Social
and Psychological Influences on Computer User Frustration
(Newhagen book chapter)
Katie Bessiere1, Irina Ceaparu2,
Jonathan Lazar3, John Robinson1 and Ben Shneiderman2
1Department of Sociology
University of Maryland, College Park, Maryland 20742
2Department of Computer
Science, Human-Computer Interaction Laboratory,
Institute for Advanced
Computer Studies & Institute for Systems Research
University of Maryland,
College Park, Maryland 20742
3Department
of Computer and Information Sciences &
Center for Applied Information Technology
Towson University, Towson, Maryland, 21252
(kbessiere@socy.umd.edu,
irina@cs.umd.edu, jlazar@towson.edu, robinson@socy.umd.edu, ben@cs.umd.edu)
Draft: September 6, 2002
Abstract
As computer usage has proliferated, so has user
frustration. Even devoted and knowledgeable users encounter annoying
delays, incomprehensible messages, incompatible files, and indecipherable
menus. The frustration generated by these problems can be personally
disturbing and socially disruptive. Psychological and social perspectives
on frustration may clarify the relationships among variables such as
personality types, cultural factors, goal attainment, workplace anger, and
computer anxiety. These perspectives may also help designers, managers,
and users understand the range of responses to frustration, which could lead to
effective interventions such as redesign of software, improved training, better
online help, user discipline, and even resetting of national research
priorities.
Introduction
Every computer user encounters problems with technology.
Frustration is a common theme among computer users. Frustration tends to be the
result when, for example, a computer application crashes with no warning,
taking the last thirty minutes of work with it. As technology rapidly advances,
users must deal with the ensuing error messages that invariably result, as well
as the gap in knowledge that users face when a new technology or software
emerges. We believe that user frustration is a significant issue that has
consequences and implications in many areas. For instance, many policymakers
discuss the digital divide, which is the growing gap between those who have
access to computers and networks, and those who do not. But even if universal access to technology
is attained, users will still struggle with the technology. Even with
up-to-date hardware and software, sufficient training and documentation, and
tech support, users may find computers difficult to use (Kraut, Scherlis,
Mukhopadhyay, Manning, and Kiesler, 1996). This is unfortunate, since the use
of well-designed, easy to use software, along with sufficient support and
training, can make a measurable impact on the lives of people. A good example
of using technological resources to improve the economic situations and overall
lives of people is the community networking and software project developed at
MIT for the residents of Camfield Estates, a low-income housing community in
Roxbury, MA (Pinkett, 2002).
Certainly,
computers should be designed in ways that make the user experience more
pleasant for everyone, including users of various ages, cultural backgrounds,
and economic situations, which is known as universal usability (Shneiderman,
2000). But while universal usability is the end goal for technology, it is important to first examine the root
causes of user frustration, from a social psychology point-of-view. It is
possible that there are other techniques, aside from improved computer design,
that could impact or lessen user frustration.
This chapter examines the factors
that influence the experience of frustration in computer usage. This chapter has three goals: 1) to examine
the research literature on human frustration, 2) to place the frustration
research in the context of human-computer interaction, and 3) to present a new
model of user frustration with technology.
Individuals’
prior experiences, psychological characteristics, level of computer experience,
and social system can all affect how they deal with frustrations with their
computers. In addition, factors such as
the importance of the task that was interrupted, the frequency of occurrence
(both of same and different frustrations), and the amount of time or work lost
as a result of the problem, can affect the experience of frustration. The
existing psychological literature on frustration provides a foundation for the
examination of the frustration process in computer use. In addition, literature on computer
attitudes and anxiety has relevance to the topic of frustration. Examining the factors correlated with
frustration helps to elucidate the nature of the frustration experience as
regards computer use. Based on this published research, a technology
frustration model will be presented. Based on the technology frustration model,
the implications for numerous stakeholders, including users, managers, software
designers, and policymakers, will be discussed.
Frustration
A review of the psychological literature
reveals diverse definitions of frustration.
Sigmund Freud introduced frustration as a concept with external and
internal aspects and related it to goal attainment. Frustration occurs when there is an inhibiting condition that
interferes with or stops the realization of a goal. All action has a purpose or goal whether explicit or implicit,
and any interruption to the completion of an action or task can cause
frustration. For Freud, frustration
included both external barriers to goal attainment and internal obstacles blocking
satisfaction (Freud 1921). This concept of frustration
as a duality is continued in the analysis of frustration as both cause and
effect (Britt and Janus 1940). As a cause, frustration is an
external event, acting as a stimulus to an individual and eliciting an
emotional reaction. The emotional
response, in this case, is the effect, the individual is aroused by this
external cause and a response is often directed towards the environment.
Dollard et al. define frustration as “an
interference with the occurrence of an instigated goal-response at its proper
time in the behavior sequence” (Dollard, Doob et al. 1939). Because an instigated goal
response entails only that the goal be anticipated, frustration is due to the
expectation and anticipation of a goal, not the actual attainment of the goal (Berkowitz 1978). If the goal is unfulfilled,
frustration is experienced because satisfaction was not achieved and the hopes
of attaining the goal were suddenly destroyed.
The thwarting or hindrance, terms often used synonymously with
frustration, is not limited to the actual activity in progress, but relates to
what the individual is expecting (Mowrer 1938).
Frustrations, in all of these cases, are aversive
events (Ferster 1957)and have as their main defining feature the element of a barrier or
obstruction. This barrier can take the
form of an actual barrier, or an imaginary one such as the response to
anticipated punishment or injury (Mowrer 1938). A frustrating situation,
then, is defined as any “in which an obstacle – physical, social, conceptual or
environmental – prevents the satisfaction of a desire” (Barker 1938). These blocks to goal
attainment may be both internal and external (Shorkey and Crocker 1981), similar to the duality proposed by Freud. Internal blocks consist of deficiencies within the individual
such as a lack of knowledge, skill, or physical ability. External blocks could include the physical
environment, social or legal barriers such as laws or mores, or the behavior of
other people.
Factors Affecting
Level of Frustration
The level of frustration experienced by an
individual clearly can differ, depending on the circumstances surrounding the
frustrating experience, and on the individual.
One major factor in goal formation and achievement is goal commitment,
which refers to the determination to try for and persist in the achievement of
a goal (Campion and Lord 1982). Research on goal theory
indicates that goal commitment has a strong relationship to performance and is
related to two factors: the importance
of the task or outcome and the belief that the goal can be accomplished (Locke and Latham 2002). Individuals will have a high commitment to a goal when the goal is
important to them and they believe that the goal can be attained (Locke 1996). How important the goal is to
the individuals, in addition to the strength of the desire to obtain the goal (Dollard, Doob et al. 1939), will affect the level of goal-commitment as well as the strength of
the subsequent reaction to the interruption.
Self-efficacy, the belief in one’s personal capabilities, can also
affect goal commitment (Locke and Latham 1990) in that the belief about how well a task can be performed when it
involves setbacks, obstacles, or failures may affect how committed individuals
are to that goal (Bandura 1986). Judgments of efficacy are
related to the amount of effort expended, how long they persist at the task,
and resiliency in the case of failure or setback (Bandura 1986; Bandura 1997). Self-efficacy also affects
emotional states as well; how much stress or depression people experience when
in difficult situations is dependent on how well they think they can cope with
the situation (Bandura 1997). The level of frustration that
people experience, therefore, would be affected by how important the goal was
to them, as well as how confident they are in their abilities. “Because goal-directed behavior involves
valued, purposeful action, failure to attain goals may therefore result in
highly charged emotional outcomes,” (Lincecum 2000) including, we believe, frustration.
Cultural factors may also play a role in the
level of frustration experienced by individuals when coming across obstacles to
their path of action. Social Learning
Theory (Bandura 1973) states that “rather than frustration generating an aggressive drive,
aversive treatment produces a general state of emotional arousal that can
facilitate a variety of behaviors, depending on the types of responses the
person has learned for coping with stress and their relative effectiveness” (p.
53). The community and culture in which
they are raised constrains the behavior of individuals, and their reactions and
acceptable responses to frustrating situations are constrained as well. Hochschild (Hochschild 1979) and Ekman (Ekman 1982) have put forth two concepts associated with the way that emotions are
governed by society, feeling rules and display rules. Feeling rules (emotion norms) regulate what kinds of feelings are
appropriate and how intense or broad they are, as well as long they can last. Display rules (expression norms) regulate
how these internal feelings can be displayed externally in terms of emotional
behaviors. According to symbolic
interactionist theory, emotions are caused by the arousal of individuals due to
environmental events combined with specific sociocultural factors (Schachter and Singer 1962). Mowrer (1938) suggests that
human frustration is linked to two major aspects of culture: the transmission of useful techniques and
skills across generations, and the perpetuation and enforcement of the
regulations and codes that govern social conduct. Ways of coping with frustration are therefore learned from the
society and are governed and constrained by the laws of a society. This can
contribute to the level of frustration tolerance that individuals have, which
is also affected by their prior experience and self-efficacy related to
specific tasks.
According to Freud, it is not simply the
nature of the frustrating incident that determines how people will react to the
incident. Rather, there is an interplay between the situation and the
psychological characteristics of individuals.
The level of maturity of the individual also plays a part (Barker, Dembo et al. 1965) in the reactions to frustration.
With maturity, there is an increase in the variety of responses to a
situation employed by individuals, in the control of the environment, and in
their ability to employ problem solving behavior and plan steps to obtain the
goal. It would appear that learning,
which is culturally determined, is a major factor in developing socially
acceptable responses to frustration.
One final factor that may affect the force of
the frustration is the severity of the interruption and the degree of
interference with the goal attainment (Dollard 1939). All obstructions are not equally frustrating, the severity and
unexpectedness of the block will also factor into the strength of the
response. In addition, if individuals
perceive that the thwarting was justified by socially acceptable rules, as
opposed to being arbitrary, the frustration response may be minimized (Baron 1977). This may be due to the
lowering of expectations because of extra information available to the
individual. As stated above, it is the anticipation of success that affects
frustration, and not the actual achievement of the goal. Therefore, if individuals expect to be
thwarted or have a low expectation of success, frustration may be minimized.
Responses to Frustration
The responses to frustration by individuals
can be either adaptive or maladaptive (Shorkey and Crocker 1981). Adaptive responses are
constructive and are implemented to solve the problem that is blocking goal
attainment. They may include preemptive
efforts to avoid the block, or once the block is encountered problem solving
strategies to overcome or circumvent the problem. Freud lists two types of adaptive responses: transforming stress into active energy and
reapplying this energy towards the original goal, and identifying and pursuing
alternative goals. Maladaptive
responses, on the other hand, are characterized by a lack of constructive
problem solving and often make the frustrating experience worse by creating
additional problems. These maladaptive
responses may be further categorized into objective (aggression, regression,
withdrawal, fixation, resignation) and subjective (extrapunitive,
intropunitive, impunitive) responses (Britt and Janus 1940).
Aggression: Early research on aggression suggested that aggression is the
natural, unlearned reaction to frustration (Mowrer 1938; Dollard, Doob
et al. 1939). Other reactions to frustration occur as a result of the
conditioning process achieved through cultural and societal restrictions. The Frustration-Aggression Hypothesis (Dollard
1939) stated that aggression is always a consequence of frustration with two
propositions: aggressive behavior
always presupposes the existence of frustration, and every frustration leads to
aggression. However, subsequent
research has shown that aggression is not the only resultant reaction to
frustration, a fact attributed to prior learning experiences (Miller 1941; Bandura 1973). Through experience,
individuals learn other, possibly more culturally acceptable, ways to react to
frustration, which in turn inhibit the aggressive tendency. Subsequently, the Frustration-Aggression
Hypothesis was revamped with a hierarchy of responses influenced by prior
learning.
Regression: Barker et al. (1965) hypothesize that regression, defined by them
as immature behavior, is the major response to frustration. Aggression, according to this theory, is
simply one type of regressive behavior.
As individuals mature, they develop a greater variety of responses as
they are able to control their environment more and learn problem solving
skills. Learning is the key factor to
developing these socially acceptable responses.
Withdrawal: Also known as regression, withdrawal here refers to a flight
reaction in the face of adversity.
Withdrawal is a learned reaction as well, social conditioning, previous
experience, or the anticipation of pain or punishment causes the individual to
withdraw from the situation and thus reduce the state of tension caused by the
frustration (White 1929).
Fixation:
The repetition of courses of action that were once effective can occur
either when this course of action was once successful in the past or because of
a lack of skill or knowledge resulting in a low problem solving ability. Here, the ability to develop new ways of
responding to situations is impaired.
When severe frustration is encountered, Maier (Maier 1961) hypothesizes that fixation occurs completely and people become
‘frozen’ in a course of action and lose awareness of the external world.
Resignation: Also known as inertia or apathy, this occurs when individuals
lose all motivation to pursue goal-directed activity and is characterized by a
complete loss of hope.
Extrapunitive/Intropunitive/Impunitive: These three subjective responses were
defined by Rosenzweig (Rosenzweig 1935) as responses to frustration.
The extrapunitive response occurs when individuals get angry at
something external such as people, objects, or circumstances, and blame the
problem on an external source.
Intropunitive responses occur when individuals attribute blame to
themselves, and feel guilt or remorse about the situation. Impunitive reactions occur when individuals
try to avoid blame or gloss over the situation and try to reconcile the
situation or make excuses for the problem.
Computer Anxiety
The reactions of people to computers have also been
studied extensively, particularly attitudes towards the computer (Loyd &
Gressard 1984, Murphy, et al 1989, Nash & Moroz
1997) computer anxiety (Raub 1981, Glass & Knight 1988, Cohen &
Waugh 1989, Cambre & Cook 1985, Torkzada & Angulo 1992, Maurer 1994),
and computer self-efficacy (Meier 1985, McInerney et al 1994, Compeau &
Higgins 1995, Brosnan 1998). Each of
these variables, combined with the factors listed above, can affect how
frustrated individuals will become when they encounter a problem while using a
computer. The number of times a problem
has occurred before can affect their perception of the locus of control, and
therefore influence their reaction as well.
This may be related to anxiety, people with low computer self-efficacy
may be more anxious (Meier 1985; Brosnan 1998) and more likely to view the computer suspiciously and react with great
frustration when something occurs, especially when they have run into it
before. Different levels of anxiety
will affect performance when something unforeseen or unknown occurs, causing
anxious people to become more anxious (Brosnan 1998). On the other hand, the level
of experience may temper this if the prior experience increases computer
self-efficacy (Gilroy and Desai 1986) by lowering anxiety and reducing frustration when a problem
occurs. The perceived ability to fix
problems on the computer, as well as the desire to do so may also affect levels
of frustration. If problems are seen as
challenges rather than problems, they may not be as frustrating, which is most
likely directly related to level of prior experience as well as computer
self-efficacy.
Computing Frustration
Model
There
are many situations that can cause frustration in users. For instance, a
software application may crash, an error message may be unclear, or an
interface can be confusing (Preece, Rogers, and Sharp, 2002). If the computer
interface does not provide sufficient information for the user, the user can be
confused as to the current status of the system and the appropriate next steps
(Preece, Rogers, and Sharp, 2002). When any of these things happen, users can
lose work and waste time. A recent news report discussed users getting so
frustrated with computers, that the users hit and break their computers, and in
some cases, even assault their co-workers (BBC, 2002). The question is, what specific
aspects of the situation or the individual lead to feelings of frustration? Based
on the frustration literature, goal-attainment theory, and the literature on
computer attitudes and anxiety, we propose a Computing Frustration Model
(Figure 1).
Frustration theory indicates that it is the interruption of
a goal or task that causes individuals to become frustrated. There are various factors that can then
subsequently affect the level of frustration experienced. These fall into two categories: the incident-specific factors, and
individual level factors.
Incident Specific Factors
The incident specific factors that
affect the level of frustration experienced by end users include the level of
goal commitment, the severity of the interruption, and the strength of the
desire to obtain the goal. These are factors that are caused by the specific
details of the incident, and these differ from incident to incident. For
instance, if the user did not feel that it was especially important to complete
the task, the result might be a low level of frustration. At the same time, if
the task was very important, and there was a large amount of time lost while
trying to achieve the goal, the user might experience a large level of
frustration.
Goal theory tells us that
experience, self-efficacy, and the importance of the goal all affect the
commitment to the goal or task. When
the goal interruption occurs, the level of goal commitment will affect the
amount of frustration experienced by individuals directly. Severity of interruption can be thought of
as a combination of the amount of time it took to fix the problem and the
amount of time lost due to the problem.
The strength of desire for the goal is also affiliated with how
important the goal was, so importance is also used here as a proxy for strength
of desire. These incident-specific factors, which influence the level of
frustration, are harder to control, as they are unpredictable, as many of the
causes of the user frustration are also unpredictable. The individual-level
factors, discussed below, are more predictable, and are therefore easier to
address.
Individual Level Factors
Individual level factors affecting
the strength of the frustration include computer experience variables, mood and
other psychological factors, and the cultural and societal influences upon the
individual. These individual-level
factors influence the level of frustration, regardless of the specifics of the
frustrating incident. For instance, satisfaction with life, how often users get
upset over things, and general mood, can all affect the level of frustration,
regardless of the specific cause of the frustration. Computer anxiety (i.e. how
users feel about computer technology), as well as self-efficacy (i.e. how
confident users feel in their ability to succeed), can also influence the level
of frustration. Computer variables are separated into computer
experience/self-efficacy and computer anxiety/attitudes. Finally, computer experience (factors such
as years of computer use, and hours of computer use per week) can influence the
level of frustration. A newer user may become more frustrated than an
experienced user. These individual-level factors of user frustration are easier
to address than the incident-specific factors of user frustration. For
instance, to improve self-efficacy and lower computer anxiety, users may be
offered training, and other forms of support, such as documentation or a help
desk. New training techniques might be developed specifically to address user
frustration, to prepare users, in advance, for situations that might be
frustrating.
Conclusion
Based on the published literature
and our technology frustration model, we can begin to understand the basis of
user frustration, with the ultimate goal being to reduce the amount of
frustration that users face with computers. Frustrating incidents are very
problematic for users, who can waste large amounts of time trying to rectify
these frustrating incidents. Preliminary research work on user frustration has
found that nearly 30-45% of the time spent on the computer is wasted, due to
frustrating situations (Ceaparu, Lazar, Bessiere, Robinson, and Shneiderman,
2002). Some of the most frustrating incidents reported by users included error
messages, dropped/refused network connections, application freezes, and long
download times (Ceaparu, Lazar, Bessiere, Robinson, and Shneiderman, 2002). The
technology frustration model can highlight some of the actions that the various
stakeholders (such as users, developers, and managers) can take towards the
goal of lessening user frustration.
For Users:
While it is hard for users to predict
in advance the various incident-specific factors (such as level of goal commitment,
and time loss) that cause frustration, it seems that the individual-level
factors that lead to frustration are easier to predict and account for. For instance,
if self-efficacy is one of the major individual-level influences on
frustration, then it is possible that comprehensive support for users can
lessen the effects of frustration. For instance, support can come in the form
of documentation (manuals), training, or a call center. It is possible that
this support will improve the user’s confidence, and perception that they can
successfully respond to the frustrating situation. While the employer should
ideally be responsible for providing such support, if the employer fails to do
so, it might be helpful for the user to acquire training or documentation,
which will possibly increase self-efficacy of the user, thereby lowering their
levels of frustration when dealing with troubling computer incidents.
For Developers:
Software
developers can do much to assist with lessening the effects of frustration. Much
of what causes user frustration with computers is due to poor or confusing
design of the interface. For example, if one of the incident-level factors that
influence frustration is the severity of interruption and the time loss, then
good interface design, through error messages, can lower the time loss, and
lower the resulting frustration. When encountering an error situation, a
clearly-worded error message would allow the user to 1)have an understanding of
what occurred, and 2) have an understanding of how to respond appropriately to
the error situation (Shneiderman, 1998). If users have a clear understanding of
what occurred, and how to respond, then the users may be able to exit the error
sequence quickly and therefore return to their previous task goals, with only a
minimal amount of time lost. If users cannot exit an error sequence quickly,
then this can lead to other more serious errors, increasing the severity of the
interruption (Carroll and Carrithers, 1984), and therefore, increasing the
frustration. A good error message can speed along this process, helping users
limit the amount of time lost, and limiting the severity of the interruption,
possibly reducing levels of frustration. Other sources of user frustration,
such as incompatible file formats and indecipherable menus, can also be
alleviated by developers.
For Managers:
Managers
in workplaces want their employees to succeed with their computer tasks.
Ideally, the employee’s computer tasks will help support the mission of the
organization, and will therefore be important to the managers. To lessen the
frustration, it might be helpful for managers to provide support to the users, to
assist them in responding to the frustrating incidents. This user support may
come in the form of a help line, tech support, training, and/or documentation. This
support may assist with the individual-level components of frustration (from
the technology frustration model), by making the users more confident in their
ability to solve a frustrating situation, and providing the information that
users need, to solve frustrating situations.
For managers, the individual-level
components of frustration are easier to address than the incident-level
components of frustration (from the technology frustration model). For
instance, on the incident-level, the managers have no control over the time
loss due to frustrating technology. In addition, another component of
incident-level frustration is the importance of the task. To lower the level of
user frustration, theoretically, the managers could lower the level of
importance of the tasks. However, it is unlikely that the managers would lower
the level of task importance, by telling the employees that the tasks are
really not that important after all! Therefore, it appears that managers could positively
affect the individual-level components of frustration, but it is unlikely that
the managers could improve the incident-level components of frustration.
If users, managers, and developers work together, it is
possible to lower the levels of user frustration. The user of the future should
not be forced to deal with systems that leave them frustrated and unable to reach
their task goals.
Acknowledgements
We appreciate partial support from National Science
Foundation grant for Information Technology Research (#0086143) Understanding
the Social Impact of the Internet: A Multifaceted Multidisciplinary
Approach. We appreciate the devoted
efforts of Prof. Shirley Anne Becker formerly of the Florida Institute of
Technology and her students Ali Al-Badi and Madhan Thirukonda in preparing the
website for data entry, and Kent McKay of Adonix Systems for help in
transferring and converting the system for use at the University of Maryland.
We also thank Cheryl Schroeder-Thomas for comments on an earlier draft.
References
Bandura, A. (1973). Aggression: A Social
Learning Analysis. Englewood Cliffs, NJ, Prentice-Hall.
Bandura, A. (1986). Social Foundation of Thought and
Action: A Social-Cognitive Theory. Englewood Cliffs, NJ, Prentice Hall.
Bandura, A. (1997). "Self-Efficacy." Harvard
Mental Health Letter 13(9): 4-6.
Bandura, A. (1997). Self-Efficacy: The Exercise of
Control. New York, Freeman.
Barker, R. (1938). "The Effect of Frustration upon the
Cognitive Ability." Character and Personality 7: 145-150.
Barker, R., T. Dembo, et al. (1965). Frustration and
Regression: An Experiment with Young Children. Frustration: The Development
of a Scientific Concept. R. Lawson. New York, MacMillan Publishing Co.
Baron, R. A. (1977). Human Aggression. New York, NY,
Plenum.
Berkowitz, L. (1978). "Whatever happened to the
frustration aggression hypothesis?" American Behavioral Scientist 21(5): 691-708.
British Broadcasting
Company (2002). Web rage hits the internet, February 20, 2002, available at:
http://news.bbc.co.uk/hi/english/sci/tech/newsid_1829000/1829944.stm
Britt, S. H. and S. Q. Janus (1940). "Criteria of
Frustration." The Psychological Review 47(6): 451-469.
Brosnan, M. J. (1998). "The Impact of computer anxiety
and self-efficacy upon performance." Journal of Computer Assisted
Learning 14: 223-234.
Campion, M. and R. Lord (1982). "A Control Systems
Conceptualization of the Goal-Setting and Changing Process." Organizational
Behavior and Human Performance 30:
265-287.
Ceaparu, I., J. Lazar, K. Bessiere, J. Robinson, and B.
Shneiderman (2002). “Determining Causes and Severity of End-User Frustration.”
Forthcoming.
Cooper, M. N. (2002).
“Does the Digital Divide Still Exist?
Bush Administration Shrugs, But Evidence Says ‘Yes’.”
Dickard, N. (2002).
“Federal Retrenchment on the Digital Divide: Potential National Impact.”
Dollard, J., L. W. Doob, et al. (1939). Frustration and
Aggression. New Haven, Yale University Press.
Ekman, P., Ed. (1982). Emotion in the Human Face.
Cambridge, Cambridge University Press.
Ferster, C. B. (1957). "The Function of Aggression and
the Regulation of Aggressive Drive." The Psychological Review 71: 257-272.
Freud, S. (1921). Types of Onset and Neurosis. The
Standard Edition of the Complete Psychological Works of Sigmund Freud. J.
Strachey. London, Hogarth Press. 12: 227-230.
Gilroy, F. and H. Desai (1986). "Computer Anxiety: Sex,
Race, and Age." International Journal of Man-Machine Studies 25(1): 711-719.
Hochschild, A. R. (1979). "Emotion Work, Feeling Rules,
and Social Structure." American Journal of Sociology 85: 551-575.
Kling, R. (ed.)
(1999). Computerization and Controversy: Value Conflicts and Social Choices.
Brooks/Cole Publishing Company.
Kraut,
R., Scherlis, W., Mukhopadhyay, T., Manning, J., Kiesler, S. (1996). The
homenet field trial of residential internet services. Communications of the
ACM, 39(12), 55-63.
Lazar, J. and Huang,
Y. (2003, in press). “Improved Error Messages for Web Browsers: An Exploratory
Experiment”. In J. Ratner (ed.) Human Factors and Web Development, 2nd
Edition, Mahwah, NJ: Lawrence Erlbaum Associates, 167-182.
Lazar, J. and
Norcio, A. (2001) “Service-Research: Community Partnerships for Research and
Training” Journal of Informatics Education and Research, 2(3), 21‑25
Lazar, J., and
Norcio, A. (2003, in press). “Training Novice Users in Developing Strategies
for Responding to Errors When Browsing the Web.” International Journal of
Human-Computer Interaction.
Lincecum, L. (2000). The Effects of Software Disruption on
Goal Commitment, Task Self-Efficacy, Computer Self-Efficacy, and Test
Performance in a Computer-Based Instructional Task. Instructional Technology,
Texas Tech University: 160.
Locke, E. A. (1996). "Motivation Through Conscious Goal
Setting." Applied Preventative Psychology 5: 117-124.
Locke, E. A. and G. P. Latham (1990). A Theory of Goal
Setting and Task Performance. Englewood Cliffs, NJ, Prentice Hall.
Locke, E. A. and G. P. Latham (2002). "Building a
Practically Useful Theory of Goal Setting and Task Motivation: A 35-Year
Odyssey." received from author.
Maier, N. R. F. (1961). Frustration: The Study of
Behavior Without a Goal. Ann Arbor, University of Michigan Press.
Meier, S. (1985). "Computer Aversion." Computers
in Human Behavior 1(1): 171-179.
Miller, N. E. (1941). "The Frustration-Aggression
Hypothesis." The Psychological Review 48: 337-342.
Mowrer, O. H. (1938). "Preparatory Set (Expectancy) --
a Determinant in Motivation and Learning." Psychological Review 45: 62-91.
Mowrer, O. H. (1938). "Some Research Implications of
the Frustration Concept as Related to Social and Educational Problems." Character
and Personality 7: 129-135.
Murphy, C., D. Coover, et al. (1989). "Development and
Validation of the Computer Self-Efficacy Scale." Educational and
Psychological Measurement 49:
893-899.
Nash, J.B. and P.A. Moroz (1997). “An Examination of the Factor Structures of the Computer Attitude
Scale.” Journal of Educational Computing Research. 17(4):
341-356.
Pinkett, R. (2002). Camfield Estates-MIT Creating Community
Connections Project: High Technology in a Low-to-Moderate Income Community. In
J. Lazar (ed.). Managing IT/Community
Partnerships in the 21st Century. Hershey, PA: Idea Group Publishing, 221-246.
Preece, J., Rogers,
Y., and Sharp, H. (2002). Interaction Design: Beyond Human-Computer
Interaction. New York: John Wiley & Sons.
Rosenzweig, S. (1935). "Tests of Frustration." American
Journal of Orthopsychiatry 5:
395-403.
Schachter, S. and J. Singer (1962). "Cognitive, Social,
and Physiological Determinants of Emotional State." Psychological
Review 69: 379-399.
Shneiderman, B. (1982). System message design: Guidelines
and experimental results. In A. Badre and B. Shneiderman (eds). Directions
in Human/Computer Interaction. Norwood, NJ: Ablex Publishing, 55-78.
Shneiderman, B. (2000). Universal Usability: Pushing
Human-Computer Interaction Research to Empower Every Citizen. Communications
of the ACM, 43(5), 84-91.
Shorkey, C. T. and S. B. Crocker (1981). "Frustration
theory: a source of unifying concepts for generalist practice." Social
Work: 374-379.
United States Congress. (1996). Telecommunications Act of 1996 (P.L. 104-104) . Washington, D.C.:
U.S. Government Printing Office.
United States Department of Commerce (1999). Falling
Through the Net: Defining the Digital Divide. Available at:
<http://www.ntia.doc.gov/ntiahome/fttn99/contents.html>
United States General Accounting Office. (1998). School
technology: Five school districts' experiences in funding technology programs
(GAO/HEHS-98-35). Washington, D.C.: United States General Accounting Office
White, W. A. (1929). "The Frustration Theory of
Consciousness: Mind as Energy." Pschoanalytical Review 16: 143-162.
