Advising, Registration & Mentoring Task Force Arab Acrao meeting Hosted by the Arab Maritime Academy March 2013

Starting Point The strategic enrollment model was initiated to address the problem and difficulties the freshman students (new and returning) encounter in their registration of their courses The prevailing system shows that the course demand as requested by the students is not linked with the course supply.

Problems encountered There are high demand courses that have limited capacity and cannot accommodate all students’ requests. There are low demand courses that students are obliged to register in because they cannot find places in the desired courses. Accordingly, there is always over enrollment in the high demand courses versus low enrollment in the low demand courses. The newly accepted students that are admitted within a week before the first day of classes, ie (IGCSE, Scholarship students, deferred payments) cannot find proper classes to register in as the slots are already filled.

Reduce the frustration for both students and faculty Classroom enrollment capacity will be maintained within acceptable standards. Academic departments will be notified early enough with the predicted courses and slots Plan for resources : Class rooms, intructors, labs, etc The Model will allow the prediction of needed courses, for all declared and undeclared students during their first 3 semesters. Advisors will estimate the needed courses for the following semesters

The idea behind the design of this model is based on the collection of data since Fall 2008, and deducing the statistical trends across them, inclusive of fall and spring semesters. These data were collected to reflect the number of “slots and trends of courses” taken for both new and returning students.

The data was analyzed as follows: English Placement Declaration Status New English Placement Declaration Status Returning

Data Analysis at the Admissions Stage Undeclared ELI 98 ELI 99 Undeclared English 100 Undeclared RHET Declared in Sc & Engineering ELI 98 ELI 99 Declared in Sc & Engineering English 100 Declared in Sc & Engineering RHET

Distribution of newly admitted student according to English Placements and major

Returning students breakdown As per the English class level : Those who passed the ELI 98 to ELI 99 (semi hypothetical) Those who passed the ELI 99 to Eng 100 (semi hypothetical) Those who passed the ENG 100 to the RHET 101 (semi hypothetical) RHET 102 students (semi hypothetical) RHET 201 students (semi hypothetical (Semi hypothetical means that we started with actual enrolled numbers and assuming that all passed and went one English level up).

English Placement Progress

Total number of students in fall 2012, new & continued, with a break down by English class 247

Returning students breakdown Cont. Returning Students (Actual Numbers) Hypothetically 1/3 =Intended Science Hypothetically 2/3= Intended Non Science

Enrollment Model New English Placement Intended MajorTrends Continued English Placement Intended MajorTrends Final Prediction model

Fall 2012 Original & Predictive numbers

With this actual, semi and hypothetical numbers, an idealistic Enrollment model is generated to list all general courses that should be offered to the students (new and returning) as planned in the catalog with their corresponding expected planned slots. Implementing this model will clarify and shed up the light on the needed places requested by freshman students in specific courses.

Actual advisors numbers versus admissions numbers

The model was computerized to include all incoming actual numbers in the semester, help in predicting the courses needed for the freshman students, new and returning and the desirable slots per section.

New & Returning students statistics from Banner.

Summary Computerization of the model : Maintain a trend that includes New and Returning student classified by their English Placement and Declaration of major status Helps in accurately predicting the number of places in the courses for the following semesters for both new and returning students To create planning scenarios for the academic departments To integrate the admissions numbers with the university advisors numbers.