As early as the mid-1960s, researchers have been exploring "talent loss." Sandra Hanson (1994) defines talent loss as a phenomenon that occurs among adolescents who show early academic potential but who had educational expectations lower than their aspirations, reduced their expectations over time, or never realized their expectations. In her study, Hanson found that social class was one of the strongest predictors of talent loss.
In 1995, a sample survey was taken of 900 high school seniors who had taken the SAT that year (King, 1996). Of those surveyed, only 15% identified themselves as coming from low-income backgrounds (having a family income of less than $20,000), and of that already small group, only 66% expressed that they thought they might attend a four year college or university. In general, it was found that low-income SAT takers are "more likely than their peers to choose an option other than attending a four-year college or university" (King, 1996, p.7).
King's study goes on to identify the major contributing factors that distinguished low-income who chose to attend college from those who did not. Three of these main factors are (1) low academic self-confidence and personal aspirations; (2) insufficient course work and low academic achievement; and (3) lack of thorough college information, financing, and preparation. Additionally, survey data showed that "receiving [college] information from other sources, such as guidebooks, catalogs, and videos, was not associated with increased college attendance" (King, 1996, p. 10).
Finally, this stratification between low-income students and their peers is likely to increase with time if this issue continues to remain unaddressed (Plank & Jordan, 2001). More and more students are enrolling in college in the United States over the past century. While enrollment in colleges and universities increased by 66% between 1970 and 1993, the total US population has increased by only 27% (US Department of Education, 1995).
The Learning Problem
Many low-income high school students have educational expectations that are lower than their aspirations and academic ability, resulting in a much lower rate of application to post-secondary institutions than student from more affluent backgrounds (Hanson, 1994). While a variety of factors contribute to this problem, a lack of reliable information about college admissions, insufficient course work and academic achievement, and a lack of academic self-confidence are among the most prominent (King, 1996).
There are over 500 students for every one school counselor in US high schools (US Department of Education, 1995), so it is difficult for many students to get the assistance they need in the college admissions process. It has also been found that existing admissions materials are "less comprehensible - especially cost, financial aid, and scholarship information - for underserved students than for middle income students" (NPEC, 2007, p. iv). In particular, college finance is largest issue for this population. According to the National Association for College Admission Counseling:
Counselors at schools with a majority of low-income students are much more likely to say that fear of debt "strongly affects" college choices (56%) than counselors at schools with fewer low-income students (34%). (NACAC, 2007, p. 5)
Low-income students and their parents tend to make decisions based on "incomplete or inaccurate information" (Plank & Jordan, 2001, p. 950) about college finances, supporting the misconception that they cannot afford to attend a post-secondary school.
In summary, lack of reliable college information, especially financial issues, combined with low academic self-confidence among underserved high school students has led to a decline in the rate of college applications from qualified students.
We have two main learning goals associated with CAIA:
- To provide financial aid information concerning college for low-income students in an interactive and easily accessible environment.
- To increase the interest and knowledge of all students in college finances with the assistance of a interactive intelligent agent.