Tools for Remote Teaching or Working
Accessing Georgia Tech Resources From Off-Campus
- ME Vlab / VM: access from https://mycloud.gatech.edu
- ME students and students enrolled in ME courses can access the ME-2020-V2
- OIT provides several FAQs about the VLab service
- Georgia Tech VPN: https://anyc.vpn.gatech.edu
- Alternative VPN Option - GlobalProtect Campus VPN
- For accessing PACE resources remotely
- Canvas provides many tools for teaching courses: https://canvas.gatech.edu
- Kaltura Capture will allow you to create lectures to upload to the My Media module of your course
- LinkedIn Learning videos (login to GT's LinkedIn Learning service, then select a link below to view the video):
- Creating exams using Respondus 4.0 (Microsoft Windows only)
- To conduct lectures remotely, you can utilize one of these virtual meeting platforms, record the session, and upload to your Canvas site using the My Media module.
- To conduct meetings remotely, you can utilize one of these virtual meeting platforms:
- ME Staff VM
- All ME Staff memberes now have available to them a staff virtual machine that is accessible through any web browser at http://mycloud.gatech.edu
- The virtual environment does not save any custom changes or files upon logout
- All working files will need to be saved and managed from Cloud storage (Dropbox, OneDrive, Sharepoint)
- Departmental Sharepoint Sites
Cloud Storage and Data Security
Category I – Public Use:This information is targeted for general public use. Examples include Internet website contents for general viewing and press releases.
Category II – Internal Use:Information not generally available to parties outside the Georgia Tech community, such as directory listings, minutes from non-confidential meetings, and internal (Intranet) websites. Public disclosure of this information would cause minimal trouble or embarrassment to the Institute. This category should be the default data classification category.
Category III – Sensitive:This information is considered private and should be guarded from disclosure; disclosure of this information may contribute to financial fraud and/or violate State and/or Federal law.
Category IV – Highly Sensitive:Data which needs to be protected with the highest levels of security, as prescribed in contractual and/or legal specifications.
Examples of Data Categorizations can be found at OIT's Data Categorization FAQ.
Original concept by Rachel Ponder in ECE,