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 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 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)