Scoring Service REST API FAQ

The process of scoring student assessments and reporting results has evolved greatly over the years. From teachers sitting with paper-based answer sheets to bubble-sheets fed through a machine that produces a percent correct, technology has helped to enhance the process of scoring tests. While percent correct on an assessment can be valuable, many assessments benefit from reporting an estimate of the underlying student ability in an educational construct (i.e. reading, mathematics). These ability estimates provide indicators of status and can be used to monitor growth over time.

What is the MetaMetrics Scoring Service REST API and how is it used?

The MetaMetrics Scoring Service REST API has been designed to simplify assigning an ability estimate to a test-taker. As students take assessments, test results can be sent to the Scoring Service API, providing real-time estimates of student ability.

What is the difference between the Scoring Service REST API and the Scoring Service XML-RPC API?

In December of 2020, MetaMetrics released a new REST-based Scoring Service API. Both APIs serve the same purpose and functionality; to assign measures to test takers with or without prior performance information. Migrating to REST improves security, is more consistent with industry standards, provides more comprehensive documentation, helps with support, and is simpler and more efficient for your technical staff to use. The XML-RPC API will be sunsetted in the summer of 2022. Existing XML-RPC users will need to migrate to the REST version before then. New users will only use the REST version.

Do I need to install or manage any Scoring Service REST API software?

MetaMetrics provides highly available and scalable services using Amazon Web Services (AWS) in geographically-diverse data centers. The Scoring Service API is a MetaMetrics-managed web service. Clients using the service are not required to install or manage anything.

What kinds of calls are supported by the Scoring Service REST API?

There are two different types of API calls supported by the Scoring Service. The first type provides a student measure for an assessment when there is no prior information available about the student (i.e., measures, uncertainties). The second group of calls provides a student measure that accounts for a student’s previous performance using Bayesian scoring.

How do I know which call to use?

When a student is administered an assessment that can report Lexile reading or Quantile mathematics measures, estimates of the student's ability (Lexile reading/Quantile mathematics measure) must be calculated. An estimate of a student's ability comprises an ability measure (i.e., Lexile reading or Quantile mathematics measure) and associated uncertainty. If prior ability information about the student is not available, the student's performance on the singular assessment can be used to estimate a measure and associated uncertainty. When a student's prior ability measure and associated uncertainty are available and used with a Bayesian scoring function call, they represent an estimate of ability given all of the student's previous testing experiences and are referred to as priors. When this prior student data is available, the Scoring Service API can provide a more accurate estimate of a student's current ability by using Bayesian scoring. The Scoring Service API will need the student's latest ability information, or priors, as well as how long ago the priors were calculated. Bayesian scoring uses the time elapsed since the last test or age of the estimate to determine how much additional uncertainty should be associated with the current estimates. The Scoring Service API will return an updated estimate of the student's ability (Lexile reading/Quantile mathematics measure) and its associated uncertainty.

How do I report Scoring Service REST API measures?

The calls in the Scoring Service API return a measure and uncertainty. If the measures are being used for research or institutional purposes, they can be used as reported. Measures provided by the standard calls can also be used when making Bayesian calls. If the measures are used for reporting to teachers, parents, and students, then proper branding needs to be applied. See Reporting Scoring Service Measures for specific information on reporting measures.

What kind of performance can I expect from the Scoring Service REST API?

See Service Level Agreement for Scoring Service API for performance commitments, problem reporting and escalation, maintenance information, and more.

What is the Forecasting REST API and how is it used?

The Forecasting API forecasts an individual student or group performance on an upcoming assessment. To accomplish this, the API uses a proprietary growth model, prior information about a student or group of students, and information about an examination to be taken in the future.