A Tool for Getting Cultural Differences in HCI

Abstract

The main objective of the IIA tool is to observe and analyze the interaction behavior of users from different cultures with a computer system to determine different interaction patterns according to their cultural background. The objective is to be able to draw inferences regarding differences of the cultural imprint of users by analyzing the interaction behavior of those users with a computer system to get knowledge that is relevant for intercultural user interface design and a necessary precondition for cultural adaptive systems (Heimgärtner, 2006). E.g. the right number and arrangement of information units is very important for an application whose display is very small and at the same time the mental workload of the user has to be as low as possible (e.g. driver navigation systems). 2. Designing a Tool for the Analysis of Cultural Differences in HCI (IIA Tool) Research of literature showed that there are no adequate methods for determining cross-cultural differences in interaction aspects of human machine interaction (HMI) and none for driver navigation systems. All the existing tools provide some functionality for (remote) usability tests and interaction behavior measurement. To motivate the user to interact with the computer and to verify the postulated hypotheses, adequate task scenarios have been developed and implemented into the IIA tool. The preparation of the collected data takes place mostly automatically by the IIA data collection tool, which saves much time, costs, and effort. Implemented variables from the UMTM in the IIA tool (the test tasks will be explained below in detail) As mentioned above, the IIA tool allows the measurement of numerical values like information speed, information density, and interaction speed in relation to the user. E.g., the hypothesis "there is a high correlation of high information density to relationship-oriented cultures such as China" should be confirmable by adjusting more points of interest (POI) by Chinese users compared to German users. So, the use case "map display" was simulated by the map display test task to measure the number of pieces of information on the map display regarding information density (e.g. restaurants, streets, POI, etc.) (cf. figure 1). Disturbing the work of the user by the virtual agent "Merlin" The interaction speed test task is very abstract and is not related to DNS. · Sequence of clicking off the dots. Abstract test task "interaction speed" In an additional test task, the user has the possibility to specify his requirements for widget position directly visually by designing the layout of the GUI e.g. by changing the widget position within the user requirement design (URD) test task. Figure 6 shows a part of a course of interaction of a user with the system during the test session represented by some parameters like mouse moves or mouse clicks as well as keyboard presses (at y-axis) displayed over time (at x-axis). 4. IIA Tool Setup, Test Setting and Usage To motivate the user to interact with the computer and to test the hypotheses, test tasks have been developed and implemented into the IIA tool as described in the last section, which the user has to work on. The method to ask many users online by letting them do special test use cases and to collect the qualitative data (user preferences) emerged by this process quantitatively, has been used for Chinese (C), English (E) and German (G) speaking employees of SiemensVDO (SV) (now Continental) worldwide by an automated online data collection using the IIA data collection module to get cultural differences in HMI. Flexible controlling of the questionnaires in the IIA data collection module by using simple excel sheets Furthermore, to analyze the cultural characteristics of the users, the value survey module (VSM94) has to be filled in by the user (cf. Hofstede, 2002). Randomly selected employees from SiemensVDO (now Continental) all over the world were invited per email to do the test session using the IIA data collection module by downloading it from the corporate intranet. the average values using the IIA analysis module, neural networks, and AMOS5 revealed that some of the parameters do really depend on culture. Cultural Interaction Indicators found in both studies The significant cultural interaction indicators are the following: MG.CarSpeed (.² (2, 916) = 29.090**) means the driving speed of the simulated car in the maneuver guidance test task ((C) less than (G) and (E)). MG.MessageDistance (F (2, 916) = 16.241**) denotes the temporal distance of showing the maneuver advice messages in the maneuver guidance test task. This is explained by the fact that the Chinese language needs considerably less characters to represent words than English or German. Cultural interaction indicators with borderline values in the studies OpenTaskBeforeTest represents the number of open tasks in the working environment (i.e. running applications and icons in the Windows TM task bar) before the test session with the IIA data collection tool began. The peculations of the cultural interaction indicators regarding the different cultures are similar comparing them between first (n=102) and second (n=916) data collection. The cultural interaction indicators can be visualized applying the IIA data analysis tool to plot "cultural HCI fingerprints" (in the style of Smith & Chang, 2003) which represent the cultural differences in HCI in respect to several variables for HCI design that depend on the cultural background of the potential target group of users (cf. figure 15). 7. Discussion: Reliability of Results, IIA Tool and Design Recommendations The two main online studies in this work revealed many aspects, which supported each other: a high discrimination rate of over 80% and the high accordance between the cultural interaction indicators found by one-way ANOVA and Kruskal-Wallis-Test respectively and the discriminance analysis on the other hand supports the high reliability and criteria validity of the statistical results received in this study using the IIA tool. Surely, all those indicators can also be connected semantically to the use cases or applications. However, simply counting such events related to the session duration from users of one culture and comparing them to users of another culture is obviously sufficient to indicate differences in interaction behavior of culturally different users.