#128,965 | AsPredicted (original) (raw)

'Human-AI Collaboration & Creative Engagement'

AsPredicted #: 128,965

Author(s)
Suqing Wu (Zhejiang University) - s.wu@zju.edu.cn
Yukun Liu (Zhejiang University) - liuyk@shanghaitech.edu.cn
Mengqi Ruan (Zhejiang University) - ruanmengqi@zju.edu.cn
Siyu Chen (Zhejiang University) - siyu_chen@zju.edu.cn
Xiao-Yun Xie (School of Management, Zhejiang University) - xiexy@zju.edu.cn

Pre-registered on
2023/04/16 23:51 (PT)

1) Have any data been collected for this study already?
No, no data have been collected for this study yet.

2) What's the main question being asked or hypothesis being tested in this study?
In this research, we are interested in examining whether and how collaborating with generative artificial intelligence (i.e., ChatGPT) in a creative task, compared to when working alone, may influence individuals' engagement and functioning in the current as well as the subsequent creative task. Importantly, we propose factors including individuals' intrinsic motivation, enjoyment, perceived sense of control, and so forth as potential underlying mediators.

3) Describe the key dependent variable(s) specifying how they will be measured.
Dependent variables:
Task engagement: measured with a three-item scale originally developed by Rich, LePine, & Crawford, (2010).
Task performance: operationalized through both subjective and objective evaluations of participants' inputs in both tasks. Specifically, independent raters will be asked to rate the creativity of participants' inputs in both tasks, using the creative performance measure as reported in Oldham & Cummings (1996). Participants' responses in the alternative uses task (AUT; Guilford, 1967) will also be objectively evaluated via the Open Creativity Scoring method, as detailed in the following website: https://openscoring.du.edu/

Mediators:
Perceived sense of control, measured with a three-item scale developed by Greenaway et al., (2015);
Boredom, measured with a four-item scaleand developed by van Tilburg, & Igou, (2012);
Intrinsic motivation, measured with a four-item scale developed by Shin & Grant (2019).

4) How many and which conditions will participants be assigned to?
We will assign participants into two conditions: the Human-ChatGPT collaboration condition and the Human working alone condition. Participants will be randomly assigned to one of the two conditions.

5) Specify exactly which analyses you will conduct to examine the main question/hypothesis.
The types of analyses to be employed in this project will involve independent samples t tests, multiple regressions, moderation and mediation analyses, etc.

6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations.
We will use an attention check to identify participants whose data are less reliable and thus should not be included in analyses.

7) How many observations will be collected or what will determine sample size? No need to justify decision, but be precise about exactly how the number will be determined.
We made a priori power analysis using G*Power and estimated a sample size of 352 (effect size = 0.3 [a small to medium effect size]; α error probability = 0.05; power (1-β error probability) = 0.80; Allocation ratio N2/N1 = 1).

8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?)
We will measure and control for perceived task load, measured with two items following Reid & Nygren, (1988). For exploratory purposes, we will measure individual self-construal, creative role identity, and cognitive styles and investigate its moderating role in influencing the proposed relationships.

Version of AsPredicted Questions: 2.00