Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Introduction and Methods of Leveling01:26

Introduction and Methods of Leveling

267
Leveling is a surveying procedure used to determine elevation differences between distant points. Elevation refers to the vertical distance above or below a reference datum, typically mean sea level (MSL). In the United States, elevations are often referenced to the mean sea level station at Father Point Rimouski along the St. Lawrence Seaway. To make the datum accessible, permanent markers are established throughout the region. These markers, called benchmarks, have known elevations. If the...
267
Survival Curves01:18

Survival Curves

396
Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
396
Sieve Analysis and Grading Curves01:19

Sieve Analysis and Grading Curves

649
Sieve analysis is a method used to determine the particle size distribution of aggregate materials. This process involves the following steps:
649
Leveling Effect01:29

Leveling Effect

1.1K
In acid-base chemistry, the leveling effect refers to the limitation imposed by the solvent on the strength of acids and bases in solution. When a base stronger than the solvent's conjugate base is used, it deprotonates the solvent until the base is entirely consumed, making it ineffective against weaker acids. Conversely, an acid stronger than the solvent's conjugate acid protonates the solvent until the acid is depleted, rendering it ineffective against weaker bases. Essentially, the...
1.1K
Differential Leveling01:12

Differential Leveling

411
Differential leveling is a precise method in surveying used to determine the elevation difference between two points. Its primary goal is to establish accurate vertical measurements to create level surfaces or grade lines critical for designing and constructing infrastructures such as roads, bridges, and buildings.The procedure for differential leveling begins with setting up and leveling the instrument at a point where the benchmark can be seen. The level rod is held on the benchmark (BM), and...
411
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

355
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
355

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Practical recommendations from a multi-perspective needs and challenges assessment of citizen science games.

PloS one·2023
Same author

Signaligner Pro: A Tool to Explore and Annotate Multi-day Raw Accelerometer Data.

Proceedings of the ... IEEE International Conference on Pervasive Computing and Communications. IEEE International Conference on Pervasive Computing and Communications·2021
Same author

Large-Scale Analysis of Visualization Options in a Citizen Science Game.

Proceedings of the ... Annual Symposium on Computer-Human Interaction in Play. ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play·2021
Same author

Introducing Foldit Education Mode.

Nature structural & molecular biology·2020
Same author

Macromolecular modeling and design in Rosetta: recent methods and frameworks.

Nature methods·2020
Same author

Expertise and Engagement: Re-Designing Citizen Science Games With Players' Minds in Mind.

FDG : proceedings of the International Conference on Foundations of Digital Games. International Conference on the Foundations of Digital Games·2019
See all related articles

Related Experiment Video

Updated: Oct 25, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.6K

Inferring and Comparing Game Difficulty Curves using Player-vs-Level Match Data.

Anurag Sarkar1, Seth Cooper1

  • 1Northeastern University, Boston, USA.

IEEE Conference on Games 2019 : London, United Kingdom, 20-23 August 2019
|August 6, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to infer game difficulty curves from player win/loss data, applicable across various games. This approach enables consistent comparison of difficulty across different game types and progression systems.

Keywords:
difficulty curvegameplay datarating systems

More Related Videos

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
05:59

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Published on: March 7, 2019

6.9K
Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
08:12

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions

Published on: June 5, 2019

20.1K

Related Experiment Videos

Last Updated: Oct 25, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.6K
Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
05:59

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Published on: March 7, 2019

6.9K
Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
08:12

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions

Published on: June 5, 2019

20.1K

Area of Science:

  • Game Studies
  • Computational Intelligence
  • Human-Computer Interaction

Background:

  • Previous research formalized difficulty curves using function composition within a single game's dynamic difficulty system.
  • Existing frameworks were limited to specific game mechanics and lacked cross-game applicability.

Purpose of the Study:

  • To develop a generalized method for inferring and comparing difficulty curves across multiple games.
  • To extend the formalization of difficulty curves beyond single-game, ratings-based systems.
  • To establish a standardized vocabulary for discussing difficulty curve transformations.

Main Methods:

  • Inferring difficulty curves from player-vs-level win/loss outcomes in gameplay data.
  • Adapting a ratings-based dynamic difficulty system for broader game application.
  • Utilizing function composition to compare difficulty curves across games with fixed or dynamic level ordering.
  • Presenting an adjusted method for analyzing traditional ratings-based match data.

Main Results:

  • Successfully inferred and compared difficulty curves from four diverse games.
  • Demonstrated the generalizability of the proposed method beyond its initial single-game context.
  • Validated the use of function composition for cross-game difficulty analysis.

Conclusions:

  • The developed method provides a robust framework for understanding and comparing game difficulty.
  • This approach facilitates the analysis of player experience across different gaming platforms and designs.
  • The findings contribute to a more formal and universal understanding of game difficulty dynamics.