College students’ perceptions of AI in multimedia content creation
Georgina Amankwa and faculty mentor Melanie Burleson Richards studied students’ perceptions of AI in multimedia content creation, focusing on technological benefits and ethical concerns including effectiveness, fake content, originality, fairness, and willingness to recommend AI tools.
All 124 participants reported some experience with AI content creation, but the study found a gap between awareness and regular use. The survey combined structured measures with open-ended responses so the researchers could examine both prevalence and explanation.
Where Evidano fit
The quantitative survey data was analyzed in SPSS. Evidano, cited under its former name AILYZE, was used for the open-ended responses.
That division of labor is methodologically clear: statistical tests summarized patterns in the structured data, while the qualitative analysis captured how students described efficiency, quality, trust, originality, and ethical uncertainty in their own words.
What the study found
Time savings was the most frequently reported benefit, identified by 67% of students. Enhanced engagement was reported by 46%, and 32% cited improved multimedia quality.
At the same time, 38% said they rarely used AI. Authenticity and originality emerged as leading ethical concerns, and students recognized efficiency without fully trusting the quality of AI-produced content. Frequent users showed a statistically significant association with awareness of ethical implications.
The study concluded that adoption depends on more than speed. Quality and trust shape whether students are willing to recommend or rely on the tools. The authors recommended practical AI education and case-based learning to help students evaluate both benefits and risks.
Why this case matters
This is a compact example of Evidano inside a conventional mixed-methods design. The platform was used for the qualitative material, not as a replacement for the statistical analysis. That makes the case relevant to student-experience, market-research, and product-research teams that collect open-ended fields alongside structured surveys.
It also shows the value of analyzing the gap between attitudes and behavior. A top-line survey might have concluded that students appreciate AI’s efficiency. The qualitative strand helped retain the counterweight: concerns about authenticity, originality, and quality remain barriers to actual use.
Publication status and limits
This work is a university research poster record, not a peer-reviewed journal article. The repository record provides the abstract and presentation metadata but does not currently host the poster or a full paper, so the exact codebook, number of qualitative themes, and validation procedures are not described in the deposited abstract.
How Evidano fit the workflow
- 1Survey students online
Structured and open-ended responses were collected from 124 ETSU psychology students.
- 2Analyze the numeric data in SPSS
Frequencies and associations described usage, perceived benefits, and ethical awareness.
- 3Analyze the written responses in Evidano
The platform supported thematic interpretation of students’ explanations and concerns.
- 4Bring the strands together
The mixed-methods synthesis compared stated benefits with actual use and trust.
Evidano handled the open-ended strand; SPSS handled the statistics.
Written responses surfaced the trust and originality concerns behind low usage.
A student researcher and faculty mentor ran the study end to end.
The analysis tools are named in the university repository record.