Elsevier

Computers in Human Behavior

Volume 22, Issue 5, September 2006, Pages 899-916
Computers in Human Behavior

Using information technology: engagement modes, flow experience, and personality orientations

https://doi.org/10.1016/j.chb.2004.03.022Get rights and content

Abstract

The engagement mode (EM) model describes how an IT user (subject) engages in an activity with an object in a certain mode. The model specifies five engagement modes (Enjoying/Acceptance, Ambition/Curiosity, Avoidance/Hesitation, Frustration/Anxiety, and Efficiency/Productivity), which are characterized on three dimensions (evaluation of object, locus of control between subject and object, and intrinsic or extrinsic focus of motivation). Using questionnaire data from 290 participants, we extended previous empirical support for the model as well as described the model’s relationship to flow experience. In addition, it was found that autonomy, controlled and impersonal orientation in conjunction with socio-demographic variables differentiated among specific engagement modes and flow experience. We conclude that the EM-model, flow experience, and causality orientation theories provide a uniform framework for understanding how people adapt to information technology.

Introduction

The most obvious reasons for using IT are to have an effective and enjoyable interaction with technology that does not frustrate the user or waste the user’s time (Norman, 1998). The challenge for researchers is to identify and describe essential conditions of this interaction in terms of positive and negative aspects associated with technology. Recent findings in usability research have emphasized the need for enhanced descriptive models that can capture the psychological characteristics of users and how users interact with computer technology (Carroll, 1991, Carroll, 1997, Carroll, 2002). Descriptive models that address the human side of interaction with IT would provide valuable and practical information regarding the design of useful IT-systems (Bannon, 1991, Carroll, 1997, Grudin, 1990, Nardi, 1996).

To fulfill these needs, we have presented a descriptive model, the engagement mode (EM) model; to address the types of interaction users engage in using IT. In addition, this model assumes that the user needs some skill to use IT and that IT helps the user acquire skills (Montgomery, Sharafi, & Hedman, in press). We define IT as the use of computers to accomplish a task such as searching and receiving information and using computers as a communication tool at work and during leisure time.

Previously, the concept of engagement mode has been used to describe general properties of people’s activities in relation to the external world (Heidegger, 1927/1996). The EM-model describes an individual’s different modes of engagement with IT, the underlying psychological aspects of these modes, and how they are related to the flow experience. The validity of the EM-model is supported by multivariate analysis (multidimensional scaling and factor analysis) of self-reported data from more than 300 participants (Montgomery et al., in press). The main purpose of this paper is to examine the reliability of the model by testing it on new data and to examine the validity of the model in a broader sense than in our previous study by exploring how it is related to certain aspects of the user’s personality.

The EM-model generally involves three interrelated topics concerning how a subject (e.g., an IT user) interacts with an object (e.g., an IT-application), all of which were examined empirically in our previous study. These topics are: (i) dimensions in engagement modes, (ii) how levels on these dimensions are combined to form engagement modes, and (iii) how engagement modes are related to the flow experience.

The EM-model assumes that when a subject (e.g., an IT user) is involved in an activity with an object (e.g., with an IT-application), he or she perceives this activity on three fundamental bipolar dimensions: (a) the extent to which the object is positive or negative (evaluation dimension); (b) the extent to which the subject controls the object (Locus S) or the object controls the subject (Locus O) (locus of control dimension); and (c) the extent to which the activity is focused on goals inherent in the activity itself (Focus I) or on external goals (Focus E) (focus of motivation dimension). These dimensions are perhaps the most frequently addressed constructs in cognitive, personality, and developmental psychology.

It is assumed that a subject’s evaluation of an activity involving a certain object depends on how the activity is perceived on the other two engagement mode dimensions (Fig. 1). Depending on whether the locus of control is congruous or incongruous with the focus of motivation, the resulting activity will be positively or negatively evaluated. Congruity or incongruity means that the possibilities afforded by the locus of control (Locus S or I) match or mismatch the rewards that might be provided by the activity (Focus I or E). Let us go through all four possible combinations of Locus and Focus to see what this means.

When the subject perceives himself or herself as controlling an object (Locus S), this skill may be used to attain various external ends (Focus E). A subject’s skill will be congruous with a focus on external rewards. To the extent that subjects perceive that this congruity is at hand, they will perceive themselves as being efficient and/or productive (engagement mode Efficiency/Productivity), which is experienced as something positive. However, if the subjects lack the skill needed to attain an external goal (Focus E) and if they need to learn this skill (Locus O), Locus and Focus will be incongruous. As a result, the subject will be frustrated (engagement mode Frustration/Anxiety). On the other hand, if subjects think that they can master the object, they will experience ambition and maybe curiosity (engagement mode Ambition/Curiosity). Thus the hope or ambition of changing incongruity to congruity will result in a positive evaluation.

Consider now engagement modes where the subject’s motivation is focused on the activity itself in different ways (Focus I). If the subjects’ activities are controlled by the advantages that the object affords them (Locus O) and if they are interested in accepting the advantages (Focus I), locus and focus will be congruous and the mode of Enjoying/Acceptance emerges, which obviously is associated with positive evaluation. However, when the subject experiences a high degree of control of the object (Locus S), the activity involving the object will provide little advantage to the subject. That is, there is little to be learned from the activity itself. Nevertheless, if the subject is focused on rewards inherent in the activity (Focus I), locus and focus will be incongruous and the result will be the Avoidance/Hesitation mode, which obviously is associated with negative evaluation.

When using computers, people hope for the Efficiency/Productivity and even Enjoying/Acceptance modes. However, the various kinds of problems either related to the design of different applications or the person’s lack of skill and knowledge may lead the user to experience Avoidance/Hesitation and Frustration/Anxiety. According to the EM-model, a possible way out of this compelling challenge is the Ambition/Curiosity mode that produces more skilled and competent users, which may lead the user toward a better interaction and hopefully even the experience of flow.

Flow has been described as an extremely rewarding experience that occurs when a person is fully involved in an activity (Csikszentmihalyi, 1993). To experience flow while being engaged in any activity, individuals must perceive a balance between their skills and the challenges posed by the object with which they interact, and both their skills and challenges must be above a critical threshold (Csikszentmihalyi, 1975, Csikszentmihalyi, 1990). As noted, skill corresponds to locus of control in the subject (Locus S). In contrast, challenge corresponds to locus of control in the object. Thus, the higher the challenge, the more the subject’s activities are controlled by the object.

Ghani and Deshpande (1994) explored the flow experience in individuals using computers by including skill as well as challenge. They found that flow occurs when challenge and skill are both high. They proposed five components of flow: pleasure, control, concentration, experimentation, and challenge. In their model, the flow experience consisted of both pleasure and concentration components. However, they noted their model lacked the motivational components. In presenting the EM-model, we aimed at bringing the motivational aspect of interaction into more focus and to find the compatibility of engagement modes with flow components.

The EM-model describes the conditions for the emergence of flow in terms of an optimal combination of the three positive engagement modes. More specifically, flow occurs when the subject is encountered with a challenge that is experienced as pleasurable (engagement mode Enjoying/Acceptance) but is also possible to master (engagement mode Efficiency/Productivity). We assume that the flow experience implies that the subject shifts between these modes because they correspond to different positions of the locus of control dimension, which cannot exist simultaneously. The shifting is driven by ambition or curiosity (engagement mode Ambition/Curiosity) that encourages subjects to find new challenges to master.

Recent research on user interaction with IT points out the need to assess the user’s personality, adaptabilities, and goal-orientation (Salas & Cannon-Bowers, 2001). In our previous study, we found that the involvement with certain engagement modes in people’s interaction with IT may be related to the user’s level of competence (skill) in using IT (Montgomery et al., in press). In this paper, we look for possible relationships among the different engagement modes, flow experience, and personality/motivational characteristics of the users. We may expect that users with different behavioral and personality orientations show different degrees of positive and negative engagement modes and different levels of flow experience. Specifically, we want to find out how different types of engagement modes with IT are related to motivational and personality factors. Furthermore, we want to examine the types of orientation that individuals have learned during their life through different experiences.

The Causality Orientation Theory (Deci and Ryan, 1985a, Deci and Ryan, 1985b, Deci and Ryan, 1987) explains how individuals interpret the causality of events, other people’s behavior, and their own influence in different situations. This theory distinguishes among three types of behavioral and motivational orientation as relatively enduring aspects of personality and a person’s disposition to events and objects. Koestner and Zuckerman (1994) found close similarities between Deci and Ryan’s model and the goal-oriented behavior described by Dweck (1986). The causality orientation theory proposes three fundamental orientations: the autonomous, controlled and impersonal orientation, which can predict and explain a significant amount of variations in people’s cognition, affect and behavior (Ryan & Deci, 2000b). These orientations define how conditions of events influence people’s behavior. They also correspond to contextual factors that may advocate and reinforce the occurrence of these three types of personality and motivational orientations (Deci and Ryan, 1985a, Ryan and Deci, 2000b).

The autonomous orientation is initiated and regulated by the person’s choice of actions and thoughts in order to reach goals and satisfy needs. The autonomous orientation correlates with a high level of self-esteem, self-awareness, confidence, internal locus of control, attribute of success to ability and effort, absence of boredom, and an effective approach for achievement (Deci and Ryan, 1985b, Ryan et al., 1997). Autonomous people show more task involvement than ego involvement (Knee & Zuckerman, 1996). They tend to view unsolved problems as challenges to be mastered and not as reflecting their failures (Koestner & Zuckerman, 1994). We may expect that autonomous-oriented people show high scores in positive engagement modes and higher levels of flow experience since they are task-oriented (Acceptance/Enjoyment) and see problems as challenges (Ambition/Curiosity), which in turn may lead to mastering relevant objects. In particular, we expect that autonomous-oriented persons show high levels of Ambition/Curiosity since this engagement mode encourages the subject to master the challenges that are involved in different interactions. However, autonomous-oriented people may also experience the negative modes (Frustration/Anxiety and Avoidance/Hesitation), which may be experienced when the search for and mastering of challenges are met with problems.

The controlled orientation is explained as being determined by imperative rewards and environmental factors. Therefore, the initiation and regulation of a person’s behavior depends on the demand and control of other people, the environment, and other extrinsic factors. The controlled orientation is motivated by the person’s need for achievement and doing well in a task assigned by someone else. It is determined by others’ influences, expectations, threats, and/or rewards. Deci and Ryan (1985b) found that controlled orientation is associated with the type A behavior pattern and a general awareness to the viewpoint of others. People with this type of motivational orientation want to look good to the controllers or evaluators. Controlled-oriented people sometimes show an explosive reaction to the controlling environment when it does not provide pleasure and when it is too threatening. It can be expected that participants with high scores on controlled orientation may show more efficiency and productivity among the positive modes since they aim to achieve higher control for looking good, receiving external rewards, or escaping pain. They may display avoidance and hesitation when the expected pleasure is not provided or if the situation seems to threaten desired results. However, their interaction may involve flow experience as well. Since flow is the function of necessary level of skill and challenge and since controlled-oriented people generally feel pressured to be more skilled in order to master the situation, they may also experience flow.

The third type of orientation is the impersonal orientation in which the initiation of behaviors is perceived to be beyond the person’s control or even independent of that person (for example, the person is not capable of mastering the situation). People with impersonal orientation do not see the causation of events as being related or regulated to them. They believe that they neither can choose nor regulate their own behaviors. In addition, they also believe events cannot be transformed or manipulated in a way that they desire. The impersonal orientation has shown association with social anxiety and personal helplessness, self-blaming, and depression, especially when faced with obstacles and difficulties (Deci & Ryan, 1985a). In relation to engagement modes, we may expect that participants with high impersonal orientation would score low in positive engagement modes and high in negative modes and would generally not be able to experience flow. This is because the causation and control of events are not experienced as being related to them. Therefore, they may simply give up or only feel the pressure and anxiety of their involvement.

As Deci and Ryan (1985a) and Ryan and Deci (2000b) proposed, the three causality orientations correspond to three classes of contextual conditions. People experience events and situations that help them to behave in an autonomous, controlled or in an impersonal way. For example, classrooms, workplaces, and people’s work assignments can facilitate or inhibit people’s personality/motivation orientations (Ryan & Deci, 2000b). This definition particularly shows the effect of the contextual conditions that either prevent or promote autonomy, controlled and impersonal orientation and consequently influences different ways of interactions.

Zuboff (1988) noted that encouraging employees to explore and innovate in different tasks help them to adjust better to new technology and also adapt it more effectively to their day-to-day work. In relation to different types of engagement modes, contextual factors that promote and prevent the controllability of tasks and events and encourage the user’s motivation and positive evaluation play an important role for efficiency and enjoyment of work and people’s well-being. Therefore, we may expect that the contextual aspects of interaction with IT and its different applications, which promote or prevent different causal orientation, may influence different engagement modes.

In this study, we examined whether the results from our previous study can be replicated regarding the relationship between the proposed dimensions, engagement modes, and flow experience when using computer technology. We also aimed at constructing a shorter version of the engagement mode questionnaire developed in the previous study. More specifically, we aim at exploring how engagement modes, number of years of experience, IT-competence, and flow experience are related to the users’ socio-demographic characteristics and motivational and personality orientations.

Section snippets

Participants

Representing different degrees of experience with IT-technology, 290 participants (mean age=29.20 years, 168 women and 122 men) took part in the study either voluntarily or for course credit. Thirty-five percent of participants were unemployed and were searching for a new job either on the Internet or through the state job agency. Sixty-five percent of the participants were students at the University of Stockholm and Royal Institute of Technology in Stockholm. Fifty-four percent of the students

Replication of the proposed structure

In order to test whether the co-variations among the items in the EM questionnaire and the flow-scale were in line with the EM-model, a non-metric multidimensional scaling was performed using the SPSS 10.0 statistical package with three dimensions. Generally, the multi-dimensional scaling method is used to give an overview of the structure of the given variables, which theoretically are assumed to have certain relationships with each other (cf. Borg, 1985). The co-variations between variables

Discussion

The multidimensional analysis and the factor analysis demonstrate that the results from our previous study can be replicated with respect to the basic structure of engagement modes in people’s interaction with IT. The reproduction of the same results suggests that the EM-model is a robust descriptive model that empirically can capture psychological characteristics of people’s interaction with IT. Moreover, the derived five factors, which were identical with the initial presentation of the

Acknowledgement

This research was supported by Grant No. 1998-0239 from the Swedish Transport and Communication Research Board and Grant No. 220-155600 from EU Goal 1 North of Sweden.

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