Cagayan State University HEEDS

HEEDS abbreviates "Higher Education Enrollment Decision Support", an open-source web-based program to support enrollment planning by Higher Educational Institutions (HEIs), particularly the State Universities and Colleges in the Philippines. Intended as an add-on module to an existing academic information system, HEEDS empowers the Registrar to single-handedly predict the demand for subjects (needs analysis) and to pre-enlist students en masse into classes. © Ricolindo L. Carino

For answers to frequently asked questions, visit the CSU HEEDS Facebook page.

Features

Primarily built to support registrars, college secretaries, deans, department chairs, academic advisers, and workload schedulers, HEEDS includes the following features :

Uses existing data (see Integration with existing academic information system)

Automated needs analysis and pre-enlistment: Registrar can, single-handedly within a few minutes, run automated advising (Needs Analysis) to predict the demand for subjects; and run automated pre-enlistment of students en masse into classes (This probably differentiates HEEDS from other online enrollment systems)

Online advising and assisted enlistment, to amend auto-advised subjects and auto-enlisted classes: Advisers can specify subjects to be enrolled by students and enlist students into classes

Online grades and self-enlistment: Students can view grades, view checklists, and, if allowed, self-enlist into classes.
STUDENTS! Self-enlist from anywhere without data costs by using a mobile device on Free Basics, or from home/cafe internet for much less time+money than travelling to campus. View your class schedule and grades anytime, or let your parents and benefactors do so. Evaluate your teachers with no hurry. Go paperless, almost.

Online evaluation of instruction/teaching effectiveness: self-evaluation, evaluation by students, peers, and supervisor; summary reports by teacher, by subject, by department

Online classlists and grade entry: Teachers can view their load forms and classlists, and can enter then print end-of semester grades for signature. Registrar can enter completions and advanced credits

Online workload preparation: Department Chairs can collaboratively prepare conflict-free Schedule of Classes (with the names of teachers hidden from display if desired)

Online pre-filled forms: Printables for signature include Teaching Workload Forms, Classlists, Certification of Grades, Gradesheets, and Unofficial Transcripts

Online monitoring of scholars by benefactors: Scholarship providers can view classes and grades of beneficiaries

Online reports of student distributions: by gender (male, female), by home address (barangay, town, province, region), by academic standing (1st yr, 2nd year, etc); per college, per curriculum, per year level

Other labor-saving features ...

Purpose

Students enroll during the start of a term. During this time, a student, probably with help from his/her registration adviser:
  1. selects the subjects to attempt for credit during the term, and
  2. selects non-conflicting classes for those subjects
When the subjects and classes are fixed, the student pays the required fees, and is considered officially enrolled for the CURRENT term.

Shortly after the start of classes, HEI administrators start preparing ("Enrollment planning") for the NEXT term. The crucial decisions to be made by administrators are:

  1. Which subjects to offer next term; and
  2. How many classes to open for each subject

Thus, administrators need a "crystal ball" to see two to three months ahead in the future: what subjects will be needed, and how many students will need each subject. This crystal ball is particularly useful to the Chairs of departments that administer 'service' or 'general elective (GE)' subjects.

HEEDS mimics the "crystal ball" to provide predictions that may be useful for university administrators. HEEDS utilizes a computational modeling and simulation approach to predict the subjects to be selected by a student. A simple count of how many students are predicted to select a subject provides the demand for the subject. This demand translates into the number of classes to open for the subject. The number of classes for each subject offered by an academic department translates into the estimated teaching load of the department. A comparison of the estimated teaching loads of departments provides quantitative insight in determining which departments require additional manpower, or which departments can "lend" their faculty to other departments.

In addition to predicting the subjects to be selected by each student, HEEDS also pre-enlists students into non-conflicting classes for their subjects. This pre-enlistment may be accepted as-is or modified by students during the actual enrollment period.

Thus, HEEDS creates a picture of possible outcomes of enrollment for next term, up to several weeks before it actually occurs.

Enrollment Planning

The figure above illustrates the overall enrollment planning process supported by HEEDS. Green ellipses are applications that may run in a server on the HEI's intranet or on a public server accessible via the Internet.

Automated advising and Demand prediction are carried out twice: the first time after enrollment is complete but grades are not yet available ( Probabilistic demand prediction), and the second time after the plans of study are updated and the grades for the term are submitted (Deterministic demand prediction). The probabilistic demand for a subject is calculated using historical failure rate in the subject. The probabilistic demand is used by the departments to estimate the number of classes, to Prepare the initial Schedule of Classes. After the plans of study are updated and grades of students are submitted (i.e., the most up-to-date information are available), Deterministic demand prediction generates information to Refine the Schedule of Classes. Based on the predicted subjects of students and the refined Schedule of Classes, Automated scheduling (timetabling) generates initial class schedules for the students to be accepted "as-is", or modified manually (Select subjects then Enlist into classes) during enrollment period.

Let D1, D2, D3 and D4 represent the following dates in a TERM of a SCHOOL YEAR:

The dates divide the TERM into the following periods:

1. [D1, D2] Registration Period

  1. Student+Adviser add and/or delete classes for CURRENT TERM.
  2. Departments finalize teaching loads, schedules and classlists for CURRENT TERM.
  3. Faculty view classlists and teaching load forms for CURRENT TERM.

2. (D2, D3] Advising Period

  1. Registrar generates the checklists of students and the probabilistic demand for subjects NEXT TERM (needs analysis).
  2. Student+Adviser edit incorrect information in student checklist, and select electives if applicable
  3. Departments view the predicted demand for subjects, and prepare the tentative Schedule of Classes and individual faculty teaching loads for NEXT TERM.

3. (D3, D4] Grading Period - Faculty submits grades.

4. (D4, D1 of next term) Pre-enlistment Period

  1. Registrar updates the lists of subjects, curricular programs, rooms, teachers, students, etc.
  2. Registrar updates the grades of students.
  3. Registrar generates the deterministic demand for subjects NEXT TERM (needs re-analysis).
  4. Departments view the revised demand for subjects, and update the Schedule of Classes and individual faculty teaching loads for NEXT TERM.
  5. Registrar generates initial class timetables of students for NEXT TERM.
  6. Registrar/VPAA view reports on underloading, insufficient number of sections, and sections with many open slots. Registrar/VPAA decide if Schedule of Classes needs further refinement. If so, repeat Steps 4.3, 4.4, 4.5 and 4.6
  7. If the pre-enlistment of students is acceptable, advance to Registration Period for NEXT TERM.

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Copyright

HEEDS Copyright (C) 2012-16 Ricolindo L. Carino

This program comes with ABSOLUTELY NO WARRANTY; for details see the GNU GENERAL PUBLIC LICENSE Version 3. This program is free software, and you are welcome to redistribute it under certain conditions; see the GPLv3 for details (http://www.gnu.org/licenses/gpl-3.0.html).

Support for the development of this program was provided by: University of the Philippines Los Banos (1997-2001); BalikScientist Program of the Department of Science and Technology (2010); Isabela State University (2011); and Cagayan State University (2012-13,2016).

The source code is available at https://github.com/rlcarino/heeds. The CSS is from http://www.w3schools.com/w3css/w3css_downloads.asp.

E-mail inquiries about HEEDS to Ricolindo.Carino@AcademicForecasts.com, or browse his other work at http://www.hpc.msstate.edu/directory/information.php?eid=2335.