Scope: Staff and Administration

Principles: To provide governance and oversight in the management of AI technologies.

Policy Details

Infrastructure development for data management, decision support and resource allocation data security and privacy

Maintaining continuous maintenance of infrastructure

Providing teachers with in service training on AI usage in the classroom and AI literacy

Maintaining accountability with AI usage

Monitoring

Performance tracking using performance indicators (KPI)

Regular system audits

Ethics and bias monitoring

Compliance and legal oversight

Implementations

Done in conjunction with training

Developing the training programs

Using pilot sessions to test training materials

Scope: Stakeholders

Principles: Privacy in ethics, clear expectations of AI in the decision-making process,

Policy details: Providing handbooks and PDTs on AI policy, Creating committees,

Scope: For teachers who desire to use AI to tailor their instructional methods for students.

Principles: Diversify teaching methods, Individualized instruction, inclusivity, equity, collaborative peer support for teachers.

• Policy Details:

  • AI Usage: Define specific AI tools that will be used in instructional settings, such as adaptive learning platforms and AI-driven analytics to assess student needs.

  • Roles and Responsibilities: Assign roles for educators, administrators, and IT support staff, specifying who will manage AI tools, provide training, and ensure ethical use.

  • Data Protection and Ethics: Include guidelines for data privacy and ethical considerations, ensuring student information is securely handled and used only for educational purposes.

  • Training Requirements: Provide professional development opportunities for teachers to learn how to effectively use AI tools and integrate them into their teaching.

  • Collaboration: Establish channels for educators to share best practices and challenges encountered when using AI tools, fostering a supportive community of practice.

  Monitoring: Develop a process to regularly evaluate the effectiveness of AI integration, including teacher and student feedback, data analysis on student outcomes, and periodic policy reviews to ensure goals are being met.

  Implementation: Create a phased rollout plan that includes pilot testing, resource allocation, timeline for full deployment, and identification of key stakeholders. List necessary resources such as hardware, software, and training programs.

  Compliance: Outline clear enforcement mechanisms, including regular audits and assessments to ensure adherence to the policy. Define consequences for non-compliance, ranging from additional training requirements to restrictions on AI usage.

• Feedback: Establish a structured process for receiving feedback from educators, students, and other stakeholders, including surveys, focus groups, and open forums. Ensure that feedback is reviewed regularly and used to make timely policy updates.

• Approval: Specify dates for policy approval by relevant authorities, as well as the planned implementation date. Include a timeline for subsequent reviews and updates to keep the policy current.