def test_grade_essay_all_feedback_only_criteria(self):
# Modify the rubric to include only feedback-only criteria
rubric = copy.deepcopy(RUBRIC)
for criterion in rubric['criteria']:
criterion['options'] = []
# Train classifiers for the rubric
train_classifiers(rubric, {})
# Schedule a grading task and retrieve the assessment
ai_api.on_init(self.submission_uuid,
rubric=rubric,
algorithm_id=ALGORITHM_ID)
assessment = ai_api.get_latest_assessment(self.submission_uuid)
# Verify that all assessment parts have feedback set to an empty string
for part in assessment['parts']:
self.assertEqual(part['feedback'], u"")
# Check the scores by criterion dict
# Since none of the criteria had options, the scores should all default to 0
score_dict = ai_api.get_assessment_scores_by_criteria(
self.submission_uuid)
self.assertItemsEqual(score_dict, {
u"vøȼȺƀᵾłȺɍɏ": 0,
u"ﻭɼค๓๓คɼ": 0,
})
def test_grade_essay_feedback_only_criterion(self):
# Modify the rubric to include a feedback-only criterion
# (a criterion with no options, just written feedback)
rubric = copy.deepcopy(RUBRIC)
rubric['criteria'].append({
'name': 'feedback only',
'prompt': 'feedback',
'options': []
})
# Train classifiers for the rubric
train_classifiers(rubric, self.CLASSIFIER_SCORE_OVERRIDES)
# Schedule a grading task and retrieve the assessment
ai_api.on_init(self.submission_uuid, rubric=rubric, algorithm_id=ALGORITHM_ID)
assessment = ai_api.get_latest_assessment(self.submission_uuid)
# Verify that the criteria with options were given scores
# (from the score override used by our fake classifiers)
self.assertEqual(assessment['parts'][0]['criterion']['name'], u"vøȼȺƀᵾłȺɍɏ")
self.assertEqual(assessment['parts'][0]['option']['points'], 1)
self.assertEqual(assessment['parts'][1]['criterion']['name'], u"ﻭɼค๓๓คɼ")
self.assertEqual(assessment['parts'][1]['option']['points'], 2)
# Verify that the criteria with no options (only feedback)
# has no score and empty feedback
self.assertEqual(assessment['parts'][2]['criterion']['name'], u"feedback only")
self.assertIs(assessment['parts'][2]['option'], None)
self.assertEqual(assessment['parts'][2]['feedback'], u"")
# Check the scores by criterion dict
score_dict = ai_api.get_assessment_scores_by_criteria(self.submission_uuid)
self.assertEqual(score_dict[u"vøȼȺƀᵾłȺɍɏ"], 1)
self.assertEqual(score_dict[u"ﻭɼค๓๓คɼ"], 2)
self.assertEqual(score_dict['feedback only'], 0)
def _ai_assess(sub):
"""
Helper to fulfill ai assessment requirements.
"""
# Note that CLASSIFIER_SCORE_OVERRIDES matches OPTIONS_SELECTED_DICT['most'] scores
train_classifiers(RUBRIC, AIGradingTest.CLASSIFIER_SCORE_OVERRIDES)
ai_api.on_init(sub, rubric=RUBRIC, algorithm_id=ALGORITHM_ID)
return ai_api.get_latest_assessment(sub)
def _ai_assess(sub):
"""
Helper to fulfill ai assessment requirements.
"""
# Note that CLASSIFIER_SCORE_OVERRIDES matches OPTIONS_SELECTED_DICT['most'] scores
train_classifiers(RUBRIC, AIGradingTest.CLASSIFIER_SCORE_OVERRIDES)
ai_api.on_init(sub, rubric=RUBRIC, algorithm_id=ALGORITHM_ID)
return ai_api.get_latest_assessment(sub)
def test_get_assessment_scores_by_criteria(self):
ai_api.on_init(self.submission_uuid, rubric=RUBRIC, algorithm_id=ALGORITHM_ID)
# Verify that we got the scores we provided to the stub AI algorithm
assessment = ai_api.get_latest_assessment(self.submission_uuid)
assessment_score_dict = ai_api.get_assessment_scores_by_criteria(self.submission_uuid)
for part in assessment['parts']:
criterion_name = part['option']['criterion']['name']
expected_score = self.CLASSIFIER_SCORE_OVERRIDES[criterion_name]['score_override']
self.assertEqual(assessment_score_dict[criterion_name], expected_score)
def get_student_info_path_and_context(self, data):
"""
Get the proper path and context for rendering the the student info
section of the staff debug panel.
"""
student_id = data.params.get('student_id', '')
submission_uuid = None
submission = None
assessment_steps = self.assessment_steps
if student_id:
student_item = self.get_student_item_dict()
student_item['student_id'] = student_id
# If there is a submission available for the requested student, present
# it. If not, there will be no other information to collect.
submissions = submission_api.get_submissions(student_item, 1)
if submissions:
submission = submissions[0]
submission_uuid = submissions[0]['uuid']
example_based_assessment = None
self_assessment = None
peer_assessments = []
submitted_assessments = []
if "peer-assessment" in assessment_steps:
peer_assessments = peer_api.get_assessments(submission_uuid)
submitted_assessments = peer_api.get_submitted_assessments(submission_uuid, scored_only=False)
if "self-assessment" in assessment_steps:
self_assessment = self_api.get_assessment(submission_uuid)
if "example-based-assessment" in assessment_steps:
example_based_assessment = ai_api.get_latest_assessment(submission_uuid)
context = {
'submission': submission,
'peer_assessments': peer_assessments,
'submitted_assessments': submitted_assessments,
'self_assessment': self_assessment,
'example_based_assessment': example_based_assessment,
'rubric_criteria': copy.deepcopy(self.rubric_criteria),
}
if peer_assessments or self_assessment or example_based_assessment:
max_scores = peer_api.get_rubric_max_scores(submission_uuid)
for criterion in context["rubric_criteria"]:
criterion["total_value"] = max_scores[criterion["name"]]
path = 'openassessmentblock/staff_debug/student_info.html'
return path, context
def test_get_assessment_scores_by_criteria(self):
ai_api.on_init(self.submission_uuid,
rubric=RUBRIC,
algorithm_id=ALGORITHM_ID)
# Verify that we got the scores we provided to the stub AI algorithm
assessment = ai_api.get_latest_assessment(self.submission_uuid)
assessment_score_dict = ai_api.get_assessment_scores_by_criteria(
self.submission_uuid)
for part in assessment['parts']:
criterion_name = part['option']['criterion']['name']
expected_score = self.CLASSIFIER_SCORE_OVERRIDES[criterion_name][
'score_override']
self.assertEqual(assessment_score_dict[criterion_name],
expected_score)
def test_grade_essay(self):
# Schedule a grading task
# Because Celery is configured in "always eager" mode, this will
# be executed synchronously.
ai_api.on_init(self.submission_uuid, rubric=RUBRIC, algorithm_id=ALGORITHM_ID)
# Verify that we got the scores we provided to the stub AI algorithm
assessment = ai_api.get_latest_assessment(self.submission_uuid)
for part in assessment['parts']:
criterion_name = part['option']['criterion']['name']
expected_score = self.CLASSIFIER_SCORE_OVERRIDES[criterion_name]['score_override']
self.assertEqual(part['option']['points'], expected_score)
score = ai_api.get_score(self.submission_uuid, {})
self.assertEquals(score["points_possible"], 4)
self.assertEquals(score["points_earned"], 3)
def test_grade_essay(self):
# Schedule a grading task
# Because Celery is configured in "always eager" mode, this will
# be executed synchronously.
ai_api.on_init(self.submission_uuid,
rubric=RUBRIC,
algorithm_id=ALGORITHM_ID)
# Verify that we got the scores we provided to the stub AI algorithm
assessment = ai_api.get_latest_assessment(self.submission_uuid)
for part in assessment['parts']:
criterion_name = part['option']['criterion']['name']
expected_score = self.CLASSIFIER_SCORE_OVERRIDES[criterion_name][
'score_override']
self.assertEqual(part['option']['points'], expected_score)
score = ai_api.get_score(self.submission_uuid, {})
self.assertEquals(score["points_possible"], 4)
self.assertEquals(score["points_earned"], 3)
def test_grade_essay_feedback_only_criterion(self):
# Modify the rubric to include a feedback-only criterion
# (a criterion with no options, just written feedback)
rubric = copy.deepcopy(RUBRIC)
rubric['criteria'].append({
'name': 'feedback only',
'prompt': 'feedback',
'options': []
})
# Train classifiers for the rubric
train_classifiers(rubric, self.CLASSIFIER_SCORE_OVERRIDES)
# Schedule a grading task and retrieve the assessment
ai_api.on_init(self.submission_uuid,
rubric=rubric,
algorithm_id=ALGORITHM_ID)
assessment = ai_api.get_latest_assessment(self.submission_uuid)
# Verify that the criteria with options were given scores
# (from the score override used by our fake classifiers)
self.assertEqual(assessment['parts'][0]['criterion']['name'],
u"vøȼȺƀᵾłȺɍɏ")
self.assertEqual(assessment['parts'][0]['option']['points'], 1)
self.assertEqual(assessment['parts'][1]['criterion']['name'],
u"ﻭɼค๓๓คɼ")
self.assertEqual(assessment['parts'][1]['option']['points'], 2)
# Verify that the criteria with no options (only feedback)
# has no score and empty feedback
self.assertEqual(assessment['parts'][2]['criterion']['name'],
u"feedback only")
self.assertIs(assessment['parts'][2]['option'], None)
self.assertEqual(assessment['parts'][2]['feedback'], u"")
# Check the scores by criterion dict
score_dict = ai_api.get_assessment_scores_by_criteria(
self.submission_uuid)
self.assertEqual(score_dict[u"vøȼȺƀᵾłȺɍɏ"], 1)
self.assertEqual(score_dict[u"ﻭɼค๓๓คɼ"], 2)
self.assertEqual(score_dict['feedback only'], 0)
def test_grade_essay_all_feedback_only_criteria(self):
# Modify the rubric to include only feedback-only criteria
rubric = copy.deepcopy(RUBRIC)
for criterion in rubric['criteria']:
criterion['options'] = []
# Train classifiers for the rubric
train_classifiers(rubric, {})
# Schedule a grading task and retrieve the assessment
ai_api.on_init(self.submission_uuid, rubric=rubric, algorithm_id=ALGORITHM_ID)
assessment = ai_api.get_latest_assessment(self.submission_uuid)
# Verify that all assessment parts have feedback set to an empty string
for part in assessment['parts']:
self.assertEqual(part['feedback'], u"")
# Check the scores by criterion dict
# Since none of the criteria had options, the scores should all default to 0
score_dict = ai_api.get_assessment_scores_by_criteria(self.submission_uuid)
self.assertItemsEqual(score_dict, {
u"vøȼȺƀᵾłȺɍɏ": 0,
u"ﻭɼค๓๓คɼ": 0,
})
def add_submission_context(self, submission_uuid, context):
"""
Add the submission information (self asssessment, peer assessments, final grade, etc.)
to the supplied context for display in the "learner info" portion of staff tools.
Args:
submission_uuid (unicode): The uuid of the submission, should NOT be None.
context: the context to update with additional information
"""
assessment_steps = self.assessment_steps
example_based_assessment = None
example_based_assessment_grade_context = None
self_assessment = None
self_assessment_grade_context = None
peer_assessments = None
peer_assessments_grade_context = []
staff_assessment = staff_api.get_latest_staff_assessment(submission_uuid)
staff_assessment_grade_context = None
submitted_assessments = None
grade_details = None
workflow = self.get_workflow_info(submission_uuid=submission_uuid)
grade_exists = workflow.get('status') == "done"
if "peer-assessment" in assessment_steps:
peer_assessments = peer_api.get_assessments(submission_uuid)
submitted_assessments = peer_api.get_submitted_assessments(submission_uuid)
if grade_exists:
peer_api.get_score(submission_uuid, self.workflow_requirements()["peer"])
peer_assessments_grade_context = [
self._assessment_grade_context(peer_assessment)
for peer_assessment in peer_assessments
]
if "self-assessment" in assessment_steps:
self_assessment = self_api.get_assessment(submission_uuid)
if grade_exists:
self_assessment_grade_context = self._assessment_grade_context(self_assessment)
if "example-based-assessment" in assessment_steps:
example_based_assessment = ai_api.get_latest_assessment(submission_uuid)
if grade_exists:
example_based_assessment_grade_context = self._assessment_grade_context(example_based_assessment)
if grade_exists:
if staff_assessment:
staff_assessment_grade_context = self._assessment_grade_context(staff_assessment)
grade_details = self.grade_details(
submission_uuid,
peer_assessments_grade_context,
self_assessment_grade_context,
example_based_assessment_grade_context,
staff_assessment_grade_context,
is_staff=True,
)
workflow_cancellation = self.get_workflow_cancellation_info(submission_uuid)
context.update({
'example_based_assessment': [example_based_assessment] if example_based_assessment else None,
'self_assessment': [self_assessment] if self_assessment else None,
'peer_assessments': peer_assessments,
'staff_assessment': [staff_assessment] if staff_assessment else None,
'submitted_assessments': submitted_assessments,
'grade_details': grade_details,
'score': workflow.get('score'),
'workflow_status': workflow.get('status'),
'workflow_cancellation': workflow_cancellation,
})
if peer_assessments or self_assessment or example_based_assessment or staff_assessment:
max_scores = peer_api.get_rubric_max_scores(submission_uuid)
for criterion in context["rubric_criteria"]:
criterion["total_value"] = max_scores[criterion["name"]]
def get_student_info_path_and_context(self, student_id):
"""
Get the proper path and context for rendering the the student info
section of the staff debug panel.
Args:
student_id (unicode): The ID of the student to report.
"""
submission_uuid = None
submission = None
assessment_steps = self.assessment_steps
if student_id:
student_item = self.get_student_item_dict()
student_item['student_id'] = student_id
# If there is a submission available for the requested student, present
# it. If not, there will be no other information to collect.
submissions = submission_api.get_submissions(student_item, 1)
if submissions:
submission_uuid = submissions[0]['uuid']
submission = submissions[0]
if 'file_key' in submission.get('answer', {}):
file_key = submission['answer']['file_key']
try:
submission['image_url'] = file_api.get_download_url(
file_key)
except file_api.FileUploadError:
# Log the error, but do not prevent the rest of the student info
# from being displayed.
msg = (
u"Could not retrieve image URL for staff debug page. "
u"The student ID is '{student_id}', and the file key is {file_key}"
).format(student_id=student_id, file_key=file_key)
logger.exception(msg)
example_based_assessment = None
self_assessment = None
peer_assessments = []
submitted_assessments = []
if "peer-assessment" in assessment_steps:
peer_assessments = peer_api.get_assessments(submission_uuid)
submitted_assessments = peer_api.get_submitted_assessments(
submission_uuid, scored_only=False)
if "self-assessment" in assessment_steps:
self_assessment = self_api.get_assessment(submission_uuid)
if "example-based-assessment" in assessment_steps:
example_based_assessment = ai_api.get_latest_assessment(
submission_uuid)
context = {
'submission': submission,
'peer_assessments': peer_assessments,
'submitted_assessments': submitted_assessments,
'self_assessment': self_assessment,
'example_based_assessment': example_based_assessment,
'rubric_criteria': copy.deepcopy(self.rubric_criteria_with_labels),
}
if peer_assessments or self_assessment or example_based_assessment:
max_scores = peer_api.get_rubric_max_scores(submission_uuid)
for criterion in context["rubric_criteria"]:
criterion["total_value"] = max_scores[criterion["name"]]
path = 'openassessmentblock/staff_debug/student_info.html'
return path, context
def render_grade_complete(self, workflow):
"""
Render the grade complete state.
Args:
workflow (dict): The serialized Workflow model.
Returns:
tuple of context (dict), template_path (string)
"""
# Peer specific stuff...
assessment_steps = self.assessment_steps
submission_uuid = workflow['submission_uuid']
example_based_assessment = None
self_assessment = None
feedback = None
peer_assessments = []
has_submitted_feedback = False
if "peer-assessment" in assessment_steps:
feedback = peer_api.get_assessment_feedback(submission_uuid)
peer_assessments = [
self._assessment_grade_context(asmnt)
for asmnt in peer_api.get_assessments(submission_uuid)
]
has_submitted_feedback = feedback is not None
if "self-assessment" in assessment_steps:
self_assessment = self._assessment_grade_context(
self_api.get_assessment(submission_uuid)
)
if "example-based-assessment" in assessment_steps:
example_based_assessment = self._assessment_grade_context(
ai_api.get_latest_assessment(submission_uuid)
)
feedback_text = feedback.get('feedback', '') if feedback else ''
student_submission = sub_api.get_submission(submission_uuid)
# We retrieve the score from the workflow, which in turn retrieves
# the score for our current submission UUID.
# We look up the score by submission UUID instead of student item
# to ensure that the score always matches the rubric.
# It's possible for the score to be `None` even if the workflow status is "done"
# when all the criteria in the rubric are feedback-only (no options).
score = workflow['score']
context = {
'score': score,
'feedback_text': feedback_text,
'student_submission': student_submission,
'peer_assessments': peer_assessments,
'self_assessment': self_assessment,
'example_based_assessment': example_based_assessment,
'rubric_criteria': self._rubric_criteria_grade_context(peer_assessments, self_assessment),
'has_submitted_feedback': has_submitted_feedback,
'allow_file_upload': self.allow_file_upload,
'allow_latex': self.allow_latex,
'file_url': self.get_download_url_from_submission(student_submission)
}
# Update the scores we will display to the user
# Note that we are updating a *copy* of the rubric criteria stored in
# the XBlock field
max_scores = peer_api.get_rubric_max_scores(submission_uuid)
median_scores = None
if "peer-assessment" in assessment_steps:
median_scores = peer_api.get_assessment_median_scores(submission_uuid)
elif "self-assessment" in assessment_steps:
median_scores = self_api.get_assessment_scores_by_criteria(submission_uuid)
elif "example-based-assessment" in assessment_steps:
median_scores = ai_api.get_assessment_scores_by_criteria(submission_uuid)
if median_scores is not None and max_scores is not None:
for criterion in context["rubric_criteria"]:
# Although we prevent course authors from modifying criteria post-release,
# it's still possible for assessments created by course staff to
# have criteria that differ from the current problem definition.
# It's also possible to circumvent the post-release restriction
# if course authors directly import a course into Studio.
# If this happens, we simply leave the score blank so that the grade
# section can render without error.
criterion["median_score"] = median_scores.get(criterion["name"], '')
criterion["total_value"] = max_scores.get(criterion["name"], '')
return ('openassessmentblock/grade/oa_grade_complete.html', context)
def get_student_info_path_and_context(self, student_username):
"""
Get the proper path and context for rendering the the student info
section of the staff debug panel.
Args:
student_username (unicode): The username of the student to report.
"""
submission_uuid = None
submission = None
assessment_steps = self.assessment_steps
anonymous_user_id = None
submissions = None
student_item = None
if student_username:
anonymous_user_id = self.get_anonymous_user_id(student_username, self.course_id)
student_item = self.get_student_item_dict(anonymous_user_id=anonymous_user_id)
if anonymous_user_id:
# If there is a submission available for the requested student, present
# it. If not, there will be no other information to collect.
submissions = submission_api.get_submissions(student_item, 1)
if submissions:
submission_uuid = submissions[0]['uuid']
submission = submissions[0]
if 'file_key' in submission.get('answer', {}):
file_key = submission['answer']['file_key']
try:
submission['image_url'] = file_api.get_download_url(file_key)
except file_api.FileUploadError:
# Log the error, but do not prevent the rest of the student info
# from being displayed.
msg = (
u"Could not retrieve image URL for staff debug page. "
u"The student username is '{student_username}', and the file key is {file_key}"
).format(student_username=student_username, file_key=file_key)
logger.exception(msg)
example_based_assessment = None
self_assessment = None
peer_assessments = []
submitted_assessments = []
if "peer-assessment" in assessment_steps:
peer_assessments = peer_api.get_assessments(submission_uuid)
submitted_assessments = peer_api.get_submitted_assessments(submission_uuid, scored_only=False)
if "self-assessment" in assessment_steps:
self_assessment = self_api.get_assessment(submission_uuid)
if "example-based-assessment" in assessment_steps:
example_based_assessment = ai_api.get_latest_assessment(submission_uuid)
workflow_cancellation = workflow_api.get_assessment_workflow_cancellation(submission_uuid)
if workflow_cancellation:
workflow_cancellation['cancelled_by'] = self.get_username(workflow_cancellation['cancelled_by_id'])
context = {
'submission': submission,
'workflow_cancellation': workflow_cancellation,
'peer_assessments': peer_assessments,
'submitted_assessments': submitted_assessments,
'self_assessment': self_assessment,
'example_based_assessment': example_based_assessment,
'rubric_criteria': copy.deepcopy(self.rubric_criteria_with_labels),
}
if peer_assessments or self_assessment or example_based_assessment:
max_scores = peer_api.get_rubric_max_scores(submission_uuid)
for criterion in context["rubric_criteria"]:
criterion["total_value"] = max_scores[criterion["name"]]
path = 'openassessmentblock/staff_debug/student_info.html'
return path, context
def get_student_info_path_and_context(self, student_id):
"""
Get the proper path and context for rendering the the student info
section of the staff debug panel.
Args:
student_id (unicode): The ID of the student to report.
"""
submission_uuid = None
submission = None
assessment_steps = self.assessment_steps
student_item = self.get_student_item_dict()
scores = {}
problem_closed = None
if student_id:
student_item['student_id'] = student_id
# If there is a submission available for the requested student, present
# it. If not, there will be no other information to collect.
submissions = submission_api.get_submissions(student_item, 1)
if submissions:
submission_uuid = submissions[0]['uuid']
submission = submissions[0]
if 'file_key' in submission.get('answer', {}):
file_key = submission['answer']['file_key']
try:
submission['image_url'] = file_api.get_download_url(file_key)
except file_api.FileUploadError:
# Log the error, but do not prevent the rest of the student info
# from being displayed.
msg = (
u"Could not retrieve image URL for staff debug page. "
u"The student ID is '{student_id}', and the file key is {file_key}"
).format(student_id=student_id, file_key=file_key)
logger.exception(msg)
example_based_assessment = None
self_assessment = None
peer_assessments = []
submitted_assessments = []
if "peer-assessment" in assessment_steps:
peer_assessments = peer_api.get_assessments(submission_uuid)
submitted_assessments = peer_api.get_submitted_assessments(submission_uuid, scored_only=False)
# Get the data we need for instructor override of the student's score
rubric_dict = create_rubric_dict(self.prompt, self.rubric_criteria_with_labels)
scores = peer_api.get_data_for_override_score(
submission_uuid,
student_item,
rubric_dict,
)
problem_closed, dummy0, dummy1, dummy2 = self.is_closed(step='peer-assessment', course_staff=False)
if "self-assessment" in assessment_steps:
self_assessment = self_api.get_assessment(submission_uuid)
if "example-based-assessment" in assessment_steps:
example_based_assessment = ai_api.get_latest_assessment(submission_uuid)
context = {
'submission': submission,
'peer_assessments': peer_assessments,
'submitted_assessments': submitted_assessments,
'self_assessment': self_assessment,
'example_based_assessment': example_based_assessment,
'rubric_criteria': copy.deepcopy(self.rubric_criteria_with_labels),
'scores': scores,
'problem_closed': problem_closed,
}
if peer_assessments or self_assessment or example_based_assessment:
max_scores = peer_api.get_rubric_max_scores(submission_uuid)
for criterion in context["rubric_criteria"]:
criterion["total_value"] = max_scores[criterion["name"]]
path = 'openassessmentblock/staff_debug/student_info.html'
return path, context
def test_get_latest_assessment_database_error(self, mock_call):
mock_call.side_effect = DatabaseError("KABOOM!")
with self.assertRaises(AIGradingInternalError):
ai_api.get_latest_assessment(self.submission_uuid)
def add_submission_context(self, submission_uuid, context):
"""
Add the submission information (self asssessment, peer assessments, final grade, etc.)
to the supplied context for display in the "learner info" portion of staff tools.
Args:
submission_uuid (unicode): The uuid of the submission, should NOT be None.
context: the context to update with additional information
"""
assessment_steps = self.assessment_steps
example_based_assessment = None
example_based_assessment_grade_context = None
self_assessment = None
self_assessment_grade_context = None
peer_assessments = None
peer_assessments_grade_context = []
staff_assessment = staff_api.get_latest_staff_assessment(submission_uuid)
staff_assessment_grade_context = None
submitted_assessments = None
grade_details = None
workflow = self.get_workflow_info(submission_uuid=submission_uuid)
grade_exists = workflow.get('status') == "done"
if "peer-assessment" in assessment_steps:
peer_assessments = peer_api.get_assessments(submission_uuid)
submitted_assessments = peer_api.get_submitted_assessments(submission_uuid)
if grade_exists:
peer_api.get_score(submission_uuid, self.workflow_requirements()["peer"])
peer_assessments_grade_context = [
self._assessment_grade_context(peer_assessment)
for peer_assessment in peer_assessments
]
if "self-assessment" in assessment_steps:
self_assessment = self_api.get_assessment(submission_uuid)
if grade_exists:
self_assessment_grade_context = self._assessment_grade_context(self_assessment)
if "example-based-assessment" in assessment_steps:
example_based_assessment = ai_api.get_latest_assessment(submission_uuid)
if grade_exists:
example_based_assessment_grade_context = self._assessment_grade_context(example_based_assessment)
if grade_exists:
if staff_assessment:
staff_assessment_grade_context = self._assessment_grade_context(staff_assessment)
grade_details = self.grade_details(
submission_uuid,
peer_assessments_grade_context,
self_assessment_grade_context,
example_based_assessment_grade_context,
staff_assessment_grade_context,
is_staff=True,
)
workflow_cancellation = self.get_workflow_cancellation_info(submission_uuid)
context.update({
'example_based_assessment': [example_based_assessment] if example_based_assessment else None,
'self_assessment': [self_assessment] if self_assessment else None,
'peer_assessments': peer_assessments,
'staff_assessment': [staff_assessment] if staff_assessment else None,
'submitted_assessments': submitted_assessments,
'grade_details': grade_details,
'score': workflow.get('score'),
'workflow_status': workflow.get('status'),
'workflow_cancellation': workflow_cancellation,
})
if peer_assessments or self_assessment or example_based_assessment or staff_assessment:
max_scores = peer_api.get_rubric_max_scores(submission_uuid)
for criterion in context["rubric_criteria"]:
criterion["total_value"] = max_scores[criterion["name"]]
def render_grade_complete(self, workflow):
"""
Render the grade complete state.
Args:
workflow (dict): The serialized Workflow model.
Returns:
tuple of context (dict), template_path (string)
"""
# Peer specific stuff...
assessment_steps = self.assessment_steps
submission_uuid = workflow['submission_uuid']
example_based_assessment = None
self_assessment = None
feedback = None
peer_assessments = []
has_submitted_feedback = False
if "peer-assessment" in assessment_steps:
feedback = peer_api.get_assessment_feedback(submission_uuid)
peer_assessments = peer_api.get_assessments(submission_uuid)
has_submitted_feedback = feedback is not None
if "self-assessment" in assessment_steps:
self_assessment = self_api.get_assessment(submission_uuid)
if "example-based-assessment" in assessment_steps:
example_based_assessment = ai_api.get_latest_assessment(submission_uuid)
feedback_text = feedback.get('feedback', '') if feedback else ''
student_submission = sub_api.get_submission(submission_uuid)
# We retrieve the score from the workflow, which in turn retrieves
# the score for our current submission UUID.
# We look up the score by submission UUID instead of student item
# to ensure that the score always matches the rubric.
# It's possible for the score to be `None` even if the workflow status is "done"
# when all the criteria in the rubric are feedback-only (no options).
score = workflow['score']
context = {
'score': score,
'feedback_text': feedback_text,
'student_submission': student_submission,
'peer_assessments': peer_assessments,
'self_assessment': self_assessment,
'example_based_assessment': example_based_assessment,
'rubric_criteria': self._rubric_criteria_with_feedback(peer_assessments),
'has_submitted_feedback': has_submitted_feedback,
'allow_file_upload': self.allow_file_upload,
'file_url': self.get_download_url_from_submission(student_submission)
}
# Update the scores we will display to the user
# Note that we are updating a *copy* of the rubric criteria stored in
# the XBlock field
max_scores = peer_api.get_rubric_max_scores(submission_uuid)
median_scores = None
if "peer-assessment" in assessment_steps:
median_scores = peer_api.get_assessment_median_scores(submission_uuid)
elif "self-assessment" in assessment_steps:
median_scores = self_api.get_assessment_scores_by_criteria(submission_uuid)
elif "example-based-assessment" in assessment_steps:
median_scores = ai_api.get_assessment_scores_by_criteria(submission_uuid)
if median_scores is not None and max_scores is not None:
for criterion in context["rubric_criteria"]:
criterion["median_score"] = median_scores[criterion["name"]]
criterion["total_value"] = max_scores[criterion["name"]]
return ('openassessmentblock/grade/oa_grade_complete.html', context)
def render_grade_complete(self, workflow):
"""
Render the grade complete state.
Args:
workflow (dict): The serialized Workflow model.
Returns:
tuple of context (dict), template_path (string)
"""
# Peer specific stuff...
assessment_steps = self.assessment_steps
submission_uuid = workflow['submission_uuid']
example_based_assessment = None
self_assessment = None
feedback = None
peer_assessments = []
has_submitted_feedback = False
if "peer-assessment" in assessment_steps:
feedback = peer_api.get_assessment_feedback(submission_uuid)
peer_assessments = [
self._assessment_grade_context(asmnt)
for asmnt in peer_api.get_assessments(submission_uuid)
]
has_submitted_feedback = feedback is not None
if "self-assessment" in assessment_steps:
self_assessment = self._assessment_grade_context(
self_api.get_assessment(submission_uuid))
if "example-based-assessment" in assessment_steps:
example_based_assessment = self._assessment_grade_context(
ai_api.get_latest_assessment(submission_uuid))
feedback_text = feedback.get('feedback', '') if feedback else ''
student_submission = sub_api.get_submission(submission_uuid)
# We retrieve the score from the workflow, which in turn retrieves
# the score for our current submission UUID.
# We look up the score by submission UUID instead of student item
# to ensure that the score always matches the rubric.
# It's possible for the score to be `None` even if the workflow status is "done"
# when all the criteria in the rubric are feedback-only (no options).
score = workflow['score']
context = {
'score':
score,
'feedback_text':
feedback_text,
'student_submission':
student_submission,
'peer_assessments':
peer_assessments,
'self_assessment':
self_assessment,
'example_based_assessment':
example_based_assessment,
'rubric_criteria':
self._rubric_criteria_grade_context(peer_assessments,
self_assessment),
'has_submitted_feedback':
has_submitted_feedback,
'allow_file_upload':
self.allow_file_upload,
'file_url':
self.get_download_url_from_submission(student_submission)
}
# Update the scores we will display to the user
# Note that we are updating a *copy* of the rubric criteria stored in
# the XBlock field
max_scores = peer_api.get_rubric_max_scores(submission_uuid)
median_scores = None
if "peer-assessment" in assessment_steps:
median_scores = peer_api.get_assessment_median_scores(
submission_uuid)
elif "self-assessment" in assessment_steps:
median_scores = self_api.get_assessment_scores_by_criteria(
submission_uuid)
elif "example-based-assessment" in assessment_steps:
median_scores = ai_api.get_assessment_scores_by_criteria(
submission_uuid)
if median_scores is not None and max_scores is not None:
for criterion in context["rubric_criteria"]:
# Although we prevent course authors from modifying criteria post-release,
# it's still possible for assessments created by course staff to
# have criteria that differ from the current problem definition.
# It's also possible to circumvent the post-release restriction
# if course authors directly import a course into Studio.
# If this happens, we simply leave the score blank so that the grade
# section can render without error.
criterion["median_score"] = median_scores.get(
criterion["name"], '')
criterion["total_value"] = max_scores.get(
criterion["name"], '')
return ('openassessmentblock/grade/oa_grade_complete.html', context)
def render_grade_complete(self, workflow):
"""
Render the grade complete state.
Args:
workflow (dict): The serialized Workflow model.
Returns:
tuple of context (dict), template_path (string)
"""
# Peer specific stuff...
assessment_steps = self.assessment_steps
submission_uuid = workflow['submission_uuid']
staff_assessment = None
example_based_assessment = None
self_assessment = None
feedback = None
peer_assessments = []
has_submitted_feedback = False
if "peer-assessment" in assessment_steps:
peer_api.get_score(submission_uuid, self.workflow_requirements()["peer"])
feedback = peer_api.get_assessment_feedback(submission_uuid)
peer_assessments = [
self._assessment_grade_context(peer_assessment)
for peer_assessment in peer_api.get_assessments(submission_uuid)
]
has_submitted_feedback = feedback is not None
if "self-assessment" in assessment_steps:
self_assessment = self._assessment_grade_context(
self_api.get_assessment(submission_uuid)
)
if "example-based-assessment" in assessment_steps:
example_based_assessment = self._assessment_grade_context(
ai_api.get_latest_assessment(submission_uuid)
)
raw_staff_assessment = staff_api.get_latest_staff_assessment(submission_uuid)
if raw_staff_assessment:
staff_assessment = self._assessment_grade_context(raw_staff_assessment)
feedback_text = feedback.get('feedback', '') if feedback else ''
student_submission = sub_api.get_submission(submission_uuid)
# We retrieve the score from the workflow, which in turn retrieves
# the score for our current submission UUID.
# We look up the score by submission UUID instead of student item
# to ensure that the score always matches the rubric.
# It's possible for the score to be `None` even if the workflow status is "done"
# when all the criteria in the rubric are feedback-only (no options).
score = workflow['score']
context = {
'score': score,
'feedback_text': feedback_text,
'has_submitted_feedback': has_submitted_feedback,
'student_submission': create_submission_dict(student_submission, self.prompts),
'peer_assessments': peer_assessments,
'grade_details': self.grade_details(
submission_uuid,
peer_assessments=peer_assessments,
self_assessment=self_assessment,
example_based_assessment=example_based_assessment,
staff_assessment=staff_assessment,
),
'file_upload_type': self.file_upload_type,
'allow_latex': self.allow_latex,
'file_url': self.get_download_url_from_submission(student_submission)
}
return ('openassessmentblock/grade/oa_grade_complete.html', context)
def test_get_latest_assessment_database_error(self, mock_call):
mock_call.side_effect = DatabaseError("KABOOM!")
with self.assertRaises(AIGradingInternalError):
ai_api.get_latest_assessment(self.submission_uuid)