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Human-computer dialogue design considerations
Automatica,Vol.19, No. 6, pp. 767-773,1983
0005 1098/83$3.00+ 0.00 PergamonPressLtd. © 1983InternationalFederationof AutomaticControl
Printed in Great Britain.
Brief Paper
Human-Computer Dialogue Design Considerations* ROBERT
C. W l L L I G E S t
and BEVERLY
H. W I L L I G E S t
Key Words--Human factors; computer interfaces; man-machine systems; text editing; computer software; computer-aided design; dialogue design; human-computer interactions.
technical reports, journal articles, and books have offered collections of software interface guidelines in the form of user considerations for the design of computer-based dialogues. Recently, Williges and Williges (1982a) compiled over 500 such considerations dealing directly with the human-computer dialogue as it relates to software design. These considerations were compiled from 16 source documents and were organized into six major sections including data organization, dialogue modes, user input devices, feedback and error management, security and disaster prevention, and multiple users (see Table 1). The topical outline in Table 1 suggests the variety of information one must consider to develop quality human-computer dialogues and demonstrates the need to provide information retrieval aids for the dialogue author who must implement these guidelines.
three critical elements of quality human-computer dialogue design include a compilation of existing design guidelines, behavioral research to expand the general dialogue principles, and a computer-aided implementation for retrieval of the guidelines by dialogue authors. The need for empirically based dialogue guidelines relating to generic human-computer taks is stressed. The results of two studies dealing with interactive text editing are presented as examples of research directed toward specifying dialogue design principles and developing formal tools for human-computer dialogue research. One of these studies deals with a methodology for developing user models, and the second study deals with the design of HELP information. Computer-aiding in the form of rule-based systems for selecting appropriate dialogue guidelines and software tools for authoring dialogues are discussed as means for implementing these dialogue design considerations. Abstract--The
Fundamentals of human-computer dialogue design. It is quite likely that many basic human factors considerations found to be fundamental to good system design in other applications will be equally important in the design of computer-based systems. Indeed, many of the user considerations proposed for computerbased systems appear to be a restatement of basic human factors design guidelines as they specifically relate to systems involving computers. The general human factors principles that seem to be present in the specific human-computer dialogue design considerations reviewed by Williges and Williges (1982a) include compatibility, consistency, flexibility, brevity, immediate feedback, and operator workload.
Introduction WITI~ the rapid advance of interactive computer systems and the growing number of computer-unsophisticated users, it is clear that the key to optimizing the human-computer interface is the appropriate design and management of dialogue. Traditionally, human factors design of the human-computer interface has been restricted primarily to hardware and workplace layout considerations. User considerations in the design of computer hardware include such topics as keyboard layout, system response delays, and quality assessment of the visual display screens. Workplace design, on the other hand, incorporates information related to anthropometrics of the user and human factors in the working environment of the computer user such as lighting, ventilation, and equipment layout. With computer-unsophisticated users the information interface between the human and the computer may be even more important. This information interface can be characterized as a communication or dialogue problem. The purpose of this paper is to discuss various human factors considerations in human-computer dialogue design. Specifically, topics dealing with existing dialogue design guidelines, types of behavioral research needed to establish general dialogue principles and/or evaluate new human factors methods, and computer-aiding for implementing dialogue guidelines are discussed.
Compatibility. In its most general form the principle of compatibility predicts that high information transfer will occur when the amount of information recoding necessary is minimal. Translated to the human-computer system this would suggest that the system must be compatible with human perception, memory, problem solving, action, and communication (Barnard and co-workers, 1981 ). Gaines and Facey (1975) emphasized the importance of adhering to the user's organization of the information, vocabulary, and language for dealing with the information. This principle also suggests that the output of the computer should be compatible with the input required of the user and vice versa. Barnard and co-workers (1981) demonstrated a sizeable advantage for a compatible left-to-right display of command elements in terms of the order in which the items had to be entered versus the incompatible right-to-left arrangement: a 12 ~ reduction in viewing time, a 19 ~ reduction in instruction requests, a 56~o reduction in reversed argument errors, and a 37 ~ reduction in total argument errors. Compatibility implications for human-computer dialogue can involve data organization, language, format, and computer action. The organization of system output should be compatible with the organization of the data to be entered. The choice of terminology, format, and system action should be consistent with user population stereotypes. Furnas and co-workers (1982) discussed some of the issues that make language selection for human-computer dialogues a very difficult task. These include the diversity of language use and the imprecision of its application by humans. Clarity of the information presented is also important. The input required of the user should not be ambiguous, and the output of the computer should be clear and, therefore, useful. To minimize the information processing requirements of the user, information should be presented in a
Compilation of existing dialogue considerations One tool for optimizing the human-computer interface is to provide a compilation of existing guidelines for the design of the human-computer interface. In the past several years a number of
* Received 21 January 1983; revised 28 June 1983. The original version of this paper was presented at the IFAC/IFIP/IFORS/IEA Conference on Analysis, Design, and Evaluation of Man-Machine Systems which was held in BadenBaden, F.R.G. during September 1982. The published proceedings of this IFAC meeting may be ordered from Pergamon Press Ltd, Headington Hill Hall, Oxford OX3 0BW, U.K. This paper was recommended for publication in revised form by editor A. Sage. t 130 Whittemore Hall, Department of Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, U.S.A. 767
768
Brief Paper TABLE I.
CLASSIFICATION SCHEME FOR DIALOGUE CONSIDERATIONS [FROM WILLIGES AND WILLIGES, 1982B)
1. DATA ORGANIZATION 1.1 Information Coding 1.1.1 Color Codes 1.1.2 Shape Codes 1.1.3 Blinking Codes 1.1.4 Brightness Codes 1.1.5 Alphanumeric Codes 1.2 Information Density t,3 Labeling 1.4 Format 1.4.1 Prompts 1.4.2 Tabular Data 1.4.3 Graphics 1.4.4 Textual Data 1.4.5 Numeric Data 1.4.6 Alphanumeric Data 1.5 Screen Layout 2. DIALOGUE MODES 2.0 Choice of Dialogue Mode 2.1 Form- Filling 2.1.1 Default Values 2.1.2 Feedback 2.1.3 Screen Layout 2.1.4 Data Entry Procedures 2.1.5 Cursor Movement 2.2 Computer Inquiry 2.3 Menu Selection 2.3.2 Selection Codes 2.3.2.1 Letter Codes 2.3.2.2 Number Codes 2.3.2.3 Graphic Symbols 2.3.2.4 Mnemonic Codes 2.3.3 Menu Layout 2.3.4 Menu Content 2.3.5 Control Sequencing 2.4 Command Languages 2.4.1 Command Organization 2.4.2 Command Nomenclature 2.4.2.1 Abbreviations 2.4.2.2 Argument Formats 2.4.2.3 Separators/ Terminators 2.4.3 Defaults 2.4.4 Editor Orientation 2.4.5 User Control 2.4.5.1 Command Stacking 2.4.5.2 Macros 2.4.5.3 Immediate Commands
directly usable form. The needs to translate, transpose, interpret, or refer to documentation should be minimized. Movement of objects displayed on the screen should parallel the direction of the input movement of the user. Wickens and his colleagues (Sandry and Wickens, 1982) have examined the importance of stimulus-central processingresponse compatibility on the effectiveness of h u m a n computer interfaces. The results of that research suggest that auditory input and speech response are compatible with verbal tasks, whereas visual input and manual response are more compatible for spatial tasks. In summary, compatibility is an essential consideration in establishing display arrangements, selecting input and output devices, developing language for dialogue, and organizing data.
Consistency. Nickerson (1981) suggests that one of the main reasons people do not like to use computer systems is their lack of consistency and integration. Interfaces differ internally and across systems resulting in the need for users to remember several different techniques to accomplish the same thing. Nickerson points out that the problem arises from the fact that in large application programs various pieces of software were written by different individuals, and the user is forced to communicate with several pieces of software. Problem solution occurs most readily in a consistent environment. To ensure consistency, it may be necessary at times to require operations that appear to decrease system throughput, such as requesting information from the user that is already known by the system in order that similar procedures require identical user actions. Both the input required of the user and the output of the system should be consistent across the display, module, program, and the information system. The system should perform in a generally predictable manner, without
2.4.6 Command Operation 2.4.7 System Lockout 2.4.8 Special Operations 2.5 Formal Query Languages 2.6 Restricted Natural Language 3. USER INPUT DEVICES 3.0 Data Entry Procedures 3.1 Selection of Input Device 3.2 Keyboards 3.2.1 Special Function Keys 3.2.2 Cursor Control 3.3 Direct Pointing Controls 3.4 Continuous Controls 3.5 Graphics Tablets 3.6 Voice Analyzers 4. FEEDBACK E. ERROR MANAGEMENT 4.1 Feedback 4.1.1 Status Messages 4.1.2 Error Messages 4.1,3 Hard Copy Output 4.2 Error Recovery 4,2.1 Immediate User Correction 4.2.2 User Correction Procedures 4.2.3 Metering and Automatic Error Checks 4.2.4 Automatic Correction 4.2.5 Stacked Commands 4.3 User Control 4.4 Help and Documentation 4.4.1 Off-Line Documentation 4.4.2 On-Line Documentation 4.5 Computer Aids 4.5.1 Debugging Aids 4.5.2 Decision Aids 4.5.3 Graphical Input Aids 5. SECURITY S DISASTER PREVENTION 5.1 Command Cancellation 5.2 Verification of Ambiguous or Destructive Actions 5.3 Sequence Control 5.4 System Failures 6. MULTIPLE USERS 6.1 Separating Messages/Inputs 6.2 Separating Work Areas 6.3 Communications Record
exception. Reisner [1981) demonstrated the impact of inconsistencies or multiple rules on the number of user errors made with an interactive graphics system. As a measure of consistency, Reisner (1982) proposes the use of formal g r a m m a r to predict performance with various user interfaces. Nickerson (1981 j suggests the development of an intermediary program between the user and the applications software to provide consistency. This intermediary program would act as a translator to prevent inconsistencies within and across software systems and relieve the user of the need to learn the details of operation of many different systems. Waterman (1978) used a similar concept of a user agent to interpret h u m a n computer dialogue in the context of flexibility in dialogue. The fundamental goal of consistency is to permit the user to develop a conceptual model of the operation of the system.
Flexibility. Individual differences a m o n g users necessitate system flexibility to insure optimum performance of all users. In many h u m a n - m a c h i n e interfaces a decision is made as to whether the system will be designed to accommodate the extreme individuals or the average individual. As a result the system is not optimum for all users. However, capitalizing upon the capabilities of the computer, one can provide a flexible or adaptive h u m a n computer interface that equally suits the needs of most potential users. A flexible interface permits the user to tailor the interface to his or her own needs, whereas an adaptive interface accommodates the individual user automatically and may change over time. In the area of computer-assisted instruction, intelligent tutoring systems are currently under investigation. In order to provide individualized instruction, these systems must provide diagnostic or student modelling capabilities as well as tutorial
Brief Paper strategies determining when to interrupt a student's activity, what to say, and how to say it (Sleeman and Brown, 1982). A parallel situation exists in the design of adaptive human-computer interfaces. The interface should change as the user gains experience with the system or whenever the tasks to be performed change. A very simple approach to this problem would be to provide two distinct dialogues, one for experienced users and one for novice users. However, recent research by Elkerton and Williges (1983) suggests that this binary division of users is too simplistic. They propose an alternative approach to the design of the human-computer interface that allows for multiple levels of sophistication. Their methodology involves the development of expert performance profiles using a polling technique. Several levels or styles of expertise can be captured simultaneously in these empirically derived profiles. Subsequently, they can be used to provide on-line aiding to novice users. Both the input required of the user and the output provided by the system should depend upon the user's expectations of the system, past experience, and capabilities. However, providing flexibility as part of the human-computer interface is not in conflict with the principle of consistency. A properly designed flexible interface allows for various approaches to a given problem based upon the needs and expectations of the individual, but each user follows a single set of consistent rules.
Brevity. Theories of human short-term memory suggest the existence of some upper limit on information that can be recalled soon after it has been presented. The upper limit of short-term memory is generally accepted to be five to nine items (Miller, 1956). However, the number of items one can remember is also related to the complexity of the items (Simon, 1974). Whenever large amounts of information must be conveyed to the user, chunking should be used and meaningful units of information should be grouped together. Badre (1982) indicates that not only is it important to group information into meaningful chunks, but the sequence of presentation is also important. To increase the number of bits of information included in one input sequence, larger chunks, each containing more information, should be built. Message format is particularly important when speech output is used because the information is presented sequentially with no possibility for subsequent referral. For example, Simpson and Coler (1982) reported that synthesized voice warnings were understood more quickly and accurately in a background of competing human speech when the synthetic messages were short sentences rather than keywords. In computer-based dialogues both the input required of the user and the output of the system should be brief to minimize the short-term memory load on the user and the probability of input errors by the user. In addition, user input and computer output should be grouped into meaningful chunks, whenever possible.
Immediate feedback. A human-computer system should be closed-loop with information feedback to the human about the quality of user performance and the condition of the system. When the response to a user's request will be delayed, the user should be given some indication that the request is being processed. Without immediate feedback which is readily understandable, the user cannot make decisions regarding the necessity for corrective action and the form it should take. However, Maguire (1982) points out that some consideration should be given to the user's sensitivity to interruption which may suggest that feedback should be provided after the user has completed an entry rather than immediately upon computer detection of the error. Research is needed to examine this potential conflict. In computer-based systems, users should at all times be aware of where they are, what they have done, and whether or not it was successful. The user should be given every opportunity to correct errors. System feedback should provide the user assurance that the system is available and information concerning whether user queries are being processed or delayed. Feedback need not be limited to the detection of user errors or replies to user requests for information. More consideration needs to be given to providing the computer with an ability to make suggestions in the absence of a request from the user. In this way the computer serves as an intelligent advisor.
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Operator workload. An assessment of potential operator workload should be one of the first tasks in the design of human-computer dialogues. Because the probability of human failure increases in overload situations, the overall goal should be to keep the workload of the user within acceptable limits. Consideration should be given to the limited channel capacity of the human to define the operator's task and interactive dialogue requirements. If the human operator acts as a single-channel capacity processor, information arriving from various sources is queued until processing can occur. Displayed output should be organized to minimize the scanning required of the user, and only information essential to the user's needs should be displayed. In some applications slow rates of information display may be preferrable even though hardware is capable of faster display rates. Workload considerations in human-computer interactions have implications for determining the information density on display screens, providing redundant information in multiple information channels, determining the appropriate size for a command language, and allocating tasks between the human and the computer.
Research on human computer dialogue principles Another key element in improving human-computer dialogue is expansion of the data base available to the dialogue author. To provide examples of empirical research directed toward the development of general human-computer dialogue principles or formal research tools, the results of two behavioral studies are summarized. Both of these studies evaluated dialogue in an interactive text editing environment representing the fundamental tasks of locating, retrieving, and manipulating alphanumeric information. The first study deals with the development of a conceptual tool, a user model for command language selection, and the second study concerns the evaluation of procedures for the retrieval of HELP information.
User models of command language selection. Most interactive text editors have been developed with little regard for the user's model of the editing task. Consequently, the novice user is often faced with the difficult task of determining the appropriate system model of a particular text editor and then adapting his or her own conceptual model to the system's model. The difficulty, of course, is determining a formal tool that will provide a performance model of the user. Recently, Folley and Williges (1982a) developed a method for determining novice and expert user's models of interactive text editing by analyzing patterns of command language usage using statistical clustering algorithms. These models, in turn, were used to develop interactive text editors designed from the user, rather than the system, point-ofview. Model development. A set of 40 command names were used by 20 computer-naive subjects and 20 computer experts to perform 20 different edit changes representing various editing tasks at the character, word, line, and general level of interaction. All subjects were instructed on the functions of the 40 editing commands before beginning the text editing. Subjects were then given two copies of the text to be edited. A BEFORE text had 20 corrections marked with circles, arrows, or underlines. An AFTER text showed the manuscript in its corrected form. The subject's task consisted of listing the edit commands in the order in which each would be used to make the given edit change. In order to avoid biasing the results based upon the operation of a specific interactive editor, each subject completed the editing task solely with paper and pencil. No computer-based editor was used. Results. A series of hierarchical cluster analyses was conducted to determine the expert and naive users' models. First, the edit commands used to perform the 20 editing changes were clustered. Both the naive users' and the expert users' data yielded the same four general clusters of commands as shown in the top part of Fig. 1. These edit clusters included changing and inserting characters and words; deleting characters, words, and lines; moving and copying lines; and changing and inserting lines. After the four common task clusters were determined, the data for naive and expert users were separated and each of these clusters was analyzed separately to determine the unique clusters of commands for naive and expert users. The commands selected by
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Brief Paper
naive and expert users for each of the four general edit tasks are listed in the bottom portion of Fig. 1. Clearly, the list of commands selected by the two user groups differ quite markedly in terms of the specific commands selected and the total number of commands used. The expert users added more powerful commands to those included in the naive users' model, but neither groups' cluster incorporated the full set of available commands. Essentially, both groups agreed quite closely upon the four general edit tasks, but each had a different user's model for the command repertoire within each of the four general edit tasks.
Their prima~ry concern was to determine what roles the novice user and the computer should perform in the retrieval of HELP information.
Method. The nine conditions investigated included a control condition in which no HELP was available and eight experimental conditions formed by the factorial combination of initiation (user vs computer), presentation (hard-copy manual vs on-line), and selection (user vs computer) of HELP information. Computer novice subjects learned a version of an experimental line editor (Ehrich, 1981). This editor was used to edit both text and data files using either a constrained or unconstrained set of editing commands. Various measures of time, accuracy, and commands used to complete the editing subtasks were recorded automatically.
Validation. Subsequently, Folley and Williges (1982b) attempted to validate these user models in an interactive editing environment. A new group of novice and expert subjects performed the same text editing tasks on an interactive system using text editors designed around the two user models developed with the clustering procedures. The results indicated that subjects did not perform significantly better using an editor based upon the appropriate users model (P>0.05). A subsequent cluster analysis using data from the interactive text editing revealed minimal agreement with the original cluster analyses for novice users. A comparison of frequency of use of various commands in the paper-pencil model development phase and the interactive validation phase show the loci of these differences. As shown in Table 2, two areas of difference seem to be in the use of commands to find a position in a file (e.g. AREA, UP) and to ascertain the current mode of operation (e.g. TO INPUT). These differences are particularly apparent for the novice users.
Results. Two general findings are evident from the data analysis as summarized in Table 3. First, providing any type of HELP information resulted in an improvement in operator performance when compared to the no HELP configuration. In addition, the time necessary to complete a task (in seconds), the errors per task, and the number of commands used were significantly larger (P < 0.05) when no HELP was provided as compared to the various HELP configurations. The second general finding of this study is related to the relative comparisons among the various HELP configurations. Both the initiation × selection and the selection × presentation mode interactions, as summarized in Table 3, demonstrate that user control rather than computer control of HELP is more beneficial to novice users of computer systems. User control of initiation and selection of HELP resulted in significantly less (P < 0.05) average time (in seconds) per task and reduced errors during text editing. Likewise, editing was completed faster and errors were reduced when the novice users selected the HELP and used hard-copy manuals.
Implications. The paper-pencil task chosen for model development does not seem to be a good representative of interactive editing tasks. The large differences in frequency of use between paper-pencil and interactive editing shown in Table 2 certainly support this contention. Deeper aspects of interactive editing not represented in paper--pencil tasks, such as mode changes and current line location, must be included in user models. Further research in interactive environments is needed to test the usefulness of statistical procedures, such as clustering, to represent the user's model of the interactive system.
Implications. The findings of this study suggest that user-initiated and user-selected hard-copy HELP yields the best performance with novice users. In this particular HELP configuration, the subjects spent most of their time browsing the HELP information and looking at a variety of information contained in the HELP file. All of the computer-initiated and selected configurations provided quite specific information, and perusing of other information was not possible. Additionally, during on-line presentation of HELP, the editing task was erased. When the HELP information was available through hard-copy manuals, the subjects could compare HELP presented in the manuals to the editing task presented on their terminal. Split-screen
Retrieval of HELP information. A second study which was designed to provide behavioral data for dialogue design guidelines investigated methods to enhance the retrieval of information from computerized HELP displays. Cohill and Williges (1982) evaluated nine procedures for initiating, presenting, and selecting HELP on interactive computer systems.
~ .~
ha racte r s,IW o rd,s~ I
I~nse rt!Chang~e
Novice
Expert
CHANGE CHANGE INSERT INSERT SWITCH SWITCH TRANSPOSE TRANSPOSE COPY n WORDS JOIN SPLIT DOWN RIGHT
DOWN RIGHT FIND FI NOU P UP
Lines
)
.L
J,J.
(Delete)
(
MovelCopy )
Novice
Expert
Novice
CHANGE
CHANGE
DELETE
DELETE DELETETO SPLIT
DOWN n LINES
DOWN n LINES
RIGHT
FIND MARK RETURN REPEAT
PASTEAND ERASE PASTEAND ERASE STORE STORE STOREAND ERASE STOREAND ERASE INPUT EDIT DOWN DOWN FIND FIND n LINES n LINES BOTTOM FINDUP MARK RETURN UP
Expert
~nsertlChange)
Novice
Expert
DELETEn LINES DELETEn LINES INPUT INPUT EDIT EDIT CHANGE UP DOWN
UP DOWN FIND
FIG. 1. Summary of naive and expert user commands within each of the four editing clusters (from Folley and Williges, 1982a!.
Brief Paper
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TABLE2. FREQUENCYOF USEOF COMMANDSIN THE PAPER-PENCILEDITORANDTHE FULL INTERACTIVEEDITOR (FROM FOLLEY AND WlLLIGES, 1982B)
Commands ADD AREA BOTTOM CHANGE CLEAR STORE DELETE DELETE UP DELETE TO DISPLAY DISPLAY STORE DOWN FIND FINDUP INSERT JOIN MARK PASTE PASTE ERASE REPEAT RETURN SPLIT CUT CUT & ERASE SWITCH TOP TRANSPOSE UP LINE TO INPUT MODE
NOVICE SUBJECTS Paper-Pencil Interactive Editor Editor
EXPERT Paper-Pencil Editor
SUBJECTS Interactive Editor
33 17 7 65 3
36 717 13 238 3
17 0 8 146 0
16 113 15 301 12
149 1
222 1
97 1
118 0
14
4
1
0
4 0
2 10
0 0
53 16
362 51 6 75 11 8 10 27
498 4 0 75 15 1 9 28
348 40 13 9 24 12 1 36
600 46 7 52 19 5 13 26
2 8 15 15 25
7 0 43 8 26
22 11 24 17 21
49 5 34 20 19
20 4 19 28 0 44
17 13 10 229 3 460
19 4 6 20 1 45
19 29 18 151 1 80
x 2 = 34926.629**
x =
=
3869.462**
** Significant at P < 0.01. presentation of HELP may facilitate comparison in computerized HELP modes. A dialogue design consideration based on the results of this study would recommend that HELP information be constructed such that the user can browse and compare the various information files. Enhancements of these automatic browsing features still need to be developed. Innovative file searching strategies such as those evaluated by Elkerton and co-workers (1982) and Elkerton and Williges (1983) may be useful in enhancing browsing capabilities on interactive terminals for novice users.
Implementation of human-computer dialogue guidelines The two studies reviewed in this paper provide examples of the type of human-computer dialogue investigations that need to be conducted in order to generate empirically based dialogue design guidelines and new conceptual tools for describing the human-computer interface. In addition, both theoretical and empirical model building procedures are needed to build a comprehensive data base of design guidelines (see Williges and Williges, 1982b). Clearly, a fairly sizeable database of dialogue design considerations currently exists and certainly it will expand rapidly with the growing interest in human factors issues in the design of human-computer interfaces. Unfortunately, many of these dialogue guidelines are not presented within the limited context in which they were researched. Maguire (1982) suggests that the apparent contradictory nature of various recommendations may actually represent alternative strategies to be followed under certain specific circumstances. Even if a completely comprehensive and nonconflicting data base of design guidelines were available, it is critical to determine how this information can be best conveyed to the designer of dialogue software. The usual approach is merely to compile these considerations into a handbook with no retrieval assistance
beyond a table of contents and/or index. Due to the complexity and overlapping nature of any comprehensive dialogue database, the organization of these handbooks and subsequent search for relevant guidelines quickly becomes unmanageable. Consequently, various forms of computer aiding should be considered. The computer aiding may be no more than tree searching procedures for data retrieval or may incorporate sophisticated rule-based procedures to aid in decision making. A computer-aided implementation of information for the dialogue author should include four basic stages. First, the complete set of empirically derived dialogue guidelines must be available in a computerized database. Obviously, this database will need to be updated and expanded as additional research is completed. Second, an on-line acquisition procedure is needed to retrieve relevant dialogue principles for a specific application. Third, providing some form of decision aiding to select the appropriate set of dialogue guidelines for a particular application environment may be helpful. Rule-based systems can be developed to check whether the rules have been violated in a specific application, to select the appropriate set of rules, or to design the specific human-computer interface based upon the rules provided. Finally, the fourth stage of computer-aiding for the dialogue author involves providing a set of software tools for rapid and easy dialogue implementation. One approach to providing these implementation tools is the dialogue management system described by Ehrich (1982) and Johnson and Hartson (1982) which provides a multiprocess execution environment and a set of automated tools for the programmer and dialogue author to create human-factored human-computer dialogues.
Conclusions Major improvements can be made in the human-computer interface through human factors design of the dialogue. Formal tools are needed to describe the user's model of the
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Brief Paper TABLE 3. COMPARISON OF VARIOUS HELP CONFIGURATIONS EVALUATED BY COHILL AND WiLLmES (1982) Dependent Variables Average Time per Task
Conditions
Comparisons
to
Average Errors per Task
Control Condition
HELP Available (Conditions 1-8)
376.6
1.4
No Help Available (Condition 9)
679.1
5.0
Initiation X Selection Interaction User Initiated, User Selected (Conditions 1 & 2l
332.0
0,8
Other HELP Configurations (Conditions 3-8)
394.8
1.7
Selection X Presentation Mode Interaction User Selected, Hard-copy Manual (Conditions 1 ~ 5)
330.5
0.9
Other HELP Configurations (Conditions 2-4 and 6-8)
392.0
1.6
human-computer interface. In addition, principles that are based on research need to be developed and organized into a retrievable database. Computer-aided procedures to facilitate the implementation of the dialogue guidelines into the design of interactive systems should be investigated. Such an approach should improve the human-computer interface in terms of user acceptance, satisfaction, and productivity.
Acknowledgements--This research was supported by the Engineering Psychology Programs, Office of Naval Research, under contract number N000148-81-0143, work unit number NR SRO-101. The technical monitor of the contract was Dr John J. O'Hare. References Badre, A. N. (1982). Designing chunks for sequentially displayed information. In A. Badreand B. Shneiderman (Eds), Directions in Human-Computer Interaction. Ablex, Norwood, N.J. Barnard, P. J., N. V. Hammond, J. Morton, J. B. Long and I. A. Clark (1981). Consistency and compatibility in human-computer dialogue. Int. J. Man-Machine Studies, 15, 87. Cohill, A. M. and R. C. Williges (1982). Computer-augmented retrieval of HELP information for novice users. Proceedings of the Human Factors Society 26th Annual Meeting. Santa Monica, California, October 1982, pp. 79-82. Ehrich, R. W. (1981). S A M - - a configurable experimental text editor for investigating human factors issues in text processing and understanding. Virginia Polytechnic Institute and State Univerity. Technical report CSIE-81-4. Ehrich, R. W. (1982). D M S - - a system for defining and managing human-computer dialogues. Proceedings of IFAC/IFIP/IFORS/IEA Conference on Analysis, Design, and Evaluation of Man-Machine Systems. Baden-Baden, F.R.G. Elkerton, J. and R. C. Williges (1983). Development of an adaptive assistant in a file search environment. Proceedings of the Conference on Artificial Intelligence. Oakland University,
Rochester, Michigan. Elkerton, J., R. C. Williges, J. A. Pittman and J. Roach (1982). Strategies of interactive file searching. Proceedings of the Human Factors Society 26th Annual Meeting. Santa Monica, California, pp. 83-86. Folley, L. J. and R. C. Williges (1982a). User models of text editing command languages. Proceedings of Human Factors in Computer Systems Conference, Gaithersburg, Maryland, pp. 326-331. Folley, L. J. and R. C. Williges (1982b). Validation of user models for interactive editing. Proceedings of the Human Factors Society 26th Annual Meeting. Santa Monica, California, pp. 616-620. Furnas, G. W., L. M. Gomez, T. K. Landauer and S. T. Dumais (1982). Statistical semantics: How can a computer use what people name things to guess what things people mean when they name things? Proceedings of the Conference on Human Factors in Computer Systems. Gaithersburg, Marlyand, pp. 251-253. Gaines, B. R. and P. V. Facey (1975). Some experience in interactive system development and application. PrEc. IEEE, 63, 894. Johnson, D. H. and H. R. Hartson (1982). The role and tools of a dialogue author in creating human-computer interfaces. Virginia Polytechnic Institute and State University. Technical report CSIE-82-8. Maguire, M. (1982). An evaluation of published recommendations on the design of man-computer dialogues. Int. J. Man-Machine Studies, 16, 237. Miller, G. A. (1956). The magical number seven, plur or minus two: Some limits on our capacity for processing information. Psychol. Rev., 63, 81. Nickerson, R. S. (1981). Why interactive computer systems are sometimes not used by people who might benefit from them. Int. d. of Man-Machine Studies, 15, 469. Reisner, P. (1981). Formal grammar and human factors design of an interactive graphics system. IEEE Trans Software Engng, SE-7, 229.
Brief P a p e r Reisner, P. (1982). Further developments toward using formal grammar as a design tool. Proceedings of Human Factors in Computer Systems Conference. Gaithersburg, Maryland, pp. 304-308. Sandry, D. and C. D. Wickens (1982). The effect of stimuluscentral-processing-response compatibility and resource competition on pilot performance. University of Illinois, Department of Psychology. Technical report EP 1-82-1/ONR82-1. Simon, H. A. (1974). How big is a chunk? Science, 183, 482. Simpson, C. A. and C. R. Coler (1982). Human factors of voice I/O for aircraft cockpit controls and displays. Paper presented at the Workshop on Standardization for Speech I/0 Technology. National Bureau of Standards, Gaithersburg, Maryland.
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Sleeman, D. and J. S. Brown (1982). Intelligent Tutoring Systems. Academic Press, New York. Waterman, D. A. (1978). A rule-based approach to knowledge acquisition for man-machine interface programs. Int. J. Man-Machine Studies, 10, 693. Williges, B. H. and R. C. Williges (1982a). Dialogue design considerations for interactive computer systems. Virginia Polytechnic Institute and State University. Technical report CSIE-81-2 (rev.). Williges, B. H. and R. C. Williges (1982b). Structuring human/computer dialogue using speech technology.
Proceedings of Workshop on Standardization for Speech I/0 Technology, National Bureau of Standards, Gaithersburg, Maryland.
0005 1098/83$3.00+ 0.00 PergamonPressLtd. © 1983InternationalFederationof AutomaticControl
Printed in Great Britain.
Brief Paper
Human-Computer Dialogue Design Considerations* ROBERT
C. W l L L I G E S t
and BEVERLY
H. W I L L I G E S t
Key Words--Human factors; computer interfaces; man-machine systems; text editing; computer software; computer-aided design; dialogue design; human-computer interactions.
technical reports, journal articles, and books have offered collections of software interface guidelines in the form of user considerations for the design of computer-based dialogues. Recently, Williges and Williges (1982a) compiled over 500 such considerations dealing directly with the human-computer dialogue as it relates to software design. These considerations were compiled from 16 source documents and were organized into six major sections including data organization, dialogue modes, user input devices, feedback and error management, security and disaster prevention, and multiple users (see Table 1). The topical outline in Table 1 suggests the variety of information one must consider to develop quality human-computer dialogues and demonstrates the need to provide information retrieval aids for the dialogue author who must implement these guidelines.
three critical elements of quality human-computer dialogue design include a compilation of existing design guidelines, behavioral research to expand the general dialogue principles, and a computer-aided implementation for retrieval of the guidelines by dialogue authors. The need for empirically based dialogue guidelines relating to generic human-computer taks is stressed. The results of two studies dealing with interactive text editing are presented as examples of research directed toward specifying dialogue design principles and developing formal tools for human-computer dialogue research. One of these studies deals with a methodology for developing user models, and the second study deals with the design of HELP information. Computer-aiding in the form of rule-based systems for selecting appropriate dialogue guidelines and software tools for authoring dialogues are discussed as means for implementing these dialogue design considerations. Abstract--The
Fundamentals of human-computer dialogue design. It is quite likely that many basic human factors considerations found to be fundamental to good system design in other applications will be equally important in the design of computer-based systems. Indeed, many of the user considerations proposed for computerbased systems appear to be a restatement of basic human factors design guidelines as they specifically relate to systems involving computers. The general human factors principles that seem to be present in the specific human-computer dialogue design considerations reviewed by Williges and Williges (1982a) include compatibility, consistency, flexibility, brevity, immediate feedback, and operator workload.
Introduction WITI~ the rapid advance of interactive computer systems and the growing number of computer-unsophisticated users, it is clear that the key to optimizing the human-computer interface is the appropriate design and management of dialogue. Traditionally, human factors design of the human-computer interface has been restricted primarily to hardware and workplace layout considerations. User considerations in the design of computer hardware include such topics as keyboard layout, system response delays, and quality assessment of the visual display screens. Workplace design, on the other hand, incorporates information related to anthropometrics of the user and human factors in the working environment of the computer user such as lighting, ventilation, and equipment layout. With computer-unsophisticated users the information interface between the human and the computer may be even more important. This information interface can be characterized as a communication or dialogue problem. The purpose of this paper is to discuss various human factors considerations in human-computer dialogue design. Specifically, topics dealing with existing dialogue design guidelines, types of behavioral research needed to establish general dialogue principles and/or evaluate new human factors methods, and computer-aiding for implementing dialogue guidelines are discussed.
Compatibility. In its most general form the principle of compatibility predicts that high information transfer will occur when the amount of information recoding necessary is minimal. Translated to the human-computer system this would suggest that the system must be compatible with human perception, memory, problem solving, action, and communication (Barnard and co-workers, 1981 ). Gaines and Facey (1975) emphasized the importance of adhering to the user's organization of the information, vocabulary, and language for dealing with the information. This principle also suggests that the output of the computer should be compatible with the input required of the user and vice versa. Barnard and co-workers (1981) demonstrated a sizeable advantage for a compatible left-to-right display of command elements in terms of the order in which the items had to be entered versus the incompatible right-to-left arrangement: a 12 ~ reduction in viewing time, a 19 ~ reduction in instruction requests, a 56~o reduction in reversed argument errors, and a 37 ~ reduction in total argument errors. Compatibility implications for human-computer dialogue can involve data organization, language, format, and computer action. The organization of system output should be compatible with the organization of the data to be entered. The choice of terminology, format, and system action should be consistent with user population stereotypes. Furnas and co-workers (1982) discussed some of the issues that make language selection for human-computer dialogues a very difficult task. These include the diversity of language use and the imprecision of its application by humans. Clarity of the information presented is also important. The input required of the user should not be ambiguous, and the output of the computer should be clear and, therefore, useful. To minimize the information processing requirements of the user, information should be presented in a
Compilation of existing dialogue considerations One tool for optimizing the human-computer interface is to provide a compilation of existing guidelines for the design of the human-computer interface. In the past several years a number of
* Received 21 January 1983; revised 28 June 1983. The original version of this paper was presented at the IFAC/IFIP/IFORS/IEA Conference on Analysis, Design, and Evaluation of Man-Machine Systems which was held in BadenBaden, F.R.G. during September 1982. The published proceedings of this IFAC meeting may be ordered from Pergamon Press Ltd, Headington Hill Hall, Oxford OX3 0BW, U.K. This paper was recommended for publication in revised form by editor A. Sage. t 130 Whittemore Hall, Department of Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, U.S.A. 767
768
Brief Paper TABLE I.
CLASSIFICATION SCHEME FOR DIALOGUE CONSIDERATIONS [FROM WILLIGES AND WILLIGES, 1982B)
1. DATA ORGANIZATION 1.1 Information Coding 1.1.1 Color Codes 1.1.2 Shape Codes 1.1.3 Blinking Codes 1.1.4 Brightness Codes 1.1.5 Alphanumeric Codes 1.2 Information Density t,3 Labeling 1.4 Format 1.4.1 Prompts 1.4.2 Tabular Data 1.4.3 Graphics 1.4.4 Textual Data 1.4.5 Numeric Data 1.4.6 Alphanumeric Data 1.5 Screen Layout 2. DIALOGUE MODES 2.0 Choice of Dialogue Mode 2.1 Form- Filling 2.1.1 Default Values 2.1.2 Feedback 2.1.3 Screen Layout 2.1.4 Data Entry Procedures 2.1.5 Cursor Movement 2.2 Computer Inquiry 2.3 Menu Selection 2.3.2 Selection Codes 2.3.2.1 Letter Codes 2.3.2.2 Number Codes 2.3.2.3 Graphic Symbols 2.3.2.4 Mnemonic Codes 2.3.3 Menu Layout 2.3.4 Menu Content 2.3.5 Control Sequencing 2.4 Command Languages 2.4.1 Command Organization 2.4.2 Command Nomenclature 2.4.2.1 Abbreviations 2.4.2.2 Argument Formats 2.4.2.3 Separators/ Terminators 2.4.3 Defaults 2.4.4 Editor Orientation 2.4.5 User Control 2.4.5.1 Command Stacking 2.4.5.2 Macros 2.4.5.3 Immediate Commands
directly usable form. The needs to translate, transpose, interpret, or refer to documentation should be minimized. Movement of objects displayed on the screen should parallel the direction of the input movement of the user. Wickens and his colleagues (Sandry and Wickens, 1982) have examined the importance of stimulus-central processingresponse compatibility on the effectiveness of h u m a n computer interfaces. The results of that research suggest that auditory input and speech response are compatible with verbal tasks, whereas visual input and manual response are more compatible for spatial tasks. In summary, compatibility is an essential consideration in establishing display arrangements, selecting input and output devices, developing language for dialogue, and organizing data.
Consistency. Nickerson (1981) suggests that one of the main reasons people do not like to use computer systems is their lack of consistency and integration. Interfaces differ internally and across systems resulting in the need for users to remember several different techniques to accomplish the same thing. Nickerson points out that the problem arises from the fact that in large application programs various pieces of software were written by different individuals, and the user is forced to communicate with several pieces of software. Problem solution occurs most readily in a consistent environment. To ensure consistency, it may be necessary at times to require operations that appear to decrease system throughput, such as requesting information from the user that is already known by the system in order that similar procedures require identical user actions. Both the input required of the user and the output of the system should be consistent across the display, module, program, and the information system. The system should perform in a generally predictable manner, without
2.4.6 Command Operation 2.4.7 System Lockout 2.4.8 Special Operations 2.5 Formal Query Languages 2.6 Restricted Natural Language 3. USER INPUT DEVICES 3.0 Data Entry Procedures 3.1 Selection of Input Device 3.2 Keyboards 3.2.1 Special Function Keys 3.2.2 Cursor Control 3.3 Direct Pointing Controls 3.4 Continuous Controls 3.5 Graphics Tablets 3.6 Voice Analyzers 4. FEEDBACK E. ERROR MANAGEMENT 4.1 Feedback 4.1.1 Status Messages 4.1.2 Error Messages 4.1,3 Hard Copy Output 4.2 Error Recovery 4,2.1 Immediate User Correction 4.2.2 User Correction Procedures 4.2.3 Metering and Automatic Error Checks 4.2.4 Automatic Correction 4.2.5 Stacked Commands 4.3 User Control 4.4 Help and Documentation 4.4.1 Off-Line Documentation 4.4.2 On-Line Documentation 4.5 Computer Aids 4.5.1 Debugging Aids 4.5.2 Decision Aids 4.5.3 Graphical Input Aids 5. SECURITY S DISASTER PREVENTION 5.1 Command Cancellation 5.2 Verification of Ambiguous or Destructive Actions 5.3 Sequence Control 5.4 System Failures 6. MULTIPLE USERS 6.1 Separating Messages/Inputs 6.2 Separating Work Areas 6.3 Communications Record
exception. Reisner [1981) demonstrated the impact of inconsistencies or multiple rules on the number of user errors made with an interactive graphics system. As a measure of consistency, Reisner (1982) proposes the use of formal g r a m m a r to predict performance with various user interfaces. Nickerson (1981 j suggests the development of an intermediary program between the user and the applications software to provide consistency. This intermediary program would act as a translator to prevent inconsistencies within and across software systems and relieve the user of the need to learn the details of operation of many different systems. Waterman (1978) used a similar concept of a user agent to interpret h u m a n computer dialogue in the context of flexibility in dialogue. The fundamental goal of consistency is to permit the user to develop a conceptual model of the operation of the system.
Flexibility. Individual differences a m o n g users necessitate system flexibility to insure optimum performance of all users. In many h u m a n - m a c h i n e interfaces a decision is made as to whether the system will be designed to accommodate the extreme individuals or the average individual. As a result the system is not optimum for all users. However, capitalizing upon the capabilities of the computer, one can provide a flexible or adaptive h u m a n computer interface that equally suits the needs of most potential users. A flexible interface permits the user to tailor the interface to his or her own needs, whereas an adaptive interface accommodates the individual user automatically and may change over time. In the area of computer-assisted instruction, intelligent tutoring systems are currently under investigation. In order to provide individualized instruction, these systems must provide diagnostic or student modelling capabilities as well as tutorial
Brief Paper strategies determining when to interrupt a student's activity, what to say, and how to say it (Sleeman and Brown, 1982). A parallel situation exists in the design of adaptive human-computer interfaces. The interface should change as the user gains experience with the system or whenever the tasks to be performed change. A very simple approach to this problem would be to provide two distinct dialogues, one for experienced users and one for novice users. However, recent research by Elkerton and Williges (1983) suggests that this binary division of users is too simplistic. They propose an alternative approach to the design of the human-computer interface that allows for multiple levels of sophistication. Their methodology involves the development of expert performance profiles using a polling technique. Several levels or styles of expertise can be captured simultaneously in these empirically derived profiles. Subsequently, they can be used to provide on-line aiding to novice users. Both the input required of the user and the output provided by the system should depend upon the user's expectations of the system, past experience, and capabilities. However, providing flexibility as part of the human-computer interface is not in conflict with the principle of consistency. A properly designed flexible interface allows for various approaches to a given problem based upon the needs and expectations of the individual, but each user follows a single set of consistent rules.
Brevity. Theories of human short-term memory suggest the existence of some upper limit on information that can be recalled soon after it has been presented. The upper limit of short-term memory is generally accepted to be five to nine items (Miller, 1956). However, the number of items one can remember is also related to the complexity of the items (Simon, 1974). Whenever large amounts of information must be conveyed to the user, chunking should be used and meaningful units of information should be grouped together. Badre (1982) indicates that not only is it important to group information into meaningful chunks, but the sequence of presentation is also important. To increase the number of bits of information included in one input sequence, larger chunks, each containing more information, should be built. Message format is particularly important when speech output is used because the information is presented sequentially with no possibility for subsequent referral. For example, Simpson and Coler (1982) reported that synthesized voice warnings were understood more quickly and accurately in a background of competing human speech when the synthetic messages were short sentences rather than keywords. In computer-based dialogues both the input required of the user and the output of the system should be brief to minimize the short-term memory load on the user and the probability of input errors by the user. In addition, user input and computer output should be grouped into meaningful chunks, whenever possible.
Immediate feedback. A human-computer system should be closed-loop with information feedback to the human about the quality of user performance and the condition of the system. When the response to a user's request will be delayed, the user should be given some indication that the request is being processed. Without immediate feedback which is readily understandable, the user cannot make decisions regarding the necessity for corrective action and the form it should take. However, Maguire (1982) points out that some consideration should be given to the user's sensitivity to interruption which may suggest that feedback should be provided after the user has completed an entry rather than immediately upon computer detection of the error. Research is needed to examine this potential conflict. In computer-based systems, users should at all times be aware of where they are, what they have done, and whether or not it was successful. The user should be given every opportunity to correct errors. System feedback should provide the user assurance that the system is available and information concerning whether user queries are being processed or delayed. Feedback need not be limited to the detection of user errors or replies to user requests for information. More consideration needs to be given to providing the computer with an ability to make suggestions in the absence of a request from the user. In this way the computer serves as an intelligent advisor.
769
Operator workload. An assessment of potential operator workload should be one of the first tasks in the design of human-computer dialogues. Because the probability of human failure increases in overload situations, the overall goal should be to keep the workload of the user within acceptable limits. Consideration should be given to the limited channel capacity of the human to define the operator's task and interactive dialogue requirements. If the human operator acts as a single-channel capacity processor, information arriving from various sources is queued until processing can occur. Displayed output should be organized to minimize the scanning required of the user, and only information essential to the user's needs should be displayed. In some applications slow rates of information display may be preferrable even though hardware is capable of faster display rates. Workload considerations in human-computer interactions have implications for determining the information density on display screens, providing redundant information in multiple information channels, determining the appropriate size for a command language, and allocating tasks between the human and the computer.
Research on human computer dialogue principles Another key element in improving human-computer dialogue is expansion of the data base available to the dialogue author. To provide examples of empirical research directed toward the development of general human-computer dialogue principles or formal research tools, the results of two behavioral studies are summarized. Both of these studies evaluated dialogue in an interactive text editing environment representing the fundamental tasks of locating, retrieving, and manipulating alphanumeric information. The first study deals with the development of a conceptual tool, a user model for command language selection, and the second study concerns the evaluation of procedures for the retrieval of HELP information.
User models of command language selection. Most interactive text editors have been developed with little regard for the user's model of the editing task. Consequently, the novice user is often faced with the difficult task of determining the appropriate system model of a particular text editor and then adapting his or her own conceptual model to the system's model. The difficulty, of course, is determining a formal tool that will provide a performance model of the user. Recently, Folley and Williges (1982a) developed a method for determining novice and expert user's models of interactive text editing by analyzing patterns of command language usage using statistical clustering algorithms. These models, in turn, were used to develop interactive text editors designed from the user, rather than the system, point-ofview. Model development. A set of 40 command names were used by 20 computer-naive subjects and 20 computer experts to perform 20 different edit changes representing various editing tasks at the character, word, line, and general level of interaction. All subjects were instructed on the functions of the 40 editing commands before beginning the text editing. Subjects were then given two copies of the text to be edited. A BEFORE text had 20 corrections marked with circles, arrows, or underlines. An AFTER text showed the manuscript in its corrected form. The subject's task consisted of listing the edit commands in the order in which each would be used to make the given edit change. In order to avoid biasing the results based upon the operation of a specific interactive editor, each subject completed the editing task solely with paper and pencil. No computer-based editor was used. Results. A series of hierarchical cluster analyses was conducted to determine the expert and naive users' models. First, the edit commands used to perform the 20 editing changes were clustered. Both the naive users' and the expert users' data yielded the same four general clusters of commands as shown in the top part of Fig. 1. These edit clusters included changing and inserting characters and words; deleting characters, words, and lines; moving and copying lines; and changing and inserting lines. After the four common task clusters were determined, the data for naive and expert users were separated and each of these clusters was analyzed separately to determine the unique clusters of commands for naive and expert users. The commands selected by
770
Brief Paper
naive and expert users for each of the four general edit tasks are listed in the bottom portion of Fig. 1. Clearly, the list of commands selected by the two user groups differ quite markedly in terms of the specific commands selected and the total number of commands used. The expert users added more powerful commands to those included in the naive users' model, but neither groups' cluster incorporated the full set of available commands. Essentially, both groups agreed quite closely upon the four general edit tasks, but each had a different user's model for the command repertoire within each of the four general edit tasks.
Their prima~ry concern was to determine what roles the novice user and the computer should perform in the retrieval of HELP information.
Method. The nine conditions investigated included a control condition in which no HELP was available and eight experimental conditions formed by the factorial combination of initiation (user vs computer), presentation (hard-copy manual vs on-line), and selection (user vs computer) of HELP information. Computer novice subjects learned a version of an experimental line editor (Ehrich, 1981). This editor was used to edit both text and data files using either a constrained or unconstrained set of editing commands. Various measures of time, accuracy, and commands used to complete the editing subtasks were recorded automatically.
Validation. Subsequently, Folley and Williges (1982b) attempted to validate these user models in an interactive editing environment. A new group of novice and expert subjects performed the same text editing tasks on an interactive system using text editors designed around the two user models developed with the clustering procedures. The results indicated that subjects did not perform significantly better using an editor based upon the appropriate users model (P>0.05). A subsequent cluster analysis using data from the interactive text editing revealed minimal agreement with the original cluster analyses for novice users. A comparison of frequency of use of various commands in the paper-pencil model development phase and the interactive validation phase show the loci of these differences. As shown in Table 2, two areas of difference seem to be in the use of commands to find a position in a file (e.g. AREA, UP) and to ascertain the current mode of operation (e.g. TO INPUT). These differences are particularly apparent for the novice users.
Results. Two general findings are evident from the data analysis as summarized in Table 3. First, providing any type of HELP information resulted in an improvement in operator performance when compared to the no HELP configuration. In addition, the time necessary to complete a task (in seconds), the errors per task, and the number of commands used were significantly larger (P < 0.05) when no HELP was provided as compared to the various HELP configurations. The second general finding of this study is related to the relative comparisons among the various HELP configurations. Both the initiation × selection and the selection × presentation mode interactions, as summarized in Table 3, demonstrate that user control rather than computer control of HELP is more beneficial to novice users of computer systems. User control of initiation and selection of HELP resulted in significantly less (P < 0.05) average time (in seconds) per task and reduced errors during text editing. Likewise, editing was completed faster and errors were reduced when the novice users selected the HELP and used hard-copy manuals.
Implications. The paper-pencil task chosen for model development does not seem to be a good representative of interactive editing tasks. The large differences in frequency of use between paper-pencil and interactive editing shown in Table 2 certainly support this contention. Deeper aspects of interactive editing not represented in paper--pencil tasks, such as mode changes and current line location, must be included in user models. Further research in interactive environments is needed to test the usefulness of statistical procedures, such as clustering, to represent the user's model of the interactive system.
Implications. The findings of this study suggest that user-initiated and user-selected hard-copy HELP yields the best performance with novice users. In this particular HELP configuration, the subjects spent most of their time browsing the HELP information and looking at a variety of information contained in the HELP file. All of the computer-initiated and selected configurations provided quite specific information, and perusing of other information was not possible. Additionally, during on-line presentation of HELP, the editing task was erased. When the HELP information was available through hard-copy manuals, the subjects could compare HELP presented in the manuals to the editing task presented on their terminal. Split-screen
Retrieval of HELP information. A second study which was designed to provide behavioral data for dialogue design guidelines investigated methods to enhance the retrieval of information from computerized HELP displays. Cohill and Williges (1982) evaluated nine procedures for initiating, presenting, and selecting HELP on interactive computer systems.
~ .~
ha racte r s,IW o rd,s~ I
I~nse rt!Chang~e
Novice
Expert
CHANGE CHANGE INSERT INSERT SWITCH SWITCH TRANSPOSE TRANSPOSE COPY n WORDS JOIN SPLIT DOWN RIGHT
DOWN RIGHT FIND FI NOU P UP
Lines
)
.L
J,J.
(Delete)
(
MovelCopy )
Novice
Expert
Novice
CHANGE
CHANGE
DELETE
DELETE DELETETO SPLIT
DOWN n LINES
DOWN n LINES
RIGHT
FIND MARK RETURN REPEAT
PASTEAND ERASE PASTEAND ERASE STORE STORE STOREAND ERASE STOREAND ERASE INPUT EDIT DOWN DOWN FIND FIND n LINES n LINES BOTTOM FINDUP MARK RETURN UP
Expert
~nsertlChange)
Novice
Expert
DELETEn LINES DELETEn LINES INPUT INPUT EDIT EDIT CHANGE UP DOWN
UP DOWN FIND
FIG. 1. Summary of naive and expert user commands within each of the four editing clusters (from Folley and Williges, 1982a!.
Brief Paper
771
TABLE2. FREQUENCYOF USEOF COMMANDSIN THE PAPER-PENCILEDITORANDTHE FULL INTERACTIVEEDITOR (FROM FOLLEY AND WlLLIGES, 1982B)
Commands ADD AREA BOTTOM CHANGE CLEAR STORE DELETE DELETE UP DELETE TO DISPLAY DISPLAY STORE DOWN FIND FINDUP INSERT JOIN MARK PASTE PASTE ERASE REPEAT RETURN SPLIT CUT CUT & ERASE SWITCH TOP TRANSPOSE UP LINE TO INPUT MODE
NOVICE SUBJECTS Paper-Pencil Interactive Editor Editor
EXPERT Paper-Pencil Editor
SUBJECTS Interactive Editor
33 17 7 65 3
36 717 13 238 3
17 0 8 146 0
16 113 15 301 12
149 1
222 1
97 1
118 0
14
4
1
0
4 0
2 10
0 0
53 16
362 51 6 75 11 8 10 27
498 4 0 75 15 1 9 28
348 40 13 9 24 12 1 36
600 46 7 52 19 5 13 26
2 8 15 15 25
7 0 43 8 26
22 11 24 17 21
49 5 34 20 19
20 4 19 28 0 44
17 13 10 229 3 460
19 4 6 20 1 45
19 29 18 151 1 80
x 2 = 34926.629**
x =
=
3869.462**
** Significant at P < 0.01. presentation of HELP may facilitate comparison in computerized HELP modes. A dialogue design consideration based on the results of this study would recommend that HELP information be constructed such that the user can browse and compare the various information files. Enhancements of these automatic browsing features still need to be developed. Innovative file searching strategies such as those evaluated by Elkerton and co-workers (1982) and Elkerton and Williges (1983) may be useful in enhancing browsing capabilities on interactive terminals for novice users.
Implementation of human-computer dialogue guidelines The two studies reviewed in this paper provide examples of the type of human-computer dialogue investigations that need to be conducted in order to generate empirically based dialogue design guidelines and new conceptual tools for describing the human-computer interface. In addition, both theoretical and empirical model building procedures are needed to build a comprehensive data base of design guidelines (see Williges and Williges, 1982b). Clearly, a fairly sizeable database of dialogue design considerations currently exists and certainly it will expand rapidly with the growing interest in human factors issues in the design of human-computer interfaces. Unfortunately, many of these dialogue guidelines are not presented within the limited context in which they were researched. Maguire (1982) suggests that the apparent contradictory nature of various recommendations may actually represent alternative strategies to be followed under certain specific circumstances. Even if a completely comprehensive and nonconflicting data base of design guidelines were available, it is critical to determine how this information can be best conveyed to the designer of dialogue software. The usual approach is merely to compile these considerations into a handbook with no retrieval assistance
beyond a table of contents and/or index. Due to the complexity and overlapping nature of any comprehensive dialogue database, the organization of these handbooks and subsequent search for relevant guidelines quickly becomes unmanageable. Consequently, various forms of computer aiding should be considered. The computer aiding may be no more than tree searching procedures for data retrieval or may incorporate sophisticated rule-based procedures to aid in decision making. A computer-aided implementation of information for the dialogue author should include four basic stages. First, the complete set of empirically derived dialogue guidelines must be available in a computerized database. Obviously, this database will need to be updated and expanded as additional research is completed. Second, an on-line acquisition procedure is needed to retrieve relevant dialogue principles for a specific application. Third, providing some form of decision aiding to select the appropriate set of dialogue guidelines for a particular application environment may be helpful. Rule-based systems can be developed to check whether the rules have been violated in a specific application, to select the appropriate set of rules, or to design the specific human-computer interface based upon the rules provided. Finally, the fourth stage of computer-aiding for the dialogue author involves providing a set of software tools for rapid and easy dialogue implementation. One approach to providing these implementation tools is the dialogue management system described by Ehrich (1982) and Johnson and Hartson (1982) which provides a multiprocess execution environment and a set of automated tools for the programmer and dialogue author to create human-factored human-computer dialogues.
Conclusions Major improvements can be made in the human-computer interface through human factors design of the dialogue. Formal tools are needed to describe the user's model of the
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Brief Paper TABLE 3. COMPARISON OF VARIOUS HELP CONFIGURATIONS EVALUATED BY COHILL AND WiLLmES (1982) Dependent Variables Average Time per Task
Conditions
Comparisons
to
Average Errors per Task
Control Condition
HELP Available (Conditions 1-8)
376.6
1.4
No Help Available (Condition 9)
679.1
5.0
Initiation X Selection Interaction User Initiated, User Selected (Conditions 1 & 2l
332.0
0,8
Other HELP Configurations (Conditions 3-8)
394.8
1.7
Selection X Presentation Mode Interaction User Selected, Hard-copy Manual (Conditions 1 ~ 5)
330.5
0.9
Other HELP Configurations (Conditions 2-4 and 6-8)
392.0
1.6
human-computer interface. In addition, principles that are based on research need to be developed and organized into a retrievable database. Computer-aided procedures to facilitate the implementation of the dialogue guidelines into the design of interactive systems should be investigated. Such an approach should improve the human-computer interface in terms of user acceptance, satisfaction, and productivity.
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