extending a user observation protocol to account for

IADIS International Conference Interfaces and Human Computer Interaction 2011

EXTENDING A USER OBSERVATION PROTOCOL TO ACCOUNT FOR PSYCHOLOGICAL TRAITS Yuska P. C. Aguiar1,4, Maria de F.Q. Vieira1,2, Edith Galy3, Jean-Marc Mercantini4 and Charles Santoni4 1

Universidade Federal da Paraíba, UFCG/ LIHM, Depto de Engenharia Elétrica - Campina Grande, Brasil Centre for Excellence in Signal & Image Processing, Dept of Electronic & Electrical Engineering, University of Strathclyde, Scotland, UK 3 Université de Provence (Aix-Marseille I), Département de Psychologie cognitive et expérimentale UFR de Psychologie, Sciences de l'Education - Aix-en-Provence, France 4 LSIS, Université Paul Cézanne (Aix-Marseille III), Département Génie Industriel et Informatique, Marseille, France 2

ABSTRACT Typically the studies of the human error are based on the analysis of incidents and accidents reports. This was also the approach adopted by the authors when analysing human errors in the context of electrical system operation. In a study of a corpus consisting of 31 error reports, extracted over a period of ten years of reports made available by an electricity company in Brazil; it was found that in spite of a detailed account from the system and operational points of view, it was also needed information on the operator's behaviour, in order to understand the error causes. Since this information was only superficially mentioned, in order to complete the study it has been proposed to immerse the user in the situations described in the error reports and to observe and analyze the behaviour when interacting with the system under similar conditions. To achieve this goal, the observation of the user behaviour must be guided by an experimental protocol adequate to behavioural data gathering and analysis. In Psychology, the study of the human behaviour is associated to the study of emotions, through methods and tools based upon the Scherer's Component Model of Emotion. Therefore this work investigates those methods and tools and proposes to extend an existing experimental protocol originally conceived for product usability evaluation, for this purpose. This paper describes the Protocol for Experimental Observation of Interaction (PEOI), and its extended version E-PEOI with the addition of the proposed methods and tools. The protocol description encompasses the activities, tools and artefacts necessary to support the observation of the user behaviour during the interaction with electric systems, with the support of Psychology. KEYWORDS Human Behaviour Observation, Registering and measuring Emotions, Human error Studies, Electric systems operation

1. INTRODUCTION Industrial systems are said to be critical when a malfunction can lead to death or serious injury to people, loss or severe damage to equipment, environmental harm or financial loss. Therefore the analysis of accidents and incidents1 is essential for the human error study, justifying the proposal of preventive strategies such as human interface adaptation, improvement in training programs, and task adaptation. The research on human error focuses on identifying the relation between errors and the human activity that caused it. Thus, contextual factors (task, work environment) and personal factors (operator's profile, emotional state, and behaviour) must be considered when trying to understand the error causes. Accident report analysis is the path followed by many authors (Rasmussen et al. 1981; van Eekhout & Rouse 1981; Johnson & Rouse 1982). This approach was also adopted when investigating the error causes in accidents reported in the operation of electrical systems at an electricity company in Brazil. The studies were based on a corpus of 31 reports of accidents and incidents during a ten year period. The studies resulted in the proposal of: a typology for error scenarios (Mercantini et al. 2004) and, a taxonomy for incident and accident description (Scherer et al. 2010b). 1

Accident: event or situation in which there was some type of loss; Incident: event or situation in which an accident nearly happened.

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As already mentioned, the analyzed corpus presented technical information on the error but did not address the operator emotional state and behaviour while performing the task that resulted in the error, needed to understand the human error. To complete the study it has been proposed to observe the operator while performing the same task under similar conditions. Since due to safety regulations it is not possible, to accomplish this observation in a real working environment, this work proposes to observe the operator working activity immersed in scenarios which replicate situations described in the analysed corpus. To support the error studies, the observation must be guided by an experimental protocol (a set of procedures, and tools) that supports the planning, data gathering and analysis, related to the user behaviour. The Protocol for Experimental Observation of Interaction (PEOI) (Aguiar & Vieira 2009) was conceived to support product usability evaluation, and is based on recommendations available in the literature (Preece et al. 2007; Mayhew 1999; Nielsen 1994; Redish 2007). In spite of being functionally acceptable, product users may experience difficulties when using a product or system which user interface does not reflect their characteristics and needs. User satisfaction can be expressed by metrics such as easy to learn and easy to use, which are at the centre of a usability evaluation procedure. PEOI has been employed to support product evaluation in different environments such as laboratory tests, field tests and in situ, and with products of different natures. However, PEOI does not clearly address the observation and analysis of the human behaviour. So this paper presents the extension of this protocol with existing methods and tools found in Psychology that enable the observation of the operator user behaviour though the measuring of emotional states, in accordance with the Scherer’s Components Model of Emotion (CME) (Scherer 2001). The CME considers emotion as an episode of interrelated synchronized state changes of subsystems as a function of the evaluation of an external or internal stimulus event. Its components are: cognitive appraisal; physiological reactions (bodily symptoms); behaviour tendencies; motor expression (facial and vocal expression); and subjective feelings (emotional experience). The complimentary data gathered with the support of the extended protocol should allow for the understanding of the human error in the analysed corpus. This paper is organized in five sections. Section 2 presents the original experimental protocol PEOI. Section 3 introduces the approach employed in Psychology studies to understanding human emotions. Section 4 presents the set of selected tools to be employed in the behavioural data gathering and analysis. Section 5 presents the extended protocol on the basis of Psychology. Finally the conclusion Section presents some considerations and future directions for this research work.

2. PROTOCOL FOR EXPERIMENTAL OBSERVATION OF INTERACTION - PEOI The original experimental protocol is organized in six steps each of which consists of a process detailed in a set of activities. Each step is associated with one or more objectives to be achieved after execution. The completion of a step is achieved by executing a set of processes and activities. Executing activities is directly related to creating or updating artefacts. Producing artefacts registers the experiment for future reference. PEOI also defines a set of roles to be played by those involved in the experiment. A role defines the responsibilities and expected behaviour during the application of the protocol. It follows the description of PEOI’s steps: Step 1: Planning the experiment consists of characterizing the product⁄system, its context of use and its users. Step 2: Training when needed, consists on introducing the evaluation team and test participants with the product and its context of use. Step 3: Preparing and Validating the experiment: consists on structuring the experiment and developing the necessary supporting materials. Validating consists in performing a pilot experiment, with a recruited participant. Step 4: Conducting the experiment and Data gathering: implements the experiment’s plan, and obtains the data sample. Step 5: Data Tabulation and Analysis: structures and organizes the gathered data for analysis. Produces a diagnostic view for the product based on the user interaction. Step 6 - Presentation of Results: specifies the form, content and media to report the experiment and its results.

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Figure 1. Steps and Processes in PEOI

To understand the behaviour when a user performs a task it is necessary to identify precisely which variables to observe, and determine how and when they should be measured. PEOI employs a set of four methods for data gathering (observation-O, interview-I, questionnaire-Q, document analysis-DA). The data is grouped into the following categories. (I) General data is gathered through interview, and aims to clarify the experiment’s objectives. On the other hand, all four methods are employed to gather data on the task, product and context of use. (II) Pre-interaction: except for observation, all four methods are employed to gather data on the user profile (personal, professional and contextual). (III) During-Interaction: observation is used to gather data on subjective indicators. Here, all four methods, except document analysis, are employed to collect objective indicators on the user activity. In the final step, (IV) Post-interaction, all methods (except document analysis) are employed to gather data on the user satisfaction with the product⁄ system under evaluation. Table 1 presents the relationship between the data categories the data gathering methods. PEOI was employed in the evaluation of the usability of different products and systems, including the electric system simulator developed to support this study. The objectives and subjective indicators proved to be sufficient from the usability point of view however, regarding the specific interest in understanding the user behaviour it would not be appropriate. Besides the operator profile: (a) physical (manual skills, weight, height), (b) psychological (motivation, attention, temperament, cognitive functions) and (c) clinical (memory, perception, psycho-motor, mental/language functions), it is necessary to know the user emotional state, before, during and after the task performance. For this purpose, besides the methods already employed by PEOI, other methods and tools are required, which are supported in theory and practice by Psychology. Table 1. Elements of interest to observe along the interaction and methods for data collection – PEOI

I

Elements of Interest

Examples

Objective Assessment

Product release of a new version, Product adaptation,...

Task

Characteristics; work Conditions, time of day, working shift.

Product and context of use Auxiliary equipment, environment conditions, Personal II

III

User

Contextual

Working hours, group work or individual work, task rhythm,

Objective

Task duration, help accesses , incorrect actions,

Subjective

Ease of understanding and learning, ease of use,

Satisfaction During: navigation, help, documentation, product features,

Results achieved IV User

Interview All

Age, gender, marital status

User (profile) Professional Job-position, experience in the task, , training level

Indicators

Generic Methods

Tasks completed, unfinished, abandoned, performed with errors

Satisfaction After: navigation, help, documentation, product features,

All (except O)

Observation All (except DA) Observation All (except DA)

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3. PSYCHOLOGY AND THE STUDY OF EMOTIONS With the advancement and popularization of interactive technologies, the users’ emotional state in the interactive systems context has become a valuable source of information to improve the interaction mechanisms offered by the system (Tayary & Le Thanh 2009). Studying human reactions to emotional episodes allows understanding the human behaviour. In this sense, the concept of emotion, the identification of basic emotions (joy, sadness, disgust, fear, anger, and surprise - universal, innate and not reducible) and complex emotions (possible combinations of basic emotions to form complex emotional states), as well as the representation and measurement of emotions, have been areas of interest in Psychology. The work related to interaction observation in the context of dynamical systems was used as a basis for selecting the variables and related measuring methods adopted in Psychology. In dynamic systems, operator actions are combined with process evolution without operator intervention. Dynamic systems can be classified as: process control, traffic control, disaster management and resources management. Emotions have been studied in dynamic environment context, and in particular in air traffic control, was used as reference for the current study. The air traffic controllers (ATC) activities focuses on sequencing aircraft approach and maintaining the airspace ordered to avoid collisions (Wickens et al.1997). Into this context, the understanding of controllers’ performance and emotional state is a key aspect to promote safety and security in work performance. In general (Cariou et al. 2008; Collet et al. 2009) the emotional variables in the context of ATC are: alertness; tension/stress and fatigue/tiredness. The principal factors that impact on those variables are related to time (time of day, time of service, shift-work, etc.) and workload (intensity of task, number of tasks, complexity of task, concurrency of tasks, etc.), and results on the performance modification. In the electric system operation context, the analyses of the corpus of reports identified many different factors that may contribute to human errors (Scherer et al. 2010b). The results classified factors in four categories: organization, task, action and operator, with the elements distributed in groups: equipment, material, environment, programming, execution, organizational data, user data, work characteristics (labour), psychological profile, mechanisms of human dysfunction and internal human dysfunction. For the category “operator” and within the group “work characteristics” there is the state of operator with the following emotions cited in the reports: anxiety, fatigue/tiredness, confusion, distraction/carefree/indifferent, overexcited/ecstasy, discouraged, tense/stressed, alert (excess), self-confident (excess) and fearful. The emotions mentioned in the ATC's study are also present on this study. Other variable that can be of interest are irritation and satisfaction. Therefore, the emotions of interest to this study are the basic emotions and those mentioned in the electricity company reports and in the ATC's studies. According to dictionary GALC (Scherer 2005) the terms adopted and their corresponding terms (within brackets) are: joy (overexcited), sadness, disgust, fear, anger, surprise, anxiety, hope (confident), interest/enthusiasm (alertness), relaxation/serenity (distraction/carefree), tension/stress, irritation, boredom (indifferent), contentment (satisfaction). Although there is no mention in GALC to the variables: fatigue/tiredness, confused and discouraged.

4. PSYCHOLOGY TOOLS FOR MEASURING EMOTIONS In the following studies Mahlke (Mahlke & Lindgaard 2007; Mahlke et al. 2006) identified how usability and emotional reactions can determine the user's overall appraisal of the system and thus influence the future decisions and behaviour. In the work it was used CME to structure a range of relevant emotion-measuring methods. Therefore this work is taken as the basis when investigating emotions and for the adaptation of PEOI. It follows a brief description of CME and the list of emotions that can be measured with the respective tools. Cognitive appraisal is defined as a quick evaluation of a situation that can direct emotional responses (positive or negative). Demir (2009) proposes the following set of appraisal components: consistency of motives, intrinsic pleasure, expectation confirmation, standard conformance, agency, coping potential, and certainty. The tool Geneva Appraisal Questionnaire - GAQ assesses the result of an individual's appraisal in the case of a specific emotional episode. GAQ aims to measure: intrinsic pleasantness, novelty, goal/need conduciveness, coping potential and norm/self-compatibility.

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Physiological reactions: these can be expressed in: cardiovascular, electro-dermal and respiratory measures. Kreibig (2010) presents a review on the investigation of different emotions using a range of emotional induction paradigms. The review argues that the elements most often investigated are distributed in three categories: (i) cardiovascular measurements: heart rate (HR), systolic and diastolic blood pressure (SBP) and heart rate variability (HRV); (ii) respiratory measurements: respiration rate (RR); and (iii) electro-dermal measurements: skin conductance level (SCL). Motor expressions: these are classed as postural, vocal and facial expressions. Considering the extent and complexity of these data, this work currently focuses only in facial expressions. To measure emotional facial expression, it is necessary to identify the facial expressions of interest and then correlate those with the appropriated emotion (or set of emotions). The most consecrated work in this context was developed by Ekman & Friesen (1978), which resulted in the Facial Action Coding System (FACS), but its adoption requires a highly skilled professional. To simplify the process, this work adopts a system for automatic facial expression analysis in real time, the FaceReader (Uyl et al. 2005). Subjective feelings: reflects a unique experience consisting of mental and bodily feelings during a particular event. Scherer (2005) claims that no objective method for measuring the subjective experience exists. To access it one must ask the individual to report on his/ her experience ("How do you feel/ felt?"). The Self-Assessment Manikin – SAM (Lang et al 1993) is a non-verbal scale, using schematic manikins (icons) to represent different feelings. SAM investigates: valence, arousal, and dominance dimensions. Whereas the Activation-Deactivation Adjective Check List - AD-ACL (Thayer 1978) is a multidimensional tool to investigate various transitory arousal states; and considers four sub-scales to measure the relation between energetic and tense arousal. The Geneva Emotion Wheel – GEW (Scherer 2005) is a verbal selfreport instrument in which the participant is asked to indicate the emotional intensity for a single emotion (or a blend of several emotions) on 20 distinct emotion families (with five degrees of intensity). The EmotAIX (Piolat & Bannour 2009) is a dictionary which automatically identifies, categorizes and records the vocabulary of emotion from oral or written language. This vocabulary (literally and figuratively) concerns: emotions, feelings, moods, humour, personality and emotional temperament. Behaviour tendencies: This component is the least explored in the reviewed literature. The studies mention measuring this component through quantitative indicators such as: task completion and time spent on task, which were already contemplated in the original PEOI, therefore, it will not be explored. Table 2. Relation between measuring tools and observed emotions

X

X

X

X X X X

X

Joy X X X

X

X

X

X

X

Surprise

X X X X

Tension

Contentment

Irritation

Fatigue

Relaxion X

X

Anger

X

X X X X X X

Fear

X X X

X

X X X X X X

Disgust

Subjective feelings

X

X

Basic

Sadness

Cardiovascular

M otor expression

Boredom

X X X X X X

Physiological reactions Respiratory Electrodermal FaceReader SAM AD-ACL GEW EmotAix

Hope

Tools GAQ

Anxiety

CME Cognitive appraisal

Interest

Emotions Found inthe reviewd literature

X X X X X X X

X

X

X

X

X

X

X X X

Besides the listed tools, there are two others which are relevant for this study. The Objective and Cognitive Profile of User - POCUS (Scherer & Vieira 2008) structures a system user profile in categories: personal, professional, contextual, physical, psychological and clinical. And NASA-TLX (Hart & Staveland 1988) employed to measure the mental workload, employing three dimensions: behaviour (effort and performance), task (physical, mental and temporal demands), and subjective (frustration). Table 2 relates the tools with the emotions of interest for the operator behaviour analysis.

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The referred tools are suited to measuring other emotions which were not mentioned because they do not concern this study, such as: pride, feeling love, guilt and jealousy. Nonetheless, other variables can be of future interest, such as: negative and positive appraisal (GAC), and neutral (GEW/FaceReader). As for the variables: confused and discouraged, they were not considered because all the tools already focus on these variables (it is possible to include questions about these emotions in GAQ or additional items in GEW).

5. ADAPTATIONS IN PEOI In spite of extending the protocol´s application to support user behavior observation, no changes were required in its general structure, with its steps and processes remaining the same. The changes required were: extending the range of data to be gathered, adding new methods for data collection, and including new activities to be performed by the evaluation team during the experiment, with respective artifacts. Given the new aspects of interest in the pre-interaction step, POCUS is proposed when gathering data on the user profile. The extended profile is relevant to support identifying personality and temperament traits. Whereas, during the steps: interaction and post-interaction, the focus becomes data gathering on the operator´s emotional state. In these two steps the elements of interest are the following emotions: joy, sadness, disgust, fear, anger, surprise, anxiety, hope, interest/enthusiasm, relaxation/serenity, tension/stress, irritation, boredom, contentment, fatigue/tiredness, confused, discouraged, negative, positive and neutral. Concerning the methods for data gathering, four new groups are being proposed: a) physiological measurements to gather physiological reactions; b) face recognition to gather motor expressions; c) selfreport and dictionary to gather subjective feelings. Regarding the team activities during the experiment, the changes concern the measurements to be performed along the process of behaviour observation. The processes related to: experiment planning activity, executing the plan and data gathering; suffered the highest impact due to the protocol extension. In the process Preparing data gathering material, four activities were modified: (1) defining which data to gather in order to include variables related to the operator´s emotional state; (2) including tools for data gathering: cognitive appraisal (GAQ), physiological measures, motor expressions (FaceReader), subjective feelings (SAM/AD-ACL/GEW/EmotAix), user profile (POCUS) and workload (NASA-TLX); (3) specifying the tools and resources required to collect physiological reactions (HR, HRV, SBP, RR, SCL); (4) preparing the artefacts required to perform the experiment: questionnaire, forms/cards, self-report, etc. In the process Data Gathering, three activities were modified: (5) Pre-test activities: apply POCUS while measuring physiological variables. Those variable values will be used as a reference to be later confronted with the values collected during task activity; (6) Conduct the observation: measure physiological variables (HR/HRV/SBP/RR/SCL), measure motor expressions (FaceReader) and measure subjective feelings (SAM/AD-ACL); (7) Conduct post-test activities: measure cognitive appraisal (GAQ), measure subjective feelings (GEW/EmotAix), measure the workload (NASA-TLX). In Step 5, the process Analysis of data gathered reflects all the changes introduced in the previous steps. Therefore the data gathered in Step 4 will impact in the analyses process because it will require the correlation analysis between subjective and objective indicators. Not all the tools and data types included in the extended protocol must necessarily be adopted in every experiment. The choice of data depends on the specific aim of the observation, with a specific experiment only encompassing a subset of the human behaviour related variables to be observed (subset of emotions). The addition of tools to support PEOI-E application implies elaborating new artefacts related to the instantiation of questionnaires and self-reports and to the recording of facial expressions and physiological parameters. However, due to this article’s restriction on length, artefact and templates will not be detailed. Due to the specificity of the data to be collected and to analysed, it is recommended to include a psychologist in the team responsible for the protocol application.

6. CONCLUSION This paper argued for the need to understand accidents and incidents in the industrial sector from the user behaviour point of view. The usual approach to human error study, that is report analysis, usually lacks

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relevant information on the operator behaviour (emotional state) during risk situations that can lead into error. In the research context in which this work is inserted, that is accidents and incidents in the electricity industry, it is proposed to acquire this information through the observation of operators interacting with a simulated environment capable of reproducing error scenarios described in the reports. In order to collect such specific data, an experimental protocol (PEOI) has been extended (PEOI-E) with a set of activities and tools that enable to collect data on the human behaviour through the analysis of emotional state variables. The set of variables of interest was extracted from studies in two different contexts: electrical systems operation and air-traffic control. Both cases relate to critical systems and dynamic environments. The variables relevant to this study are: joy, sadness, disgust, fear, anger, surprise, anxiety, hope, interest/enthusiasm, relaxation/serenity, tension/stress, irritation, boredom, contentment, fatigue/tiredness, confused, discouraged, negative, positive and neutral. To measure the emotions a set of tools was proposed and grouped according to CME into the categories: physiological reactions (cardiovascular/respiratory/electro-dermal); motor expressions (FaceReader); subjective feelings (EmotAix/SAM/AD-ACL/GEW); cognitive appraisal (GAQ). The changes in the original protocol consisted in including new activities to be performed; corresponding artefacts required; the actors and respective roles. The extended protocol (PEOI-E) is currently being employed in the observation of operators of a system developed to support the elaboration of contingency plans for maritime accidents involving cargo ships containing polluting materials. In the context of electrical systems error studies the research will progress into performing the experiments, replicating error scenarios and gathering the data from the operator behaviour during risk situations; in order to complement the analysis of the corpus of reports. As a consequence of this study it is intended to apply the knowledge on user behaviour in the refinement of a programmed user behaviour model (Scherer et al. 2010a; Ademar Netto et al. 2009) that was conceived to support the development of more ergonomic human interfaces. This model is currently used by designers to simulate user behaviour and analyse the corresponding outcomes to the task being performed by the user. This model is associated to the Method for Conception of Ergonomic Interfaces - MCIE (Turnell 2004).

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