Filter Course Schedule by College, Department, Program, Subject, and/or Instructor

Description

Applies one or more filters to a course schedule using pattern matching on instructor, subject, college, department, and program. All matching is case-insensitive and based on partial string matching.

Usage

filter_schedule(
  schedule,
  subject_pattern = NULL,
  instructor_pattern = NULL,
  college_pattern = NULL,
  department_pattern = NULL,
  program_pattern = NULL
)

Arguments

Value

A filtered data frame of matching courses.

Examples

schedule <- data.frame(
  INSTRUCTOR = c("Lee", "Smith", "Jones", "Dawson", "Garcia"),
  SUBJ = c("MATH", "NURS", "CSCI", "ENGL", "COMM"),
  COLLEGE = c("Science", "Nursing", "Science", "Arts and Sciences", "Arts and Communication"),
  DEPARTMENT = c("Math", "Nursing", "CS", "English", "Comm Studies"),
  PROGRAM = c("BS", "BSN", "BS", "BA", "BA"),
  stringsAsFactors = FALSE
)

filter_schedule(schedule, subject_pattern = "^MATH|^STAT")
filter_schedule(schedule, instructor_pattern = "smith")
filter_schedule(schedule, college_pattern = "Science")
filter_schedule(schedule, department_pattern = "Comm")
filter_schedule(schedule, program_pattern = "^BA$")

Filter Course Schedule by Instructor (Regex-Friendly, Case-Insensitive)

Description

Returns a subset of the course schedule containing courses taught by the specified instructor. Matching is case-insensitive and supports regular expressions, allowing flexible partial or pattern-based matching. If no match is found, a warning is issued and an empty data frame is returned.

Usage

get_instructor_schedule(instructor_name, schedule_df = schedule)

Arguments

Value

A data frame of courses assigned to instructors matching the given pattern, sorted by descending enrollment.

Examples

get_instructor_schedule("smith", schedule_df = schedule)  # partial match
get_instructor_schedule("^Smith,", schedule_df = schedule)  # regex: starts with Smith
get_instructor_schedule("Robinson|Smith", schedule_df = schedule)  # regex: matches either

Filter Course Schedule by Subject Code (Regex-Friendly)

Description

Returns a subset of the schedule where the SUBJ (subject code) column matches a given pattern. Matching is case-insensitive and supports regular expressions.

Usage

get_subject_schedule(subject_pattern, schedule)

Arguments

Value

A filtered data frame containing only matching subject codes.

Examples

schedule <- data.frame(SUBJ = c("CSCI", "MATH", "STAT"))
get_subject_schedule("CSCI", schedule)
get_subject_schedule("^MATH|^STAT", schedule)

Get Unique Instructor Names

Description

Extracts a sorted vector of unique, non-empty instructor names from a schedule data frame.

Usage

get_unique_instructors(schedule_df)

Arguments

Value

A character vector of instructor names, sorted alphabetically.

Examples

get_unique_instructors(schedule)

Calculate Overload Compensation for One Instructor

Description

Computes prorated overload pay and qualified credit hours for a single instructor based on course credit hours, enrollment, and institutional overload rules.

Usage

ol_comp(
  instructor_schedule,
  L = 4,
  U = 9,
  rate_per_cr = 2500/3,
  reg_load = 12,
  favor_institution = TRUE
)

Arguments

Details

If favor_institution = TRUE (default), the function assigns high-enrollment qualified courses to the regular load first, resulting in lower compensation because only low-enrollment courses are left for overload pay — this favors the institution.

If favor_institution = FALSE, the function assigns low-enrollment qualified courses to the regular load first, preserving high-enrollment courses for compensation — this favors the instructor.

Note: This function assumes that instructor_schedule is already filtered for one instructor. Use get_instructor_schedule() to extract an instructor’s schedule using flexible, case-insensitive pattern matching (regex supported, e.g., "smith|jones").

Value

A tibble with course-level compensation and a human-readable summary block.

Calculate Overload Compensation for One Instructor (by Index)

Description

Retrieves an instructor's name by index from the schedule and calculates their overload compensation using ol_comp(). Returns a clean, readable course-level compensation summary.

Usage

ol_comp_byindex(
  i,
  schedule_df,
  L = 4,
  U = 9,
  rate_per_cr = 2500/3,
  reg_load = 12,
  favor_institution = TRUE
)

Arguments

Details

If favor_institution = TRUE (default), the function assigns high-enrollment courses to the regular load first, minimizing compensation.

If favor_institution = FALSE, low-enrollment courses are used toward the regular load first, preserving high-enrollment courses for overload pay.

This function internally uses get_instructor_schedule(), which supports flexible, case-insensitive regex matching for instructor names (e.g., "^smith$" or "johnson|williams").

Value

Invisibly returns a tibble with the instructor’s course-level overload compensation summary.

Examples

# Example usage with a schedule dataframe:
# ol_comp_byindex(1, schedule_df = schedule)

Summarize Overload Compensation

Description

Calculates overload compensation for each instructor based on institutional policy. The output includes course-level payments, qualified credit hours, and a readable instructor-level summary block that follows each instructor's courses.

Usage

ol_comp_summary(
  schedule_df,
  instructor = NULL,
  L = 4,
  U = 9,
  rate_per_cr = 2500/3,
  reg_load = 12,
  favor_institution = TRUE
)

Arguments

Details

If the instructor argument is specified, the function limits the summary to that instructor. Matching is exact and case-sensitive unless pre-filtered using get_instructor_schedule(), which supports regex-based, case-insensitive pattern matching (e.g., "smith|jones").

Value

A tibble combining course-level compensation and a summary section for each instructor.

Sample Schedule Dataset

Description

This dataset represents a sample class schedule used by several institutions, with slight variations in variable names. Users must ensure that the key variables—HRS, ENRLD, and INSTRUCTOR—are properly named and formatted for the functions in this package to work correctly.

Usage

schedule

Format

An object of class data.frame with 665 rows and 15 columns.

Details

A dataset containing instructor schedules for overload analysis.

The dataset has 665 rows and 15 columns, including:

HRS

Credit hours of the course.

ENRLD

Number of students enrolled in the course.

INSTRUCTOR

Name of the instructor teaching the course (anonymized).

Source

Included in the package under data/schedule.rda