Keywords

1 Introduction

Forms are the most commonly used method for data collection [1]. Various formats of interactive forms have been designed to streamline user’s interaction in order to collect data from the end user with minimal effort. In most cases, designers use wizard form pattern when a large amount of data entry is required. Wizards divides the complex task into simpler and understandable steps [2]. Users appreciate forms that indicate the clear process through the steps. Conversely, they got frustrated when they had to repeatedly got an unavoidable error in wizard form. Error becomes a pain-point for a user which leads to the negative User eXperience (UX). UX includes users emotional, cognitive, perceptions, preferences, beliefs and behaviors aspects that occur before, during, or after the use of product, system, or services. In literature, different UX assessment methods have mentioned to measures the different aspects of UX related to usability, user perception, and human emotional reaction [3,4,5]. Emotion is one of the major aspect/dimension of the UX. Therefore, understanding the user’s emotions have always been the goal of UX moderators. Emotional UX helps the UX moderators to know about the attractive elements of the product, system, or service.

Emotions are the complicated psycho-physiological processes that are related to many internal and external activities of the user. Emotional reaction can be measured by subjective measures through questionnaire and objective measure through physiological sensors (EEG, EMG, HR, EDA, Respiration rate, and others) and ocular devices (camera, Kinect, eye tracker, and webcam). Different modalities characterize particular aspects of emotions through containing related information extracted from those modalities. Integrating modalities information can improve emotion recognition performance as compared with the unimodal approach.

In order to evaluate the emotional UX on wizard form pattern (multi-step form), we proposed three hypotheses. (a) Error on the first step affects the feeling of motivation (b) Error on the second step affects the feeling of excitement (c) Error on the last step affects the feeling of frustration. To analyze our hypotheses, we employed a multimodal user emotion recognition methodology, which collects both subjective and objective data on the multi-step form. First, we analyzed the utilized information from the physiological sensor such as EEG combined with eye tracker for the cognitive state, then we collect subjective measures by self-assessment information through the questionnaire for validating the mentioned hypotheses.

2 Experimental Setup and Procedure

2.1 Subjects and Apparatus

A total number of fifteen subjects (N = 15) including Ten males and Five females participated in the experiment on a voluntary basis. All Subjects were healthy with normal vision and adequate sleep. We used Tobii Pro X2-30 screen-based eye tracker to track, collect eye tracking metrics such as Fixations and gaze data, area of Interest, heatmap, and fixation sequences. Gaze data provides pupil diameter to identify the user emotions, pupil diameter was chosen as a feature in our experiment because it is correlated with different emotional states and provides a measure of emotional response. At the same time, An EMOTIV EPOC+ 14-channel EEG was used for the assessment of the inner state of the user. EEG collects brain activity in the central nervous system. The sampling rate was 40 Hz (±2 Hz) with 40–90 cm operation distance. Furthermore, brain activity data recorded at 2048 Hz sample rate.

2.2 Design and Procedure of the Experiment

This study used a wizard form pattern (Multi Step Form) based on single subject simulation. The form consists of three small steps and an average takes five minutes to fill the form. Every participant’s filled the form randomly and completed one particular task. In order to change the subject experience, the experiment was manipulated by generating a sudden error. After completing the task, the participant was asked to report their experience by using the self-assessment (AttrakDiff) questionnaire.

2.3 Validation of Experimental Results

In order to extract quantitative values of fixation eye movement, first Area of interest (AOI) was defined on the presented stimuli as the location of the triggered error. We extracted the total duration of dwell time from our defined AOI which shows the required cognitive load by the participant to find the AOI.

To extract the real-time changes in the objective emotions of the user, Emotiv Xavier was used during the experiment with the help of EEG. The emotion that have taken into account in the experiments includes stress level, relaxation, focus level, sadness, and happiness. We grouped the participants on the basis of their errors. The participants who got an error on the first step, second step, third step, and no error in wizard form pattern (Multi Step Form) was named as G1, G2, G3, and G4 respectively. The results achieved for each group is shown in Fig. 1.

Fig. 1.
figure 1

The average emotional experience result achieved for each group.

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The experimental result shows that the stress level of G4 is very low (10.4) because of no error. The stress level of G1 was less (65.3) as compared to G2 (78.58). While G3 participants noted as high (92.3) stress level. Similarly, G4 participants seem more relax as compare to other groups. While G3 was the most tensed compare to others. The focus level of G4 was the least compare to other groups. While G3 where the most focused group. There was no error for G4 participants. Therefore, the sadness level was minimum while the G3 where the sadness due the effort they required to fill the form again. The happiness level of G4 was the most and least for G3 due to the error generation. From the Fig. 1 we can conclude that the G3 participants has worst experience with the application and G4 has the best compared to other groups.

The AttrakDiff questionnaire’s self-reporting results given by the participant is shown in Fig. 2. Graph (a) shows the comparison between G1, graph (b) represents G2 compare to G3. While graph (c) represents the evaluation result of error (G1, G2, G3) compare to no-error (G4). As we can see in Fig. 2(a), the pragmatic quality, hedonic quality and attractiveness of G1 is higher than G2. Similarly, all three qualities of G2 is greater than G3. The primary reason is the step at which error occurs and the task user needs to complete again. It is easy to refill the form at step one compare to refilling all three step like in case G3. The comparison of error vs no-error shown in Fig. 2(c) represents the user fell satisfied and happy while there is no error in the system and they complete the task smoothly.

Fig. 2.
figure 2

Group wise value of user experience dimensions.

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3 Conclusion

Wizard form pattern divides tasks into small sub tasks for user assistance. However, the errors that occur at different steps strongly impact on the user emotions which leads to the negative user experience. This study concluded that an error while submitting a form is more emotional than technical. Therefore, our study may be used as a guideline for web developers and designers to avoid error-prone forms by offering suggestions for better user experience. In future, we aim to perform same experiment with large sample size to get more informed results.