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Gap Analysis: Closing the Achievement Gap

Part 1: Identify the demographics of your school/classroom. You must complete the demographic chart on the entire school.

Part 2: Academic Data: Gap Analysis Using Assessment Data.
Review test scores preferably LEAP or EOC data from the 2015 – 2016, 2016-2017 and 2017-2018, 2018-2019 school years. You should use three years of data if available. Determine if there are gaps among the students in your school. You should create a data chart that includes information on the scores by proficiency level, race, grade level, and socioeconomic status. This information should be included on the school’s report card or in the school improvement document.
Note: Statewide assessment data is available by accessing the Data Center on the Louisiana Believes website. You may wish to use the links below to begin reviewing data or you may use data from your school and/or district. You will have to do a little research to assess the information as it may not necessarily be easy to find.

Elementary and Middle School Performance – Data available from 1997 – 2018 : http://www.louisianabelieves.com/resources/library/elementary-and-middle-school-performance

High School Performance – Available data includes ACT, EOC, LEAP 2025, Advanced Placement, Cohort Graduation, etc. from 2012 – 2018: http://www.louisianabelieves.com/resources/library/high-school-performance

The Louisiana Equity Reports for 2017 and 2018 may also be helpful to review when completing this assignment. Use the following link to access the reports. http://www.louisianabelieves.com/resources/library/closing-the-equity-gap

Part 3: Discipline Data: Examining Patterns of Discipline and Disproportionality
Review the discipline data and determine if school leaders are using equity-driven principles when administering school discipline. Focus on numerical, social justice and cultural and beliefs-oriented goals when examining discipline data. If discipline data is available to you for the 2015 – 2016, 2016-2017, 2017 – 2018, and 2018-2019 school years, please use the data based on your school. Again, use three years of data if it is available. If data is not available, I will provide sample data in table form for you to review. The tables provided will serve as examples of the data you should obtain on your school if possible. You may choose to use the tables provided to address the questions related to discipline data.
Part 4: Technology Integration

How is technology integrated into the school, classrooms, daily lessons? Identify the types of technology and technology tools used to support instruction and assessment. Please be very specific in your response.

EDCI 5030 Closing the Achievement Gap
Part 1: Identifying the Demographic Make-Up of the School
Complete the chart below with information on your school. Replace the numbers with actual enrollment data from your selected school.

School Name: ¬¬¬¬¬¬-__________________________________________
Total Number of Students in the School: _________________________________
School Socio-Economic Make-Up (i.e., % receiving free and reduced lunch): ___
Create a chart of student enrollment: example below
Grade Level 9 10 11 12
Number of Students 688 650 612 550
Gender:
Number of Females:
Number of Males:
Ethnic/Cultural Make-Up
Caucasian/White:
African American/ Black:
Hispanic/Latino:
Asian/Pacific Islander:
American Indian/Alaskan Native:
Language Proficiency
Number of English Language Learners (ELL):
Academic Performance
Number of Students Performing
Below Grade Level:
Number of Student Performing
Above Grade Level:
Students with Special Needs
Learning Disabled:
Emotionally or Behaviorally Impaired:
Attention Deficit Disorder (ADD):
Developmentally Disabled/
Mental Retardation:
Speech and Language Disorder:
Autism/ PDD/Asperger Syndrome:
Gifted and Talented:
Blind or Visually Impaired (VI):
Deaf or Hearing Impaired (HI):
Physically Disabled:
Other Health Impaired:

Student Characteristics:
Describe developmental characteristics of students in your school.
(Cognitive, Physical, Emotional, Social).

Highlight the prior knowledge and interests of students in your school.

Environmental Factors:
Describe district, school, and classroom environmental factors impacting the quality of education for all of your students.

Describe community and family environmental factors impacting the quality of education for all of your students.

Instructional Strategies Appropriate for Student Characteristics and Environmental Factors:
Based on the student characteristics and environmental factors you noted above, describe the instructional strategies that teachers can use to meet the unique learning needs of your students.

Part 2: Academic Data: Gap Analysis Using Assessment Data.
Review assessment data (test scores) preferably LEAP or EOC data, and discipline data. Determine if there are gaps among the students in your school. You should create a data chart that includes information on the scores by proficiency level, race, grade level, and socioeconomic status. This information should be included on the school’s report card or in the school improvement or balanced score card document. In order to determine if patterns exist, you may wish to review data from the 2015-2016, 2016-2017 and 2017-2018 school years/assessment cycles.

• The term achievement gap refers to the difference in academic achievement between white, Asian (specifically Chinese-American, Japanese-American, and Korean-American), and economically advantaged students and their African-American, Hispanic/Latino, Native American, Southeast Asian, and socioeconomically disadvantaged counterparts.
• Example:

• Alarmingly, the gaps widen as children go through the school system. Nationwide, African-American children average one year behind white students in second or third grade; by 12th grade, they have fallen to three or four years behind. The average African-American or Hispanic/Latino student graduates from high school with the mathematics, reading, and vocabulary skills of a typical white eighth grade student (Donahue, Voelkl, Campbell, & Mazzeo, 1999; Smith, 1995).
• Even when controlling for families’ education backgrounds or socioeconomic status, gaps among racial/ethnic groups persist (Phillips, Brooks-Gunn, Duncan, Klebanov, & Crane, 1998).
• Differences in achievement cannot be attributed to poverty; even middle-class children of color lag significantly behind their white counterparts (Noguera & Akom, 2000).

Example of chart to include in this project. (This is just one example.)

You will need a chart for each content area (ELA, math, science, and social studies) tested. If you are a high school you will need a chart to represent each of the EOC tests (Algebra 1, Geometry, English II, English III, Biology and U.S./American History). Those of you working with elementary grades, I would strongly advise you to work with grades 3-5. Grades K-2 will not necessarily have assessment data.

Once you have created your charts, you will need to analyze the information and determine strengths and weaknesses with respect to each grade level and content area. Please list three strengths and weaknesses and then discuss strategies to improve student outcomes.
A. What specific content areas (concepts and skills, not just subject area) have been identified as areas of strength and areas of improvement for the school? Document this information in a chart or table and include grade levels, test data, 3 areas of strength and 3 improvement areas (weaknesses).
B. What instructional strategies/programs have been used in the school in the last school year to address these areas of improvement? (List any programs, special initiatives along with impacted grade levels that were implemented at the school even if you were not directly involved) Are these initiatives aligned with Best Practices, UbD and DI? Explain completely.
C. Analyze and discuss the gaps in achievement based on race, gender and socioeconomic status. Develop a plan to address these gaps using specific best practice strategies including UbD and Differentiated Instructional (DI) strategies.

Part 3: Discipline Data: Examining Patterns of Discipline and Disproportionality

Review the discipline data and determine if school leaders are using equity-driven principles when administering school discipline. Focus on numerical, social justice and cultural and beliefs-oriented goals when examining discipline data. If discipline data is available to you for the 2016-2017 and 2018-2019 school years, you may use the data based on your school. You will have to create tables like the tables provided below. If data is not available or if you would prefer to analyze the data provided, use the data below.

Sample data for use if data is unavailable at your school site. The data below represents a fictious school, Early College Career Academy, with an enrollment of nearly 1500 students with the following racial/ethnic structure: 45% White, 34% Black, 9 % Asian, 7% Hispanic/Latino, and 5% Multiracial/Other.
Table 3.1 Discipline/Behavioral Referral Data
2015 – 2016 2016 – 2017 2017 – 2018
All Students 1804 1152 1076
White 442 268 166
Black 1171 755 806
Multiracial/Other 73 50 37
Latino 100 55 55
Asian 18 19 12
SWD 285 185 222
FRLP 1420 935 909
% of referrals Black 65% 65% 75%
% of referrals non-Black 35% 35% 25%
% of referrals White 25% 23% 15%
Key: SWD – Students with Disabilities; FRLP – Free and Reduced Lunch Program

Table 3.2 Suspension Data
2015 – 2016 2016 – 2017 2017 – 2018
All Students 229 159 155
White 39 35 29
Black 168 102 106
Multiracial/Other 9 7 6
Latino 12 13 9
Asian 1 2 2
SWD 43 32 43
FRLP 190 129 127
% of referrals Black 73% 64% 68%
% of referrals non-Black 27% 36% 32%
% of referrals White 17% 22% 19%
Key: SWD – Students with Disabilities; FRLP – Free and Reduced Lunch Program

  1. Discuss the data in each table. What types of patterns persist? What conclusions can be drawn based on the information in each table. Please be very thorough in your analysis.
  2. What are some processes, practices and policy areas that need to be examined?
  3. What are some social justice-oriented concerns about these patterns?
  4. Is there a connection between referrals and academic achievement? If so, what connections have you observed in your experiences as an educator?
  5. Suspensions live in referrals, what can be done to improve the number of and suspension rates for students?
  6. What types of programs do you have in place in your current schools to reduce the rate of referrals and suspensions? List the programs and discuss why you believe these programs are effective or ineffective.
  7. How would you improve discipline in a school? What specific strategies would you address through professional development to improve discipline in individual classrooms and the whole school?
    Part 4: Technology Integration
    Please describe the technology available and technology tools used to support instruction and assessment. It is important to describe the technology and technology tools that are available for teachers and students. Please be very detailed and specific in your descriptions.

Note: ETEC members of the group, please consider how the group can incorporate technology to the specific strategies for improving outcomes in each school and the district.

Sample Solution

Introduction Both mental and developmental disorders in childhood, refers to syndromes in neurological, emotional or behavioral development, with serious impact in psychological and social health of children (Nevo & Manassis., 2009). Children who suffer from these types of disorders, they need special support firstly from their close family environment and then from educational systems. In many case, the disorders continue to exist in adulthood (Scott et al., 2016). According to Murray and partners (2012), mental and developmental syndromes in childhood, are an emerging challenge for modern health care systems worldwide. The most common factors that tend to increase such syndromes in low and middle income countries, is the reduced mortality of children under the age of five and the onset of mental and developmental syndromes in adults during their childhood One of the most common mental disorders in children with developmental disorder is anxiety disorder. In the Diagnostic and Statistical Manual of Mental Disorder, seven types of anxiety disorder are recognized both in childhood and adolescents. Among them are Separation Anxiety Disorder (SAD) and Generalized Anxiety Disorder (GAD) (American Psychiatric Association, 2000). The aim of this study is, to present a common mental disorder that affects children with a developmental syndrome. Thus, try to present the clinical features, the prevalence and diagnostic issues in this population. 1. Mental disorders in children World Health Organization (WHO) has identified mental health disorders, as one of the main causes of disability globally (Murray & Lopez., 2002). According to the same source of evidence, childhood is a crucial life stage on the occurrence of mental disorders, which are likely to affect the quality of life, the learning and social level of a child. Within this framework, possible negative experiences at home like family conflicts or bullying incidents at school, may have a damaging effect on the development of children, and also in their core cognitive and emotional skills. Moreover, the socioeconomic conditions within some children grow up can also affects their choices and opportunities in adolescence and adulthood. On the other hand, children’s exposure in risk factors during early life, can significantly affect their mental health, even decades later. The coherences of such exposure can lead on high and periodically increasing rates of mental health, and also behavioral problems. In European Union countries, anxiety and depression syndromes are among top 5 causes of overall disease burden among children and adolescents. But, suicide is the most common cause of death between 10 to19-year-olds, mainly in countries with low- and middle-income and the second cause in high income countries (WHO, 2013-2020). 2. Anxiety disorder in children with neurodevelopmental disorder According to American Psychiatric Association (APA, 2013), anxiety disorder is characterized by excessive or improper fear, which is connected with behavioral disorders that impair functional capacity. Furthermore, anxiety is characterized as a common human response in danger or threat and can be highly adaptive in case of elicited in an appropriate context. Is clinically important when anxiety is persistent and associated with impairment in functional capacity, or affects an individuals’ quality of life (Arlond et al., 2003). Especially in childhood, clinical characteristics of anxiety is complicated when complicated by developmental factors, due to the reason that some type of fears maybe characterizes as normative in certain age of groups (Gullone, 2000). Additionally, although a child is able of experiencing the emotional and physiologic components of anxiety at an early age, definite mental abilities may be prerequisites for the full expression of an anxiety disorder (Freeman et al., 2002). Within this framework, Separation Anxiety Disorder (SAD) is characterized by excessive and developmental inappropriate anxiety, as a response to separation from the close family environment or from attached figures. The most common symptoms in such disorder are, anticipatory anxiety concerning with separation occasions, determined fears about losing or being separated 2.1. Anxiety disorder prevalence in children Although an essential body of data are available about the epidemiology of anxiety disorders, the evidence for prevalence presented are highly fragmented and the reports for prevalence varies considerably (Baxter et al., 2012). According to global epidemiological data evidence, mental disorders is a difficult task, due to significant absence of officially data for many geographical regions globally. These evidence are less in pediatric patients – children, particularly in low to middle income countries where other concerns are in the front line. The above issue of data absence, is highlighted in the Global Burden of Disease Study 2010 (Whiteford et al., 2013). Childhood mental disorders epidemiologically data, were remain relatively constant during the 21 world regions defined by Global Burden of Disease Study 2010. However, these prevalence rates were based on sporadic data, for some disorders or no data for specific disorders in childhood. According to the12-month global prevalence of childhood mental disorders in 2010 is shown that, anxiety disorder rates were higher in adolescents between the age of 15 to 19 years old and especially in females (32,2% general rate, 3,74% in males and 7,02% in females). Moreover The anxiety disorder rates in children between the age of 5 to 9 years old were (5,4%) and 21,8% in children between the age of 10-14. In both groups of children, the percentages of prevalence were higher in females. These systematic reviews were then updated for GBD 2013, were the data for mental disorders in children and adolescents were sparse. This resulted in large uncertainty intervals around burden estimates despite mental disorders being found as the leading cause of disability in those aged under 25 years. Moreover, lack of absence of empirical data restricts the visibility of mental disorders in comparison with other diseases in childhood and makes it difficult to advocate for their inclusion as a priority in health initiatives 2.2. Anxiety disorder clinical features The main clinical features of Separation Anxiety Disorder (SAD) is, the inordinate and developmental inappropriate anxiety about separation from the home or from attachment figures. The leading symptoms of that type of mental disorder, refers to anticipatory anxiety regarding separation events, persistent concerns about losing or being separated from an attachment figure, school denial, unwillingness to stay alone in the home, or to sleep alone, recurrent nightmares with a separation theme, and somatic complaints. In particular, the clinical feature of school refusal has been reported to happen in about 75% of children with SAD, and also SAD occurs in 70%to 80% of children presenting with school refusal. In that case, epidemiologic studies exhibit that the rates of prevalence are from 3.5% to 5.1% with a mean age of onset from 4.3 to 8.0 years old (Masi et al., 2001). One area that has attracted considerable attention is the potential link between childhood SAD and panic disorder in adulthood. Indirect support for this hypothesis is provided by retrospective studies of adults with anxiety disorders. Furthermore, the developmental sequel between childhood anxiety disorders and panic disorders in adult age, is also supported by the biologic challenge study, of Pine et al. (2000). Researchers at this study found that, children who suffer from SAD (but not social phobia) they showed respiratory changes during carbon dioxide inhalation that which had common characteristics with adults’ panic attacks. In a similar study, children with SAD and parents who suffer with panic attacks, were found to have significant percentage of atopic disorders, including asthma and allergies (Slattery et al., 2002). On the other hand, Generalized Anxiety Disorder (GAD) in childhood, is characterized by immoderate worry and stress about daily life events that the child is not able to control effectively. That anxiety is expressed on most days and has a duration for at least 6 months, and also there is an extended distress or difficulty in performing everyday processes (Gale & Millichamp., 2016).
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