Are you currently enrolled as a student at a college or university?
- Yes
- No
A research survey examining how AI tools are reshaping academic integrity norms among college and university students. Covers policy awareness, personal usage patterns, acceptability perceptions, peer behavior observations, and policy recommendations.
A preview of what’s in the template. Every question is editable before you launch.
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Built-in safeguards against rushed answers and low-quality respondents.
Wording, ordering, and branching written by the AI — tuned to your research goal.
Themes, quotes, and a plain-English summary write themselves once responses come in.
We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.
This is a static, fielding-ready form template rather than a research instrument, likely oriented toward reporting or acknowledging integrity policies rather than studying attitudes and usage patterns. It's easy to deploy and customize with Jotform's drag-and-drop builder, but it isn't designed to probe nuanced student perceptions or behaviors. No mention of adaptive questioning or AI-assisted follow-up.
A generic academic research form template rather than one purpose-built around AI and academic integrity themes, so a researcher would need to substantially rewrite questions to cover policy awareness, usage, and peer-behavior topics. Typeform's conversational one-question-at-a-time format is pleasant for respondents, but the template itself is a generic starting point, not a subject-matter-specific instrument. No adaptive AI interviewing is indicated.
Open this template in the editor. Every part is yours to change before the first respondent sees it.
More studies from the same category.
An academic research survey exploring faculty attitudes, concerns, and readiness regarding AI-assisted grading and assessment tools. Covers current practices, openness to adoption, concerns about bias/accuracy/privacy, training needs, and willingness to participate in controlled experiments.
View templateAn academic instrument measuring student awareness of, exposure to, and attitudes toward artificial intelligence ethics. Covers concept familiarity, training exposure, ethical dilemma responses, regulation views, and willingness to prioritize ethics over convenience. Estimated completion: 8–12 minutes.
View templateAn academic research survey examining how college and university students perceive and use AI writing tools such as ChatGPT, Copilot, and similar technologies. The survey covers usage patterns, perceived benefits and dependency concerns, academic integrity perspectives, quality comparisons, and instructor communication about AI policies.
View templateMeasures student satisfaction, instructional quality, curriculum relevance, and near-term learning transfer for fintech courses. Designed for course administrators and instructional designers seeking actionable improvement data.
View templateMeasures research participants' preferences for study session length, break scheduling, and compensation structures. Designed for academic and UX researchers optimizing study design for participant comfort and data quality.
View templateMeasures student perceptions of rubric clarity, fairness, and usefulness for learning. Designed for course designers and academic researchers seeking to improve grading transparency and rubric design.
View template