the tutoring sessions. All attendance was voluntary. At each tutoring
session, food was provided for both the tutors and tutees.
For
the mentorship program, in October of 2011 an informational meeting was
advertised through the PTA. The community volunteers were provided with an
informational meeting to communicate expectations, procedures, district
policies, goals, and the vision of the program. After the information of the
program was provided, volunteer questions were answered and the community
volunteers were asked to sign a document stating they would commit one day a
week for an entire school year, abide by district policies and state laws, and
complete a district background check. Once all signed volunteer commitment
contracts and background checks were received, letters were sent to the parents
of the targeted students. In the letter, the parents were given information
about the program, the time of the meetings, the duration of the program, the
screening of the volunteers, the staff members involved, and the goals for each
participant. Included with the informational letter was a release form for the
parent to sign, indicating that they were providing parent consent for their
child to participate in the mentorship program. In November of 2011, the
community volunteers were paired to a student based on gender. The community
volunteer decided the day that worked best for them and, each week, the mentors
met with their designated student during the student’s lunch, which was 30
minutes in length. During the lunch period, the mentor followed provided
curriculum, which covered a variety of academic subject matter. The curriculum
topics included occupational interests, continuing education, college funding,
goal setting, organization, and other life skills. The program’s curriculum was
created using the Mentorship Partnership of Long Island’s “Discovering the possibilities:
‘C’ing your future” (n.d.) as a template, altered to meet the needs of the
campus. When the mentors arrive at the school, the campus secretary had the
volunteers sign in at the front office. Once the mentors signed in, the mentors
received a sticker, indicating the volunteers were community mentors, and the
mentors were given a folder with the curriculum material. The students had
passes, which allowed the student to leave a few minutes early to get their
lunch from the cafeteria and arrive to the school library as quickly as
possible. The mentors and students met in the library, which was supplied with
tables, chairs, computers, writing utensils, and paper, to have a quiet working
space without interruptions. In the library, the librarian, teachers,
counselors, or administrators rotated to serve as a resource and a monitor the
mentoring time. The resource person was responsible for monitoring the safety
of the students and mentors, and provides advice, materials, answers on curriculum,
or help with technical problems. Several of the economically disadvantaged
“high risk” students were in special education. For those students with special
needs, the special education teachers or paraprofessionals were available as a
resource for the mentor. During the time with the student, the mentors followed
the topics of the curriculum and the mentor related the material with the
student’s life.
The
program was constructed to function without any fiscal responsibilities. By
providing a meeting time during the student’s lunchtime, the largest expense,
transportation, was alleviated. The resources used for the mentorship project
were minimal due to the restraint on fiscal resources. The resources for the
project were the community volunteers, school library, schoolteachers, school
computers, pencils, paper, and highlighters. The school and the PTA funded
purchases, such as snacks, drinks, plastic utensils, and napkins. The greatest
resource for the mentorship program was time given to the students and the
curriculum.
Data Collection
The
data used for the research project was collected from state testing scores,
such as MAP and TAKS tests, and individual grades in core subjects, including
math, science, english, and history. TAKS and MAP scores were analyzed and used
to determine the “at-risk” and “high risk” students. The economically disadvantaged student’s individual grades
were used to determine the success of the programs, independently and
collaboratively.
Findings
The
student passing and failure rates are available in Table 1, before they
participated in either the tutoring program, the mentorship program, or both
programs. This chart displays the student’s grades in the first six weeks of
school, which is prior to the research study, and provides the number of core
class periods that the students passed and failed during this time period. The
group who only participated in the peer-tutoring group consisted of eight
students who passed a total of 31 classes and failed one class. The two students that only participated
in the mentorship program passed six classes and failed two classes. The three
students who participated in both the mentorship and tutoring program passed
thirteen classes and failed three classes. The passing percentage for the
tutoring program students was 97%, the mentoring program students was 75%, and
the duel program students was 81% prior to the start of the research study.
In
Table 2, the data chart provides the students passing and failure rates after
the students participated in either the tutoring program, the mentorship
program, or both programs. The chart indicates the number of classes the
students passed and failed in a 30 week span. The eight students who
participated only in the tutoring program, passed 192 classes and failed 18
classes. The two students who
participated only in the mentorship program passed 44 classes and failed four
classes. The three students who participated in both the mentorship and
tutoring program passed 69 classes and failed three classes. In the students’
core classes, the passing percentage for the tutoring program students was 91%,
the mentoring program students was 92%, and the duel program students was
96%.
Table
3 provides the 13 students in each program and the student’s average grades
before and after participating in the study. In Table 3, the students averages were
provided based on the core classes, including as math, science, english, and
history grades. The pre-program grades were the grades the students received
during the first six weeks of school, which was before the creation of the two
programs. The post-program grades were the average grades the student received
during the 30 weeks of participated in the voluntary programs.
Conclusion
Upon
the analysis of the study’s data, the partnership between the mentorship
program and the tutoring program provided the greatest gain in the student’s
academic achievement. The core class passing rate for the students who
participated only in the tutoring program decreased, while the students in the
mentorship program or in the duel program increased their passing rate in core
classes. The mentorship and tutoring generated data helped the campus decide
that the program could increase academic achievement through stable relationships
with appropriate role models and additional tutoring. Although the increased
student grades were minimal, the mentorship program provided a consistent adult
presence for the economically disadvantaged students. The mentors volunteered
their time to show the students they cared about their academic success and
future. The balance of providing adult support and academic tutoring provided
the largest increase among the studies participants. The students who received
tutoring but did not receive support from a mentor saw a decrease in their
grades throughout the tutoring program. The conclusion drawn from the data was
that tutoring was important, but middle school students needed adults to show
interest in their academic success to motivate, engage, and understand the
importance of their academics.
Recommendations
Due to the
programs’ short existence, the amount of data collected was minimal. In the
future, additional studies will need to include data from teachers, school
records, behavior referrals, classroom grades, state testing scores, and
surveys from parents, mentors, staff and students to determine a more accurate
conclusion on the effectiveness of mentoring and peer-tutoring programs. The
quantitative data in the study reflects the effects on the students’ grades,
but the study’s data does not reflect the qualitative data. An increase of
participants’ observations and interviews will provide data on the students’
enthusiasm, motivation, and engagement in the program and their academic
success. Additional studies will need to increase the sample size of students
and mentors to gain an extensive amount of data for analysis. With a small
amount of participants, the data may be skewed due to the large amount of
variables. For example, during the end of the research study, two of the
students were diagnosed as qualifying for special education. To create a larger
participation rate, parent contact is instrumental in the creating a positive
outlook in the program and in gaining permission for the students to
participate. During the study, letters and e-mail were used in parent
communication but phone conversations with the parent were increasingly
successful.
In addition to the
increase of participants and data, the study will need to manage the effectiveness
and efficiency of the mentors through the training of the mentors. The research
study must provide the mentors with guidelines for discussion and to provide a
direction for student improvement. Further development of mentor training
methods and resources needs to be implemented.
Although the study
was smaller than expected, the two programs created a culture of hope, good
will, and success. The economically disadvantaged students were provided with support
from their community and a sense of hope for their future. Based on the study
and the data provided, Murphy Middle School will continue to provide a
mentoring and tutoring program to their economically disadvantaged at-risk
students.
References
Diaz, R. (2009). After school
mobile literacy: Serving youth in underserved neighborhoods.
Teacher Librarian, 36(3), 37-38.
Discovering the Possibilities:
“C”ing your Future (n.d.). Mentoring
Partnership of Long
Ding, N., & Harskamp, E.
(2011). Collaboration and peer tutoring in chemistry laboratory
education. International Journal of Science Education, 33(6),
839-863.
Freedman, M. (2000). The politics
of mentoring: What must happen for it to work. In Henderson,
N., Benard, B., & Sharp-Light, N. (Eds.), Mentoring for resiliency: Setting
up programs for moving youth from “stressed to success” (23-31). Rio Rancho,
NM: Resilency in Action, Inc.
Jackson, Y., Johnson, T., &
Askia, A. (2010). Kids teaching kids. Educational Leadership, 68(1),
60-63.
MENTOR. (2005). How to build a
successful mentoring program using the elements for
effective
practice. Retrieved from http://www.mentoring.org/program_resources/elements_and_toolkits?eeptoolkit
Payne,
R. K. (2001). A framework for understanding poverty. Highlands, TX: aha!
Process, Inc.
Wynn, M. (1992). Empowering
African-American males: Teaching, parenting, & mentoring
successful black males. Marietta, GA:
Rising Sun Publishing.
Table 1
Student Passing and Failure Rates Before Program
Participation
|
|
# of
Stud.
|
PRE
|
|||||||||
|
Pass
|
Fail
|
||||||||||
|
M
|
S
|
E
|
H
|
T
|
M
|
S
|
E
|
H
|
T
|
||
|
Peer Tutoring
|
8
|
8
|
8
|
7
|
8
|
31
|
0
|
0
|
1
|
0
|
1
|
|
Mentor
|
2
|
1
|
2
|
2
|
1
|
6
|
1
|
0
|
0
|
1
|
2
|
|
Peer Tutoring and Mentor
|
3
|
3
|
4
|
4
|
2
|
13
|
1
|
0
|
0
|
2
|
3
|
Note. Grade for first
6 weeks of the school year
Table 2
Student Passing and Failure Rates After Program
Participation
|
|
# of
Stud.
|
POST
|
|||||||||
|
Pass
|
Fail
|
||||||||||
|
M
|
S
|
E
|
H
|
T
|
M
|
S
|
E
|
H
|
T
|
||
|
Peer Tutoring
|
8
|
48
|
48
|
48
|
48
|
192
|
9
|
2
|
4
|
3
|
18
|
|
Mentor
|
2
|
8
|
12
|
12
|
12
|
44
|
4
|
0
|
0
|
0
|
4
|
|
Peer Tutoring and Mentor
|
3
|
15
|
18
|
18
|
18
|
69
|
3
|
0
|
0
|
0
|
3
|
Note. POST = Average grade for last 30 weeks
of the school year
Table 3
Average Student Grades Before and After Participating in
the Study
|
Peer tutoring
|
PRE
|
POST
|
||||||
|
|
Math
|
Sci.
|
Eng.
|
Hist.
|
Math
|
Sci.
|
Eng.
|
Hist.
|
|
Student 1
|
95
|
74
|
88
|
81
|
79.5
|
85.4
|
81.8
|
74.2
|
|
Student 2
|
87
|
83
|
90
|
80
|
76
|
82.8
|
84.8
|
86.2
|
|
Student 3
|
80
|
77
|
99
|
80
|
81.6
|
84.4
|
94.4
|
86.4
|
|
Student 4
|
72
|
82
|
91
|
83
|
72
|
79.2
|
78
|
82.4
|
|
Student 5
|
74
|
94
|
91
|
84
|
68.6
|
81.8
|
79.4
|
81.6
|
|
Student 6
|
66
|
86
|
70
|
73
|
74.8
|
79.2
|
72.6
|
81.2
|
|
Student 7
|
75
|
82
|
70
|
74
|
68.8
|
72.6
|
71.4
|
66.2
|
|
Student 8
|
72
|
71
|
64
|
74
|
66.2
|
70.4
|
80.4
|
76
|
|
Mentorship
|
PRE
|
POST
|
||||||
|
|
Math
|
Sci.
|
Eng.
|
Hist.
|
Math
|
Sci.
|
Eng.
|
Hist.
|
|
Student 1
|
62
|
80
|
93
|
50
|
56
|
86.3
|
85.6
|
71.3
|
|
Student 2
|
70
|
91
|
93
|
80
|
71.6
|
87
|
85.2
|
81
|
|
Peer tutoring
and
Mentorship
|
PRE
|
POST
|
||||||
|
|
Math
|
Sci.
|
Eng.
|
Hist.
|
Math
|
Sci.
|
Eng.
|
Hist.
|
|
Student 1
|
75
|
60
|
81
|
70
|
79
|
72.4
|
83.4
|
79.4
|
|
Student 2
|
57
|
80
|
70
|
56
|
67.4
|
77.4
|
74.4
|
74.4
|
|
Student 3
|
79
|
70
|
89
|
66
|
71
|
70.4
|
77.6
|
66
|
Note. PRE = Grade for
first 6 weeks of the school year
POST = Average
grade for 30 weeks of the school year
