In reflecting on my questionnaire’s reliability, I am moderately confident that the scale demonstrates acceptable internal consistency. Although I have not yet calculated C...
In reflecting on my questionnaire’s reliability, I am moderately confident that the scale demonstrates acceptable internal consistency. Although I have not yet calculated Cronbach’s Alpha, I designed the questionnaire items carefully to ensure that they measure the same underlying construct, which is students’ use and perceptions of AI tools in academic writing.
To promote internal consistency, I grouped the items into clear categories, such as frequency of AI use, perceived usefulness, ease of use, and challenges encountered. Within each section, the questions were written with similar wording and focused on one central idea at a time. I also tried to avoid double-barreled or leading questions so that respondents could provide clear and accurate answers.
One of the main challenges I faced was making sure that the items were sufficiently related without sounding repetitive. At times, it was difficult to balance consistency with variety in wording. Some questions initially overlapped in meaning, which could have confused respondents or artificially increased similarity among responses.
For the next draft, I would like to improve the scale by revising items that may be too broad or ambiguous. In addition, I plan to pilot the questionnaire with a small group of students first in order to identify unclear items and calculate Cronbach’s Alpha to obtain statistical evidence of reliability. This would help strengthen the overall quality of the instrument.
Overall, while I believe the questionnaire is reasonably reliable in its current form, I would feel more confident after conducting a formal reliability analysis.