Data from: ChatGPT performance on radiation technologist and therapist entry to practice exams
<p>This dataset contains the data needed to reproduce all results and figures described in "ChatGPT performance on radiation technologist and therapist entry to practice exams".</p> <p>Details about the data collection can be found in the paper referenced below. Briefly, ChatGPT (GPT-4) was prompted with multiple choice questions from 4 practice exams provided by the Canadian Association of Medical Radiation Technologists (CAMRT). ChatGPT was promted with the questions from each exam 5 times between July 17 and August 13, 2023. Table 1, below, provides details about the dates for data collection.<br><br></p> <p><strong>Variable descriptions</strong></p> <ul> <li><code>question</code>: Question number, provided by CAMRT. Skipped question numbers indicate image-based questions that were excluded from the study.</li> <li><code>discipline</code>: Indicates the CAMRT exam discipline, abbreviated as follows <ul> <li>RAD: radiological technology</li> <li>MRI: magnetic resonance</li> <li>NUC: nuclear medicine</li> <li>RTT: radiation therapy</li> </ul> </li> <li><code>question_type</code>: Indicates the type of competency being assessed by the question (Knowledge, Application, or Critical thinking). Competency categories were assigned by CAMRT.</li> <li><code>corrrect_response</code>: The correct multiple choice response ("A", "B", "C", or "D"), assigned by CAMRT.</li> <li><code>attempt1-5</code>: ChatGPT's response to the multiple choice questions for attempts 1 through 5, indicated using the letters "A", "B", "C", or "D". In a few cases, ChatGPT did not provide a reference to a multiple choice response and "NA" is recorded in the dataset. </li> </ul> <p><em>Note: The long-form questions from CAMRT and answers provided by ChatGPT are not available as a part of this dataset.<br><br></em></p> <p><strong>Table 1</strong>: Dates for data collection</p> <table> <tbody> <tr> <td> </td> <td><strong>Attempt 1</strong></td> <td><strong>Attempt 2</strong></td> <td><strong>Attempt 3</strong></td> <td><strong>Attempt 4</strong></td> <td><strong>Attempt 5</strong></td> </tr> <tr> <td><strong>Radiological technology</strong></td> <td>2 Aug 2023</td> <td>2 Aug 2023</td> <td>8 Aug 2023</td> <td>9 Aug 2023</td> <td>11 Aug 2023</td> </tr> <tr> <td><strong>Magnetic resonance </strong></td> <td>17 Jul 2023</td> <td>18 Jul 2023</td> <td>18 Jul 2023</td> <td>9 Aug 2023</td> <td>12 Aug 2023</td> </tr> <tr> <td><strong>Nuclear medicine</strong></td> <td>8 Aug 2023</td> <td>9 Aug 2023</td> <td>12 Aug 2023</td> <td>12 Aug 2023</td> <td>12 Aug 2023</td> </tr> <tr> <td><strong>Radiation therapy</strong></td> <td>9 Aug 2023</td> <td>12 Aug 2023</td> <td>12 Aug 2023</td> <td>13 Aug 2023</td> <td>13 Aug 2023</td> </tr> </tbody> </table> <p> </p>
ShareScore
52/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 12
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 8