# Evaluating Singleplayer and Multiplayer in Human Computation Games

arXiv: https://arxiv.org/abs/1703.00818 · HTML: https://mlsanity.com/paper/1703.00818/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Mar 2017.

## Built on by (most cited first, 1 of 1)

- [Improving Deep Localized Level Analysis: How Game Logs Can Help](https://mlsanity.com/paper/2212.03376/) (2022)

## Abstract (arXiv)

Human computation games (HCGs) can provide novel solutions to intractable computational problems, help enable scientific breakthroughs, and provide datasets for artificial intelligence. However, our knowledge about how to design and deploy HCGs that appeal to players and solve problems effectively is incomplete. We present an investigatory HCG based on Super Mario Bros. We used this game in a human subjects study to investigate how different social conditions---singleplayer and multiplayer---and scoring mechanics---collaborative and competitive---affect players' subjective experiences, accuracy at the task, and the completion rate. In doing so, we demonstrate a novel design approach for HCGs, and discuss the benefits and tradeoffs of these mechanics in HCG design.