Learner code.

KLD expects adult learners to participate with focus, respect, and honest effort. A serious learning environment is not rigid, but it does require preparation, attention, and care for the work of others.

Learners are expected to attempt activities before asking for answers, bring useful questions to review, listen during critique, and contribute in ways that help the group or teaching relationship move forward.

Learners keep ownership of their original work, but submitted work must honestly represent their own learning, decisions, and contribution. Copying, buying, outsourcing, impersonating, or submitting work that someone else completed is not acceptable.

Collaboration is welcome when it is part of the task. Collaboration becomes a problem when individual work is presented as independent but was completed through undisclosed help, shared answers, copied artifacts, or hidden outside contribution.

KLD teaches AI as a practice partner. Learners may use AI for exploration, explanation, critique, drafting, comparison, and revision unless a specific activity says otherwise.

Learners must keep human judgment visible. When AI materially helps with a submitted artifact, learners disclose the use, check the output, correct errors, identify assumptions, and explain the decision they made after using the tool.

Product work depends on evidence. Learners must distinguish observation from opinion, cite or link meaningful sources where relevant, and avoid inventing users, research findings, interview results, screenshots, metrics, quotes, or references.

If a source, statistic, quote, or example cannot be verified, learners must label it as uncertain, remove it, or ask for support before relying on it in an artifact.

Feedback is part of the learning method. Learners are expected to receive critique without defensiveness, ask clarifying questions, and use revision notes to improve the next version of the work.

Review comments must be specific and useful. KLD does not accept harassment, humiliation, discriminatory remarks, personal attacks, or repeated disruption in live sessions, written comments, or shared workspaces.

Course participation depends on a steady rhythm of practice. Learners should submit work by the requested time, communicate early when something is late, and ask for support when access, workload, health, language, or tool issues interfere with learning.

Missed work is handled through a practical support route where possible. Repeated non-submission, unresponsive participation, or disregard for review expectations may limit access to feedback, cohort activities, or completion recognition.

Learners must respect privacy, confidentiality, and intellectual property. Private learner work, partner material, unpublished course content, feedback notes, and screenshots from restricted spaces must not be shared publicly without permission.

Learners should also protect their own information when using third-party AI, design, whiteboard, or collaboration tools. Sensitive personal, client, employer, or partner material must not be uploaded into external tools without permission.

Questions, concerns, access needs, and conduct issues can be raised with KLD. Learners are encouraged to ask early, especially when confusion, pressure, tool friction, or workload could lead to poor decisions.

KLD may review a concern, ask for context, request a revision, limit access, or take another reasonable step where conduct undermines learning integrity, learner safety, or the quality of the institute environment.

Last updated: 14 May 2026.