Agent-based Simulation Models of the College Sorting Process

We explore how dynamic processes related to socioeconomic inequality operate to sort students into, and create stratification among, colleges. We use an agent-based model to simulate a stylized version of this sorting processes in order to explore how factors related to family resources might influence college application choices and college enrollment. We include two types of “agents”—students and colleges—to simulate a two-way matching process that iterates through three stages: application, admission, and enrollment. Within this model, we examine how five mechanisms linking students’ socioeconomic background to college sorting might influence socioeconomic stratification between colleges including relationships between student resources and: achievement; the quality of information used in the college selection process; the number of applications students submit; how students value college quality; and the students’ ability to enhance their apparent caliber. We find that the resources-achievement relationship explains much of the student sorting by resources but that other factors also have non-trivial influences

A Cognitive Agent Computing-Based Model For The Primary School Student Migration Problem Using A Descriptive Agent-Based Approach

Students' migration from public to private schools, due to lack of school performance of public schools, is one of the major issues faced by the Government of Punjab to provide compulsory and quality education at low cost. Due to complex adaptive nature of educational system, interdependencies with society, constant feedback loops conventional linear regression methods, for evaluation of effective performance, are ineffective or costly to solve the issue. Linear regression techniques present the static view of the system, which are not enough to understand the complex dynamic nature of educational paradigm. We have presented a Cognitive Agent Computing-Based Model for the School Student Migration Problem Using a Descriptive Agent-Based Modeling approach to understand the causes-effects relationship of student migration. We have presented the primary school students' migration model using descriptive modeling approach along with exploratory modeling. Our research, in the context of Software Engineering of Simulation & Modeling, and exploring the Complex Adaptive nature of school system, is two folds. Firstly, the cause-effect relationship of students' migration is being investigated using Cognitive Descriptive Agent-Based Modeling. Secondly, the formalization extent of Cognitive Agent-Based Computing framework is analyzed by performing its comparative analysis with exploratory modeling protocol 'Overview, Design, and Detail'.Comment: 117 pages, MS thesi

College Choice and College Match Among High-Achieving Pell-Eligible Students: An Instrumental Case Study Exploring Social Actor Influence

College undermatch, the pattern of well-qualified students applying to and attending less selective colleges than their academic qualifications would permit, disproportionally affects low-SES students, a particular concern since attending a match college increases the likelihood that a student will graduate and reduces the amount of time to degree. The number of college-going individuals in one’s social network (including parents, peers, teachers, mentors, etc.) has a strong influence on whether a student attends a good academic match college, but little is known about the nature of the interactions between students and these college-going influencers. This instrumental case study sought to fill that gap by exploring how students perceived influencers of college choice, the nature of the interactions with and/or among these influencers, and, finally, how these influencers may have impacted the selectivity level of institution attended. Using participant-aided sociograms within one-on-one interviews, along with constant comparison analysis and classical content analysis, this study found parents and teachers to be the most influential on the college choice decision process of Pell-eligible students. A typology of advice-giving styles blended with three decision-making styles in that process. Participant communication patterns ranged from fully open to fully restricted and, at times, participants intentionally restricted communication about college choice to manage social exchanges. Addressing financial anxiety seemed to be the most salient factor to increase the selectivity of a Pell-eligible student’s enrollment choice, and financial counseling from non-family college graduates appeared to be the most connected to intentional changes of college selectivity level, though that influence occurred in multiple directions. The study’s findings suggest new ways to think about college financing, changes in teacher and counselor preparation programs and new directions in college choice and college undermatch research