Sunbird QUML Player

GovTech Context

Assessing learners’ understanding of a concept is vital to determine whether or not the learner has mastered the concept. Due to the ongoing pandemic, every state government is trying to assess the learning loss. One way of doing this is to conduct assessments to evaluate where the learners’ understanding of concepts and plan for interventions.

States are currently conducting various forms of assessments (Formative, Summative, Baseline, spot assessments) where students undertake the assessment online on a Mobile App or offline in schools.

Prashnavali is an open source solution built on Sunbird building blocks which is adopted by DIKSHA - the national learning platform that is used by all state education departments. The platform enables crowd-sourcing of questions by teachers that can be tagged to specific learning outcomes, and be distributed to users as worksheets and assessments across offline / online channels.

Product Explanation

Sunbird inQuiry Sunbird inQuiry is a building block, open sourced under MIT license, that enables setting up of question banks that can contain questions and question sets for various use cases such as practice, assessment, quiz, worksheet and many more.

Key capabilities of inQuiry:

1. Creation: of question(s) and question set(s) as per an interoperable QuML spec either using the question set editor, by bulk upload of questions or API .

2. Configuration: of the question set behaviour. For ex., randomize the questions from the question bank, limit the number of attempts, set timer etc.

3. Tagging: of question(s) and question set(s) with meaningful metadata useful for discovery and analysis.

4. Publish: Curation and publishing of question(s) and question set(s). Publish workflow also ensures that the published assets can be played in both offline & online modes.

5. Play: The player for question set(s) is embeddable, configurable and extendable.

6. Data Emission:

Emission of question response and result data using an interoperable specification (QuML)
Emission of question set result and summary data using an interoperable specification (QuML)
The editor and player emit useful telemetry to make meaning of the user's action, which can be used to generate reports and derive insights.

Features to be implemented

Below are the two project ideas as part of this project:

1. Shuffle answers to increase the efficacy of learning: Randomization of questions in a question set and shuffling of answers are some of the ways to ensure that learners are prevented from gaming the assessment or quiz. inQuiry has the capability to randomize questions within a question set but does not yet enable creators to shuffle answers within each question.

Question schema needs to be updated with a new property which enables ‘Shuffling of answers’ for Questions.
Question set editor, tool used to create question sets, should allow creators to enable/disable ‘Shuffling of answers’.
End users when consuming these question sets using the QuML player should experience this behavior.

2. Enable MMCQ (More than one correct answer for Multiple Choice Question): Current MCQ implementation allows for creators to create MCQs with only one right answer. Having more than one right answer to a MCQ question brings down the chance of learners’ guessing answers and getting questions right - which can help in painting a true picture of learners’ understanding of a concept.

Question creation UI we should enable creators to mark more than one option as correct answer using checkbox
End user while consuming, He/she can select multiple options in all layout.
Score should be calculated based on below logic
- If user choose only all correct options then only score should be 1 and and same will be send in telemetry events.
- If user choose only one correct option score should be 0 only and same will be send in telemetry events.
Send multiple options in telemetry Data.