Goal-Setting Behavior of Workers on Crowdsourcing Platforms: An Exploratory Study on MTurk and Prolific

Author:

Abbas Tahir,Gadiraju Ujwal

Abstract

A wealth of evidence across several domains indicates that goal setting improves performance and learning by enabling individuals to commit their thoughts and actions to goal achievement. Recently, researchers have begun studying the effects of goal setting in paid crowdsourcing to improve the quality and quantity of contributions, increase learning gains, and hold participants accountable for contributing more effectively. However, there is a lack of research addressing crowd workers' goal-setting practices, how they are currently pursuing them, and the challenges that they face. This information is essential for researchers and developers to create tools that assist crowd workers in pursuing their goals more effectively, thereby improving the quality of their contributions. This paper addresses these gaps by conducting mixed-method research in which we surveyed 205 workers from two crowdsourcing platforms -- Amazon Mechanical Turk (MTurk) and Prolific -- about their goal-setting practices. Through a 14-item survey, we asked workers regarding the types of goals they create, their goal achievement strategies, potential barriers that impede goal attainment, and their use of software tools for effective goal management. We discovered that (a) workers actively create intrinsic and extrinsic goals; (b) use a combination of tools for goal management; (c) medical issues and a busy lifestyle are some obstacles to their goal achievement; and (d) we gathered novel features for future goal management tools. Our findings shed light on the broader implications of developing goal management tools to improve workers' well-being.

Publisher

Association for the Advancement of Artificial Intelligence (AAAI)

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Longitudinal Loyalty: Understanding The Barriers To Running Longitudinal Studies On Crowdsourcing Platforms;ACM Transactions on Social Computing;2024-07-11

2. "Are we all in the same boat?" Customizable and Evolving Avatars to Improve Worker Engagement and Foster a Sense of Community in Online Crowd Work;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

3. Are We All in a Truman Show? Spotting Instagram Crowdturfing through Self-Training;2023 32nd International Conference on Computer Communications and Networks (ICCCN);2023-07

4. CrowdSurfer: Seamlessly Integrating Crowd-Feedback Tasks into Everyday Internet Surfing;Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19

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