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Adjunct Faculty
Art
College of Fine Arts
Spring 2024

60-424 AI Animation (14-week course)

1. To what extent does student use of generative AI tools to make animations impact the technical and aesthetic control over their art?
2. To what extent does student self-efficacy for animation and genAI skills change over the course of a semester in which students could use genAI to create animations?

Andrew’s students used genAI tools to support their creation of animations, especially during creative editing and stylization decisions. Applications during and between class sessions included generating storyboards, scripts, animated sequences, synthesized voice narration and voice acting, and sound designs, resulting in both narrative and experimental works of animation. The suite of genAI tools included Runway, Deforum Stable Diffusion, ChatGPT, ElevenLabs, Midjourney, Dall-E and more.

Students used a suite of genAI tools across all animation assignments. Using genAI, the first assignment required students to recreate an animation from a previous course for which genAI was not originally used. Andrew compared students’ animations created with (treatment) and without (control) the assistance of genAI. He also measured changes in students’ self-efficacy regarding creating animations with and without genAI throughout the course. 

Sample size: Total sample (13 students completed the control, followed by the treatment condition) 

Data Sources:

1. Students’ animations created without and then with genAI, scored via a rubric to evaluate aesthetic and technical control.
2. Pre/post surveys of students’ self-efficacy regarding skills using genAI and course learning objectives.

1. RQ1: Animations created with genAI scored significantly higher on aesthetic control than those created without genAI, but they did not significantly differ on technical control. 
   
   

   Figure 1. Students earned significantly higher rubric scores (0-3 points for each criterion) on aesthetic control for an animation created with genAI assistance (M = 3.00, SD = .00) than on the same animation created without the help of genAI (M = 2.33, SD = .49), t(11) = 4.69, p < .001, Hedges’ g = 1.26. Students’ rubric scores did not differ for technical control (t(11) = 1.77, p = .10). Error bars are 95% confidence intervals for the means.

2. RQ2: Students entered the course with significantly lower self-efficacy for using genAI tools to make animations than for animating without genAI. By mid-semester, their self-efficacy for animating with and without genAI no longer differed, and both types were equivalent by the end of the semester, representing a doubling in confidence of using genAI for animation.
   
   

   Figure 2. Students entered the semester with significantly lower self-efficacy for creating animations with genAI assistance compared to creating animations without genAI assistance (t(12) = 3.08, p = .01, Hedges’ g = .80), this difference was no longer present by the middle of the semester (t(10) = .98, p = .35), nor the end (t(11) = .49, p = .64). Self-efficacy for creating animations with genAI support increased significantly across the semester (F(2, 18) = 9.99, p = .001, η_p² = .53), specifically from pre to mid, p = .04, and pre to post,  p = .002, and marginally from mid to post, p = .06, whereas self-efficacy for creating animations without genAI assistance remained the same across the semester (F (2, 18) = .50, p = .61). Error bars are 95% confidence intervals for the means.

Eberly Center’s Takeaways: 

1. RQ1:  Results suggest that genAI use may confer a possible advantage for aesthetic control, but not technical control. However, students recreated an animation done in a previous course without genAI. Consequently, improvements in aesthetic control could also reflect the impacts of repeated practice over time. Lastly, the instructor knew which animations were created with genAI assistance when scoring, which may have biased ratings. 
2. RQ2: While self-efficacy for creating animations without genAI remained stable throughout the semester, students’ self-efficacy for using genAI for animations had doubled by the end of the semester. Repeated practice with various genAI tools for creating animations may have contributed to these increases in student confidence.