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Status

Status
colourYellow
titlePROPOSAL / DRAFT

Contributing Team

Marco Morales - Schema Education

Earlier Discovery

(ORA v3 - Schema Discovery not yet published!)

Linked Initiatives

N/A

Overview

This proposed XBlock offers a lightweight solution to short answer text responses with static and LLM based student feedback options. This XBlock fills the gap between pattern-matching short text input problems and multi-step rubric-graded ORAs. It integrates AI-powered instant feedback and coaching and allows for the re-display of student responses across multiple pages in a course. It is an ideal solution for student predictions, reflections, and section summaries, and allows all of these to later be built up into a larger project or essay.

Overview

Excerpt
hiddentrue
nameoverview

This proposed XBlock offers a lightweight solution to short answer text responses with static and LLM based student feedback options. This XBlock fills the gap between pattern-matching short text input problems and multi-step rubric-graded ORAs. It integrates AI-powered instant feedback and coaching and allows for the re-display of student responses across multiple pages in a course. It is an ideal solution for student predictions, reflections, and section summaries, and allows all of these to later be built up into a larger project or essay.

This proposed XBlock offers a lightweight solution to short answer text responses with static and LLM based student feedback options. This XBlock fills the gap between pattern-matching short text input problems and multi-step rubric-graded ORAs. It integrates AI-powered instant feedback and coaching and allows for the re-display of student responses across multiple pages in a course. It is an ideal solution for student predictions, reflections, and section summaries, and allows all of these to later be built up into a larger project or essay.

Key Use Cases

  • Instant Feedback

    • As a course designer, I can quickly create short response questions and add a LLM pre-prompt for instant feedback while avoiding timely grading by instructors.

    • As a learner, I can receive instant feedback on short responses throughout the learning process rather than waiting for delayed feedback on my writing after I moved on.

  • Open-ended Predictions

    • As a course designer, I can ask learners to make open-ended predictions and later explain how their understanding has changed to help them expose and overcome misconceptions.

    • As a learner, I can record my open-ended predictions at a snapshot in time and later review and write how my understanding has changed to clearly demonstrate my growth.

  • Built-up Reflections

    • As a course designer, I can ask learners to reflect frequently throughout the course, and then have them review, synthesize, and build on these in broader reflections.

    • As a learner, I can see my short reflections, with feedback, when I’m reflecting on larger timescales of learning.

  • Iteration

    • As a course designer, I can set checkpoint questions in a course that provide sufficient time and feedback cycles so that most learners can reach a specific form of proficiency before moving on.

    • As a learner, I can use writing as a tool for formulating and building on thoughts with several cycles of feedback before moving past a question, allowing me to advance quickly through topics I understand and slow down through parts that I do not.

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