Intervention Programs on At-Risk Students in Rural Communities

Introduction

Background and Significance

Rural communities often face challenges that urban cities and suburbs do not have. Some of the issues are trying to recruit and retain high-quality teachers, not enough funding, inadequate supplies and tools and so much more. One major issue is assisting at-risk students to be successful and graduate. “Nationally, over 15 percent of the potential high school graduates dropout before graduation” (US Department of Education, 2015). With the national high school dropout rate being high, studies have found that rural school district have a higher graduation rate compared to urban areas. Even though the dropout rate is lower, rural communities have students that are considered at-risk for similar or/and different reasons. Little research has been conducted on the effectiveness of intervention programs for at-risk students in rural communities.

 Most rural communities do not have the resources for alternative schools. “Alternative schools address the issues specific to at-risk students, such as truancy, poor grades, and emotional health issues, and school programs can range from being more disciplinary to having a specific academic focus” (Szlyk, 2018, pg.2). In many areas, without extra funding, rural communities must implement an effective intervention programs for their at-risk students.

Statement of the Problem

At-risk students are described as those who are considered to have a higher probability of failing academically or dropping out of school. Students may be identified by teachers, administration, and/or parents. Some of the identifiers may be a combination of low academic achievement, low self-esteem, low socioeconomic status families, parents with low educational background, parents with no or low educational expectations for their child, and disciplinary and truancy problems.

Intervention programs are a mix of different methods and techniques to improve or change a habit to help at-risk students complete and graduate high school. “These include remediation programs, tutoring, child care services, medical care, substance abuse awareness programs, bilingual instruction, employment training, and close follow-up procedures on truancy and absenteeism” (Donnelly, 1987, pg.1). Successful programs will separate at-risk students, have a low student to teacher ratio, and provide additional services like counseling and academic monitoring (Donnelly, 1987).

Rural communities are usually farmlands found outside of cities and towns. According to the 2016 US Census, rural communities cover 97 percent of the nation’s land area but contain 19.3 percent of the population (US Census, 2016).

The purpose of this study is to investigate the effectiveness of evidence-based intervention programs, such as Check and Connect or the GradWay Program, on at-risk students in rural communities.

Literature Review

 At risk-students only represent a small percentage of the student body with a school district. School districts in urban and suburban areas often have access to a variety of resources and programs to help at-risk students. Van Norman, Nelson, and Klingbeil look at 3 different types of screening approaches to assist in identifying at-risk students in Single Measure and Gated Screening Approaches for Identifying Students At-Risk for Academic Problems: Implications for Sensitivity and Specificity (Van Norman, 2017). The three approaches studied were single screening, gated screening, and state scores used as predictive data. Results of the data showed that schools need to be selective in their screening practices. Using a combination of the screening tools will enable schools to make a more effective assessment on students being at-risk.

In the past last 20 years, Positive Behavior Support (PBS) has been used as school wide systems to support students. The study Schoolwide Screening and Positive Behavior Supports: Identifying and Supporting Students at Risk for School Failure by Walker, Cheney, Stage, and Blum looks at at-risk students within 3 elementary schools that implement PBS (Walker, 2005). PBS had 3 main tiers of intervention for students; primary, secondary, and tertiary. The primary or universal tier will meet approximately 80% of students and these students will not need further assistance. The secondary tier is more individualized and meets approximately 10% to 15% of students. These individualized interventions can be anything from social skill groups, school counseling programs, peer tutoring, after-school homework clubs and etc. (Walker, 2005). The finial tier known as tertiary is for approximately 5% of students and consist of comprehensive individual support. Researchers Walker, Cheney, Stage, and Blum found that two out of three schools studied had results that were very close to the established percentiles.

Rationale for the Study

Statement of Research Question (Qualitative)

 Despite all the studies done on intervention programs on at-risk students, there is little research done in rural communities. Using the qualitative approach, the research will explore how evidence-based intervention programs engage at-risk students, how evidence-based intervention program strategies improve academic success and how are students from rural communities identified as at-risk.

Method

Participants

 Participants will be selected from school districts located in rural communities with less than two hundred students per grade. Schools can be participating in PBS (Positive Behavior System) but the intervention program will be a separate program than PBS. All students classified as ninth graders and in their first year of high school (no repeat freshmen) in the school district will be considered. Special education students have additional resources and will not be considered since their caseload workers often have similar programs. The program will not be administered to other grades for the study since many rural schools cannot afford the resources for multiple grades. Administration, counselors, teachers, and/or parents will assist in the selection process of participants. Students will be selected using the Student Engagement Instrument (SEI) and criterion sampling. Participants that scored at the 10^th percentile or below on the SEI, has had course failures (previous and current), excessive truancies or absences, behavior or disciplinary issues, and a high number of missing assignments (Szlyk, 2018).

 Southwestern CUSD #9 has 41.8 percent of students that come from low-income homes and a 3.8 percent chronic truancy rate (Southwestern CUSD 9). For the study, students will be selected from the freshmen class at Southwestern High School in Piasa, IL. With approximately 85.1% of freshmen on track to graduation, 20-30 students will be selected and split into two groups (Southwestern CUSD 9).

Instruments

 Check and Connect is an intervention program for k-12 that contains four main components and three elements. The four main components consist of the mentor, the “check” component, the “connect” component, and parent/family engagement. The three elements consist of relationships, problem solving and capacity building, and persistence. As part of their intervention program, they provide and use SEI as a self-report measurement to identify warning signs of disengaging students, poor attendance, behavioral issues, and/or low grades (Institute on Community Integration). “The “check” component refers to the process where mentors systematically monitor student performance variables (e.g., absences, tardies, behavioral referrals, grades), while the “connect” component refers to mentors providing personalized, timely interventions to help students solve problems, build skills, and enhance competence” (Institute on Community Integration).

 Check and Connect provides free resources to schools like the SEI and the monitoring form. In order to be trained or use premium features like the app, school districts must pay a fee. Many school district have been able to all of Check and Connects features by writing a grant. For our research, we will be utilizing the free resources provided.

Qualitative Research Design

A major component of the study is to identify the effectiveness of intervention programs in rural communities. The data being collected by the mentor teachers and researchers are mostly qualitative but does include quantitative data. Since the study will be obtaining both types of data, we will be using the QUAL-quan model. The qualitative data in the study will include information about teacher, peer, and family support, future aspirations and goals, level of intrinsic motivation. Some of the quantitative data in the study will include number of absences and tardies, numbers of d’s and f’s, grade percentages, and number of missing assignments. The study focuses on qualitative data and will be utilizing the case study research method. Mentor teachers will be providing support to at-risk students using the Check and Connect resources.

The researcher will be a nonparticipant observer, but the mentors will be considered participant observers. As the research study progresses, mentors will interview students a minimum of once a month a minimum of 15 minutes to assist in monitoring student achievement. At the end of the study, the researcher will conduct a focus group with mentor teachers to obtain results from the study.

The mentors will be considered participant observers. As the case study progresses, mentors will interview students a minimum of once a month to assist in monitoring student achievement. Mentors will be collecting data weekly course failures, number of absences and tardies, behavior and disciplinary issues, and number of missing assignments. Mentors will assist students in creating weekly goals and evaluate each week if the student has successfully met the goal. At the end of the case study, students will be evaluated the same way as the beginning of the school year to determine the effectiveness of the intervention program.

Procedure

The study will begin with assessing all of freshmen students using the Student Engagement Instrument (SEI). After students have completed the SEI, all students will be evaluated by administration, counselors, teachers, and/or parents to identify at-risk students based on examining academic and behavior records. Once students have been selected and assign to a mentor. Mentors will begin collecting data for each student by completing the daily Check and Connect high school monitoring form. The form includes academic data (number of d’s and f’s, number of missing assignments, and current cumulative grades) and behavior data (tardies, skipping classes, absences, behavior referral, detentions, and suspensions).

Each school district will have one or two voluntary teachers that will be working with no more than fifteen and no less than five students depending on the students’ needs and school resources. Teachers will be given time every day to work with students; approximately 20-40 minutes in the school day. Ideally, this time should already be blocked out in the school schedule (e.g., homeroom, study hall, etc.). Students will begin working with voluntary teachers after the first quarter of the school year. Teachers will collect data on each student and work with them to achieve academic success.

Data Analysis Plan

From the data collected from teachers, students will be compared academically to themselves weekly. Student’s grades, missing assignments, attendance, and disciplinary issues will be analyzed weekly by the teacher and/or researcher using the Check and Connect High School Monitoring Form. Students will be reidentified as at-risk quarterly based off of the same criteria as the initial identifiers.

Time Schedule

The study will begin with the school year 2019-2020 in August and will continue the entire school year. Students will be identified in the first quarter of school (August 2019 – October 2019). Students will work with teachers from October 2019 to the end of the school year. At the end of each quarter, teachers and/or researcher will write a report of findings.

Assessment

 Throughout the research, teachers will be using the Student Engagement Instrument (SEI) provided from Check and Connect. Check and Connect was established in the 1990’s with a five-year grant provided from the U.S. Department of Education (Institute on Community Integration). In order to identify and assist at-risk students, the SEI was created. “The SEI is a student self-report survey designed to measure cognitive and affective engagement” (Institute on Community Integration).

The SEI is a 35 question Likert scale questionnaire that consists of questions about affective engagement (teacher-student relationship, peer support at school, and family support for learning) and cognitive engagement (control and relevance of school work, future aspirations and goals, intrinsic motivation). Each question is worth a single point. There are 9 questions associated with teacher-student relationships, 6 questions with peer support at school, 4 questions with family support for learning, 9 questions with control and relevance of school work, 5 questions with future aspirations and goals, and 2 questions with intrinsic motivation. Since the SEI is a Likert questionnaire 4-point scale is used. Strong agree is associated with 1, agree is associated with 2, disagree is associated with 3, and strongly disagree is 4. Students in the 10^th percentile or lower were found to be absent more frequently, have behavior issues, and lower standardized test scores. Check and Connect provides two SEI assessments; one version for grades and one version for grades 9-12. As part of the program mentors are provided with administration standardization procedures to administer the questionnaire. Very similar to some standardized test, a script of what to say is provided to the administer of the test to students. The administrator will read each questionnaire item aloud and pause 3- to 5- seconds for students to answer the question. Students can move ahead in the questionnaire if the administers pace of reading is to slow for them. The questionnaire should take less than 30 minutes to administer. Once the questionnaire is completed, the administer will come around and collect the questionnaire.

In Lovelace, Reschly, Appleton, and Lutz conducted a research study to determine if the SEI was concurrently and predictively valid. In the study Concurrent and Predictive Validity of the Concurrent and Predictive Validity of the Student Engagement Instrument Student Engagement Instrument by Lovelace, Reschly, Appleton, and Lutz, researchers tested the concurrent and predictive validity of the SEI and the SEI scores. “Each group mean comparison of SEI factor scores was statistically significant (P<0.05 level), and all effects but one (CRSW by achievement level) were in the expected direction” (Lovelace, 2014, pg.515).

References

• Donnelly, M. (1987). At-Risk Students. ERIC Digest Series, 21st ser. Retrieved from https://www.ericdigests.org/pre-928/risk.htm
• Institute on Community Integration. (n.d.). Check & Connect Student Engagement Intervention Model. Retrieved November 6, 2018, from http://checkandconnect.umn.edu
• Lovelace, M. D., Reschly, A. L., Appleton, J. J., & Lutz, M. E. (2014). Concurrent and Predictive Validity of the Student Engagement Instrument. Journal of Psychoeducational Assessment, 32(6), 509–520. Retrieved from https://login.libproxy.siue.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ1035535&site=ehost-live&scope=site
• Southwestern CUSD 9 Piasa, IL. 2017-2018 School Report Card. Retrieved from http://webprod.isbe.net/ereportcard/publicsite/getReport.aspx?year=2018&code=400560090_e.pdf
• Szlyk, H. S. (2018). Fostering Independence through an Academic Culture of Social Responsibility: A Grounded Theory for Engaging At-Risk Students. Learning Environments Research, 21(2), 195–209. Retrieved from https://login.libproxy.siue.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ1181854&site=ehost-live&scope=site
• US Census. (2016, December 8). New Census Data Show Differences Between Urban and Rural Populations. Retrieved from https://www.census.gov/newsroom/press-releases/2016/cb16-210.html
• U.S. Department of Education, National Center for Education Statistics (NCES) through Public high school 4–year adjusted cohort graduation rate (ACGR), by race/ethnicity and selected demographics for the United States, the 50 states, and the District of Columbia: School year 2014–15. Retrieved from: https://nces.ed.gov/ccd/tables/ACGR_RE_and_characteristics_2014-15.asp.
• Van Norman, E. R., Nelson, P. M., & Klingbeil, D. A. (2017). Single Measure and Gated Screening Approaches for Identifying Students At-Risk for Academic Problems: Implications for Sensitivity and Specificity. School Psychology Quarterly, 32(3), 405–413. Retrieved from https://login.libproxy.siue.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ1153008&site=ehost-live&scope=site
• Walker, B., Cheney, D., Stage, S., Blum, C., & Horner, R. H. (2005). Schoolwide Screening and Positive Behavior Supports: Identifying and Supporting Students at Risk for School Failure. Journal of Positive Behavior Interventions, 7(4), 194–204. Retrieved from https://login.libproxy.siue.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ806879&site=ehost-live&scope=site