Without concrete data, there’s no way to know whether learners are actually grasping the decision-making concepts being taught. Where did learners accomplish their goals? Where were they challenged? Why did half of them choose a poor pathway option?
DecisionSim offers reports that answer these vital questions—and thereby enhance the learning process.
Our platform includes management features that let educators and administrators track all case interaction and performance by learners. Detailed reports can be generated at multiple levels (institution, school, department, group and individual user) and can include granular data regarding a learner’s selections, timing and associated scoring metrics.
Authors can assign various scoring metrics to learner choices, and apply rules to give feedback. By combining metrics and rules, authors can send the learner to conditional, specific feedback. For instance, metrics can include such items as score, time, patient status and money spent. These metrics can be combined with the rule, “If the learner’s score < 100 then jump to remediation.” Learners who fall into that profile might receive the feedback, “You have not followed the standard guidelines, please review the following…”
At the end of a case, authors can provide learners with a summary of the case, learning objectives, decision points, scores and final case outcome. These end-of-case reports provide immediate feedback for learners, while also enabling authors to review aggregate learner data. This data can be used to improve case design, understand current practice habits and identify additional educational needs.
To better gauge learners’ knowledge and decision-making skills, DecisionSim provides reports that contain:
- Performance data: Collected and analyzed as learners progress through each case, this data can be used to trigger changes in the path through the case as well as the feedback learners receive.
- Assessment data: This provides a pre-case measurement of a learner’s baseline knowledge and post-case measurement of a learner’s improvement.
- Aggregate data: Educators compile and analyze individual or aggregate data, gaining insight to: better understand the decision points that cause deviation from expected pathways; strengthen their educational offerings; and improve healthcare professionals’ decision-making skills.