{"id":"https://openalex.org/W2345359441","doi":"https://doi.org/10.1145/2851581.2892364","title":"Reporting and Visualizing Fitts's Law","display_name":"Reporting and Visualizing Fitts's Law","publication_year":2016,"publication_date":"2016-05-06","ids":{"openalex":"https://openalex.org/W2345359441","doi":"https://doi.org/10.1145/2851581.2892364","mag":"2345359441"},"language":"en","primary_location":{"id":"doi:10.1145/2851581.2892364","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2851581.2892364","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065019193","display_name":"Alvin Jude","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139236","display_name":"Ericsson (United States)","ror":"https://ror.org/03q3bdj78","country_code":"US","type":"company","lineage":["https://openalex.org/I1306339040","https://openalex.org/I4210139236"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Alvin Jude","raw_affiliation_strings":["Ericsson, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Ericsson, San Jose, CA, USA","institution_ids":["https://openalex.org/I4210139236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066833706","display_name":"Darren Guinness","orcid":null},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Darren Guinness","raw_affiliation_strings":["University of Colorado Boulder, Boulder, CO, USA"],"affiliations":[{"raw_affiliation_string":"University of Colorado Boulder, Boulder, CO, USA","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066646201","display_name":"G. Michael Poor","orcid":"https://orcid.org/0009-0002-4512-9687"},"institutions":[{"id":"https://openalex.org/I157394403","display_name":"Baylor University","ror":"https://ror.org/005781934","country_code":"US","type":"education","lineage":["https://openalex.org/I157394403"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"G. Michael Poor","raw_affiliation_strings":["Baylor University, Waco, TX, USA"],"affiliations":[{"raw_affiliation_string":"Baylor University, Waco, TX, USA","institution_ids":["https://openalex.org/I157394403"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5065019193"],"corresponding_institution_ids":["https://openalex.org/I4210139236"],"apc_list":null,"apc_paid":null,"fwci":1.1171,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.784375,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2519","last_page":"2525"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10789","display_name":"Interactive and Immersive Displays","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10789","display_name":"Interactive and Immersive Displays","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10914","display_name":"Tactile and Sensory Interactions","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6868982315063477},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6851347088813782},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6685305833816528},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.598594069480896},{"id":"https://openalex.org/keywords/fittss-law","display_name":"Fitts's law","score":0.5795700550079346},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.5706093907356262},{"id":"https://openalex.org/keywords/goodness-of-fit","display_name":"Goodness of fit","score":0.5566846132278442},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.5028206706047058},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.462228387594223},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.46210962533950806},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45149654150009155},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4132283329963684},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.35323843359947205},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.32532334327697754},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2127498984336853},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1860010325908661},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.1026742160320282},{"id":"https://openalex.org/keywords/accounting","display_name":"Accounting","score":0.09410840272903442},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08574461936950684},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07196411490440369}],"concepts":[{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6868982315063477},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6851347088813782},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6685305833816528},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.598594069480896},{"id":"https://openalex.org/C159842133","wikidata":"https://www.wikidata.org/wiki/Q1137548","display_name":"Fitts's law","level":3,"score":0.5795700550079346},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.5706093907356262},{"id":"https://openalex.org/C132480984","wikidata":"https://www.wikidata.org/wiki/Q2034239","display_name":"Goodness of fit","level":2,"score":0.5566846132278442},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.5028206706047058},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.462228387594223},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.46210962533950806},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45149654150009155},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4132283329963684},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.35323843359947205},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.32532334327697754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2127498984336853},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1860010325908661},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.1026742160320282},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.09410840272903442},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08574461936950684},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07196411490440369},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2851581.2892364","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2851581.2892364","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1981395927","https://openalex.org/W1981820838","https://openalex.org/W1996349741","https://openalex.org/W2025017591","https://openalex.org/W2030813129","https://openalex.org/W2041655977","https://openalex.org/W2053557669","https://openalex.org/W2102148524","https://openalex.org/W2118232088","https://openalex.org/W2121723351","https://openalex.org/W2153657884","https://openalex.org/W2170810427","https://openalex.org/W6604223232","https://openalex.org/W6663860138"],"related_works":["https://openalex.org/W2028463249","https://openalex.org/W2009373886","https://openalex.org/W2016343001","https://openalex.org/W1980747699","https://openalex.org/W4256504150","https://openalex.org/W4256254269","https://openalex.org/W2011381500","https://openalex.org/W2953976309","https://openalex.org/W2327598865","https://openalex.org/W797770227"],"abstract_inverted_index":{"In":[0],"this":[1,16,109,128],"paper":[2,110,129],"we":[3],"compare":[4],"methods":[5],"of":[6,27,53,91],"reporting":[7,15,142],"and":[8,64],"visualizing":[9,144],"Fitts":[10,145],"regressions.":[11,146],"We":[12,55,87],"show":[13],"that":[14,57],"metric":[17],"using":[18,51],"mean":[19],"movement":[20],"time":[21],"per":[22],"user":[23],"over":[24],"accuracy-adjusted":[25],"Index":[26,52],"Difficulty":[28],"(IDe)":[29],"produces":[30],"more":[31,40],"descriptive":[32],"visualization.":[33],"This":[34],"method":[35],"displays":[36],"variance,":[37],"which":[38,79,134],"is":[39,59],"useful":[41],"in":[42,62,138],"understanding":[43],"the":[44,67,72,89,121],"interfaces,":[45],"than":[46,102],"an":[47],"aggregated":[48],"means-of-means":[49],"approach":[50],"Difficulty.":[54],"demonstrate":[56],"there":[58],"little":[60],"difference":[61],"slope":[63],"intercept":[65],"between":[66],"two":[68],"methods,":[69],"but":[70],"has":[71],"potential":[73],"to":[74,94],"uncover":[75],"wider":[76],"goodness-of-fit":[77],"coefficients":[78],"could":[80],"allow":[81],"for":[82,141],"better":[83],"comparison":[84],"across":[85],"experiments.":[86],"propose":[88],"use":[90],"quantile":[92],"regression":[93],"report":[95],"central":[96],"tendencies":[97],"as":[98],"a":[99],"trend,":[100],"rather":[101],"box":[103],"plots.":[104],"The":[105,124],"tools":[106],"released":[107,126],"with":[108,114,120,127],"can":[111,135],"be":[112,136],"used":[113,137],"any":[115],"pointing":[116],"device":[117],"evaluation":[118],"done":[119],"FittsStudy":[122],"program.":[123],"dataset":[125],"contains":[130],"almost":[131],"25,000":[132],"samples,":[133],"future":[139],"research":[140],"or":[143]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
