Response
The response will be an HTTP 200 along with a JSON body that describes the report model.
A unique survey identifier (survey_id) is included so meta-data about the survey can be queried (using GET /survey/:surveyID).
The type of report (admin, chair, ...) and the data model are also included.
The data model contains aggregated data (number of respondents asked, number answered, and response rate) and a list of unique identifiers for each survey question on this report.
Each question ID (question_id) can be used in the GET /report/:reportID/model/:questionID end-point to get data for a specific question on this report.
If a report with the given report_id cannot be found, an HTTP 404 (Not Found) will be returned. All other errors will return an HTTP 500 (Internal
Server Error).
Response Parameters (JSON Body)
survey_id
Example: "survey_id": 12345
The ID of the survey this report is associated with. This provides a way to track down the survey meta-data (survey subject, institution, etc.).
It can be used with the GET /survey/:surveyID end-point.
type
Example: "type": "Diagnostic"
The type of report this is.
It will be one of the following: [Admin, Chair, Comment, Extra Likert, Diagnostic, Short, Teaching Essentials, Advisor, Advising Staff, Advising Student].
includes_sub_groups
Example: "includes_sub_groups": "true"
[Optional] Boolean flag (will be "true" or "false") indicating if the report contains information on demographic sub-groups.
This is only available for surveys that use the Feedback System for Administrators.
sub_group_responded_count_map
Example: "sub_group_responded_count_map": {"5": 34, "8": 27, "10": 18, "11": 21}
[Optional] A map containing a count of the number of respondents in each demographic sub-group.
The key in this map is the demographic sub-group ID and the value is the number of respondents. Mapping the demographic sub-group
back can use the GET /demographic_group/:demographicGroupID REST end-point or by getting all the possible demographic
sub-groups using the GET /demographic_groups REST end-point.
This is only available for surveys that use the Feedback System for Administrators.
aggregate_data
Example: "aggregate_data": { ... }
The report model information. This contains the aggregated and calculated data.
aggregate_data.asked
Example: "asked": 26
The number of respondents asked to complete the survey (rater form).
aggregate_data.answered
Example: "answered": 23
The number of respondents that submitted responses to the survey (rater form). It will never be greater than the number asked.
aggregate_data.response_rate
Example: "response_rate": "88.46"
The response rate (as a percentage) for the survey, rounded to 2 decimal places.
aggregate_data.overall_ratings
Example: "overall_ratings": { ... }
The overall ratings are used for student ratings survey reports and provide an average of the 'excellent teacher'
and 'excellent course' ratings.
aggregate_data.overall_ratings.result
Example: "result": { ... }
The values in this collection are based on data from a single survey (unlike the discipline_result and institution_result).
aggregate_data.overall_ratings.result.raw
Example: "raw": { ... }
Raw calculated data. If mean or t-score are missing, the values are undefined.
aggregate_data.overall_ratings.result.raw.mean
Example: "mean": 3.5
Average of raw means for 'excellent teacher' and 'excellent course' questions.
aggregate_data.overall_ratings.result.raw.tscore
Example: "tscore": 78.0
Average of raw t-scores for 'excellent teacher' and 'excellent course' questions.
aggregate_data.overall_ratings.result.adjusted
Example: "adjusted": { ... }
Adjusted calculated data; this attempts to separate the contributions of the teacher from the
contributions of the extraneous factors to student learning.
For more information about adjusted scores, see
IDEAedu.org/AdjustedScores.
If mean or t-score are missing, the values are undefined.
aggregate_data.overall_ratings.result.adjusted.mean
Example: "mean": 3.5
Average of adjusted means for 'excellent teacher' and 'excellent course' questions.
aggregate_data.overall_ratings.result.adjusted.tscore
Example: "tscore": 78.0
Average of adjusted t-scores for 'excellent teacher' and 'excellent course' questions.
aggregate_data.overall_ratings.discipline_result
Example: "discipline_result": { ... }
Calculated values comparing this survey to other surveys in the same discipline.
This is included for Student Ratings surveys only.
aggregate_data.overall_ratings.discipline_result.raw
Example: "raw": { ... }
Raw calculated data. If mean or t-score are missing, the values are undefined.
aggregate_data.overall_ratings.discipline_result.raw.mean
Example: "mean": 3.5
Average of raw discipline means for 'excellent teacher' and 'excellent course' questions.
aggregate_data.overall_ratings.discipline_result.raw.tscore
Example: "tscore": 78.0
Average of raw discipline t-scores for 'excellent teacher' and 'excellent course' questions.
aggregate_data.overall_ratings.discipline_result.adjusted
Example: "adjusted": { ... }
Adjusted calculated data; this attempts to separate the contributions of the teacher from the
contributions of the extraneous factors to student learning.
For more information about adjusted scores, see
IDEAedu.org/AdjustedScores.
If mean or t-score are missing, the values are undefined.
aggregate_data.overall_ratings.discipline_result.adjusted.mean
Example: "mean": 3.5
Average of adjusted discipline means for 'excellent teacher' and 'excellent course' questions.
aggregate_data.overall_ratings.discipline_result.adjusted.tscore
Example: "tscore": 78.0
Average of adjusted discipline t-scores for 'excellent teacher' and 'excellent course' questions.
aggregate_data.overall_ratings.institution_result
Example: "institution_result": { ... }
Calculated values comparing this survey to other surveys in the same institution.
This is included for Student Ratings surveys only.
aggregate_data.overall_ratings.institution_result.raw
Example: "raw": { ... }
Raw calculated data. If mean or t-score are missing, the values are undefined.
aggregate_data.overall_ratings.institution_result.raw.mean
Example: "mean": 3.5
Average of raw institution means for 'excellent teacher' and 'excellent course' questions.
aggregate_data.overall_ratings.institution_result.raw.tscore
Example: "tscore": 78.0
Average of raw institution t-scores for 'excellent teacher' and 'excellent course' questions.
aggregate_data.overall_ratings.institution_result.adjusted
Example: "adjusted": { ... }
Adjusted calculated data; this attempts to separate the contributions of the teacher from the
contributions of the extraneous factors to student learning.
For more information about adjusted scores, see
IDEAedu.org/AdjustedScores.
If mean or t-score are missing, the values are undefined.
aggregate_data.overall_ratings.institution_result.adjusted.mean
Example: "mean": 3.5
Average of adjusted institution means for 'excellent teacher' and 'excellent course' questions.
aggregate_data.overall_ratings.institution_result.adjusted.tscore
Example: "tscore": 78.0
Average of adjusted institution t-scores for 'excellent teacher' and 'excellent course' questions.
aggregate_data.summary_evaluation
Example: "summary_evaluation": { ... }
The summary evaluation is used for student ratings survey reports and provides an average of the overall ratings
and the relevant results (progress on relevant objectives).
aggregate_data.summary_evaluation.result
Example: "result": { ... }
The values in this collection are based on data from a single survey (unlike the discipline_result and institution_result).
aggregate_data.summary_evaluation.result.raw
Example: "raw": { ... }
Raw calculated data. If mean or t-score are missing, the values are undefined.
aggregate_data.summary_evaluation.result.raw.mean
Example: "mean": 3.5
Average of overall_ratings.result.raw.mean and relevant_results.result.raw.mean.
aggregate_data.summary_evaluation.result.raw.tscore
Example: "tscore": 78.0
Average of overall_ratings.result.raw.tscore and relevant_results.result.raw.tscore.
aggregate_data.summary_evaluation.result.adjusted
Example: "adjusted": { ... }
Adjusted calculated data; this attempts to separate the contributions of the teacher from the
contributions of the extraneous factors to student learning.
For more information about adjusted scores, see
IDEAedu.org/AdjustedScores.
If mean or t-score are missing, the values are undefined.
aggregate_data.summary_evaluation.result.adjusted.mean
Example: "mean": 3.5
Average of overall_ratings.result.adjusted.mean and relevant_results.result.adjusted.mean.
aggregate_data.summary_evaluation.result.adjusted.tscore
Example: "tscore": 78.0
Average of overall_ratings.result.adjusted.tscore and relevant_results.result.adjusted.tscore.
aggregate_data.summary_evaluation.discipline_result
Example: "discipline_result": { ... }
Calculated values comparing this survey to other surveys in the same discipline.
This is included for Student Ratings surveys only.
aggregate_data.summary_evaluation.discipline_result.raw
Example: "raw": { ... }
Raw calculated data. If mean or t-score are missing, the values are undefined.
aggregate_data.summary_evaluation.discipline_result.raw.mean
Example: "mean": 3.5
Average of overall_ratings.discipline_result.raw.mean and relevant_results.discipline_result.raw.mean.
aggregate_data.summary_evaluation.discipline_result.raw.tscore
Example: "tscore": 78.0
Average of overall_ratings.discipline_result.raw.tscore and relevant_results.discipline_result.raw.tscore.
aggregate_data.summary_evaluation.discipline_result.adjusted
Example: "adjusted": { ... }
Adjusted calculated data; this attempts to separate the contributions of the teacher from the
contributions of the extraneous factors to student learning.
For more information about adjusted scores, see
IDEAedu.org/AdjustedScores.
If mean or t-score are missing, the values are undefined.
aggregate_data.summary_evaluation.discipline_result.adjusted.mean
Example: "mean": 3.5
Average of overall_ratings.discipline_result.adjusted.mean and relevant_results.discipline_result.adjusted.mean.
aggregate_data.summary_evaluation.discipline_result.adjusted.tscore
Example: "tscore": 78.0
Average of overall_ratings.discipline_result.adjusted.tscore and relevant_results.discipline_result.adjusted.tscore.
aggregate_data.summary_evaluation.institution_result
Example: "institution_result": { ... }
Calculated values comparing this survey to other surveys in the same institution.
This is included for Student Ratings surveys only.
aggregate_data.summary_evaluation.institution_result.raw
Example: "raw": { ... }
Raw calculated data. If mean or t-score are missing, the values are undefined.
aggregate_data.summary_evaluation.institution_result.raw.mean
Example: "mean": 3.5
Average of overall_ratings.institution_result.raw.mean and relevant_results.institution_result.raw.mean.
aggregate_data.summary_evaluation.institution_result.raw.tscore
Example: "tscore": 78.0
Average of overall_ratings.institution_result.raw.tscore and relevant_results.institution_result.raw.tscore.
aggregate_data.summary_evaluation.institution_result.adjusted
Example: "adjusted": { ... }
Adjusted calculated data; this attempts to separate the contributions of the teacher from the
contributions of the extraneous factors to student learning.
For more information about adjusted scores, see
IDEAedu.org/AdjustedScores.
If mean or t-score are missing, the values are undefined.
aggregate_data.summary_evaluation.institution_result.adjusted.mean
Example: "mean": 3.5
Average of overall_ratings.institution_result.adjusted.mean and relevant_results.institution_result.adjusted.mean.
aggregate_data.summary_evaluation.institution_result.adjusted.tscore
Example: "tscore": 78.0
Average of overall_ratings.institution_result.adjusted.tscore and relevant_results.institution_result.adjusted.tscore.
aggregate_data.relevant_results
Example: "relevant_results": { ... }
For single survey Student Ratings reports, this collection contains calculations combining responses from all
objectives questions selected as "Important" or "Essential" by the survey subject (information form respondent).
Also known as "Progress on Relevant Objectives".
This includes:
- results for this survey (
result)
- comparative results for discipline (
discipline_result)
- comparative results for institution (
institution_result)
For single survey Chair reports, this collection contains calculations combining responses from all
responsibilities questions selected as "Relevant" or "High Priority" by the survey subject (information form respondent).
This includes:
- results for this survey (
result)
- No comparative results are provided on the Chair report.
aggregate_data.relevant_results.questions
Example: "questions": [ ... ]
For Student Ratings reports, this is a collection of the objectives questions selected as "Important" or "Essential" by the survey subject (information form respondent).
For Chair reports, this is a collection of the responsibilities questions selected as "Relevant" or "High Priority" by the survey subject (information form respondent).
aggregate_data.relevant_results.questions.question_id
Example: "question_id": 123
A unique question identifier in the IDEA system.
aggregate_data.relevant_results.questions.response
Example: "response": "Essential"
The response description.
aggregate_data.relevant_results.result
Example: "result": { ... }
The values in this collection are based on data from a single survey (unlike the discipline_result and institution_result).
For Student Ratings reports, this collection contains values calculated by combining responses from all objectives questions selected as
"Important" or "Essential" by the survey subject (information form respondent).
These values are also known as "Progress on Relevant Objectives".
For Chair reports, this collection contains values calculated by combining responses from all responsibilities questions selected as
"Relevant" or "High Priority" by the survey subject (information form respondent).
aggregate_data.relevant_results.result.raw
Example: "raw": { ... }
Raw calculated data. If mean/tscore are missing, the values are undefined.
aggregate_data.relevant_results.result.raw.mean
Example: "mean": 3.5
Weighted raw mean for relevant (essential and important) objectives.
aggregate_data.relevant_results.result.raw.tscore
Example: "tscore": 78.0
Weighted raw t-score for relevant (essential and important) objectives.
aggregate_data.relevant_results.result.adjusted
Example: "adjusted": { ... }
Adjusted calculated data; this attempts to separate the contributions of the teacher from the
contributions of the extraneous factors to student learning.
For more information about adjusted scores, see
IDEAedu.org/AdjustedScores.
If mean/tscore are missing, the values are undefined.
aggregate_data.relevant_results.result.adjusted.mean
Example: "mean": 3.5
Weighted adjusted mean for relevant (essential and important) objectives.
aggregate_data.relevant_results.result.adjusted.tscore
Example: "tscore": 78.0
Weighted adjusted t-score for relevant (essential and important) objectives.
aggregate_data.relevant_results.discipline_result
Example: "discipline_result": { ... }
Calculated values comparing this survey to other surveys in the same discipline.
This is included for Student Ratings surveys only.
aggregate_data.relevant_results.discipline_result.raw
Example: "raw": { ... }
Raw calculated data. If mean/tscore are missing, the values are undefined.
aggregate_data.relevant_results.discipline_result.raw.mean
Example: "mean": 3.5
Weighted raw discipline mean for relevant (essential and important) objectives.
aggregate_data.relevant_results.discipline_result.raw.tscore
Example: "tscore": 78.0
Weighted raw discipline t-score for relevant (essential and important) objectives.
aggregate_data.relevant_results.discipline_result.adjusted
Example: "adjusted": { ... }
Adjusted calculated data; this attempts to separate the contributions of the teacher from the
contributions of the extraneous factors to student learning.
For more information about adjusted scores, see
IDEAedu.org/AdjustedScores.
If mean/tscore are missing, the values are undefined.
aggregate_data.relevant_results.discipline_result.adjusted.mean
Example: "mean": 3.5
Weighted adjusted discipline mean for relevant (essential and important) objectives.
aggregate_data.relevant_results.discipline_result.adjusted.tscore
Example: "tscore": 78.0
Weighted adjusted discipline t-score for relevant (essential and important) objectives.
aggregate_data.relevant_results.institution_result
Example: "institution_result": { ... }
Calculated values comparing this survey to other surveys in the same institution.
This is included for Student Ratings surveys only.
aggregate_data.relevant_results.institution_result.raw
Example: "raw": { ... }
Raw calculated data. If mean/tscore are missing, the values are undefined.
aggregate_data.relevant_results.institution_result.raw.mean
Example: "mean": 3.5
Weighted raw institution mean for relevant (essential and important) objectives.
aggregate_data.relevant_results.institution_result.raw.tscore
Example: "tscore": 78.0
Weighted raw institution t-score for relevant (essential and important) objectives.
aggregate_data.relevant_results.institution_result.adjusted
Example: "adjusted": { ... }
Adjusted calculated data; this attempts to separate the contributions of the teacher from the
contributions of the extraneous factors to student learning.
For more information about adjusted scores, see
IDEAedu.org/AdjustedScores.
If mean/tscore are missing, the values are undefined.
aggregate_data.relevant_results.institution_result.adjusted.mean
Example: "mean": 3.5
Weighted adjusted institution mean for relevant (essential and important) objectives.
aggregate_data.relevant_results.institution_result.adjusted.tscore
Example: "tscore": 78.0
Weighted adjusted institution t-score for relevant (essential and important) objectives.
aggregate_data.response_data_points
Example: "response_data_points": [ ... ]
Contains unique question identifiers for each survey question on this report.
aggregate_data.response_data_points.question_id
Example: "question_id": 123
This is a unique question identifier in the IDEA system.
This can be used in a follow-up query to the GET /report/:reportID/model/:questionID end-point.
aggregate_data.response_data_points.url
Example: "url":
Specific question URL for the GET /report/:reportID/model/:questionID end-point
