Show Me How You Interact, I Will Tell You What You Think - Exploring the Effect of the Interaction Style on Users’ Sensemaking about Correlation and Causation in Data

Oct 22, 2026

Uploaded by Riley

Findings from embodied cognition indicate that whole-body input (beyond eye gaze) shapes how people interpret information during data visualization interaction. The study examines how two interaction designs influence how participants discuss and report correlation and causation in data. A lab experiment compares a Full-Body gesture-and-movement setup with a Gamepad control condition on a geo-referenced display. Participants show lower agreement with correlation/causation statements and make fewer FORCE-schema-related remarks under Gamepad.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages12

Reading Time30 min

AccessFree to download

Abstract

Introduction

Data exploration in everyday life

Correlation vs. causation in interpretation

Prior approaches in data visualization

Embodied interaction and learning background

Experimental study setup and conditions

Full-Body interaction

Gamepad interaction

Results and discourse analysis

Agreement with correlation/causation statements

Conceptual Metaphor Theory findings

Show Me How You Interact, I Will Tell You What You Think: Exploring the Effect of the Interaction Style on Users’Sensemaking about Correlation and Causation in Data A’aeshah Alhakamy∗ University of Tabuk Tabuk, Saudi Arabia [aalhakami@ut.edu.sa](aalhakami@ut.edu.sa) Milka Trajkova∗ Indiana University-Purdue University Indianapolis Indianapolis, Indiana, United States [milktraj@iu.edu](milktraj@iu.edu) Francesco Cafaro∗ Indiana University-Purdue University Indianapolis Indianapolis, Indiana, United States [fcafaro@iu.edu](fcafaro@iu.edu) Figure 1: We conducted an in-lab study using two alternative prototypes of an interactive data visualization (two 3D globes representing geo-referenced data on a 65" screen). Participants in the first condition (Full-Body) were able to control the data visualization using mid-air gestures and body movements. Participants in the second condition (Gamepad) used a gamepad to interact with the screen. ABSTRACT Findings from embodied cognition suggest that our whole body (not just our eyes) plays an important role in how we make sense of data when we interact with data visualizations. In this paper, we present the results of a study that explores how different designs of the "interaction" (with a data visualization) alter the way in which people report and discuss correlation and causation in data. We conducted a lab study with two experimental conditions: Full body (participants interacted with a 65” display showing geo-referenced data using gestures and body movements); and, Gamepad (people used a joypad to control the system) . Participants tended to agree less with statements that portray correlation and causation in data after using the Gamepad system. Additionally, discourse analysis based on Conceptual Metaphor Theory revealed that users made fewer remarks based on FORCE schemata in Gamepad than in Full-Body. ∗ All authors contributed equally to this research. This work is licensed under a Creative Commons Attribution International 4.0 License. DIS ’21, June 28-July 2, 2021, Virtual Event, USA © 2021 Copyright held by the owner/author(s) . ACM ISBN 978-1-4503-8476-6/21/06 . [https://doi.org/10.1145/3461778.3462083](https://doi.org/10.1145/3461778.3462083) CCS CONCEPTS • Human-centered computing → Userstudies;Interactionparadigms; Ubiquitous and mobile computing design and evaluation methods. KEYWORDS Embodied Interaction; Human-Data Interaction; Public Displays; Data Visualization; Informal Learning ACM Reference Format: A’aeshah Alhakamy, Milka Trajkova, and Francesco Cafaro. 2021. Show Me How You Interact, I Will Tell You What You Think: Exploring the Effect of the Interaction Style on Users’ Sensemaking about Correlation and Causation in Data. In Designing Interactive Systems Conference 2021 (DIS ’21), June 28-July 2, 2021, Virtual Event, USA. ACM, New York, NY, USA, 12 pages. [https://doi.org/10.1145/3461778.3462083](https://doi.org/10.1145/3461778.3462083) 1 INTRODUCTION In today’s world, people produce 2.5 quintillion bytes of data per day –while searching for information on the Internet, reading newspapers, using social media, or listening to debates [2] . Thus, data exploration is no longer limited to the realm of research laboratories, in which scientists define experimental scenarios to validate hypotheses [44] . For example, during the 2020 pandemic, people have spontaneously created hundreds of data visualizations about COVID-19 and posted them on Twitter and other social media [64] . In such a context, being able to make sense of data is a particularly crucial skill, because more and more people have relied on their own data analyses to inform their personal and business decisions DIS ’21, June 28-July 2, 2021, Virtual Event, USA A’aeshah Alhakamy, Milka Trajkova, and Francesco Cafaro (for example, whether it is safe enough to go to the beach or toreopen the dining room of their restaurant to customers [64]) . Additionally, as the gathe

FAQs

What does the research investigate about interaction styles?

It investigates how different interaction designs with a data visualization change how users make sense of correlation and causation in data and how they discuss these ideas.

How do the two experimental conditions differ?

In the Full-Body condition, participants use mid-air gestures and body movements to control a geo-referenced 3D globe display, while the Gamepad condition uses a gamepad to interact with the system.

What were the key findings about correlation and causation sensemaking?

Participants agreed less with statements portraying correlation and causation after using the Gamepad system, and discourse analysis found fewer remarks based on FORCE schemata in the Gamepad condition than in Full-Body.

Oct 22, 2026

Uploaded by Riley