Assessing User Experience via Biometric Sensor Affect Detection

2018 ◽  
pp. 123-139 ◽  
Author(s):  
Irfan Kula ◽  
Russell J. Branaghan ◽  
Robert K. Atkinson ◽  
Rod D. Roscoe
Keyword(s):  
User Experience ◽  
System Performance ◽  
Technology Development ◽  
Self Report ◽  
Psychological States ◽  
Human System ◽  
Observational Measures ◽  
Product Features ◽  
Affect Detection ◽  
Detection Technologies

Traditional user experience assessments rely on self-report, human-system performance, and observational data that incompletely capture users' psychological demands, processing, or affect. Specifically, self-report measures require users to identify and articulate subjective responses to product features, yet users may not possess accurate awareness or may be unwilling or unable to express themselves. Similarly, human-system performance and observational measures require analysts to make inferences about hidden psychological states based on observed external patterns. This chapter discusses how biometric sensor-based affect detection technologies (e.g., eye tracking and EEG) may supplement traditional methods. By measuring biometric indicators of psychological states, researchers can gain potentially richer and more accurate insights into user experience. These technologies are gaining traction in educational technology development and functionality, and thus the extension of these tools for usability and user experience evaluation is highly feasible.

Assessing User Experience via Biometric Sensor Affect Detection

2019 ◽  
pp. 698-714
Author(s):  
Irfan Kula ◽  
Russell J. Branaghan ◽  
Robert K. Atkinson ◽  
Rod D. Roscoe
Keyword(s):  
User Experience ◽  
System Performance ◽  
Technology Development ◽  
Self Report ◽  
Psychological States ◽  
Human System ◽  
Observational Measures ◽  
Product Features ◽  
Affect Detection ◽  
Detection Technologies

Traditional user experience assessments rely on self-report, human-system performance, and observational data that incompletely capture users' psychological demands, processing, or affect. Specifically, self-report measures require users to identify and articulate subjective responses to product features, yet users may not possess accurate awareness or may be unwilling or unable to express themselves. Similarly, human-system performance and observational measures require analysts to make inferences about hidden psychological states based on observed external patterns. This chapter discusses how biometric sensor-based affect detection technologies (e.g., eye tracking and EEG) may supplement traditional methods. By measuring biometric indicators of psychological states, researchers can gain potentially richer and more accurate insights into user experience. These technologies are gaining traction in educational technology development and functionality, and thus the extension of these tools for usability and user experience evaluation is highly feasible.

An experimental approach to communal coping

2021 ◽  
pp. 026540752199246
Author(s):  
Melissa Zajdel ◽  
Vicki S. Helgeson
Keyword(s):  
Health Outcomes ◽  
Positive Relationship ◽  
Experimental Approach ◽  
Positive Mood ◽  
Self Report ◽  
Communal Coping ◽  
Observational Measures ◽  
Relationship Outcomes ◽  
The Individual

Communal coping has been linked to better psychological and physical health across a variety of stressful contexts. However, there has been no experimental work causally linking communal coping to relationship and health outcomes. In addition, research has emphasized the collaboration over the shared appraisal component of communal coping. The present study sought to isolate the role of appraisal by manipulating whether dyads viewed a stressor as shared or individual. Friend dyads (n = 64 dyads; 128 participants) were randomly assigned to view a stressor as either a shared or an individual problem, but both groups were allowed to work together. Across self-report and observational measures dyads reported more collaboration and support, better relationship outcomes, and more positive mood after the stressor in the shared than the individual appraisal group. This is the first laboratory evidence to establish causal links of communal coping—specifically shared appraisal—to positive relationship and health outcomes.

Sensitivity to financial rewards and impression management links to smartphone use and dependence

2021 ◽  
Vol 25 (2) ◽  
pp. 107-128
Author(s):  
Graham Pluck ◽  
◽  
Pablo Emilio Barrera Falconi ◽  
◽  
◽  
...  
Keyword(s):  
Impression Management ◽  
Technology Use ◽  
Experimental Studies ◽  
Negative Relationship ◽  
Reward Sensitivity ◽  
Self Report ◽  
Smartphone Addiction ◽  
Observational Measures ◽  
Instant Messenger ◽  
Smartphone Use

Computational modeling and brain imaging studies suggest that sensitivity to rewards and behaviorist learning principles partly explain smartphone engagement patterns and potentially smartphone dependence. Responses to a questionnaire, and observational measures of smartphone use were recorded for 121 university students. Each participant was also tested with a laboratory task of reward sensitivity and a test of verbal operant conditioning. Twenty-three percent of the sample had probable smartphone addiction. Using multivariate regression, smartphone use, particularly the number of instant messenger services employed, was shown to be significantly and independently predicted by reward sensitivity (a positive relationship), and by instrumental conditioning (a negative relationship). However, the latter association was driven by a subset of participants who developed declarative knowledge of the response-reinforcer contingency. This suggests a process of impression management driven by experimental demand characteristics, producing goal-directed instrumental behavior not habit-based learning. No other measures of smartphone use, including the self-report scale, were significantly associated with the experimental tasks. We conclude that stronger engagement with smartphones, in particular instant messenger services, may be linked to people being more sensitive to rewarding stimuli, suggestive of a motivational or learning mechanism. We propose that this mechanism could underly problem smartphone use and dependence. It also potentially explains why some aspects of smartphone use, such as habitual actions, appear to be poorly measured by technology-use questionnaires. A serendipitous secondary finding confirmed that smartphone use reflected active self-presentation. Our ‘conditioning’ task-induced this behavior in the laboratory and could be used in social-cognition experimental studies.

scholarly journals Ability of observer and self-report measures to capture shared decision-making in clinical practice in the UK: a mixed-methods study

BMJ Open ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. e029485
Author(s):  
Denitza Williams ◽  
Adrian Edwards ◽  
Fiona Wood ◽  
Amy Lloyd ◽  
Kate Brain ◽  
...  
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Patient Preferences ◽  
Early Stage ◽  
Self Report ◽  
Shared Decision ◽  
Clinical Nurse ◽  
Clinical Nurse Specialists ◽  
Observational Measures ◽  
Breast Care

ObjectivesTo examine how observer and self-report measures of shared decision-making (SDM) evaluate the decision-making activities that patients and clinicians undertake in routine consultations.DesignMulti-method study using observational and self-reported measures of SDM and qualitative analysis.SettingBreast care and predialysis teams who had already implemented SDM.ParticipantsBreast care consultants, clinical nurse specialists and patients who were making decisions about treatment for early-stage breast cancer. Predialysis clinical nurse specialists and patients who needed to make dialysis treatment decisions.MethodsConsultations were audio recorded, transcribed and thematically analysed. SDM was measured using Observer OPTION-5 and a dyadic SureScore self-reported measure.ResultsTwenty-two breast and 21 renal consultations were analysed. SureScore indicated that clinicians and patients felt SDM was occurring, but scores showed ceiling effects for most participants, making differentiation difficult. There was mismatch between SureScore and OPTION-5 score data, the latter showing that each consultation lacked at least some elements of SDM. Highest scoring items using OPTION-5 were ‘incorporating patient preferences into decisions’ for the breast team (mean 18.5, range 12.5–20, SD 2.39) and ‘eliciting patient preferences to options’ for the renal team (mean 16.15, range 10–20, SD 3.48). Thematic analysis identified that the SDM encounter is difficult to measure because decision-making is often distributed across encounters and time, with multiple people, it is contextually adapted and can involve multiple decisions.ConclusionsSelf-reported measures can broadly indicate satisfaction with SDM, but do not tell us about the quality of the interaction and are unlikely to capture the multi-staged nature of the SDM process. Observational measures provide an indication of the extent to which elements of SDM are present in the observed consultation, but cannot explain why some elements might not be present or scored lower. Findings are important when considering measuring SDM in practice.

scholarly journals Can Genetic Factors Explain the Spillover of Warmth and Negativity Across Family Relationships?

2007 ◽  
Vol 10 (2) ◽  
pp. 299-313 ◽  
Author(s):  
Jody M. Ganiban ◽  
Erica L. Spotts ◽  
Paul Lichtenstein ◽  
Gagan S. Khera ◽  
David Reiss ◽  
...  
Keyword(s):  
Marital Satisfaction ◽  
Family Relationships ◽  
Marital Quality ◽  
Genetic Factors ◽  
Self Report ◽  
Maternal Warmth ◽  
Emotional Climate ◽  
Observational Measures ◽  
Maternal Negativity ◽  
Marital Warmth

AbstractPrevious studies indicate that the emotional quality of marital relationships is mirrored in parent–child relationships. We explored the degree to which these associations are explained by genetic and environmental factors. Participants were drawn from the Twin and Offspring Study in Sweden (TOSS), and included 544 female twin pairs (258 monozygotic [MZ], 286 dizygotic [DZ]), and 311 male twin pairs (128 MZ, 183 DZ). The spouses and one adolescent child of each twin also participated in this study. The twins completed self-report measures that assessed their marital quality and their warmth and negativity towards their children. Observational ratings of marital warmth and negativity, and of maternal warmth and negativity were obtained for a subset of female twin pairs (150 MZ, 176 DZ). Selfreported marital satisfaction was associated with self-reported parental warmth and negativity for mothers (rs = .25, -.36) and fathers (rs = .25, -.44). For the observational measures, marital warmth was associated with maternal warmth (r = .42), while marital negativity was associated with maternal negativity (r = .34). On average genetic factors explained nearly half of the covariance between selfreported marital satisfaction and parenting for mothers (48%) and fathers (47%). Genetic factors explained 21% of the covariance between observed marital and maternal warmth, but did not contribute to associations between marital and maternal negativity. These findings indicate that parents' genetically influenced characteristics help shape the emotional climate of the family.

scholarly journals Comparative study of user experience on mobile pedestrian navigation between digital map interface and location-based augmented reality

2020 ◽  
Vol 10 (2) ◽  
pp. 2037
Author(s):  
Komang Candra Brata ◽  
Deron Liang
Keyword(s):  
Augmented Reality ◽  
User Experience ◽  
Technology Development ◽  
Task Completion ◽  
Navigation Systems ◽  
Digital Map ◽  
Pedestrian Navigation ◽  
Points Of Interest ◽  
Overall Performance ◽  
Hedonic Quality

Fast-paced mobile technology development has permitted augmented reality experiences to be delivered on mobile pedestrian navigation context. The fact that the more prevalent of this technology commonly will substituting the digital map visualization to present the geo-location information is still debatable. This paper comprises a report on a field study comparing about user experience when interacting with different modes of mobile electronic assistance in the context of pedestrian navigation interfaces which utilize location-based augmented reality (AR) and two-dimensional digital map to visualize the points of interest (POIs) location in the vicinity of the user. The study was conducted with two subsequent experiments in the Zhongli District, Taoyuan City, Taiwan. The study involved 10 participants aged between 22 and 28 years with different experiences in using smartphones and navigation systems. Navigation performance was measured based on a usability approach on pragmatic quality and hedonic quality like effectiveness (success rate of task completion), efficiency (task completion time) and satisfaction in real outdoor conditions. The evaluation findings have been cross-checked with the user’s personal comments. We aim at eliciting knowledge about user requirements related to mobile pedestrian interfaces and evaluating user experience from pragmatic and hedonic viewpoints. Results show that in the context of pedestrian navigation, digital map interfaces lead to significantly better navigation performance in pragmatic attributes in comparison to AR interfaces. Nevertheless, the study also reveals that location-based AR is more valued by participants in hedonic qualities and overall performance.

Logic Models as a Framework for Iterative User Research in Educational Technology

2018 ◽  
pp. 52-75
Author(s):  
Yvonne S. Kao ◽  
Bryan J. Matlen ◽  
Michelle Tiu ◽  
Linlin Li
Keyword(s):  
Educational Technology ◽  
Research Program ◽  
Technology Development ◽  
Learning Outcome ◽  
Logic Model ◽  
User Research ◽  
Specific Product ◽  
Product Features ◽  
Key Stakeholders ◽  
Tangible Product

Educational technology development is a design problem. Product developers must optimize between what educational research suggests would be most effective, technological or other software development constraints, and the practical needs of end users and key stakeholders. Creating a logic model and using it to guide a user research program can help product developers tackle this problem. A logic model is a structured description of how a specific product achieves an intended learning outcome. Developing a logic model helps product developers make explicit their assumptions about users, product features, and use cases. Then a user research program can be constructed to test each of these assumptions and provide actionable feedback for further iterations of the product. In this chapter, we present three cases that highlight how the logic model approach can guide a program of research, and how that research has led to tangible product improvements.

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