| dc.contributor.advisor | Hu, Tony | |
| dc.contributor.author | Kumar, Aditi | |
| dc.date.accessioned | 2022-01-14T15:13:42Z | |
| dc.date.available | 2022-01-14T15:13:42Z | |
| dc.date.issued | 2021-06 | |
| dc.date.submitted | 2021-06-25T20:20:16.797Z | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/139477 | |
| dc.description.abstract | With the increasing popularity of and avenues for online learning, a considered approach to academic integrity has emerged as a priority. Artificial intelligence (AI) enabled proctoring software has been touted as a solution. However, it relies on imperfect and biased technology. For this dissertation, the author partnered with an online education company to provide alternatives to AI proctoring that include assessment design and administration, honour code, and in-house authentication. In addition to recommending the alternatives, a phased implementation plan was also created. | |
| dc.publisher | Massachusetts Institute of Technology | |
| dc.rights | In Copyright - Educational Use Permitted | |
| dc.rights | Copyright retained by author(s) | |
| dc.rights.uri | https://rightsstatements.org/page/InC-EDU/1.0/ | |
| dc.title | Design Alternatives to AI Proctoring Software | |
| dc.type | Thesis | |
| dc.description.degree | S.M. | |
| dc.contributor.department | System Design and Management Program. | |
| dc.identifier.orcid | 0000-0002-7949-9208 | |
| mit.thesis.degree | Master | |
| thesis.degree.name | Master of Science in Engineering and Management | |
