Joshua Bates
Dr. Weir
2 August 2011
Dr. Weir
2 August 2011
Developmental Assets as Predictors of Scholastic Success
Introduction
“It’s difficult to convey the almost unbearable sweetness of this kind of American childhood to anybody who didn’t live it,” wrote blogger Jim Manzi, referring to his childhood. “The safety and freedom that Krugman describe are rare now even for the wealthiest Americans – by age 9, I would typically leave the house on a Saturday morning on my bike, tell my parents I was “going out to play,” and not return until dinner; at age 10, would go down to the ocean to swim with friends without supervision all day; and at age 11 would play flashlight tag across dozens of yards for hours after dark” (2011). Paul Krugman and Jim Manzi appeared to have the kind of perfect childhoods, rendered impossible by modern life and the risks children face today. In fact, Carol Tilley wrote that modern childhood has been “Pathologized” (2011).
Fortunately there have been recent attempts to strengthen children against the dangers of society, “In the past few decades, researchers and policymakers from fields including education, social work, and public health have proposed an alternative approach to understanding childhood and adolescence: positive youth development (PYD)” (Tilley 2011, 42). Developmental assets are the evolution of positive youth development; the idea is that there are areas of development that allow children to resist societal ills, and that these areas, these assets, can be built if they do not occur naturally. The Developmental Assets Profile is a tool for measuring these assets (See Appendix 2); school districts would like to know if measures of asset development can be used to measure academic development.
One of the measures of academic development is the On-Track Indicator. Dr. Weir, developer of the indicator for the Dallas Independent School District, describes the indicator:
The Consortium on Chicago School Research (CCSR) developed an On-Track indicator in 1999 to gauge whether students in their first year of high school were making enough progress to have a reasonable expectation of graduating in four years.
Like the Chicago indicator, the Dallas indicator combines two factors: the number of credits earned during freshman year and the number of semester Fs in core subjects. A student is considered to be On-Track at the end of ninth grade if he or she has met both of the following criteria:
· The student has accumulated five full course credits, and
· The student has no more than one semester F (that is, one-half of a full credit) in a core subject (English, math, science, or social studies).
This has already shown itself to be a useful indicator of future performance. A Consortium on Chicago School Research report showed that, “81% of on-track students in CPS graduate from high school in four years whereas only 22% of off-track students graduate in the same period” (Montgomery and Roderick 2009, 5). Perhaps DAP can add further insight to this problem. While the Developmental Assets Profile is a fine measure of overall student growth and well being, there are only a few items that correlate with grade performance; those who do their homework regularly, avoid alcohol, tobacco and other drugs and are eager to do well in school and other activities are more likely to have a higher grade point average and be On-Track.
The C Range Is Where Big Gains in Graduation can be had for Small Gains in GPA
Often times there is much emphasis put on students who are likely to drop out; here the emphasis is put on those who are at risk of dropping out. According to the Consortium on Chicago School Research, only 22% of off track freshmen go on to graduate (Montgomery and Roderick 2009). Using the On-Track Indicator, the C range has been identified as the danger zone for at risk students. A grade point average between 70 and 71 seems to be on the right side of the passing border; however, only 1% of these students are currently On-Track. On-Track really starts to jump in the middle C range; between 74 and 75, 25% of freshmen are On-Track, compared to 71% of students in the 78-79 range. These numbers seem to indicate that the problem is less about finding huge improvements in grade point average. Rather this suggests that scratching out a few points can mean the difference between graduating and dropping out.
The Largest Differences between A Students and F Students Are Homework, Alcohol and Motivation
With this in mind, it seems like the best place to look for areas to optimize is where the differences between successful students and unsuccessful students are highest. The Developmental Assets Profile seems like a nice tool to look for factors outside of the classroom, as well as inside, that contribute to healthy student growth. The profile asks 58 questions that are graded on a zero to three scale, with zero being “Not At All or Rarely,”one1 being “Somewhat or Sometimes,” two being “Very or Often” and three being “Extremely or Almost Always.” The phrasing of the questions is such that answering in the affirmative is always the preferred answer. Ideally the high performing students would also answer more highly on these questions, particularly on questions referring to scholarly matters, while lower performing students would answer lower, indicating where assets need to be built.
The largest difference between an A student and an F student is that an A student averages a 2.48 out of three on item eight, do my homework, while the F student averages just a 1.2. Furthermore, the third largest difference is a difference of scholarly motivation. A students average a 2.65 on item 38, eager to do well in school and other activities, while F students 1.78. This comes as no surprise since homework is directly tied to grade point average in many cases, and it should be hoped that those who try harder will succeed more often; the second largest difference was less obvious, however.
The second largest difference is that A students admit to substance abuse much less readily than F students; A students average 2.74 out of three on item nine, stay away from tobacco, alcohol, and other drugs, compared to an F student’s 1.86. This category may be even more pronounced if not for the inclusion of tobacco. It seems clear that one could smoke tobacco while being otherwise studious; however, this becomes less likely with the inclusion of alcohol or stronger drugs. The substance question is exactly the sort of issue that can easily be buried in statistics involving academic performance, and it is also the exact sort of issue that requires something like the DAP to bring to the fore. This is a treatable issue since feeder patterns can be used to trace the problem back it its source and tackle it there if necessary.
These items are also helpful as part of a regression analysis. Controlling for school, gender, attendance, race and past achievement, students who report doing more homework, avoiding substances more often and being more motivated to succeed get better grades. Combining these items into a scale score using Search Institute’s method of taking the average of the response and multiplying it by ten, giving it a maximum of thirty, perfect answers on these three questions nets 6.6 additional points toward grade point average compared to a score of zero. While this may not seem like much, to a borderline student, these points could be the difference between graduation and dropping out. A table with the complete regression results is included in Appendix 1.
The Impact of Improving These Assets Is Small but Enough
As stated previously, there is a razor thin margin between a student who is likely to graduate and a student who likely will not graduate. In the last example, if there was a freshman making a 73.4, with zeros (Not At All/Rarely) on all three items, he would be only 13% likely to be On-Track to graduate. If he scored three (Extremely/Almost Always) on each item, and boosted his average to an 80, he would have an 80% likelihood of being on-track; Montgomery and Roderick state that 81% of students who are On-Track their freshman year graduate. The C range is where large gains in graduation can be had without requiring huge gains in grades.
One example of this possibility is the case of African American female students who went to the same high school and the same middle school. Both attended 94% of the days they were enrolled. One student, Kim, had an 81.13 her final semester in middle school, 2222 on the reading TAKS, 2400 on the math TAKS, 2067 on the social studies TAKS and 1916 on the science TAKS. The other student, Erica, had an 81.5 her final semester in middle school, 2277 on the reading TAKS, 2416 on the math TAKS, 2251 on the social studies TAKS and 2070 on the science TAKS. Kim had a 70 average for the spring semester of 9th grade, and was off track, while Erica had a 74 and was On-Track. Kim responded that she sometimes did her homework, that she never stayed away from alcohol, tobacco and drugs and that she was very eager to do well in school and other activities. Erica responded that she did her homework often, always stayed away from substances and also was very eager to do well in school and other activities. While neither student was able to pass the ninth grade TAKS, with Kim making a 1984 on the reading and 1943 on the math (2100 is passing) and Erica making a 2052 on the reading and a 2024 on the math, there is still plenty of time to correct that; if Erica can keep up her study habits, she looks to be on an upward trajectory. Kim, meanwhile, should not require too much help to get to Erica’s level, or even higher. All that is needed is knowledge of the problem, and the tools to correct it.
DAP May Not Lend Itself to Innovative Intervention, but Existing Techniques Can Be Effective
While there is no shortage of research on how one might correct these types of issues, the research in how DAP applies seems to be lacking. One place to look for such tools is Search Institute’s own research, “Although there is a lack of research on interventions explicitly based on the Developmental Assets, more general ways to increase students’ developmental assets have been suggested in the Search Institute literature” (Stevens and Wilkerson 2010). The Institute advocates what they term an “asset-building” approach, an example of which is provided in a program designed to help 9th graders succeed in school and avoid risky behavior. According to the study by Eugene C. Roehlkepartain, Peter L. Benson and Arturo Sesma, “The 9th Grade Program is an important innovation for St. Louis Park and the broader asset building movement. It provides some of the first evidence from an independent evaluation that an asset-building approach can have a measurable impact in the lives of young people (particularly in reducing risks, as evidenced in the MIPH evaluation)” (2003, 56). Perhaps this approach could be applied here with similar success; however, new practices may not be necessary. Stevens and Wilkerson report that, “Although the ideas for practice presented are all positive and productive, parallel practices, such as service learning, mentoring, and community and family involvement, have been in the school counseling literature for years” (2010).
DAP is Heavy on Personal Factors, but Light on Scholastic Items
As nice as DAP is for finding factors outside the classroom for student success, its predictive power is limited by its lack of depth in measuring performance inside the classroom. According to Stevens and Wilkerson, ” According to the crosswalk, the Developmental Assets framework places primary emphasis on personal/social development, puts secondary emphasis on academic development, and lacks significant emphasis on career development” (2010). However, this is not the only indication; many of the items in the survey were either lightly correlated, or not correlated at all with scholastic achievement. Although average scores tended to rise with grade, only i8, Does Homework, and the scale created by combining i8, i9 (Avoids Alcohol) and i38 (Motivated) were even moderately correlated with grade point average, and adding other items to the model only decreased its effectiveness. Therefore, it is apparent that only these three items measure achievement with any reliability.
This graph shows on-track as well as a few different categories of DAP results broken up as suggested by Search Institute. These show that while there is a generally upward trend in DAP scores as grades increase, these trends to not fit well with on-track. It is probable that the reason for this is the wide variety of questions asked that may not have anything to do with succeeding in school. It should be noted that the “School” category was both more correlated with GPA than the other categories and seems to come closest to fitting the path carved by the on-track curve.
One of the items, Avoids Alcohol, is correlated with grades, but is not defined as a scholastic asset. Certainly substance abuse is a hindrance to achievement of any kind, but since this is the case, it is not accurately classified as a predictor of student performance; it should be classified as a predictor of personal as well as professional success. Furthermore, the only moderate correlation is between homework and grades. While indirect factors that impact grade point average are quite well measured, direct impact seems to be overlooked entirely. DAP should be given in addition to other methods designed to more accurately and directly calculate factors impacting student performance.
Conclusion
DAP appears to do nice job of discovering indirect factors for scholastic achievement as well as other assets that help students to succeed in life; however, these seem to come at the expense of more direct analysis of what causes a student to perform and eventually graduate. This does not mean that it is not helpful for teachers, councilors and administrators; it may even be more helpful than current procedures. Since the necessary improvement in grades is small, the fact that the DAP does not have a large scale impact in predicting grades does not matter as much. This could be a way for counselors and administrators to find a new approach to attacking the problem of off-track students, along with improving student outcomes as a whole; certainly the impacts of substance abuse and, to a lesser extent, motivation were unanticipated. These also seem to be issues that given the proper focus can be mended.
Methodology
This survey covered 5976 high school freshmen from DISD schools; the survey was administered in the spring semester of the 2009/2010 school year. This was the first year that the survey was given district wide. Where it was possible, means and correlation analysis were used to ensure that the results were easy to interpret. Linear regression was also used to provide more insight into the marginal effects of the results. The dependent variable was grade point average of the spring semester of the 2009/2010 school year. The regression equation controlled for gender, race, language and the high school of the student surveyed; some of these were included despite their insignificance for completeness. Attendance was also controlled for using a ratio of days attended over days enrolled since not all students were enrolled the entire semester, and only the spring semester attendance was counted. Scores on TAKS tests were included to act as a pretest.
Works Cited
Manzi, Jim. 2011. “A Moment of Communion with Paul Krugman.” The American Scene, April 29.
http://theamericanscene.com/2011/04/29/a-moment-of-communion-with-paul-krugman
Montgomery, Nicholas and Melissa Roderick. 2009. “Getting On-Track: Understanding Freshman Performance in CPS.”
Roehlkepartain, Eugene C., Peter L. Benson and Arturo Sesma. 2003. Signs of Progress in Putting Children First. Minneapolis: Search Institute.
Tilley, Carol L. 2011. “Developmental Assets.” School Library Monthly 27, no. 7: 41-44.
Stevens, Holly, and Kevin Wilkerson. 2010. “The Developmental Assets and ASCA’s National Standards: A Crosswalk Review.” Professional School Counseling 13, no. 4: 227-233. Academic Search Complete, EBSCOhost (accessed July 26, 2011).
Appendix 1
Model with i8, i9 and i38
| Model Summary | ||||
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | .730a | .533 | .530 | 4.3199202 |
| a. Predictors: (Constant), i38 Motivated, Wilson, Angelou, Middle College, Asian, Roosevelt, SCGC, KJ Gilliam Collegiate ACAD, Nativeamerican, Early College, Rangel, Washington, Lincoln, Seagoville, Smith, Madison, Carter, Hillcrest, Pinkston, Spruce, Kimball, North Dallas, Female, South Oak Cliff, Conrad, Jefferson, Limited English Proficiency, Adamson, Samuell, Bryan Adams, Spring Attendance Ratio, Molina, i9 Avoids Alcohol, White, Sunset, i8 Does Homework, Math Scale Score 8th grade, Townview, Exited Limited English Proficiency, Social Studies Scale Score 8th grade, Reading Scale Score 8th grade, Science Scale Score 8th grade, Black, Skyline | ||||
| ANOVAb | ||||||
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | Regression | 126336.102 | 44 | 2871.275 | 153.859 | .000a |
| Residual | 110701.268 | 5932 | 18.662 | | | |
| Total | 237037.369 | 5976 | | | | |
| a. Predictors: (Constant), i38 Motivated, Wilson, Angelou, Middle College, Asian, Roosevelt, SCGC, KJ Gilliam Collegiate ACAD, Nativeamerican, Early College, Rangel, Washington, Lincoln, Seagoville, Smith, Madison, Carter, Hillcrest, Pinkston, Spruce, Kimball, North Dallas, Female, South Oak Cliff, Conrad, Jefferson, Limited English Proficiency, Adamson, Samuell, Bryan Adams, Spring Attendance Ratio, Molina, i9 Avoids Alcohol, White, Sunset, i8 Does Homework, Math Scale Score 8th grade, Townview, Exited Limited English Proficiency, Social Studies Scale Score 8th grade, Reading Scale Score 8th grade, Science Scale Score 8th grade, Black, Skyline b. Dependent Variable: gpa_0910_sem2 | ||||||
| Coefficientsa | ||||||
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | ||||
| 1 | (Constant) | 11.935 | 1.184 | | 10.081 | .000 |
| Spring Attendance Ratio | 31.518 | .897 | .341 | 35.135 | .000 | |
| Female | 2.142 | .115 | .170 | 18.556 | .000 | |
| Nativeamerican | 1.697 | 1.377 | .011 | 1.232 | .218 | |
| Asian | 3.093 | .473 | .059 | 6.534 | .000 | |
| Black | -.242 | .206 | -.017 | -1.171 | .242 | |
| White | 1.468 | .327 | .047 | 4.494 | .000 | |
| Limited English Proficiency | .332 | .224 | .019 | 1.479 | .139 | |
| Exited Limited English Proficiency | .221 | .177 | .017 | 1.253 | .210 | |
| Reading Scale Score 8th grade | .002 | .000 | .082 | 6.318 | .000 | |
| Math Scale Score 8th grade | .008 | .000 | .252 | 19.457 | .000 | |
| Social Studies Scale Score 8th grade | .001 | .000 | .033 | 2.415 | .016 | |
| Science Scale Score 8th grade | .003 | .000 | .129 | 9.103 | .000 | |
| Bryan Adams | 1.073 | .339 | .038 | 3.167 | .002 | |
| Adamson | 2.148 | .356 | .070 | 6.027 | .000 | |
| Carter | -.850 | .433 | -.021 | -1.962 | .050 | |
| Conrad | 3.237 | .385 | .093 | 8.398 | .000 | |
| Hillcrest | 2.420 | .390 | .068 | 6.199 | .000 | |
| Jefferson | 3.912 | .383 | .113 | 10.224 | .000 | |
| Kimball | 2.419 | .390 | .069 | 6.202 | .000 | |
| Lincoln | .367 | .527 | .007 | .697 | .486 | |
| Madison | 4.163 | .502 | .085 | 8.289 | .000 | |
| Molina | 1.776 | .332 | .065 | 5.344 | .000 | |
| North Dallas | 2.309 | .390 | .065 | 5.915 | .000 | |
| Pinkston | 2.413 | .413 | .063 | 5.849 | .000 | |
| Roosevelt | 3.290 | .516 | .065 | 6.374 | .000 | |
| Samuell | 1.780 | .359 | .058 | 4.951 | .000 | |
| Seagoville | 1.870 | .416 | .049 | 4.498 | .000 | |
| Skyline | .419 | .284 | .022 | 1.473 | .141 | |
| South Oak Cliff | 1.046 | .400 | .030 | 2.615 | .009 | |
| Spruce | 2.978 | .394 | .083 | 7.557 | .000 | |
| Sunset | 2.889 | .315 | .118 | 9.178 | .000 | |
| Wilson | .833 | .410 | .022 | 2.033 | .042 | |
| KJ Gilliam Collegiate ACAD | .669 | .561 | .012 | 1.193 | .233 | |
| Early College | .032 | .525 | .001 | .061 | .951 | |
| Middle College | 4.013 | .723 | .052 | 5.551 | .000 | |
| Rangel | 3.730 | .673 | .053 | 5.546 | .000 | |
| Smith | 2.894 | .449 | .069 | 6.440 | .000 | |
| Townview | -.911 | .315 | -.039 | -2.887 | .004 | |
| Washington | 2.710 | .541 | .050 | 5.008 | .000 | |
| Angelou | 5.359 | 2.508 | .019 | 2.137 | .033 | |
| SCGC | -.405 | .737 | -.005 | -.550 | .583 | |
| i8 Does Homework | 1.396 | .072 | .197 | 19.303 | .000 | |
| i9 Avoids Alcohol | .288 | .060 | .046 | 4.768 | .000 | |
| i38 Motivated | .570 | .074 | .077 | 7.710 | .000 | |
| a. Dependent Variable: gpa_0910_sem2 | ||||||
Model with Scale Score Made from i8, i9 and i38
| Model Summary | ||||
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | .724a | .524 | .520 | 4.3616291 |
| a. Predictors: (Constant), Motivated, Avoids Alcohol, and Does Homework, Angelou, Carter, Nativeamerican, Lincoln, Roosevelt, Madison, Asian, Middle College, KJ Gilliam Collegiate ACAD, Smith, Seagoville, SCGC, Pinkston, Rangel, Early College, Washington, Hillcrest, Wilson, Kimball, Jefferson, South Oak Cliff, North Dallas, Spruce, Limited English Proficiency, Female, Conrad, Adamson, Samuell, Bryan Adams, Molina, Spring Attendance Ratio, White, Sunset, Math Scale Score 8th grade, Townview, Exited Limited English Proficiency, Social Studies Scale Score 8th grade, Reading Scale Score 8th grade, Science Scale Score 8th grade, Black, Skyline | ||||
| ANOVAb | ||||||
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | Regression | 124150.089 | 42 | 2955.954 | 155.382 | .000a |
| Residual | 112887.280 | 5934 | 19.024 | | | |
| Total | 237037.369 | 5976 | | | | |
| a. Predictors: (Constant), Motivated, Avoids Alcohol, and Does Homework, Angelou, Carter, Nativeamerican, Lincoln, Roosevelt, Madison, Asian, Middle College, KJ Gilliam Collegiate ACAD, Smith, Seagoville, SCGC, Pinkston, Rangel, Early College, Washington, Hillcrest, Wilson, Kimball, Jefferson, South Oak Cliff, North Dallas, Spruce, Limited English Proficiency, Female, Conrad, Adamson, Samuell, Bryan Adams, Molina, Spring Attendance Ratio, White, Sunset, Math Scale Score 8th grade, Townview, Exited Limited English Proficiency, Social Studies Scale Score 8th grade, Reading Scale Score 8th grade, Science Scale Score 8th grade, Black, Skyline b. Dependent Variable: gpa_0910_sem2 | ||||||
| Coefficientsa | ||||||
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | ||||
| 1 | (Constant) | 11.619 | 1.195 | | 9.726 | .000 |
| Spring Attendance Ratio | 31.732 | .905 | .343 | 35.052 | .000 | |
| Female | 2.186 | .116 | .174 | 18.782 | .000 | |
| Nativeamerican | 1.870 | 1.390 | .012 | 1.345 | .179 | |
| Asian | 3.256 | .478 | .062 | 6.817 | .000 | |
| Black | -.225 | .208 | -.016 | -1.082 | .279 | |
| White | 1.604 | .330 | .051 | 4.866 | .000 | |
| Limited English Proficiency | .390 | .226 | .023 | 1.723 | .085 | |
| Exited Limited English Proficiency | .193 | .178 | .015 | 1.080 | .280 | |
| Reading Scale Score 8th grade | .002 | .000 | .078 | 5.979 | .000 | |
| Math Scale Score 8th grade | .008 | .000 | .257 | 19.629 | .000 | |
| Social Studies Scale Score 8th grade | .001 | .000 | .033 | 2.385 | .017 | |
| Science Scale Score 8th grade | .003 | .000 | .126 | 8.798 | .000 | |
| Bryan Adams | 1.021 | .342 | .036 | 2.985 | .003 | |
| Adamson | 2.066 | .360 | .067 | 5.743 | .000 | |
| Carter | -.963 | .437 | -.024 | -2.203 | .028 | |
| Conrad | 3.162 | .389 | .091 | 8.125 | .000 | |
| Hillcrest | 2.314 | .394 | .065 | 5.874 | .000 | |
| Jefferson | 3.921 | .386 | .114 | 10.150 | .000 | |
| Kimball | 2.277 | .393 | .065 | 5.787 | .000 | |
| Lincoln | .278 | .531 | .005 | .523 | .601 | |
| Madison | 4.058 | .507 | .083 | 8.010 | .000 | |
| Molina | 1.740 | .335 | .064 | 5.186 | .000 | |
| North Dallas | 2.094 | .394 | .059 | 5.319 | .000 | |
| Pinkston | 2.274 | .416 | .059 | 5.469 | .000 | |
| Roosevelt | 3.227 | .521 | .063 | 6.194 | .000 | |
| Samuell | 1.696 | .363 | .055 | 4.675 | .000 | |
| Seagoville | 1.788 | .420 | .047 | 4.262 | .000 | |
| Skyline | .357 | .287 | .019 | 1.245 | .213 | |
| South Oak Cliff | .953 | .404 | .027 | 2.359 | .018 | |
| Spruce | 2.786 | .397 | .078 | 7.015 | .000 | |
| Sunset | 2.791 | .318 | .114 | 8.786 | .000 | |
| Wilson | .784 | .414 | .021 | 1.895 | .058 | |
| KJ Gilliam Collegiate ACAD | .667 | .566 | .012 | 1.177 | .239 | |
| Early College | .063 | .530 | .001 | .120 | .905 | |
| Middle College | 4.162 | .730 | .054 | 5.704 | .000 | |
| Rangel | 4.015 | .679 | .057 | 5.916 | .000 | |
| Smith | 2.842 | .454 | .067 | 6.265 | .000 | |
| Townview | -.859 | .318 | -.036 | -2.698 | .007 | |
| Washington | 2.655 | .546 | .049 | 4.861 | .000 | |
| Angelou | 5.399 | 2.532 | .019 | 2.133 | .033 | |
| SCGC | -.334 | .744 | -.004 | -.449 | .654 | |
| Motivated, Avoids Alcohol, and Does Homework | .220 | .009 | .236 | 24.750 | .000 | |
| a. Dependent Variable: gpa_0910_sem2 | ||||||
Appendix 2
The Developmental Assets Profile
Dallas ISD Student Services
Search Institute
Developmental Assets Overview
The Developmental Assets are 40 common sense, positive experiences and qualities that help influence choices young people make and help them become caring, responsible adults. Because of its basis in youth development, resiliency, and prevention research and its proven effectiveness, the Developmental Assets framework has become one of the most widely used approach to positive youth development in the United States.
Research on Developmental Assets
Search Institute is an independent nonprofit organization whose mission is to provide leadership, knowledge, and resources to promote healthy children, youth, and communities. Over the past 20 years, Search Institute has surveyed nearly three million youth about how they experience the 40 Developmental Assets—a research-based framework that identifies basic building blocks of human development. They have found clear relationships between youth outcomes and asset levels in both cross-sectional and longitudinal studies.
Developmental Assets are powerfully related to a range of outcomes among children and youth. Low levels of assets are related to increased risk for negative outcomes including academic underachievement and school problems; alcohol, tobacco, and illicit drug use; precocious sexual activity; and antisocial behavior and violence. High levels of assets are related to positive outcomes including academic achievement, leadership, thriving, and well being. Assets are crucial for the healthy development of all youth, regardless of their community size, geographic region, gender, economic status, race or ethnicity.
The Developmental Assets Profile
The Developmental Assets Profile (DAP) provides an assessment of the Developmental Asset categories for youth ages 11-18. Based on Search Institute’s Developmental Assets framework, the DAP provides a quick, simple, valid, and reliable self-report of the Developmental Asset categories currently being experienced by adolescents. The DAP provides a way to document, quantify, and portray adolescents’ reports of the types and levels of Developmental Assets working in their lives.
The DAP was not designed to yield information about the presence or absence of each of the 40 Developmental Assets. Instead, the DAP yields quantitative scores on eight asset categories, as well as five context areas. The DAP can be a useful descriptive tool in a wide range of settings including schools, mental health practices, family services organizations, and youth programs; and for diverse purposes including individual assessment, research, and program evaluation.
The Developmental Assets framework includes both external and internal assets. External assets are positive experiences, relationships, and encouragement and support young people receive from peers, parents, teachers, neighbors, and other adults in the community. They include positive role models, boundaries and expectations, as well as young people’s constructive use of time. Internal assets are characteristics and behaviors that reflect positive personal and psychological development in young people. They include strengths such as positive values, positive identity, social competencies, and commitment to learning.
© 2010, Search Institute, Minneapolis, MN
Scoring and Reporting DAP Results
There are two alternative ways of scoring and portraying reported assets. The DAP yields quantitative scores on eight asset categories, as well as five context areas. Of 58 items, 26 tap external assets, and the remaining 32 tap internal assets.
On the external asset side, the DAP scales are:
I. Support—support from parents, family and other adults; parent-adolescent communication; advice and help from parents; helpful neighbors; and caring school environment.
II. Empowerment—feeling safe at home, at school and in the neighborhood; feeling valued; and having useful jobs and roles.
III. Boundaries and Expectations—having good role models; clear rules at home and school; encouragement from parents and teachers; and monitoring by family and neighbors.
IV. Constructive Use of Time—participation in religious or spiritual activity; involvement in a sport, club, or group; creative activities; and quality time at home.
On the internal asset side, the DAP scales are:
V. Commitment to Learning—enjoys reading and learning; caring about school; doing homework; and being encouraged to try new things.
VI. Positive Values—standing up for one’s beliefs; taking responsibility; avoiding alcohol, tobacco and drugs; valuing honesty; healthy behaviors; being encouraged to help others; and helping, respecting, and serving others.
VII. Social Competencies—building friendships; properly expressing feelings; planning ahead; resisting negative peer pressure; being sensitive to and accepting others; and resolving conflicts peacefully.
VIII. Positive Identity—optimism; locus of control; and self-esteem.
The 58 items can also be grouped according to five context areas. The context areas scales are:
A. Personal Assets—individual psychological and behavioral strengths such as self esteem, valuing honesty, taking responsibility, planning ahead, managing frustration, enjoying reading, and feeling in control of one’s life.
B. Social Assets—assets based on social relationships with one or more people outside of the family, such as friendships, positive peer and adult role models, resisting pressure from others, resolving conflicts peacefully, being sensitive to others, and feeling valued by others.
C. Family Assets—positive family communication and support, clear family rules, quality time at home, advice and encouragement from parents, and feeling safe at home.
D. School Assets—clear and fair school rules, encouragement from teachers, a caring school environment, feeling safe at school, caring about school, being motivated to learn, and being actively engaged in reading and learning.
E. Community Assets—activities and involvements in the larger community such as sports, clubs, groups and religious activities, creative activities such as music and the arts, having good neighbors, accepting others, and helping in the community.
© 2010, Search Institute, Minneapolis, MN
Notes
I would like to find some way of fitting this chart in somewhere; it is the average answers for each DAP question by letter grade. I think that this is probably the principle finding of the research; everything else is applications.
Once again it decided to nix the graphs. If you want to see them, I can send you a copy with the graphs. I also plan to update this post whenever I make major changes to the paper.
ReplyDelete