Keywords

1 Introduction

Complex information systems are becoming increasingly important and having significant impact on many areas of life. User-centered system development and usability should therefore play an important role in development of intuitive system use. It is particularly important to understand users in order to evaluate existing systems or develop new concepts. In the research on relevant perception and decision-making processes, therefore, the diverse life experiences and the wide range of life situations of user groups should also be considered. However, in the course of a generalized perception of users and user groups in the software development process, important gender aspects are often not taken into account. It can be assumed that through a gender-appropriate design process, target group-oriented and needs-based user interfaces can be developed.

Studies show that female users tend to process information in a comprehensive way and to examine all available indications and information to make a decision, whether the problem is simple or complex. Male users on the other hand, avoid comprehensive information processing on lighter tasks and access heuristics more quickly. Comprehensive information processing is more likely to be carried out by male users on complex tasks [1].

Bandura’s self-efficacy construct from the field of psychology describes the personal assessment of one’s own competencies in coping with difficulties and barriers. People with low self-efficacy tend to place less effort in challenging situations and show less persistence when encountering difficulties. Self-efficacy plays an important role in the context of the operation of a graphical user interface. Self-efficacy influences many aspects of human activity, such as endurance, use of strategy and even dealing with failure [2]. People who have low self-efficacy tend to use cognitive strategies less and to spend less effort, for example, on a difficult task than people who have high self-efficacy. Some studies show that females have lower self-efficacy than males [3]. There is also a significant correlation between self-efficacy and computer performance for females. This is not the case for males [4].

Furthermore, the process of developing user interfaces is also a very important factor. Without taking gender into account, gender-related problems can occur. An example of this is “I-Methodology,” where software developers unreflectively assume their own characteristics, preferences and competencies are representational of many user groups, or they make stereotypes about users without performing an actual requirements analysis with actual users [5].

2 Empirical Methodology

To investigate whether there are gender differences in computer performance, self-efficacy, decision-making, or processing information while using software, an empirical study has been carried out at the Ostfalia University of Applied Sciences in Germany.

Thirty participants took part in the study: 15 females and 15 males between the ages of 21 and 63 (M = 36 years; SD = 14.19 years). The study was conducted on the participants’ use of image-editing software. This software was previously unknown to the participants.

First, the participants had 5 min for free exploration of the software. After that, three tasks had to be performed. The tasks differed according to degree of difficulty. Task 3 also aimed to address the major usability problems in the software.

An eye tracker was used to investigate perception and decision-making processes. In addition, the method of “Thinking Aloud” was applied [6].

Here, the participants verbalize all thoughts and impressions regarding the use of the software, while using the software. This enabled conclusions to be made about the cognitive processes during the processing of tasks.

Self-efficacy was measured with the Allgemeine Selbstwirksamkeit Kurzskala (ASKU) questionnaire [7]. The format for the answers of the three items on the ASKU questionnaire was a five-point scale from does not apply at all (1) to applies completely (5). This questionnaire was given at the beginning of the empirical study.

After completing all three tasks, participants filled out the System Usability Scale (SUS) questionnaire, for measuring the usability of the software [8] and the NASA-Task Load Index (NASA-TLX) that rates perceived workload [9]. A semi-structured final interview was conducted at the end of the study. The interview consisted of a list of questions with the possibility to discuss individual topics and collect in-depth information from direct conversations with the participants.

3 Results

The results of the empirical study presented in this paper focus on the evaluation of objective data (task performance) and the ASKU questionnaire in order to establish a correlation between subjective assessment of self-efficacy and the actual performance of the subjects. Performance was objectively measured with appropriate performance variables. The most important aspects of human performance are the accuracy and speed of the execution of tasks [10]. An important measure of accuracy is the correct handling of tasks. The speed performance parameter could be evaluated from the processing times of task execution.

The data show that female participants had a slightly lower self-efficacy than male participants. In the user group aged 35–64, the differences in self-efficacy are more evident. Here it is also interesting to observe the individual items on the ASKU scale. The item titled “I am able to solve most problems on my own” shows little difference in the responses of male and female participants. On the other hand, the difference in self-evaluation of male and female participants is greater for two other items: “I can rely on my own abilities in difficult situations” and “I can usually solve even challenging and complex tasks well” (Table 1).

Table 1. Descriptive evaluation ASKU questionnaire. Participants aged 35–64 (Mean and standard deviation)
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Analyzing objective data also shows a difference between both gender groups. In the user group, aged 18–34, female participants were faster at completing two of three tasks (Fig. 1). In the user group aged 35–64 female participants took longer to complete all three tasks than male participants (Fig. 2).

Fig. 1.
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Mean of task completion time for user group aged 18–34

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Fig. 2.
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Mean of task completion time for user group aged 35–64

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Fig. 3.
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NASA TLX results. User group aged 18–34

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The differences in the third task were clear. A significant correlation was found between the gender of the users and the performance of the third task (r (30) = −0.391, p = 0.05). It is likely that the association with self-efficacy could play a role here.

The results of the NASA TLX questionnaires’ shows that on the dimensions of effort and frustration, female participants reported higher values than male participants (effort: male age 35–64 (M = 9.8, SD = 4,02), female age 35–64 (M = 12.28, SD = 6.52), frustration: male age 35–64 (M = 7.8, SD = 5.4), female age 35–64 (M = 12.57, SD = 6.6), whereas males aged 35–64 have higher scores in the subjective assessment of task accomplishment performance (M = 9, 6, SD = 6.84), female age 35–64 (M = 6.85, SD = 4.29) (Fig. 4). Female participants age 18–34 also rated their performance lower (M = 6,63, SD = 4,24) that male participants age 18–34 (M = 9,1, SD = 5,1) although they actually achieved better results (Fig. 3).

Fig. 4.
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NASA TLX results. User group age 35–64

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The results of the SUS questionnaire for the entire software are M = 39.83, SD = 18.14 for male participants and M = 35.83, SD = 19.33 for female, which is a poor result. Values below 60 indicate significant usability issues [8]. The assessments of male and female is very similar.

Evaluating the qualitative data from “Thinking Aloud” method it becomes clear that female participant were less persistent when a task became challenging and showed a tendency to attribute failure at a task to their own lack of capability, whereas male participants attributed this to the difficulty of the task.

Analyzing of the participants’ eye movement patterns with eye tracking system show relatively similar approach by solving easy tasks. By challenging tasks however, a different picture emerged. Male and female participants showed different approaches: male participants are more likely to use right mouse button to search for required function, however female participants often use the help function of the software or asked for help.

4 Discussion

This paper presents the results of the empirical study. The results show that there are certainly gender differences in the usage of graphical user interfaces. The self-efficacy of the participants correlates with the actual objective performance (processing times of the tasks). Female participants in the age group 35–64 assessed their skills with lower scores than participants in other user groups. Since low self-efficacy is strongly tied to poor computer performance, it is important to find ways to support this user group. One way to do this is providing software-integrated video tutorials and assistance functions. Future research could focus on developing and evaluating this type of support.

This study has shown that usability problems are especially challenging for users with lower self-efficacy. In order to prevent these problems, it is logical to include gender and diversity research in the development process of information-technical systems in order to ensure user-centered design.

These research results from Germany correspond with the research results from other studies (mostly from the United States). However, it may be important to conduct more research or a replication of the study in different countries with different cultures. There is the possibility of finding different results.