Added data for CARS and ABET samples of work

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]],