TY - JOUR
T1 - Performance with tables and graphs
T2 - Effects of training and a visual search model
AU - Meyer, Joachim
N1 - Funding Information:
Thisstuyipsdtoatrefhau’sdtholtohcsrteatotsehDireaptaofIrntmdl uenstria EngineeringandMnaantgatBen-GurioemnUniversite yoftheNegev,Beer-Sheva, Israel, with D. Shinar and D. Leiser as avdis. Thseoauthorr thanks G. Meyer and a numberofstudentsintheDepaenrttofIndustriam lEngineeringandMemenatatnag Ben-Gurion University for thr helep iin prpaengrtheiexpmentesrandicollecingtthe data. The study was suppodrin partet by the Center for Erogmicns anod Safety at Ben-Gurion Universtyiand by a grant from the Human FacstBrancohrof the Israeli Ministry of Defense, and the author would like to thank contttechnicaacl monitor I. Shelach for his support.
PY - 2000/11/1
Y1 - 2000/11/1
N2 - After more than 70 years of research it is still not clear under what conditions graphic presentations of information have an advantage over tables. A minimum assumption Visual Search Model (VSM) was designed to predict the performance of various tasks with tables and graphs that show data with different levels of complexity. An experiment tested the performance of five tasks with tables, bargraphs and line-graphs, showing data with various levels of complexity, over the course of nine experimental sessions in order to assess possible changes in the relative efficiency of the displays after practice. Tables had an initial advantage over graphs for all tasks, and there were complex interactions between the variables. The initial differences between the displays disappeared for some tasks after users gained experience with the displays, while for other tasks the differences continued to exist even after extended practice. The VSM predicted the results for tables well. For graphs the model was adequate for tasks that involve single data points, such as reading values or comparing pairs of values. The performance of tasks that require the analysis of data configurations, such as reading a trend, could not be predicted with the VSM. Hence the VSM can predict task performance with tables and graphs for low-integration tasks.
AB - After more than 70 years of research it is still not clear under what conditions graphic presentations of information have an advantage over tables. A minimum assumption Visual Search Model (VSM) was designed to predict the performance of various tasks with tables and graphs that show data with different levels of complexity. An experiment tested the performance of five tasks with tables, bargraphs and line-graphs, showing data with various levels of complexity, over the course of nine experimental sessions in order to assess possible changes in the relative efficiency of the displays after practice. Tables had an initial advantage over graphs for all tasks, and there were complex interactions between the variables. The initial differences between the displays disappeared for some tasks after users gained experience with the displays, while for other tasks the differences continued to exist even after extended practice. The VSM predicted the results for tables well. For graphs the model was adequate for tasks that involve single data points, such as reading values or comparing pairs of values. The performance of tasks that require the analysis of data configurations, such as reading a trend, could not be predicted with the VSM. Hence the VSM can predict task performance with tables and graphs for low-integration tasks.
KW - Graphic displays
KW - Human-computer interaction
KW - Information presentation
KW - Models
KW - Skill acquisition
KW - Tables
UR - https://www.scopus.com/pages/publications/0033741145
U2 - 10.1080/00140130050174509
DO - 10.1080/00140130050174509
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C2 - 11105976
AN - SCOPUS:0033741145
SN - 0014-0139
VL - 43
SP - 1840
EP - 1865
JO - Ergonomics
JF - Ergonomics
IS - 11
ER -