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    Twin tide skopje2012_june5 Twin tide skopje2012_june5 Presentation Transcript

    • Measuring users’ experiences or, the memory of them?Trajectory reminders EmoSnaps Footprint tracker iScale Evangelos Karapanos Skopje, 5 June 2012Wednesday, June 6, 12
    • My  background BSc Physics / microelectronics, U Patras, Greece (2004) Thesis: Model based design and evaluation of walk-up-and-use interfaces (HCI Group, ECE department) MSc HCI / UCL Interaction Centre, UK (2005) Thesis: User acceptance of nomadic user interfaces (Philips Research, Eindhoven) PhD HCI / TU Eindhoven, NL (2010) Title: Quantifying diversity in user experience Assist. Prof. HCI / Madeira ITI (2010-) Design for Experience in pervasive computingWednesday, June 6, 12
    • Soft Reliability 48% of returned products are not attributed to a violation of product specificationsWednesday, June 6, 12
    • problems rooted early in (concept) design phaseWednesday, June 6, 12
    • failure to truly incorporate it in one’s lifeWednesday, June 6, 12
    • 436 Studies in Computational Intelligence 436 The series Studies in Computational Intelligence (SCI) publishes new developments Karapanos and advances in the various areas of computational intelligence – quickly and with high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, hybrid intelligent, and virtual reality systems. Of particular value to both the contributors and the Coming! readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output. Over the past decade the field of Human-Computer Interaction has evolved from the study of the usability of interactive products towards a more holistic understanding Evangelos Karapanos of how they may mediate desired human experiences. This book identifies the notion of diversity in users? experiences with interactive 1 products and proposes methods and tools for modeling this along two levels: Modeling Users Modeling Users Experiences with Interactive Systems (a) interpersonal diversity in users? responses to early conceptual designs, and (b) the dynamics of users? experiences over time. The Repertory Grid Technique is proposed as an alternative to standardized June 2012 psychometric scales for modeling interpersonal diversity in users? responses to early concepts in the design process, and new Multi-Dimensional Scaling procedures are Experiences with Interactive Systems introduced for modeling such complex quantitative data. iScale, a tool for the retrospective assessment of users? experiences over time is proposed as an alternative to longitudinal field studies, and a semi-automated technique for the analysis of the elicited experience narratives is introduced. Through Foreword: Jean-Bernard Martens these two methodological contributions, this book argues against averaging in the subjective evaluation of interactive products. It proposes the development of interactive tools that can assist designers in moving across multiple levels of Closing note: Marc Hassenzahl abstraction of empirical data, as design-relevant knowledge might be found on all these levels. Foreword by Jean-Bernard Martens and Closing Note by Marc Hassenzahl. issn 1860-949X isbn 978-3-642-30999-1 9 783642 309991 springer.com 13Wednesday, June 6, 12
    • Wednesday, June 6, 12
    • Nuno  Nunes Vassilis  Kostakos Monchu  Chen Laura Rodríguez Gonçalo  Gouveia Néstor  Catano • 20  faculty Pedro  Campos Paulo  Sampaio Eduardo  Fermé – 14  countries,  8  languages • Areas: Larry  ConstanIne Jos  van  Leeuwen Barbara  Pizzileo – 11  CS,  2  physics/electronics,   2  psychology,  2  architecture,   2  design,  2  art,  2  other Ian  Oakley Luis  Gomes Ron  Salden Leonel  Nóbrega ValenIna  Nisi Evangelos  Karapanos David  Aveiro Luis  Gomes Yoram  ChisikWednesday, June 6, 12
    • MSc HCI & Entertainment TechnologyWednesday, June 6, 12
    • Industry InvolvementWednesday, June 6, 12
    • Design  for  Experience  in  pervasive  compu3ng Socially translucent eco-feedback technologies How do eco-feedback technologies: a) raise mutual awareness of family members’ consumption behaviors ! b) induce feelings of accountability on individuals regarding their consumption behaviors. Technologies for Social Inclusion in primary schools a) Using sociometric technologies to assess the inclusiveness of school communities b) Designing Persuasive technologies that challenge pupils’ perceptions of diversity Citizen participation on the go How can we motivate citizen participation through mobile technologies? •Public transit: The role of psychological empowerment: self-efficacy, sense of community, and causal importance Awareness technologies for parents, children and schoole Senseµ ( a) To support interpersonalinfer the physical,within family social activity of a pupil b) Using mobile sensors to connectedness verbal andhat aims at supporting awareness in parent c) To engage parents and school in ad-hoc communication Location-aware narratives: Does locality matter? Does the coupling between physical and virtual space result to increased immersion in the narrative world? Wednesday, June 6, 12
    • Design  for  Experience  in  pervasive  compu3ng Socially translucent eco-feedback technologies How do eco-feedback technologies: a) raise mutual awareness of family members’ consumption behaviors ! b) induce feelings of accountability on individuals regarding their consumption behaviors. Technologies for Social Inclusion in primary schools a) Using sociometric technologies to assess the inclusiveness of school communities b) Designing Persuasive technologies that challenge pupils’ perceptions of diversity Citizen participation on the go How can we motivate citizen participation through mobile technologies? •Public transit: The role of psychological empowerment: self-efficacy, sense of community, and causal importance Awareness technologies for parents, children and schoole Senseµ ( a) To support interpersonalinfer the physical,within family social activity of a pupil b) Using mobile sensors to connectedness verbal andhat aims at supporting awareness in parent c) To engage parents and school in ad-hoc communication Location-aware narratives: Does locality matter? Does the coupling between physical and virtual space result to increased immersion in the narrative world? Wednesday, June 6, 12
    • Design  for  Experience  in  pervasive  compu3ng Socially translucent eco-feedback technologies How do eco-feedback technologies: a) raise mutual awareness of family members’ consumption behaviors ! b) induce feelings of accountability on individuals regarding their consumption behaviors. Technologies for Social Inclusion in primary schools a) Using sociometric technologies to assess the inclusiveness of school communities b) Designing Persuasive technologies that challenge pupils’ perceptions of diversity Citizen participation on the go How can we motivate citizen participation through mobile technologies? •Public transit: The role of psychological empowerment: self-efficacy, sense of community, and causal importance Awareness technologies for parents, children and schoole Senseµ ( a) To support interpersonalinfer the physical,within family social activity of a pupil b) Using mobile sensors to connectedness verbal andhat aims at supporting awareness in parent c) To engage parents and school in ad-hoc communication Location-aware narratives: Does locality matter? Does the coupling between physical and virtual space result to increased immersion in the narrative world? Wednesday, June 6, 12
    • Design  for  Experience  in  pervasive  compu3ng Socially translucent eco-feedback technologies How do eco-feedback technologies: a) raise mutual awareness of family members’ consumption behaviors ! b) induce feelings of accountability on individuals regarding their consumption behaviors. Technologies for Social Inclusion in primary schools a) Using sociometric technologies to assess the inclusiveness of school communities b) Designing Persuasive technologies that challenge pupils’ perceptions of diversity Citizen participation on the go How can we motivate citizen participation through mobile technologies? •Public transit: The role of psychological empowerment: self-efficacy, sense of community, and causal importance Awareness technologies for parents, children and schoole Senseµ ( a) To support interpersonalinfer the physical,within family social activity of a pupil b) Using mobile sensors to connectedness verbal andhat aims at supporting awareness in parent c) To engage parents and school in ad-hoc communication Location-aware narratives: Does locality matter? Does the coupling between physical and virtual space result to increased immersion in the narrative world? Wednesday, June 6, 12
    • Design  for  Experience  in  pervasive  compu3ng Socially translucent eco-feedback technologies How do eco-feedback technologies: a) raise mutual awareness of family members’ consumption behaviors ! b) induce feelings of accountability on individuals regarding their consumption behaviors. Technologies for Social Inclusion in primary schools a) Using sociometric technologies to assess the inclusiveness of school communities b) Designing Persuasive technologies that challenge pupils’ perceptions of diversity Citizen participation on the go How can we motivate citizen participation through mobile technologies? •Public transit: The role of psychological empowerment: self-efficacy, sense of community, and causal importance Awareness technologies for parents, children and schoole Senseµ ( a) To support interpersonalinfer the physical,within family social activity of a pupil b) Using mobile sensors to connectedness verbal andhat aims at supporting awareness in parent c) To engage parents and school in ad-hoc communication Location-aware narratives: Does locality matter? Does the coupling between physical and virtual space result to increased immersion in the narrative world? Wednesday, June 6, 12
    • Measuring users’ experiences or, the memory of them?Trajectory reminders EmoSnaps Footprint tracker iScale Skopje, 5 June 2012Wednesday, June 6, 12
    • Technology Assisted ReconstructionTrajectory reminders EmoSnaps Footprint tracker iScale Skopje, 5 June 2012Wednesday, June 6, 12
    • User Experience defined a momentary, primarily evaluative feeling (good-bad) while interacting with a product or service Hassenzahl, 2008Wednesday, June 6, 12
    • Most of our evaluation tasks rely on memoryWednesday, June 6, 12
    • Heuristics and biases • Peak-and-end phenomenon • Summary judgments can be best predicted by a simple average of the most extreme and the last experience (Fredrickson and Kahneman, 1993) • Replicated in HCI - Summarizing mental effort to perceived usability: end matters (Hassenzahl and Sandweg, 2004) • Other biases (e.g., Rosy retrospection, Focusing illusion etc.)Wednesday, June 6, 12
    • Why do memory biases exist? Robison & Clore (2002) “The emotional experience can neither be stored nor retrieved” it is reconstructed from recalled contextual detailsWednesday, June 6, 12
    • Why do memory biases exist? Robison & Clore (2002)event, but instead, every attempt to Type of Knowledge Source of information Type of Self-Report often altered representation of the “The emotional experience can neither articipants to recall an unfamiliar Experiential Online emotion, e.g. Episodic be stored nor retrieved”d 20 hours before. Recalled stories Knowledge Experience Samplingnal one in missing details, alteringance is reconstructedin applying it of events, or from recalled Retrospective, e.g. contextual details erpretations to the original story. Episodic Episodic memory Day Reconstruction r distorted through repeated Situation-specific Semantic Exit questionnaires bering is an act of reconstruction beliefction has received wide support. Atction lies the distinction between Identity-related memory [69]. While episodic Semantic belief Exit questionnaires a particular event from the past,ot tied to any particular event but Robinson & Clore (2002) n generalizations (i.e. beliefs) that Figure 1. Four sources of information in emotional self-repor 935). These two types of memory according to Robinson and Clore [63]. Figure adapted from [6 uch as learning new information Wednesday, June 6, 12
    • bottom line... If you want to know what the user really experiences, ask her at that exact moment!Wednesday, June 6, 12
    • Experience Sampling Method Prompts at random, or computationally estimated times, to self-report on ongoing behaviors and experiences. – Where are you? – What are you doing? – How far is your mobile phone? – How do you feel? Karapanos, E. (2012) Experience Sampling, Day Reconstruction, what’s next? Towards Technology-Assisted Reconstruction. M-ITI internal report.Wednesday, June 6, 12
    • Experience Sampling Method Prompts at random, or computationally estimated times, to self-report on ongoing behaviors and experiences. – Where are you? – What are you doing? – How far is your mobile phone? – How dovenues would the ACM a substantial number a few relevant you used still miss Guide to Computing of studies. We instead feel? method while following a user-initiated diary approach. The analysis of the remaining 49 studies is being reported Literature querying for the term “experience sampling” below. No of papers referring to without constraining to particular venues. This query returned 284 papers, published in more than fifty venues. Study length, sampling frequency, and response rate Experience Sampling The majority (80%) of the studies had a duration of several 60 days up to one month with 14 studies (34%) lasting between four and seven days (see figure 3). Only two studies had a duration of more than a month. 45 15 30 15 10 0 2001 2003 2005 2007 2009 2011 5 Figure 2. 243 papers referring to experience sampling over a Karapanos, E. (2012) Experience Sampling, Day Reconstruction, what’s next? ten-year period. Retrieval took place on August 26th, 2011. Towards Technology-Assisted0 Reconstruction. M-ITI internal1m > 1m ≤1h < 24h ≤ 3d ≤ 1w ≤ 2w ≤ report. Fourty-one papers were excluded from further processing.Wednesday, June 6, 12
    • What variables do ES studies measure? sampling method. Two of these provided no justifications Experience Sampling Method We distinguish below between self-reported measures of for their choice. Analyzing the remaining 19 papers resulted behavior and experience (see Table 1). This distinction is to a total of 11 reasons for choosing alternative methods to relevant as their reconstruction follows a different process ESM (see table 2). whereas behavioral information may be directly accessible through episodic memory while experiential information Table 2. Reasons for not selecting the Experience Sampling has to be further inferred from recalled episodic cues [63]. Method along with frequency of occurence (No of papers). Prompts at random, orES studies eliciting self-reported Table 1. Number of computationally Reason No measures of behavior, experience, or both. estimated times, to self-report on ongoing Disrupts the activity 6 behaviors and experiences. Type of measures that studies elicit No Imposes high burden to participants 3 Self-reported measures of behavior 5 Requires high effort from researchers 3 – Where areSelf-reported measures of experience you? 22 – What are you doing? of behavior & experience 18 Self-reported measures Inappropriate for eliciting rich qualitative data 3 – How far is your mobile phone? Misses rare and brief events 3 – How dovenues would thethe participant Computing with analysisactivityremainingThe studiesshould be in control of when, what and you used stillACM a substantial number method whileofbeing a user-initiated isdiary approach. feel? miss Guide to was engaged The prior to following 49 user being reported a few relevant Behavioral measures related most frequently to the of studies. We instead that (n=18) the 2 Literature querying for the term “experience sampling” (n=2) (e.g. [35]), the interrupted (e.g. [30]), its duration below. how often to report Noparticipant’s referringphysical location (n=15) (e.g.sampling frequency, and response rate of papers current to without constraining to particular venues. This query returned 284 papers, published in more than fifty venues. Study length, [17]) Experience Sampling (n=10), e.g. the number or nature ofof the studies hadsample size several and the social context The majority (80%) Limits a duration of 2 relationship of people that are in close proximity month with 14 studies (34%) lasting days up to one or 60 participate with in a conversation (e.g. [34]). Other between four and seven days (see figure 3). Only two Depends on participants’ ability to articulate 2 measures of behavior related to modestudiestransitduration of moreongoing experience of had a [25], than a month. 45 participants’ current physical engagement [18] and mode of convrersation (e.g. f2f, fixed/mobile phone etc.) [32]. 15 30 Poses privacy concerns 2 Experiential measures related to: 15 10 • Attitudes towards behaviors or events (n=15) such as Limits number of measured variables 1 0 being interrupted (e.g. [55]), disclosing information to 2001 2003 2005others (e.g. [17]), or being video recorded (e.g. relevant 2007 2009 2011 Technology limitations 1 5 [58]). Figure 2. 243 papers referring to experience sampling over a • Measures of affectE. (2012) Experience Sampling, Day Reconstruction, the most frequent reason Karapanos, and experience (n=18) such as mental ten-year period. Retrieval took place on August 26th, 2011. As expected, what’s next? for not selecting the 0 Towards [18]) and concentration [14], ≤ 3d ES 1w ≤ 2w was the interruptions that method engagement (e.g. Technology-Assisted Reconstruction. M-ITI internal1m > 1m report. the method imposes ≤1h < 24h ≤ ≤ Fourty-one papers were excluded [27], further processing.Wednesday, June 6, 12 satisfaction from mood and emotional states (e.g. [53], on the user’s activity (eg. [48], [5]). For instance, Lindley
    • Day Reconstruction Method Kahneman et al. (2004) Can a retrospective method help participants in recalling more accurately their experiences? ry attempt to Type of Knowledge Source of information Type of Self-Reportntation of thean unfamiliar Episodic Experiential Knowledge Online emotion, e.g. Experience Sampling called stories tails, altering in applying Retrospective, e.g. Episodic Episodic memory riginal story. Day Reconstruction h repeated Situation-specific Semantic Exit questionnaireseconstruction belief e support. At ion between Identity-relatedhile episodic Semantic belief Exit questionnaires om the past,lar event but Robinson & Clore (2002) beliefs) that Wednesday, June 6, 12 Figure 1. Four sources of information in emotional self-report
    • Day Reconstruction Method Kahneman et al. (2004) Can a retrospective method help participants in recalling more accurately their experiences?Wednesday, June 6, 12
    • Technology  Assisted  ReconstrucIon Can mobile sensors assist participants in reconstructing their daily experiences and whereabouts?Trajectory reminders EmoSnaps Footprint tracker iScaleWednesday, June 6, 12
    • Trajectory reminders in location-based preferences Do trajectory reminders (locations visited before and after) increase the test-retest reliability of the reconstruction process? Control condition With trajectory reminders ! !Wednesday, June 6, 12
    • Emosnaps - inferring emotion from self-face pics Can self-face pictures assist in recalling momentary emotions? If so, is it through a recognition or a reconstruction process?Wednesday, June 6, 12
    • Emosnaps - inferring emotion from self-face pics Can self-face pictures assist in recalling momentary emotions? If so, is it through a recognition or a reconstruction process?Wednesday, June 6, 12
    • Emosnaps - inferring emotion from self-face pics Can self-face pictures assist in recalling momentary emotions? If so, is it through a recognition or a reconstruction process? Experience Sampling (Ground truth) 78% of pictures could be used for inferring emotions Time-Day Photo-day Photo-week control condition Emotion reconstruction Emotion recognitionWednesday, June 6, 12
    • Emosnaps - inferring emotion from self-face pics Can self-face pictures assist in recalling momentary emotions? If so, is it through a recognition or a reconstruction process? Experience Sampling (Ground truth) 78% of pictures could be used for inferring emotions Time-Day Photo-day Photo-week control condition Emotion reconstruction Emotion recognitionWednesday, June 6, 12
    • Footprint tracker How do visual cues (i.e., Sensecam), location cues, and context cues (SMS and calls made or received) assist in reconstructing daily behaviors and experiences? 1. Sensecam 2. Location logging 3. Context logging(SMS/calls made or received)Wednesday, June 6, 12
    • Karapanos, E., Martens, J.-B., Hassenzahl, M. (2009) Reconstructing Experiences through Sketching. Arxiv preprint, arXiv:0912.5343.Wednesday, June 6, 12
    • Cross-­‐sec8onal Repeated  sampling “Longitudinal”  paradigms  in  HCI Longitudinal Retrospec8veWednesday, June 6, 12
    • Karapanos, E., Martens, J.-B., Hassenzahl, M. (2009) Reconstructing Experiences through Sketching. Arxiv preprint, arXiv:0912.5343.Wednesday, June 6, 12
    • Karapanos, E., Martens, J.-B., Hassenzahl, M. (2009) Reconstructing Experiences through Sketching. Arxiv preprint, arXiv:0912.5343.Wednesday, June 6, 12
    • Constructive Value-Account Control (no-graphing) Constructive iScale, but not the Value-Account, performed better than control condition •More experience reports •With more details (references to temporal information, discrete events) •Higher test-retest consistency of time estimation (i.e., when did an experience take place) •Higher test-retest consistency of graphed patterns (over Value- Account) 33 Karapanos, E., Martens, J.-B., Hassenzahl, M. (2009) Reconstructing Experiences through Sketching. Arxiv preprint, arXiv:0912.5343.Wednesday, June 6, 12
    • 436 Studies in Computational Intelligence 436 The series Studies in Computational Intelligence (SCI) publishes new developments Karapanos and advances in the various areas of computational intelligence – quickly and with high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, hybrid intelligent, and virtual reality systems. Of particular value to both the contributors and the Coming! readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output. Over the past decade the field of Human-Computer Interaction has evolved from the study of the usability of interactive products towards a more holistic understanding Evangelos Karapanos of how they may mediate desired human experiences. This book identifies the notion of diversity in users? experiences with interactive 1 products and proposes methods and tools for modeling this along two levels: Modeling Users Modeling Users Experiences with Interactive Systems (a) interpersonal diversity in users? responses to early conceptual designs, and (b) the dynamics of users? experiences over time. The Repertory Grid Technique is proposed as an alternative to standardized June 2012 psychometric scales for modeling interpersonal diversity in users? responses to early concepts in the design process, and new Multi-Dimensional Scaling procedures are Experiences with Interactive Systems introduced for modeling such complex quantitative data. iScale, a tool for the retrospective assessment of users? experiences over time is proposed as an alternative to longitudinal field studies, and a semi-automated technique for the analysis of the elicited experience narratives is introduced. Through Foreword: Jean-Bernard Martens these two methodological contributions, this book argues against averaging in the subjective evaluation of interactive products. It proposes the development of interactive tools that can assist designers in moving across multiple levels of Closing note: Marc Hassenzahl abstraction of empirical data, as design-relevant knowledge might be found on all these levels. Foreword by Jean-Bernard Martens and Closing Note by Marc Hassenzahl. issn 1860-949X isbn 978-3-642-30999-1 9 783642 309991 springer.com 13Wednesday, June 6, 12
    • Can we really trust 6-month old memories? • Validity? i.e. do memories reflect what we really experienced? • Reliability? i.e. in a second trial, will we recall the same experiences?Wednesday, June 6, 12
    • Memories are (sometimes) more important than experiences • Memories define how you evaluate your past and how you decide on your future • What do we measure for? • Why do people drive irresponsibly? • Why do people recommend their productsWednesday, June 6, 12