Age- and experience-related user behavior differences in the use of complicated electronic devices

Abstract

In this study, we observed the behavior of younger adults (20–29 years old) and middle-aged adults (46–59 years old) interacting with complicated electronic devices. Two recently released multi-functional multimedia devices, namely PMPs (portable multimedia players) and MP3 players were used in the observations. We examined various aspects of interaction behaviors in terms of performance, strategies, error consequences, physical operation methods, and workload. Our analysis of age-related differences included differences in background knowledge as an important independent factor. The results revealed that differences in age meaningfully affected the observed error frequency, the number of interaction steps, the rigidity of exploration, the success of physical operation methods, and subjective perception of temporal demand and performance. In contrast, trial-and-error behavior and frustration levels were influenced by background knowledge rather than age. These novel findings provide important new insights into user interaction characteristics between different age groups and may facilitate the design of age group-appropriate interfaces for complicated electronic devices.

Introduction

It is generally accepted that physical, sensory, and cognitive factors decline with age (Craik and Salthouse, 2000; Hitchcock et al., 2001; Scialfa et al., 2004), with such declines accelerating after individuals reach their mid-forties (Hawthorn, 2000). Due to this trend, older people tend to have more difficulty using PCs and/or electronics, and show poorer performance with these devices compared to younger people. Older people also took longer and made more errors in computer-based work (Czaja and Sharit, 1993; Laberge and Scialfa, 2005; Sayer, 2004), showed less speed and made more slip errors in using input devices (Chaparro et al., 1999; Smith et al., 1999), and had more usability problems in the use of cellular phones (Ziefle and Bay, 2005).

Most previous studies on age-related differences in performance, however, compared younger adults aged up to about 30 years with elderly individuals over 60 years of age. Middle-aged adults have received relatively less attention in this context, even though they are important to the workforce and are widely exposed to technology in everyday life. According to OECD Statistics, in the Republic of Korea in 2006, the proportion of middle-aged adults (45–59 years of age) was 28.5%. This proportion was greater than those of younger adults aged 20–29 years (19.8%), and elderly people over 60 years of age (19.7%). In addition, 30.2% of all jobs are filled by middle-aged adults, compared to 17.5% of jobs filled by younger adults and only 10.8% of jobs held by elderly people. Similarly, in the United States, the United Kingdom, and the European Union, middle-aged adults comprise 31.5%, 30.5%, and 30.4% of total employed adults and fill 32.3%, 31.9%, and 32.5% of jobs, respectively.

However, the physical, sensory, and cognitive abilities of middle-aged adults are generally poorer than those of younger adults (Hawthorn, 2000). Middle-aged people have less knowledge of technology compared with younger adults; so middle-aged adults may experience more difficulty in using technology than younger adults. Thus, studies of technology focusing on age-related differences between younger adults and middle-aged adults will be useful in the study of HCI. Here, we examined technology interaction behavior differences between younger adults (20–29 years of age) and middle-aged adults (46–59 years of age).

Besides of declines of abilities, the gap between younger and older people appears to be also at least partially due to older people tending to have less experience with technology. Previous studies found that differences in experience were an important factor in efficient computer interaction (Birdi et al., 1997; Sjölinder et al., 2005) and that practice by older adults resulted in age-related performance improvements in the use of personal digital assistants (PDAs) (Mayhorn et al., 2005; Sterns, 2005). In addition, computer use and/or training over multiple weeks was found to improve the negative attitudes of older people toward technology (Danowski and Sacks, 1980; Jay and Willis, 1992), and diminish their anxiety levels (Charness et al., 1992).

However, even when the experience gap is controlled, there is still a gap in technology use and comfort between younger and older people. For example, the time and number of interaction steps required to complete various information-processing-based computer tasks were significantly associated with differences in both age and computer experience (Czaja and Sharit, 1993). In addition, prior experience improved the performance of older people to some degree, but age-related differences remained, indicating that experience alone was unable to offset the age effect (Czaja and Sharit, 1997; Laberge and Scialfa, 2005).

These days, various mono-function devices have been merged into single devices offering multiple functions (Lindholm et al., 2003; Pemberton, 2001). However, this increased functionality does not always guarantee increased usability. Many users find it difficult to use multi-functional devices, and those difficulties have been connected to lost sales (Gussow, 2005; Van Grinsven, 2004). In addition, the size reduction of many devices has complicated their ease of use. In small multi-functional devices, the number of functions is higher, but the UI (user interface) objects and controls tend to be limited in number and smaller than those found on single-function devices. Therefore, a given UI object or input device (i.e. button, joystick, knob, etc.) typically controls multiple functions through different operation methods. For example, the simple “on/off” button of a newer device might be pressed for various durations to enable different functions. Frequently, several buttons must be pressed in combination to achieve the desired functionality. A previous study showed that users take more time and make more errors when a single UI object provides multiple and/or dissimilar functions (Ziefle et al., 2006).

Not unexpectedly, complicated multi-functional devices tend to be more challenging for older users compared to their younger counterparts. Visual information details and useless information (e.g., advertisements, decorated text, and animation) negatively impact task completion more often in older than younger adults (Curzon et al., 2005; Kosnik et al., 1988). Thus, older adults are more likely to have difficulties in recognizing and selecting a desired function among various information items on the small screens of multi-functional devices. Hasher and Zacks (1988) found that the inhibitory function of working memory declines with age, leading to more distraction by irrelevant information; this may suggest a possible mechanism underlying the tendency of older adults to have difficulty selecting among information items. In addition, older adults often have decreased motor skills compared to younger adults (Siedler and Stelmach, 1996), making it difficult for them to operate the small, multi-functional UIs found on many devices. Although many studies have identified age-related differences in the use of computer-related appliances and the Internet (Birdi et al., 1997; Curzon et al., 2005; Sayers, 2004; Sjölinder, 2005), few studies have focused on age effects in the use of complicated electronics such as small multi-functional devices.

The study of age- and background-related differences in user behavior can provide important new insights into the fundamental characteristics of interaction behaviors between different age groups and help researchers predict users’ interaction problems based on these variables. Since electronic devices and information systems are increasingly common not only in the workplace, but also in the home, multi-functional devices are likely to become a part of everyday life. Therefore, studies identifying age- and background knowledge-related behavior differences in the use of multi-functional devices will be of significant value in the areas of HCI.

In the present study, we examined user behavior differences when using small multi-functional devices, a PMP and an MP3 player, and analyzed the effect of age and background knowledge on the identified behavior differences between the younger adults (20–29 years old) and the older adults (46–59 years old). PMPs and MP3 players are representative of small multi-functional electronic devices frequently used in many aspects of daily life, including in the home, the workplace, and while in transit. These devices support various functions previously found in single devices (e.g., FM radio, audio player, video player), but have only a small number of UI controls because the devices are small. Moreover, the controls themselves have become more complex as devices acquire multiple operation methods. Thus, PMPs and MP3 players are suitable experimental devices with which to explore possible age-related differences in the use of small multi-functional devices.