Use Case | Review of Academic Policies with Automated Summary Generation

Use Case: Review of Academic Policies with Automated Summary Generation

Overview:

Reviewing academic policies is essential to ensure that educational institutions comply with internal and external regulations while implementing clear guidelines for students, faculty, and administrators. A generative semantic model capable of processing PDFs can automatically analyze extensive documents related to educational regulations or internal policies, extracting key points and generating clear, structured summaries.

How It Works:

1. Document Upload in PDF Format:

1. • Users upload educational regulations, academic manuals, internal policies, or external guidelines to the system.

2. Document Processing:

1. • The model analyzes the document content using natural language processing (NLP).
   • Identifies and organizes key sections related to:
     • Admission and graduation requirements.
     • Evaluation and grading policies.
     • Guidelines on behavior, ethics, and discipline.
     • Procedures for appeals and academic exceptions.

3. Summary Generation:

1. • Extracts key points from each section.
   • Produces a structured report highlighting the most relevant aspects of each area of the academic policy.

4. Storage and Semantic Search:

1. • Generated summaries are stored in vector databases for quick keyword or context-based searches.

Practical Example

Scenario:
A university needs to review and update its academic evaluation policies to align with new government regulations.

Process with the Model:

1. Document Upload:

1. • The administrator uploads a 100-page academic manual that includes evaluation policies to the system.

2. Model Analysis:

1. • Evaluation requirements: Identifies that exams must account for at least 50% of the final grade.
   • Grading criteria: Extracts that grades are assigned on a 0-to-10 scale but lacks details about reevaluation rounds.
   • Appeals: Detects that students can appeal their grades within seven business days, but no procedures for resolving conflicts are specified.

3. Summary Generation:

1. • The model generates a structured report that includes:
     • Current policies:
       • Evaluations: Exams with a minimum weight of 50%.
       • Grading scale: 0–10.
     • Identified omissions:
       • Lack of clarity on reevaluation procedures.
       • Incomplete procedures for resolving appeals.
     • Recommendations:
       • Include details on the reevaluation process.
       • Specify steps and timelines for resolving academic conflicts.

4. Report Output:

1. • The administrative team receives a clear summary highlighting areas needing updates, simplifying the review and implementation of changes.

Benefits of the Model in Academic Policy Review

1. Time Savings:

1. • Automates the review of lengthy manuals, significantly reducing the time needed to identify key points.

2. Clear and Organized Summaries:

1. • Provides an overview of policies, highlighting the most important aspects and potential omissions.

3. Identification of Critical Areas:

1. • Detects inconsistencies, ambiguities, or gaps that could lead to conflicts or difficulties in implementation.

4. Improved Regulatory Compliance:

1. • Ensures internal policies align with local and international educational regulations.

5. Efficient Organization for Easy Reference:

1. • Enables efficient storage and quick context-based searches for processed documents.

Additional Applications

1. Academic Audits:

1. • Verifies that internal policies comply with government or accreditation standards.

2. Student Handbook Preparation:

1. • Generates clear and accessible summaries of regulations for students and academic staff.

3. Review of Ethics and Conduct Guidelines:

1. • Extracts and organizes rules on behavior, discipline, and appeal procedures.

4. Policy Comparison:

1. • Analyzes and compares different versions of internal policies to identify changes and improvements.

Practical Example: Additional Scenario

Scenario:
An educational institution receives a new set of government regulations on inclusion policies and needs to adjust its internal policies.

Without the Model:

• Administrators spend weeks manually reviewing regulations and comparing them to existing policies.

With the Model:

• The system analyzes both the regulations and internal policies, generating a summary that highlights areas where adjustments are needed to comply with new requirements.

Conclusion

Automated review of academic policies with summary generation transforms a manual, detailed process into a fast, precise, and strategic task. This model not only facilitates identifying key points and critical areas but also ensures that educational policies align with current regulations. Ideal for educational institutions aiming to optimize the management of their internal regulations and comply with government or international standards.