diff --git a/analyze_grades.py b/analyze_grades.py
index 32c86bc0cc630c476e39c29737f3dc490c8b3084..aa2e9e20f3d40d550e6de94ec531d6ccd03fc324 100644
--- a/analyze_grades.py
+++ b/analyze_grades.py
@@ -3,7 +3,7 @@
import datetime
import statistics
import sys
-from typing import List, Optional, Dict, Set
+from typing import List, Optional, Dict, Set, Tuple
from api.canvas_classes import CanvasAssignment, CanvasAssignmentGroup, CanvasCourse, CanvasUser
from common_functions import select_from_list
@@ -49,6 +49,94 @@ def create_semester_filter() -> str:
return f'1{str(year)[-2:]}{month}' # introducing a y2.1k problem
+def select_students_for_material_collection(assignment, student_subset) -> Tuple[CanvasUser, CanvasUser, CanvasUser]:
+ points_possible: float = assignment.get_points_possible()
+ grade_thresholds: Dict[str, float] = {
+ 'A': 0.93 * points_possible,
+ 'A-': 0.90 * points_possible,
+ 'B+': 0.87 * points_possible,
+ 'B': 0.83 * points_possible,
+ 'B-': 0.80 * points_possible,
+ 'C+': 0.77 * points_possible,
+ 'C': 0.73 * points_possible,
+ 'C-': 0.70 * points_possible
+ }
+ a_student: Optional[CanvasUser] = None
+ b_student: Optional[CanvasUser] = None
+ c_student: Optional[CanvasUser] = None
+ candidates_for_material_collection: Set[CanvasUser] = \
+ {student for student in student_subset
+ if assignment.get_score(student) is not None
+ and assignment.get_score(student) >= grade_thresholds['A']}
+ if len(candidates_for_material_collection) == 0:
+ candidates_for_material_collection = \
+ {student for student in student_subset
+ if assignment.get_score(student) is not None
+ and assignment.get_score(student) >= grade_thresholds['A-']}
+ if len(candidates_for_material_collection) > 0:
+ a_student = candidates_for_material_collection.pop()
+ candidates_for_material_collection = \
+ {student for student in student_subset if assignment.get_score(student) is not None
+ and grade_thresholds['B'] <= assignment.get_score(student) < grade_thresholds['B+']}
+ if len(candidates_for_material_collection) == 0:
+ candidates_for_material_collection = \
+ {student for student in student_subset if assignment.get_score(student) is not None
+ and grade_thresholds['B-'] <= assignment.get_score(student) < grade_thresholds['A-']}
+ if len(candidates_for_material_collection) > 0:
+ b_student = candidates_for_material_collection.pop()
+ candidates_for_material_collection = \
+ {student for student in student_subset if assignment.get_score(student) is not None
+ and grade_thresholds['C'] <= assignment.get_score(student) < grade_thresholds['C+']}
+ if len(candidates_for_material_collection) == 0:
+ candidates_for_material_collection = \
+ {student for student in student_subset if assignment.get_score(student) is not None
+ and grade_thresholds['C-'] <= assignment.get_score(student) < grade_thresholds['B-']}
+ if len(candidates_for_material_collection) > 0:
+ c_student = candidates_for_material_collection.pop()
+ return a_student, b_student, c_student
+
+
+def print_sample_scores(assignment: CanvasAssignment, majors: Set[Major],
+ major_partitions: Dict[Major, Set[CanvasUser]],
+ students: Optional[List[CanvasUser]] = None) -> None:
+ points_possible: float = assignment.get_points_possible()
+ a_student: Optional[CanvasUser] = None
+ b_student: Optional[CanvasUser] = None
+ c_student: Optional[CanvasUser] = None
+ for major in majors:
+ student_subset: Set[CanvasUser] = major_partitions[major] if students is None \
+ else major_partitions[major].intersection(students)
+ selected_students: Set[CanvasUser] = set()
+ if len(student_subset) == 0:
+ print(f'{major.name}: no students.')
+ elif len(student_subset) <= 30:
+ print(f'{major.name} has {len(student_subset)} students: reporting scores for all students.')
+ selected_students = student_subset
+ a_student, b_student, c_student = select_students_for_material_collection(assignment, student_subset)
+ else:
+ print(
+ f'{major.name} has {len(student_subset)} students: reporting scores for 30 randomly-selected students.')
+ # let's make sure there are an 'A', a 'B', and a 'C' student in the mix
+ a_student, b_student, c_student = select_students_for_material_collection(assignment, student_subset)
+ for student in (a_student, b_student, c_student):
+ if student is not None:
+ student_subset.remove(student)
+ selected_students.add(student)
+ while len(selected_students) < 30:
+ student = student_subset.pop()
+ selected_students.add(student)
+ i = 1
+ for student in selected_students:
+ print(f'Student {i:>2} -- raw score: {assignment.get_score(student)}'
+ f'\tscaled score: {100 * assignment.get_score(student) / points_possible}')
+ print('Collect sample materials --')
+ print(f'"A" student: {a_student.get_name()}')
+ print(f'"B" student: {b_student.get_name()}')
+ print(f'"C" student: {c_student.get_name()}')
+ i += 1
+ print()
+
+
def print_statistics_for_some_majors(assignment: CanvasAssignment, majors: Set[Major],
major_partitions: Dict[Major, Set[CanvasUser]],
students: Optional[List[CanvasUser]] = None) -> None:
@@ -76,6 +164,8 @@ def print_statistics(assignment: CanvasAssignment, major_partitions: Dict[Major,
non_computing_majors: Set[Major] = {major for major in major_partitions.keys() if not major.is_computing_major}
print_statistics_for_some_majors(assignment, computing_majors, major_partitions)
print_statistics_for_some_majors(assignment, non_computing_majors, major_partitions)
+ print()
+ print_sample_scores(assignment, computing_majors, major_partitions)
def print_statistics_by_section(course: CanvasCourse, assignment: CanvasAssignment,
@@ -95,6 +185,8 @@ def print_statistics_by_section(course: CanvasCourse, assignment: CanvasAssignme
print_statistics_for_some_majors(assignment, computing_majors, major_partitions, students)
print_statistics_for_some_majors(assignment, non_computing_majors, major_partitions, students)
print()
+ print_sample_scores(assignment, computing_majors, major_partitions, students)
+ print()
def assess_assignments(course: CanvasCourse, major_partitions: Dict[Major, Set[CanvasUser]],