Follow the steps below to create scorecards:
Log in to your admin account, click the ‘Library’ tab, and then select the ‘Scorecards’ tab.
2. Click the ‘New Scorecard’ button on the Scorecards page to create a new scorecard.
3. To create your scorecard, you must first enter a name for it.
4. Once you've entered the name, you can create the criteria by clicking the ‘Create Section’ tab. You can add as many criteria sections as needed.
i. In the criteria section, you must enter the name of the criterion.
ii. Next, you can manually enter the ‘Top Score’ for the criterion. The score you enter will be the basis for grading, with metrics for ‘Poor,’ ‘Average,’ and ‘Strong’.
iii. There are two radio buttons:
a. The first option is ‘Graded Marking,’ which allows learners to receive any score between 0 and the top score. If you select ‘Graded Marking,’ you must create a scoring guide. To generate a scoring guide, you can use the AI by clicking the ‘Generate’ tab.
Or you can manually add an outline of the criteria and expectations.
b. The second option is ‘Pass/Fail,’ where learners can either receive a full score or a 0. The ‘Pass/Fail’ selection does not include the ‘Poor,’ ‘Average,’ and ‘Strong’ metrics. Instead, it allows you to enter a description outlining the requirements to pass the criterion or use the AI again to generate a scoring guide.
5. Once you have completed all the necessary sections, click the ‘Create Scorecard’ button. The system will save your scorecard and redirect you to the ‘Scorecards’ page, where your newly created scorecard will appear at the top. You can duplicate, delete, or edit the scorecards at any time.
Now that you've learned how to create and customise scorecards, you can efficiently track learner performance, provide valuable feedback, and enhance training outcomes.
If you have any further questions or need assistance, please refer to our support resources or contact the Solidroad team via the 'Get Help' tab within the platform.
User manual definition of terms:
Scorecard: A tool for users to track performance, monitor progress, and get feedback during AI simulations.
Top Score: A learner's highest score in a simulation or assessment.
Metrics: Data used to measure learner performance and progress, often categorised as poor, average, or strong.
Simulation: A virtual replica of real-world scenarios used for training, practice, or testing without the risks or costs of real-life situations.
Criteria: The standards or guidelines used to evaluate and assess learner performance or the quality of training outcomes.