The influence of pane position on CSCW* task performance in joint action perception space *Computer Supported Collaborative Work G. Metaxas, B. Metin,

Slides:

Advertisements

Similar presentations

School of Computing FACULTY OF ENGINEERING MJ11 (COMP1640) Modelling, Analysis & Algorithm Design Vania Dimitrova Lecture 19 Statistical Data Analysis:

Advertisements

Frequency Distributions Quantitative Methods in HPELS 440:210.

Comparing Two Means Dr. Andy Field.

Comparing Two Means.

Describing Quantitative Variables

Independent t -test Features: One Independent Variable Two Groups, or Levels of the Independent Variable Independent Samples (Between-Groups): the two.

Statistics Unit 6.

Statistical Methods II

Measures of Dispersion

Analyzing and Presenting Results Establishing a User Orientation Alfred Kobsa University of California, Irvine.

Chapter 15 (Ch. 13 in 2nd Can.) Association Between Variables Measured at the Interval-Ratio Level: Bivariate Correlation and Regression.

Measures of Dispersion or Measures of Variability

INDEPENDENT SAMPLES T Purpose: Test whether two means are significantly different Design: between subjects scores are unpaired between groups.

Inferences About Means of Two Independent Samples Chapter 11 Homework: 1, 2, 3, 4, 6, 7.

Analysis of Variance. Experimental Design u Investigator controls one or more independent variables –Called treatment variables or factors –Contain two.

Lesson #25 Nonparametric Tests for a Single Population.

Slides by JOHN LOUCKS St. Edward’s University.

Inferences About Means of Two Independent Samples Chapter 11 Homework: 1, 2, 4, 6, 7.

© 2004 Prentice-Hall, Inc.Chap 10-1 Basic Business Statistics (9 th Edition) Chapter 10 Two-Sample Tests with Numerical Data.

Non-parametric statistics

Measures of Central Tendency

Statistics for Everyone Workshop Fall 2010 Part 2 Descriptive Statistics: Measures of Central Tendency and Variability Workshop presented by Linda Henkel.

Choosing Statistical Procedures

Analysis of Variance. ANOVA Probably the most popular analysis in psychology Why? Ease of implementation Allows for analysis of several groups at once.

Conducting a User Study Human-Computer Interaction.

Census A survey to collect data on the entire population. Data The facts and figures collected, analyzed, and summarized for presentation and.

Comparing Two Samples Harry R. Erwin, PhD

Class Meeting #11 Data Analysis. Types of Statistics Descriptive Statistics used to describe things, frequently groups of people.  Central Tendency 

A statistical method for testing whether two or more dependent variable means are equal (i.e., the probability that any differences in means across several.

User Study Evaluation Human-Computer Interaction.

Measures of Central Tendency and Dispersion Preferred measures of central location & dispersion DispersionCentral locationType of Distribution SDMeanNormal.

Research and Statistics in Psychology Wadsworth, a division of Thomson Learning.

What is variability in data? Measuring how much the group as a whole deviates from the center. Gives you an indication of what is the spread of the data.

AP Statistics Chapter 23 Notes

Hypothesis Testing A procedure for determining which of two (or more) mutually exclusive statements is more likely true We classify hypothesis tests in.

Inference and Inferential Statistics Methods of Educational Research EDU 660.

Describing and Displaying Quantitative data. Summarizing continuous data Displaying continuous data Within-subject variability Presentation.

An Introduction to Statistics and Research Design

Section 10.1 Confidence Intervals

Experimental Psychology PSY 433 Appendix B Statistics.

Nonparamentric Stats –Distribution free tests –e.g., rank tests Sign test –H 0 : Median = 100 H a : Median > 100 if median = 100, then half above, half.

Statistical Fundamentals: Using Microsoft Excel for Univariate and Bivariate Analysis Alfred P. Rovai Independent t-Test PowerPoint Prepared by Alfred.

Logic and Vocabulary of Hypothesis Tests Chapter 13.

AP Statistics Section 11.1 B More on Significance Tests.

6 Making Sense of Statistical Significance.

BPS - 5th Ed. Chapter 251 Nonparametric Tests. BPS - 5th Ed. Chapter 252 Inference Methods So Far u Variables have had Normal distributions. u In practice,

Biostatistics Nonparametric Statistics Class 8 March 14, 2000.

LIS 570 Summarising and presenting data - Univariate analysis.

Science Fair Projects Part 2. Data/Log Book Data refers to information gathered during your investigation. List all materials used Notes on all preparations.

Internal assessment, Results, Discussion, and Format By Mr Daniel Hansson.

Descriptive Statistics Unit 6. Variable Any characteristic (data) recorded for the subjects of a study ex. blood pressure, nesting orientation, phytoplankton.

HYPOTHESIS TESTING FOR DIFFERENCES BETWEEN MEANS AND BETWEEN PROPORTIONS.

Statistics Unit Test Review Chapters 11 & /11-2 Mean(average): the sum of the data divided by the number of pieces of data Median: the value appearing.

Describing Data Week 1 The W’s (Where do the Numbers come from?) Who: Who was measured? By Whom: Who did the measuring What: What was measured? Where:

Inferential Statistics Assoc. Prof. Dr. Şehnaz Şahinkarakaş.

Guidelines for building a bar graph in Excel and using it in a laboratory report IB Biology (December 2012)

PS Research Methods I with Kimberly Maring Unit 9 – Experimental Research Chapter 6 of our text: Zechmeister, J. S., Zechmeister, E. B., & Shaughnessy,

Week 2 Normal Distributions, Scatter Plots, Regression and Random.

Descriptive Statistics ( )

Statistics Unit Test Review

Frequency Distributions

Numerical Measures: Skewness and Location

Some Nonparametric Methods

Significance and t testing

Quartile Measures DCOVA

Research Strategies: How Psychologists Ask and Answer Questions

Chapter 6: Becoming Acquainted with Statistical Concepts

Statistics and Data (Algebraic)

Statistical reasoning vocabulary review

Presentation transcript:

The influence of pane position on CSCW* task performance in joint action perception space *Computer Supported Collaborative Work G. Metaxas, B. Metin, E. Pelgrim, J. Schneider, G. Shapiro

*Computer Supported Collaborative Work VIP – USI ‘2004 Introduction Vertical screen more appropriate for communicating (social interaction; face-to- face communication) Horizontal screen more appropriate for working space (Meyer, Cohen & Nilsen, 1994; horizontal placement of input devices faster and favoured over vertical placement)

*Computer Supported Collaborative Work VIP – USI ‘2004 Problem statement What is better for a task that includes both communication and drawing; a horizontal oriented screen or a vertical oriented screen? [ ]

*Computer Supported Collaborative Work VIP – USI ‘2004 Objectives Main: To compare setting 1 with setting 2 based on the ISO standards (effectiveness, efficiency and satisfaction). Setting 1: Video-conferencing and drawing tool are both projected onto a horizontally placed digital board. Direct manipulation of the drawing tool by a digital pen. Setting 2: Video-conferencing tool and drawing tool are both presented on a vertical screen, digital pen is used to manipulate the drawing tool.

*Computer Supported Collaborative Work VIP – USI ‘2004 Research questions H0 = There will be no difference in the task performance between Setup 1 and Setup 2.

*Computer Supported Collaborative Work VIP – USI ‘2004 Experimental set up VIP system and horizontal set up Vertical set up, cameraRemote station

*Computer Supported Collaborative Work VIP – USI ‘2004 Sample size Usable data: 10 subjects Age Experienced with drawing applications Students from USI

*Computer Supported Collaborative Work VIP – USI ‘2004 Tasks Video-conference with experimenter Draw lines between basic geometrical figures Digital pen as drawing tool Within subjects design

*Computer Supported Collaborative Work VIP – USI ‘2004 Errors Correct task execution ErrorTask figure

*Computer Supported Collaborative Work VIP – USI ‘2004 Measurements Dependent variables Efficiency: Time to complete a task Effectiveness: Total amount of errors during task Satisfaction: Ask directly which setting they prefer Independent variables Setting

*Computer Supported Collaborative Work VIP – USI ‘2004 Analysis T-test comparing the means of two related samples (the horizontal setting and the vertical setting). Wilcoxon Signed Ranks test comparing the medians of two related samples (more robust against extreme values). Check for outliers An outliers is an observation that has a value which is at least 1.5 * IQD above the third quartile or below the first quartile. p.s More individual variation in condition 2. Median: In condition 1, the horizontal condition, 50% of the participants performed the task in 70.3 or less seconds. Mean: 71.4 seconds.

*Computer Supported Collaborative Work VIP – USI ‘2004 Analysis Rough scores D time,gem. : On average all participants perform the task in the horizontal setting 33.8 seconds faster than in the vertical setting (rough effect) How big is this effect in proportion to the noise (individual variations)? Cohen’s d dev = 1,99, the error distributions of the two settings are very far apart from each other. All participants made more errors in the vertical condition than in the horizontal condition. Cohen’s d time = 0,75. The two distributions overlap (but still a big effect)

*Computer Supported Collaborative Work VIP – USI ‘2004 Analysis Assume the conditions for the parametric test are met: T-test.

*Computer Supported Collaborative Work VIP – USI ‘2004 Analysis Communication errors Significantly more errors in the vertical condition than in the horizontal condition (p <.05). Satisfaction Which setting do you prefer? Half of the participants preferred the horizontal setting; Two preferred the vertical; Three had no opinion.

*Computer Supported Collaborative Work VIP – USI ‘2004 Problems Preparing the vertical set up Calibration of the pen Counterbalance Drawing figures

*Computer Supported Collaborative Work VIP – USI ‘2004 Conclusion and Discussion Performance on different device orientations may depend on task (writing vs. drawing) Not sure if it can be generalized Participants perform better in the horizontal setting than in the vertical setting.  They are faster and make less errors. Participants make less communication errors in the horizontal setting. Participants prefer the horizontal setting.