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Research Needs for Human Factors able results. Constraints and opportunities are therefore more likely than assigned priorities to dictate what research is performed. Third, there is a definite need for good human factors research in all the areas we discuss, even with the caveat that technology is changing rapidly and good research is difficult to conduct. With these qualifications in mind, we do provide at certain places in this chapter, short summaries indicating those research needs that we feel have higher priorities than others. THE COMPUTER SYSTEM Computer systems and their environments have been diagrammed and modeled in various ways. Figure 5–1 illustrates elements that are important from a human factors standpoint: the user, the task, the hardware, the software, the procedures, and the work environment. Together they cluster around what is commonly called the user-computer interface—that invisible surface that binds the various elements together. Diagramming a computer system in this way is to a large extent artificial, because the various elements cannot really be considered in isolation. As will be apparent later on, there are interactions among all of them. The figure is merely a convenient way of FIGURE 5–1 Important Elements of Computer Systems Source: Adapted from Chapanis (1982).
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Research Needs for Human Factors structuring and organizing the subtopics of this chapter, which are described briefly below and treated in detail in subsequent sections. The Users. Beginning with the users is a natural starting point for any discussion of the human factors involved in computer systems. Focusing on users implies what is sometimes referred to as user-oriented design, rather than machine-oriented design. Perhaps the most important questions about users are “Who exactly are the users?” “What are their characteristics?” and “How can user requirements be translated into design requirements?” The Task. The second element is the task or the job that the user has to do with the computer. The complexity of the job, the kinds of information the operator needs to perform the job, and the constraints under which jobs must be performed are all relevant considerations in the human factors design of computer systems. Task requirements are discussed in the section on users. The Hardware. Hardware means input devices, output display, and signaling devices, and the work station that the computer operator has to use. The Software. Software generally refers to the data bases, computer programs, and procedures available in a computer system. Procedures. Procedures, manuals, and documentation are often included under software. They are shown separately in Figure 5–1 because the problems associated with manuals and documentation are somewhat different from those associated with programming languages, commands, and menus. The Work Environment. Generally speaking, computers and computer systems are found in relatively benign work environments. Nonetheless, some features of the work environment—excessive glare, noise, and sometimes dirt and vibration—have to be considered in the design of the user-computer interface. Since standard human factors recommendations and good engineering practice are usually adequate guides for designing most work environments in which computers are located, we do not cover environmental variables in this chapter. USERS AND TASKS Computer users today are almost as varied as people in general. Although there have been a number of attempts
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Research Needs for Human Factors to categorize or classify computer users into various groups or along various dimensions, there is today no generally accepted way of doing either. Computer tasks, by contrast, can be classified under the same headings as are used in task analyses. Proceeding from the more global to the more detailed they are jobs, functions, tasks, and subtasks. According to Ramsey and Atwood (1979), most of the literature about computer tasks is at the job level. Some people think, however, that computer tasks cannot be classified in isolation, but that tasks interact with users and that the two must be treated together. Examples are: professional programmers designing systems, professionals using application programs with command languages, occasional users using application programs with menus. In short, classifying computer users and tasks is clearly in need of systematic work, and it is treated more fully in the sections that follow. We rely in our discussion on the exemplary review of the literature on human-computer interaction by Ramsey and Atwood (1979), which was supported by the Office of Naval Research. Users Attempts to classify users have followed one of several quite different approaches. The first is to categorize users into more-or-less distinct groups on the basis of their familiarity or sophistication with computers. This way of classifying users has yielded a large collection of names. Examples, in alphabetical order, are: casual users (Martin, 1973), computer professionals (Barnard et al., 1981), dedicated users (Martin, 1973), discretionary users (Bennett, 1979), experienced users (Shackel, 1981), familiar users (Ledgard et al., 1981), first-time users (A1-Awar et al., 1981), the general public (Shackel, 1981), general users (Miller and Thomas, 1977), inexperienced users (Dzida et al., 1978), naive users (Thompson, 1969), noncomputer specialists (Shackel, 1981), nonprogrammers (Martin, 1973), occasional users (Hammond et al., 1980), programmers (Martin, 1973), regular users (Dzida et al., 1978), and untrained users (Martin, 1973). Another way of categorizing users has focused more on the nature of the user’s job. This has produced such categories as: analysts (S.L.Smith, 1981), clerical workers (Stewart, 1974), managers (Eason, 1974), operators (Smith, 1981), programmers (Martin, 1973), rugged opera-
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Research Needs for Human Factors tors (Martin, 1973), service personnel (Smith, 1981), specialists (Stewart, 1974), and technical users (Ramsey and Atwood, 1979). Quite a different way of classifying users is in terms of underlying personal characteristics. Thus, Ramsey and Atwood suggest obtaining data about users’ abilities, acquired skills, general background (including formal education), sex, age, attitude measures, mechanical (perhaps also spatial) aptitudes, vocabulary test performance, recency and length of training periods, training scores, cognitive decision style, and general intelligence. Another classification of users’ characteristics would include data on the following: Sensory capacities, e.g., visual acuity Motor abilities, e.g., typing skills Anthropometric dimensions, for hardware design Intellectual capacities, e.g., general intelligence and special abilities in order to evaluate reading levels for information presented Learned cognitive skills, including familiarity with the English language Mathematical and logical skills Experience with computers and proficiency in training Personality, e.g., attitudes toward computers Shneiderman (1980), by contrast, classifies users only according to their semantic and syntactic knowledge about computers. This way of classifying users yields the simple matrix shown in Figure 5–2. The diversity of approaches that have been taken to this problem indicates that we need research to understand and identify which of many possible user characteristics are important for software design. In addition, research is needed to understand how to express and translate user characteristics into terms that can be used in systems design, i.e., into specifications for designers of system software. It is important to recognize that all users, whether they are seasoned systems programmers or less experienced users, continue to learn as newer systems are developed and/or updated. For that reason, Cuff (1980) has suggested that we need to consider the casual user of computers as well as expert or naive users. Additional dimensions of user behaviors could give us evidence of the functionality of systems, e.g., the range of tasks
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Research Needs for Human Factors FIGURE 5–2 Classification of Users According to the. Extent of Their Semantic and Syntactic Knowledge Source: Adapted from Shneiderman (1980). users can perform with a given system, how long it takes a user to learn a system or a system update, and the time it takes a user to perform a particular task or job. We need to know what kinds of errors users make when learning new systems as well as how many errors are made and how often they are made or repeated, how well users adapt to changes in system software (robustness) that are “upward compatible,”★ and how users rate subjectively the quality of the output or product and the systems that perform their set of tasks. When we look at what is currently known about the novice compared with the expert user, it appears that the former is generally engaged in problem solving and is very susceptible to task-structure variations. The expert systems programmer typically interacts with a computer as a routine cognitive skill and is somewhat immune to structural variations in the tasks performed (see Moran, ★ Upward compatible means that commands and features used in an older version of software are still available in a newer version, although the newer version may provide new commands or features that are more efficient for accomplishing the same ends.
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Research Needs for Human Factors 1981; Mayer, 1981). A simple dialog in the software that is computer-initiated and tutorial in nature is probably more appropriate for the occasional and naive user, but an abbreviated, user-initiated dialog appears to be more appropriate for the experienced user. It is clear that we need to gather more data about problem-solving strategies and preferences across different types of tasks for different levels of users. Of particular concern is that the research methods used in evaluating user characteristics for hardware design have been used in studies evaluating user characteristics for software design. It is not known if these research methods are appropriate for evaluating software use or which methods will provide the most information to designers. Moran (1981) has addressed this issue in part. Perhaps the two most pressing research needs in this area are to find some meaningful way of classifying or categorizing users and translating user characteristics into specific recommendations that can be used in the design of computer hardware, software, and documentation. Tasks Most computer and human factors specialists agree that a task taxonomy is needed and that system designers need a set of benchmark tasks to evaluate hardware/software development and changes. A task structure provides the rules of the game that determine the range of actions users can and cannot take (Moran 1981). Tasks can vary in several ways. They may (1) fulfill different functions for the user, e.g., professional, educational, or home hobby functions, (2) require different forms of language such as natural language, BASIC, COBOL, or APL, and (3) be performed on different kinds of systems. In addition, almost all system designers recognize that the user’s interface with a computer system changes as tasks or jobs change. The user interface includes any part of the computer system that the user comes in contact with physically, perceptually, or conceptually. The user’s conceptual model of the system to be used to perform a given task is part of that interface. Thus, we also need research to understand how to discover a user’s conceptual model(s) when he or she is interfacing with the computer. Models suggested by Moran (1981) involve explicit information processes that spell out step-by-step the
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Research Needs for Human Factors mental operations the user must go through to complete the task application. These models need to be based on a psychological theory of users. One example of specific models that describe individual user differences in understanding calculator languages is described by Mayer and Bayman (1981). It would be helpful if a subset of the task taxonomy or benchmark tasks could be integrated into the accounting systems of computers so that system designers could be provided with statistical data about tasks and users. These statistics on users should include information about the user type and systems used as well as errors in usage. One example of a keystroke-level model for evaluating performance is described by Card et al. (1980). Of primary need are systematic studies of the conceptual models of users when they interact with a variety of hardware and software systems to do specified sets of tasks, e.g., text editing, numerical problem solving, or querying data bases. These studies should choose successful methodologies for producing results that can be directly applied to system design, or they should include new methods for evaluating the interactions of user characteristics with task requirements. Another pressing problem is the development of a meaningful task taxonomy that includes both behavioral and cognitive elements for a set of four or five different representative tasks. COMPUTER HARDWARE Computer hardware cannot be designed in isolation because the kind of hardware available on a computer terminal determines in part the kinds of dialog and the kinds of command languages that can be implemented in the system. Ideally, decisions about important aspects of computer dialogs should precede decisions about terminal hardware. In practice, the reverse often occurs. While recognizing that these interactions exist and that they are important in design, we discuss the human factors aspects of computer hardware with only passing reference to their software implications. Input Devices Designers of interactive computer systems can select from an array of devices for inserting information into computers. Table 5–1, modified from the work of Ramsey
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Research Needs for Human Factors TABLE 5–1 Computer Input Devices With Some of Their Principal Features and References Input Device Features References Keyboard The vast majority of past research on input devices has dealt with keyboards. Reasonable and fairly detailed guidelines exist with respect to the physical properties of keys and keyboards and—to a lesser extent—their layout, logical properties, operating procedures, etc. Guidelines for alphabetic keyboards are particularly good, and those for numeric keypads are reasonable. Function keyboards are rather system-dependent; guidelines can specify their physical properties but can only suggest methods and basic principles for function selection and layout. It is not clear that chorded keyboards are viable except in highly specialized situations. Alden et al. (1972) Seibel (1972) Light pen, light gun—a wand with a light detecting tip used to determine the specific point on a display it touches. Light pens can be used effectively for cursor placement and text selection, command construction, and for interactive graphical dialogs in general, including drawing. There is evidence, however, that greater accuracy may be possible with a mouse in discrete tasks and with a trackball in drawing tasks. Mode mixing, as by alternating use of light pen and keyboard, can significantly disrupt performance, since the light pen must be picked up and replaced with each interval of use. Continuous use of a light pen, at least on commercially available Cathode ray tube (CRT) terminals with vertical display surfaces, can be quite fatiguing. There has been no known research on desirable physical and logical properties for light pens. English et al. (1967)★ Goodwin (1975)★★ Irving et al. (1976)★
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Research Needs for Human Factors Joystick—a vertical stick generally used to move a display cursor in a direction corresponding to the direction of stick movement. There are many studies of the use of joysticks for continuous tracking tasks, but few studies of their use for discrete or continuous operand selection or graphical input tasks. The studies that have been performed have found the mouse, light pen, and trackball preferable in terms of speed, accuracy, or both. Joysticks are sometimes used for windowing and zooming control in graphical displays. No research on this topic was found, although the results of tracking studies may be applicable here. Otherwise, no clear recommendations for joystick properties have emerged, even with respect to basic issues like position versus rate versus acceleration control. These issues may be fairly task-specific. Card et al. (1978)★ English et al. (1967)★ Irving et al. (1976)★ Trackball—a partially exposed ball in a fixed base rotated by the hand generally used to move a displayed cursor in a direction corresponding to the direction of movement of ball rotation. The trackball appears to be effective for both discrete and continuous operand selection and graphical input tasks, and it may yield the best performance when graphical inputs must be alternated with keyboard input. No empirical data on physical properties were found, but some such data are thought to exist in the tracking literature. Irving et al. (1976)★
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Research Needs for Human Factors Input Device Features References Mouse—a small device rolled by hand on a surface generally used to move a displayed cursor in a direction corresponding to the direction of movement of the mouse. Although the mouse is not in widespread use, there is evidence that it is an effective device for text selection. No data are known concerning its physical properties, or its use in other tasks. Card et al. (1978)★ Engelbart (1973) English et al. (1967)★ Graphical input tablet—a flat surface which detects the position and movement of a hand-held stylus generally used to generate a drawing on a display. Graphical input tablets are capable of fairly high pointing accuracy (within 0.08 cm, according to one study). They are commonly used for freehand drawing but may be inferior for discrete position input tasks. They may also involve a performance decrement due to low stimulus-response compatibility when the drawing surface is separate from the display surface. English et al. (1967)★ Myer (1968)★
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Research Needs for Human Factors Touch panel—a device which overlays the display and senses the location touched by a finger or stylus. No empirical performance data were found dealing with the touch panel. While its inherent resolution limits may preclude serious use for fine discrete position and continuous position input, it feels natural and may become a common device for more coarse positioning and selection from lists. Hlady (1969) Johnson (1977) Knee control A knee control has been used in one research study for discrete position input. It is not known to be in use otherwise and seems unlikely to see serious use. English et al. (1967)★ Thumbwheels, switches, potentiometers These have been studied primarily outside the computer systems domain and are discussed in standard human factors reference sources. They are not often used as input devices for interactive computer systems. Chapanis (1972)★ Tactile input devices Although some tactile input devices have been proposed, little human factors research has been done on them other than that concerned with prosthetics. Noll (1972) Psychophysiological input devices Electromyographic signals have provided superior performance in some control tasks to joysticks and other manual control devices. Use of heart rate, keyboard response latency, electroencephalographic input, etc. is technologically feasible, although sophisticated input is not yet achievable via these methods. There are ethical and legal problems as well as technological difficulties. Significant human factors Slack (1971) Wargo et al. (1967)★
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Research Needs for Human Factors Input Device Features References data were not found with respect to computer-related use of these techniques. Automated speech recognition The current state of this technology limits its use to relatively simple input tasks. Even in these there are problems with different speakers, noise, etc. Although speech input seems like a very desirable and natural input mode and is clearly preferred over other communication modes for interpersonal communication, it is not clear whether it will prove to be widely applicable for human-computer interaction tasks. Very little information was found that would assist the designer in recognizing tasks for which speech input is appropriate or in selecting an appropriate speech input device. Addis (1972)★★ Bezdel (1970)★ Braunstein and Anderson (1961)★ Chapanis (1975, 1981)★★ Turn (1974) Hand printing for optical character recognition (or for subsequent entry by typist) The constrained hand printing required for optical character recognition (OCR) input results in low input rates and sometimes high recognition-error rates as well. Although manual transcription of such data clearly cannot be avoided in many cases, the preponderance of evidence suggests that direct keyboard entry yields better performance than printing, with a little practice, even when users are not skilled typists. Some error and input rate data on hand printing exists, along with some information about the effect of various printing contraints on input performance. Apsey (1976)★ Devoe (1967)★ Masterson and Hirsch (1962)★ L.B.Smith (1967)★ Strub (1971)★
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Research Needs for Human Factors Mack sensing As with hand printing, this form of transcription results in lower input rates than does practiced but unskilled typing. Some error and input rate data exist. May be slightly faster than constrained hand printing. Devoe (1967)★ Kulp and Kulp (1972)★ Punched cards Keypunching performance differs significantly from ordinary typing because of differences in both the machine and the typical data to be keyed. Some reasonably good data exist on keypunch timing and error rates. Neal (1977)★ Touch-tone telephone Several studies suggest that the touch-tone telephone is a satisfactory device for occasional use as a computer terminal, even by naive computer users. It seems clear, though, that it is not a satisfactory device for prolonged interaction or for significant amounts of nonnumeric input. Miller (1974)★ Smith and Goodwin (1970) Witten and Madams (1977) ★The reference contains user performance data or relatively detailed results of controlled experimental work. ★★The reference presents survey or questionnaire data or summarizes experimental results. Source: Adapted from Ramsey and Atwood (1979).
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Research Needs for Human Factors and Atwood (1979), lists 16 different kinds of input devices, comments on some of their features, and identifies the principal references to studies of these devices. Since the situation has not changed materially since the Ramsey-Atwood report was issued, its findings are still valid. By far most of the work on computer input devices has been done on keyboards; the literature is large and varied. Seibel’s chapter in the Van Cott and Kinkade (1972) handbook is a good starting point for anyone interested in these problems. Ramsey and Atwood reference a number of studies done after Seibel’s chapter was written, and there is a fair amount of even newer work, e.g., Hirsch (1981) and Hornsby (1981). The available literature on keyboards is sufficient to answer most practical questions. This is no longer an area urgently in need of extensive research. The situation with regard to alternative input devices, such as light pens, touch panels, and hand printing, is different. Most of the work that has been done on these devices has compared two or more input devices in specific applications. There are not many studies of this kind in the literature, although Card et al. (1978) did evaluate the speed and accuracy of four devices for text selection. Research is needed that will lead to a set of recommendations about the kinds of input devices that are best suited to general classes of tasks (e.g., text input, input of numerical data, selection of commands and operands from displays, discrete positional [graphical] input, and continuous positional [graphical] input) and perhaps to general classes of work environments. A much more serious concern is that there have been practically no studies of the optimal design of input devices, except for keyboards. That is, given that a light pen is better than a keyboard for some applications, how exactly would one design the best light pen for the job? Research is clearly needed on the optimal design parameters of all input devices other than keyboards. Voice input to computers deserves special treatment because (1) it does not involve a physical mechanism that the user manipulates as such and (2) speech as a human output is distinctly different from the movements of fingers, hands, or feet that are required for the activation of most conventional computer input devices. Speech has a number of characteristics that theoretically make it an attractive candidate for computer inputs,
Representative terms from entire chapter: