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ENROLLMENT_ALL_V - Data Element Index . Tables and Data Elements . Student Data Home . Data Warehouse Home

ENROLLMENT Table/View

(dwadmin.enrollment_all_v)

Explanation

Term-specific data about the course sections in which a student has enrolled. The table has information which applies before the student completes the course section, such as Registered_Credit and Section_Id; and information which applies after completion of the course section, such as Official_Grade and Quality_Points. Contains one record for each course section for which a student was enrolled, for each term for which the student has data. It allows reporting all course sections a student has enrolled in and all the students that enrolled in a course section. Grades and credits received are some of the most-used elements in this table.

Common Uses

  • Creating pseudo-transcripts (though only the Office of the Registrar creates actual transcripts). ("I need to see what courses my advisees have already taken.")
  • Finding the course sections in which a student was enrolled for a particular term. ("Here's a student's ID. Give me a printout of all that student's enrollments for the previous spring and fall terms.")
  • Creating class lists showing all students enrolled in a particular course section in a term. ("The professors in our department want classlists for the courses that they teach.")
  • Analyzing grades. ("Is there any relationship between grades given in either the spring and fall and those given in the summer?")
Primary Key Indexed Data Elements Related Tables
SSN, TERM, SECTION_ID, OWNER   ASSIGNMENT
CEN_STDT_ENROLLMENT
COURSE_SECTION
DEGREE_TERM_ALL_V
PERSON_ALL_V

Cautions

  • Though Section_Id is indexed, the related elements -- Subject_Area, Course_Number, Section_Number and Course_Id -- are not indexed. Whenever possible, use Section_Id in record selection conditions, therefore, and use the related elements primarily for easy display. For example, rather than using "WHERE Subject_Area = 'ENGL'", use "WHERE Section_Id LIKE 'ENGL%'" to have the speedier queries that an indexed element allows.
  • Owner in the primary key can be ignored. The access privileges on this table use Owner to allow users to see only the records "owned" by their department or school if they have restricted warehouse access. Since access security takes Owner into account, you may ignore it in your queries.
  • A student's enrollments for a term may not all apply to the degree in which you are interested. See the ASSIGNMENT Table for determining the degree or degrees to which an enrollment applies.
  • Many courses require students to enroll in course sections having different activities -- for example, both a lecture and a laboratory, or a lecture and a recitation. In this case the Official_Grade and associated Earned_Credit may not be awarded to both course sections: for lecture/lab, for example, the lecture may have all the credit and the lab none, or the reverse. When doing analyses, then, be prepared for course sections which have no grade (the grade likely was awarded to another course section of the course if the term is completed). Also, use Earned_Credit and Quality_Credit to determine whether the course section is included in your query or not.
  • Though they have many similar data elements, this table and CEN_STDT_ENROLLMENT differ because ENROLLMENT_ALL_V contains grades for enrollments from previous terms, while CEN_STDT_ENROLLMENT will never have grades. Also, ENROLLMENT_ALL_V will have the latest data for all date elements, whereas CEN_STDT_ENROLLMENT will have data as it was at the time of the Census Date. (See also the CEN_STDT_ENROLLMENT Table.)
  • While SSN is part of the key, it is not visable to most queries and users. Use PennID for identification of individuals in this table. Joins in the Business Objects universes are done on PennID, instead of SSN.

ENROLLMENT_ALL_V - Data Element Index . Tables and Data Elements . Student Data Home . Data Warehouse Home

 


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Information Systems and Computing
University of Pennsylvania
Information Systems and Computing, University of Pennsylvania