590 likes | 706 Views
Alternate Keyboards for Text Entry – And How to Evaluate Them. I. Scott MacKenzie. Plan. Background Keyboards Evaluation Case study. Background. HUMAN-COMPUTER INTERACTION GUIs Mouse input Direct manipulation. MOBILE COMPUTING Pen-based input Handwriting recognition
E N D
Alternate Keyboards for Text Entry – And How to Evaluate Them I. Scott MacKenzie
Plan • Background • Keyboards • Evaluation • Case study
HUMAN-COMPUTER INTERACTION • GUIs • Mouse input • Direct manipulation • MOBILE COMPUTING • Pen-based input • Handwriting recognition • Email, SMS messaging • Two-way pagers, mobile phones • HUMAN FACTORS • Office automation • Word processing • Document management Text Entry Research - Timeline Lots Research Activity Little 1960 1970 1980 1990 2000 Year
Virtual vs Physical Keyboards • Virtual keyboards • Aka “soft keyboards” or “on-screen keyboards” • Similar to clicking buttons in a GUI • Typically used with a stylus (but also with eye/head trackers and other input mechanisms) • Physical keyboards • Desktop qwerty, miniature qwerty, mobile phone keypad, 5-button pager, 3-key date stamp, 1-key input, etc. • Design Issues • Key layout, key size, key shape, number of keys, activation force, disambiguation, language modeling, word prediction, etc.
Hello ther _abcdefghijklmnopqrstuvwxyz e Select Three-key date stamp
More Ambiguity Continuum Less Number-of-keys Continuum Number of Keys
? R U N N E R Ambiguity • Ambiguity occurs if there are fewer keys than symbols in the language • Disambiguation is needed to select the intended letter from the possibilities • Phone keypad is a typical example Or, is it SUMMER, is it STONES ? Demo: java Decode d1-wordfreq-phoneks.txt 10
Word Prediction • Basic problem… • Given some amount of preceding text, predict subsequent text • Design issues • Dynamic vs. static language model • Word-level or phrase-level prediction • Size of candidate word list • Candidate word selection • Improving performance Demo: java WordPredict d1-wordfreq.txt 10
Disambiguation + Word Prediction Demo: java PhoneKeypad d1-wordfreq-phoneks.txt
Quick Example Qwerty Opti • Is Opti as fast as Qwerty?
Opti is faster, but only after about 4 hours of practice Opti vs. Qwerty
Evaluation • Research questions • Typically, something like… • Is design A as fast/accurate as design B? • Research questions come together as… • Independent variables, and • Dependent variables
Independent Variables • These are the factors and levels in your experiment • Examples
Opti vs. Qwerty • Two Independent variables • Keyboard layout with 2 levels: Opti, Qwerty • Session with 20 levels: 1, 2, 3, … 20 • Referred to as a 2 x 20 factorial design • The 40 test conditions were given to all participants, thus we have a 2 x 20 within-subject design (i.e., each subject received all 40 test conditions) • Note: within-subject design = repeated measures design (cf. between-subjects design)
Dependent Variables • These are the behaviours you measure • Examples
Speed as a Dependent Variable • Relatively straight forward to measure • Example... 1 2 3 41234567890123456789012345678901234567890123the quick brown fox jumps over the lazy dog t = 60 seconds = 1 minute Number of characters = 43 Number of words = 43 / 5 = 8.6 Speed = 8.6 / 1 = 8.6 wpm Note: Definition of a word: “five characters, including spaces, punctuation, etc”
Accuracy as a Dependent Variable • A bit trickier to measure • Example... • How many errors? • What are the errors? • What is the error rate (%)? Presented text 2 (gee, that was easy) the quick brown fox the quixck brwn fox • An “x” was inserted • An “o” was omitted Transcribed text ER = 2 / 19 = 0.105 = 10.5% Easy? Try this one (next slide)
quic--klyqu-cehklyquic-klyqucehklyqui-cklyqucehklyqu-icklyqucehklyquic--klyqu-cehklyquic-klyqucehklyqui-cklyqucehklyqu-icklyqucehkly Hmm, let’s see Accuracy is a Bit Tricky • How many errors? • What are the errors? • What is the error rate? Presented text 3 (that was a bit tricky) quickly qucehkly Transcribed text ER = 3 / 8.25 = 0.364 = 36.4%
Error rate = 36.4% KSPC = 10 / 8 = 1.2 Note: KSPC = keystrokes per character Accuracy is a Bit Tricky (2) Presented text quicklyqxucehkly qucehkly Input stream Transcribed text
Keystrokes Per Character (KSPC) • KSPC is useful both as a characteristic of text entry methods and as dependent variable in evaluations of text entry methods • KSPC as a characteristic • The average number of keystrokes to produce each character of text for a given language and entry method; e.g., • KSPC 1.00 for the Qwerty keyboard • KSPC 2.02 for multitap on a mobile phone • KSPC as a dependent variable • A behavioural measure of the keystroke activity in entering text; e.g., (see previous slide)
KSPC Characteristics KSPC > 1 KSPC < 1
Hello ther _abcdefghijklmnopqrstuvwxyz e Select Three-key Text Entry • The basic idea… Edit buffer “Virtual” keyboard Physical keys
Design Issues • Cursor modes • “Persistent” = stays put after each entry • “Snap to home” = snap to SPACE after each entry • SPACE position • Left, middle, right, etc. • Letter order • Alphabetical • By probability of letters, digrams, etc. • Fluctuating (next slide)
FOCL • FOCL = fluctuating optimal character layout • Letters rearranged after each entry • “Highly probable next characters” positioned closest to cursor • Advantage: fewer keystrokes • Disadvantage: increased cognitive load
Three-Key Method Comparisons The next step…
User Testing Methods #2 and #6 chosen for user testing
Participants and Apparatus • Participants • 10 paid volunteers (8 male, 2 female) • Ages 20 to 49 (mean = 30.1, sd = 8.5) • 3+ hours of computer usage per day • Apparatus (standard PC) • Input • Keyboard keys (configurable) • Most used “z” = left arrow, “x” = right arrow, “Enter” = Select • Output • CRT display (next slide)
Display - Method #2 Transcribed text Presented text Virtual keyboard
Typamatic Cursor Keys • Auto-repeat, or typamatic, cursor key behaviour possible • Used at discretion of participant • Spec’s • Delay = 176 ms • Repeat rate = 31.2 char/second
Procedure and Design • One-hour session per participant • About 25 minutes of text entry for each condition • Order of conditions counterbalanced • Instructions: Enter text phrases as quickly and accurately as possible. Ignore mistakes. Continue in the event of a error. • A few practice phrases, then data collection • Post-test questionnaire
Speed • 9-10 wpm • Difference not statistically significant
Accuracy • Difference not statistically significant