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2004 46: 334Human Factors: The Journal of the Human Factors and Ergonomics SocietyHenry Montgomery, Parvaneh Sharafi and Leif R. Hedman

FlowEngaging in Activities Involving Information Technology: Dimensions, Modes, and

  

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INTRODUCTION

A growing body of literature portrays inter-action between humans and information tech-nology (IT) as a dynamic system that cannot beunderstood by looking at the user and the ITproduct as separate entities. The theoretical per-spective of the present study is in line with con-textually oriented approaches that stress dynamicviews of relations between a subject (the user)and an object (the IT object), such as activitytheory (Cole & Engeström, 1993; Nardi, 1996),situated action (Suchman,1987), and distributedcognition (Salomon, 1993). Drawing on theseapproaches, we present a general model of en-gagement modes (the EM model) that may beused for understanding how IT-related activitiesare shaped by properties of the user and the ITobject.

The Concept of Engagement Mode

The concept of engagement mode has been

used for describing general properties of peo-ple’s activities in relation to the external world(Heidegger, 1927/1962). We assume that an en-gagement mode involves a subject (e.g., a per-son using the computer) who is engaged in anactivity with an object (e.g., a specific computerprogram) in a certain manner (the mode). Thesubject’s engagement with the object is situatedin a perceived external environment. In the pre-sent context, the perceived external environmentrefers to the subject’s perception of externalconstraints and possibilities related to his or heruse of technology (Norman, 1998).

We believe that knowledge of IT users’ en-gagement is of great importance for under-standing how users should be motivated to finda balance between IT’s possibilities to make lifemore efficient and enjoyable, on the one hand,and IT-related risks of frustration or overdepen-dence, on the other hand. More specifically, webelieve that training programs based on en-gagement modes may be set up for teaching

Engaging in Activities Involving Information Technology:Dimensions, Modes, and Flow

Henry Montgomery and Parvaneh Sharafi, Stockholm University, Stockholm, Sweden,and Leif R. Hedman, Umeå University, Umeå, Sweden

An engagement mode involves a subject (e.g., a user of information technology, orIT) who is engaged in an activity with an object in a certain manner (the mode).The purpose of this study is to develop a general model of engagement modesthat may be used for understanding how IT-related activities are shaped by proper-ties of the user and the IT object. A questionnaire involving items on IT engage-ment and the experience of flow was administered to 300 participants. The resultssupported an engagement mode (EM) model involving 5 different engagementmodes (enjoying/acceptance, ambition/curiosity, avoidance/hesitation, frustration/anxiety, and efficiency/productivity) characterized on 3 dimensions (evaluation ofobject, locus of control between subject and object, and intrinsic or extrinsic focusof motivation). The flow experience follows from a balance between enjoying/acceptance and efficiency/productivity propelled by ambition/curiosity. The EMmodel could provide a platform for considering how IT users, IT applications, andIT environments should work together to yield both enjoyment and efficiency.Actual or potential applications of this research include designing IT training pro-grams on different levels of specificity.

Address correspondence to Henry Montgomery, Department of Psychology, Stockholm University, S-10691 Stockholm,Sweden; hmy@psychology.su.se. HUMAN FACTORS, Vol. 46, No. 2, Summer 2004, pp. 334–348. Copyright © 2004,Human Factors and Ergonomics Society. All rights reserved.

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ENGAGING IN INFORMATION TECHNOLOGY ACTIVITIES 335

people how to use IT in a more efficient and en-joyable way.

In this paper we first specify, theoretically andempirically, a number of dimensions that definedifferent engagement modes in IT interaction.In this connection, we discuss how engagementmodes may shed light on the experience of flowin interaction with IT. Second, we report empir-ical data that are used for constructing a generalmodel of engagement modes (the EM model).This model also specifies relationships betweenengagement modes and components of the flowexperience. Third, we examine relationships be-tween engagement modes and user characteris-tics. Fourth, we discuss how the EM model maybe used practically.

Dimensions of Engagement Modes

Engagement modes are assumed to refer tohow people perceive qualities of their interac-tion with an object. In this section we describethree dimensions that research in cognition andmotivation has identified as relating to howpeople perceive their activities. We also relateeach dimension to the flow experience. Basical-ly, the three dimensions reflect the followingquestions that people have in their minds whenbeing engaged in an activity (such as using IT):Do I like this activity (evaluation)? How andhow well can the activity be controlled (locus ofcontrol)? Which goal is focused on when doingthe activity (focus of motivation)?

The evaluative dimension. In a classic article,Zajonc (1980) reviewed studies showing thatpeople automatically and constantly evaluatetheir experiences as likeable or not likeable. Inthe same vein, Osgood, Suci, and Tannenbaum(1971; see also Osgood, 1969) found that eval-uation was the most inclusive dimension involv-ing meaning, encompassing practically all wordsin human languages (see also Russell, 1980).Almost all theories of emotion, affect, motiva-tion, attitudes, and decision making involve anevaluative component. Zajonc (1998) proposedthat at each instant in time, individuals are con-fronted with alternatives as to objects that haveto be selected and evaluated in relation to theindividual’s needs, wishes, hopes, and desires(i.e., in relation to goals of some sort). Theseevaluations are typically linked to pleasant affect

(positive evaluation) or to unpleasant affect (neg-ative evaluation).

Evaluation is often associated with theapproach-avoidance distinction (Eagly & Chai-ken, 1998). In the present context we see eval-uation as primarily related to whether theindividual’s goals are reached (or reachable) ornot (Zajonc, 1998), which in turn may be relat-ed to the approach/avoidance distinction, al-though not in an unequivocal manner. Theexperience of reaching a goal is typically associ-ated with approach behavior in the sense thatthe individual then probably would like to con-tinue to do the activity that led to goal attain-ment. However, the experience of not reachinga goal does not necessarily lead to avoidancebehavior. That is, if the individual does not findan alternative activity that would lead to fulfill-ment of some goal, he or she may still continuedoing the activity even though he or she maynot like it.

The evaluation dimension goes from a max-imally positive evaluation to a maximally nega-tive evaluation. The midpoint of the dimensioncorresponds to an evaluation that is neither pos-itive nor negative (i.e., is neutral or indifferent).The flow experience occurs when a person ishighly involved in an activity and the results aredeep enjoyment and content (Csikszentmihalyi,1975, 1990). Thus flow is associated with posi-tive evaluation. The two additional engagementmode dimensions discussed in the followingparagraphs may clarify why flow is experiencedas rewarding.

The locus of control dimension. The term lo-cus of control was coined by Rotter (1966) fordescribing a personality dimension that is impor-tant for people’s experienced well being. Locusof control, as we define it, generally concernsthe subject’s experience of how control of theactivity is allocated between himself or herselfand an object. The midpoint of the dimensionis where the locus of control is equally distrib-uted between subject and object. When the locusof control is within the subject (Locus S), theperson experiences that he or she can use the ob-ject for various purposes. In this case the objectbecomes more useful thanks to the subject’s skillin using the object. Put differently, the subjectpossesses the information that is needed for han-dling the object. When the locus of control is

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336 Summer 2004 – Human Factors

within the object (Locus O), the subject experi-ences that the object possesses information thatmust be acquired before he or she can use it topursue specific goals. In this case the object be-comes useful because of the object’s potentialrather than because of the subject’s skill. Thismeans in turn that the subject will feel chal-lenged to learn how to use this information inorder to be able to use the object in a productiveway. Thus Locus O implies that properties of theobject will constrain (temporarily or permanent-ly) the subject’s activities.

Our definition of the locus dimension may becompared with Bandura’s (1977, 1997) theory ofself-perceived efficacy. Locus S will be equivalentto a relatively high degree of self-perceived effi-cacy. Locus O, however, may not necessarily belinked with a low degree of self-perceived effica-cy, in the sense that the individual feels helpless.To the extent that the individual experiences thathe or she is able to learn something useful fromthe object, he or she need not feel helpless.

Csikszentmihalyi’s (1990) theory of the flowexperience is also related to the locus dimension.Use of a computer has often been identified aschallenging and, in many cases, troublesome.This is because computer-related activities oftenrequire considerable skill, patience, and prac-tice. However, when an individual accomplish-es a difficult task by becoming involved withthe requirements of the task at hand and uses theappropriate skills to manage these requirements,he or she experiences the positive affect associ-ated with the flow experience (Ghani & Desh-pande, 1994). The experience of flow impliesthat a subject, in interacting with an object, istotally focused on the object, paying little or noattention to himself or herself (Csikszentmihalyi& Figurski, 1982). Thus the subject is complete-ly absorbed in his or her engagement with theobject.

Flow is assumed to be a function of two fac-tors–namely, the subject’s skill (Locus S) and thechallenge of the activity (Locus O) in whichthe subject is engaged. More precisely, flow oc-curs when a person’s skills are fully involved inovercoming a challenge that is just manageable(Csikszentmihalyi & Rathunde, 1993). Anotherway to describe this is that flow will occur whenthe subject switches back and forth betweenengagement modes that correspond to Locus O

and Locus S. The subject will then experienceboth that he or she is in control of the object(high level of Locus S: high skill) and that theobject puts high demands on him or her (highlevel of Locus O: high challenge).

The focus of motivation dimension. This di-mension concerns a motivational component inengagement modes. It is assumed that the sub-ject’s engagement with an object is focused onaspects that reinforce the particular engagement.More specifically, when a person engages in anactivity, he or she may assume either an intrinsicor extrinsic motivational orientation (Pittman,Boggiano, & Ruble,1983), which in turn impliesa focus on different aspects. Pittman (1998) ex-plained this distinction in the following words:“When a person adopts an intrinsic motivation-al orientation, the primary focus is on rewardsin engagement with the activity; the activity isapproached as an ‘end in itself’ (Kruglanski,1975)....When a person adopts an extrinsicmotivational orientation, the primary focus ison rewards that are mediated by but not part ofthe target activity. The activity is approached asa ‘means to an end’ (Kruglanski), either moti-vated by or a step along the way to somethingelse” (p. 566).

In the present context, we denote the focusinvolved in intrinsic motivation as Focus I (i.e.,focus on the rewards that the subject gets fromhis or her engagement with the object). Here-in, the subject focuses on his or her positive ornegative experiences of the engagement. Thefocus involved in extrinsic motivation is denot-ed as Focus E because in this instance the focusis on the external consequences of the activity,which may provide direct rewards. In this case,the focus is on the changes in the external envi-ronment that are seen as required for reachinga desired goal. The midpoint of the focus dimen-sion corresponds to a case in which the subjectperceives himself or herself to be equally moti-vated by intrinsic and extrinsic rewards. Thefocus dimension highlights how engagement inIT-related activities may be linked to a socialcontext. The engagement may be compatibleor incompatible with various goals that the sub-ject has in his or her life besides the activityitself (Focus E), and a focus on the activity itself(Focus I) may be compatible or incompatiblewith these external goals.

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ENGAGING IN INFORMATION TECHNOLOGY ACTIVITIES 337

Flow theory demonstrates how involvementin a demanding task can be experienced as high-ly rewarding, possibly with respect to our con-cepts of both intrinsic (Focus I) and extrinsicmotivation (Focus E). High involvement may beintrinsically rewarding but might also be a nec-essary requirement for attaining external goals.Engagement modes are assumed to correspondto specific combinations of levels of the evalua-tion, locus, and focus dimensions. However, wedefer discussion of this topic until we have pre-sented the empirical results of the present study.

Present Study

Here we describe how we developed a ques-tionnaire purporting to lead to a model of en-gagement modes in relation to IT. The aims ofthe model construction were to identify partic-ular different engagement modes and to findout whether and how these engagement modescould be characterized in terms of the hypothe-sized engagement mode dimensions. We alsoexamined how the flow experience is related toengagement modes. Among the empirical stud-ies on flow in the use of computer technology(e.g., Csikszentmihalyi, 1990; Hoffman & No-vak, 1996; Trevino & Webster, 1992; Webster,Trevino, & Ryan, 1993), the investigation byGhani and Deshpande (1994) was seen as par-ticularly relevant for the present study. In linewith the theory of flow, those researchers as-sumed that flow is determined by perceivedcontrol and challenge and that it leads to explo-rative behavior, which may optimize possibili-ties for continued flow.

The flow experience itself is assumed to con-sist of pleasure and concentration. Ghani andDeshpande (1994) developed a questionnaireto measure the factors associated with flowand found support for the hypothesized rela-tionships among the flow-related components(pleasure, control, concentration, exploring, andchallenge). In the present investigation we ex-amined how these components relate to engage-ment modes.

METHOD

Participants

A total of 420 participants (265 women and155 men) took part in two pilot studies and themain study. In the main study, 300 participants

(191 women and 109 men) ranging in age be-tween 18 and 65 years (mean = 31 years) filledout the questionnaire. Sixty percent of the par-ticipants were students at the Department ofPsychology at Stockholm University and theRoyal Institute of Technology in Stockholmwho received credit for a course requirement orvoluntarily took part in the study; 30% of thestudents had at least one part-time job in addi-tion to their education. The remaining 40%were (a) staff at a kindergarten; (b) school-teachers in Sundsvall, a medium-sized town innorthern Sweden; (c) staff at the Swedish Agri-cultural University in Uppsala; (d) staff at theCenter for Educational Technology at UmeåUniversity; or (e) staff at the Swedish NationalRoad Administration in Stockholm. The high-est educational level was high school for 49%of the participants and university for 44%. Themedian time participants had used a computerwas 5.5 years; 54% of the participants used itevery day, and 48% had used the Internet dailyfor at least the last 3 years.

Pilot Studies

To find items for a questionnaire on engage-ment modes, we recruited 70 persons fromamong the students and staff at the Departmentsof Psychology at Stockholm and Tromsö Uni-versities (45 women and 25 men, mean age =34 years) and asked them to list nouns or adjec-tives describing what a computer and IT meantto them. In a second pilot study, items wereconstructed based on a content analysis of theresponses in the first pilot study to create a pre-liminary version of an engagement mode ques-tionnaire. The questionnaire was filled out byparticipants recruited from staff and studentsat the Department of Psychology at StockholmUniversity (29 women and 21 men, mean age =36 years). In addition, participants were givenan open-ended question and were asked to writedown what computers and IT meant to them.Finally, we constructed a new version of the EMquestionnaire with 83 items and used it in themain study after considering the results of the twopilot studies.

Questionnaire

The 300 participants in the main study filledout the EM questionnaire. The introduction to

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the questionnaire explained that they were par-ticipating in a study about their engagementmodes in relation to IT. Information technology(IT) was defined as the usage of computers andthe Internet for communicating and for searchingfor and receiving information, for work or leisure.

The items in the questionnaire were orga-nized in four sections. First, there were 8 ques-tions about the participants’ sociodemographiccharacteristics (e.g., age, gender, and educationlevel). Second, 39 items were presented to assessthe participant’s competence in using IT. Theitems covered a wide variety of IT-related activ-ities that may be performed for work or leisure(e.g., testing new functions or services, usingword processing, drawing figures and makingtables, writing computer programs, testing dif-ferent search engines, creating a home page,reading news and newspapers, shopping, andplaying on-line computer games). Third, partici-pants were presented with a Swedish translationof Ghani and Deshpande’s (1994) questionnaire,which includes 16 items selected to measurefive components of the flow experience: plea-sure (4 items), control (4 items), concentration(3 items), exploring (3 items), and challenge (1item). Fourth, 83 items were presented to assessthe participants’ engagement modes in relationto IT. The items were presented in a random or-der (the same order for each participant). Re-sponses were made on 5-point scales rangingfrom strongly disagree (1) to strongly agree (5).

Procedure

The participants were recruited by seekingpersons who indicated they would like to takepart in a questionnaire study about interactionwith IT. Participation was voluntary, even forthe students who received the credit for theircourse requirement. The participants were al-lowed to fill out the questionnaire whereverthey found it suitable. They returned the ques-tionnaire to the investigator (by hand or mail)within a few days. It took about 30 to 45 minto fill out the questionnaire.

RESULTS

Multidimensional Scaling

A nonmetric multidimensional scaling analy-sis using SPSS 10.0 for Macintosh was per-

formed on the 83 engagement mode items aswell as on the five flow component scales. Thismethod was used to get a general overview ofthe data structure that was optimally close to theactual covariations among the responses for dif-ferent items (Borg, 1985). More specifically, themultidimensional scaling attempted to determinewhether the three hypothesized engagementmode dimensions could be found in the data.The Euclidean distance procedure with trans-formed z score values was used. The distancesbetween variables in the multidimensional spaceillustrate the extent to which the variables co-vary. The shorter distance, the greater the covari-ation. This means that the closer two items arein the space, the more likely they have some-thing in common. Thus items belonging to agiven engagement mode may be expected to bein the same region in the space. Insofar as wehypothesized that engagement modes are func-tions of three dimensions, a 3-D solution wassought. The model converged normally in fiveiterations, with an S (stress) value obtained of.223 and an R2 of .808.

The first dimension is interpreted as an eval-uative dimension. Relevant items revealed eithera positive or a negative evaluation of how ITfunctioned for the participants. The evaluationwas expressed in terms of positive or negativeconsequences for the participant (e.g., “IT en-riches my life”; “IT threatens my goals”), posi-tive or negative affects (e.g., “I feel good whenusing IT”; “IT irritates me”), or simply positiveor negative descriptions of IT (e.g., “IT is a goodfriend”; “IT is a suppressor”). For convenientdisplay of all the variables, the results of thescaling are presented in one plot of the secondand third dimension for only the positive val-ues of the evaluative dimension (Figure 1) andin another plot for only the negative values ofthe evaluative dimension (Figure 2). Thus Fi-gure 1 shows the locations in the second andthird dimension of items in the positive half ofthe 3-D space (i.e., items expressing positiveevaluations) and Figure 2 shows the location ofitems in the negative half of the 3-D space (i.e.,items expressing negative evaluations). Thesize of the circles in the plots shows the size ofpositive or negative values of the first dimen-sion. Larger circles correspond to more extremescale values on the evaluative dimension.

338 Summer 2004 – Human Factors

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ENGAGING IN INFORMATION TECHNOLOGY ACTIVITIES 341

Figure 1 shows that the positive items tendto form an area with a positive slope. The sloperesults mainly from the fact that items are lack-ing in the lower right part of the plot. In thelower left part there are items correspondingto enjoyment of using IT and an overall positiveevaluation of IT, such as experiencing IT as apartner, a good friend, a toy, interesting, a posi-tive challenge, and entertaining. In the upperright part, the items concern efficiency and man-aging problems, including having more controlof one’s life, becoming more independent, find-ing more time for other things by using IT,knowing how to do the job, and being able toget help when needed. In the upper left part ofthe figure are items denoting an overall ambitionto become better at using IT, such as expressingan interest in learning more and in better utiliz-ing IT’s possibilities.

Figure 2 shows how items related to negativeevaluation form an area with a negative slope –that is, a slope opposite that of the one foundfor the positive items in Figure 1. In this in-stance the slope is clearer, with items lacking inboth the lower left and upper right part of theplot. In the upper left area of the plot are itemsrelated to frustration, which include feeling ir-ritation; being afraid of using IT; and experienc-ing IT as a troublemaker, as demanding, and asan antagonist. In the lower right area there areitems depicting experiences related to avoidanceof IT, such as worries about bad social influ-ence, change of identity, wanting to keep a dis-tance, and resisting and ignoring IT.

To examine whether the locus and focus di-mensions are visible in the data, one may in-spect items at the extremes of the vertical andhorizontal coordinates to see if they correspondto opposite poles of each of the two dimen-sions. The pattern is especially clear for posi-tive evaluations (Figure 1). At the left end ofthe horizontal coordinate in Figure 1 is the item“I think IT serves as a model” and at the rightend “I know how to use IT.” The horizontal co-ordinate reflects the locus dimension, with LocusO at the left extreme (IT controls the subject)and Locus S at the right extreme (the subjectcontrols IT).

The focus dimension is reflected in Focus-E-related items such as “I find more time” (upperright of the plot) and “IT is a practical tool”

(upper middle left of the plot). Focus I is re-flected quite clearly in the item “IT helps meforget my problems.” It may be noted that itemssuch as “I am afraid that IT changes my identity”(see lower middle right of Figure 2) representextreme cases of Focus I in the sense that thesubject wants to avoid too much involvementwith IT.

Figure 1 also shows the location of the fiveflow components (challenge, pleasure, control,concentration, and exploring). It can be seenthat the pleasure and control flow componentsare located to the left and right, respectively, onthe horizontal coordinate (i.e., the locus dimen-sion). The control component is surrounded bythe concentration and exploring components,and the concentration component is closer tothe efficiency items than is the exploring com-ponent. Thus it seems that the present opera-tionalization of flow involves both Locus S andLocus O. Furthermore, as may be expected, thechallenge flow component is located in the areaof ambition-related items.

Identification of Engagement Modes andConstruction of EM Scales

A number of steps were taken to find itemsfor identifying particular engagement modesand for constructing scales measuring the iden-tified modes. First, items that were weakly cor-related with all three dimensions (r < .20) wereexcluded. Scores on each dimension for eachparticipant were obtained by assigning the rat-ing of each item a positive or negative valueaccording to its sign in the relevant dimensionand then summing all positively or negativelysigned ratings.

Second, separate indexes were constructedfor the focus and locus dimensions for posi-tively and negatively evaluated items, allowingus to compute the following index variables:focus positive, focus negative, locus positive,and locus negative. Cronbach’s alpha was com-puted for each index variable, and items thatwould increase Cronbach’s alpha when removedwere discarded when they were found. Cron-bach’s alpha for the remaining items indicated ahigh degree of reliability, with scores of .89 forlocus positive (18 items), .83 for locus negative(12 items), .88 for focus positive (13 items), and.86 for focus negative (14 items).

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342 Summer 2004 – Human Factors

Third, in order to identify the different typesof engagement modes, we performed a principalcomponents analysis with oblimin rotation onthe 57 remaining items. The reason we chose theoblimin rotation procedure is that it gave a moreidentifiable and meaningful factor solution thandid other procedures. The extracted factors wereinterpreted in terms of their positions in the 3-Dspace shown in Figures 1 and 2. We found thefollowing five factors: (a) enjoying/acceptance,referring to positively evaluated items in theLocus O-Focus I region (lower left quadrant ofFigure 1, items marked “E/A”); (b) ambition/curiosity, referring to positively evaluated itemsin the Locus O-Focus E region (upper left quad-rant of Figure 1, items marked “A/C”); (c) efficiency/productivity, referring to positivelyevaluated items in the Locus S-Focus E region(upper right quadrant of Figure 1, items marked“E/P”); (d) frustration/anxiety, referring to neg-atively evaluated items in the Locus O-Focus Eregion (upper left region of Figure 2, itemsmarked “F/A”); and (e) avoidance/hesitation,referring to negatively evaluated items in theLocus O (mainly)-Focus I region (lower rightregion of Figure 2, items marked “A/H”). Theinternal consistency reliabilities (Cronbach’salpha) for each factor and factor loadings (>.40)for the items that loaded highest in a given factor(in all 38 items) are presented in Table 1. Theaverage interitem correlation between factorswas .23.

Fourth, scale values for each of the five en-gagement modes were constructed by takingthe mean of all items with loading >.40 in eachengagement mode factor.

Characteristics of Participants’Engagement Modes

Table 2 presents correlations among the fiveengagement mode scales. It can be seen thatthere are quite high positive correlations amongthe scales for the three positive engagementmodes and also between the two negative en-gagement mode scales (although slightly lower).The correlations among positive and negativeengagement mode scales are close to zero.

Table 2 also shows means and standard devi-ations for each of the engagement mode vari-ables. It can be noted that the participants tendedto be more positive than negative in their en-

gagement with IT, considering that the three“positive” engagement modes have higher meansthan do the two “negative” engagement modes.

To examine how user characteristics are re-lated to engagement modes, we performed aregression analysis for each index variable (en-gagement mode) as the dependent variableagainst the independent variables of age, gender,education, and IT competence. IT competencescores were assessed from the 39 IT-competenceitems, with answers coded as 1 or 0 dependingon whether or not participants indicated IT com-petence. The results of the regression analysisare shown in Table 3.

Viewing each independent variable across en-gagement modes (the dependent variables), thefollowing observations can be made: Age hasno significant association with any engagementmode. Gender is negatively related to frustration/anxiety, such that women tended to experiencemore frustration and anxiety than men did. How-ever, men were more involved in the avoidance/hesitation engagement mode than women were.Education had a marginally significant negativerelation (p = .06) to enjoying/acceptance. ITcompetence was positively related to all “posi-tive” engagement modes, especially enjoying/acceptance and efficiency/productivity, and wasnegatively related to frustration/anxiety. Therewas no significant relation to avoidance/hesita-tion. The proportion of variance explained foreach dependent variable varied considerably, al-though the general level was quite low, with avery low proportion for avoidance/hesitation(.02) and the highest proportions for frustration/anxiety (.14) and enjoying/acceptance (.12).

DISCUSSION

The multidimensional scaling suggests thatengagement in IT could be described generally interms of three assumed dimensions (evaluation,locus of control, and focus of motivation) ormore specifically in terms of particular combina-tions of levels of these basic dimensions. Usingthe patterns found in the multidimensional scal-ing and in the factor analysis, we describe theEM model in the following sections.

The EM Model

The results show that positive and negativevalues of the evaluation dimension are associated

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TABLE 1: Items of the Engagement Modes Scale, Factor Loading of Each Item,and Alpha Coefficients for Each Engagement Mode

Factor Loadingand Alpha

Factors and Items Coefficient

Enjoying/acceptanceI think IT is an entertainer .67329IT has made my life more interesting .63565IT enriches my social life .63276I think IT serves as a model .63148By using IT I can develop my personality in a positive way .62710When I work with IT, I feel we have something in common .61452I think IT is a positive challenger .58353I feel calm when I am using IT .55292IT can give me knowledge about life .54989IT is a fun toy .54199When I work with IT, it is difficult to stop using it .54117I think many things become more fun when I use IT as help .50239I think IT is a collaborator .49190Alpha .88650

Avoidance/hesitationI want sometimes to keep totally away from IT .71495I want sometimes to totally ignore IT .69125I want to resist how IT functions in my life .66723I am afraid that use of IT will change my identity .66285I am on my guard not to become addicted to IT .64859I wonder about the role IT plays in my life .62620I think that IT restricts my life .58131I wonder about how much I use IT .57176I want to change how IT becomes useful for me .54819Alpha .82630

Frustration/anxietyI am not satisfied about my capability to manage IT .76441When I have a problem using IT I feel stupid .76183I experience that others think I am bad in using IT .71867When there is a problem in my use of IT I become frightened .62854I am pushed to learn about IT .62808IT is demanding .54327Alpha .82430

Efficiency/productivityI find more time for other things when I am using IT .81429I can be more effective using IT .68283I have more control over my life when I use IT .65327I think that IT permits me to become more independent .42149I think IT is a practical tool .47346Alpha .72180

Ambition/curiosityI want to learn more about IT .78925I want to do better when I am using IT .77001I want to take more of IT’s possibility .73964It is interesting to learn how IT functions .67784I can learn a lot by using IT .49297Alpha .83150

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344 Summer 2004 – Human Factors

with different combinations of levels on thefocus and locus dimensions. We interpret thesefindings as indicating that different combina-tions of locus and focus are either congruous orincongruous (typically corresponding to posi-tive or negative evaluations of the object; seeFigure 3). When locus and focus are congruous,the possibilities afforded by the locus match therewards (internal or external) associated withthe focus. Conversely, incongruity correspondsto a mismatch between possibilities affordedby the locus and the rewards associated withthe focus. Thus our interpretation of the dataimplies that focus and locus vary independentlyof each other (all four combinations of locusand focus are possible), whereas evaluation isdependent on whether focus and locus are con-gruous or incongruous.

We explain the following combinations offocus and locus as corresponding to differentengagement modes.

Locus S–Focus E: Efficiency/productivity.Here the subject experiences that he or she canuse the object (IT) to attain various external re-wards (Locus S) and is also motivated to attainsuch rewards when using the object (Focus E).This implies that IT will be experienced as awell-functioning tool (efficiency) that yields val-uable results (productivity). This engagementmode implies that locus and focus are congru-ous inasmuch as the perceived locus of controlmatches the focused reward, and hence a posi-tive evaluation of the object will be obtained.

Locus O–Focus I: Enjoying/acceptance. Thisengagement mode emerges when the object(i.e., an activity involving the object) has some-thing to offer – for example, by making lifemore interesting or by offering entertainment(Locus O) – and the subject is motivated to re-ceive this offer from the activity as such (FocusI). As a consequence of this congruity betweenlocus and focus, the subject accepts and even

TABLE 2: Correlations Among Engagement Modes and User Characteristics

M SD 1 2 3 4 5 6 7 8 9

1. Age 31.460 10.000 —2. Gendera — — .14 —3. Education 2.49 0.62 .01 .03 —4. IT competence 0.51 0.20 .02 **.29** *.13* —5. Avoidance/hesitation 2.06 0.74 –.050 *.11* –.060 .01 —6. Ambition/curiosity 4.05 0.71 –.040 –.000 –.040 **.23** .11 —7. Efficiency/productivity 3.00 0.73 –.060 –.010 –.060 **.29** .09 **.48** —8. Frustration/anxiety 2.38 0.86 –.060 –.22** –.040 –.34** **.42****.19** .01 —9. Enjoying/acceptance 2.46 0.70 –.090 .07 –.060 **.33** **.24****.57** **.46** .08 —

Note: n = 300.aWomen were coded as 1 and men as 2.*p < .05. **p < .01.

TABLE 3: Regression Analyses of Engagement Mode as a Function of User Characteristics

Ambition/ Frustration/ Enjoying/ Avoidance/ Efficiency/Curiosity Anxiety Acceptance Hesitation Productivity

UserCharacteristics β t β t β t β t β t

Age –0.040 –0.660 –0.040 –0.790 –0.090 –1.600 –0.070 –1.200 –0.050 –0.960Gendera –0.070 –1.260 –0.130 –2.3*0 –0.001 –0.160 0.13 02.17* –0.100 –1.720Education –0.070 –1.220 –0.070 –1 .400 –0.100 –1.900 –0.060 –0.100 0.05 0.88IT competence 0.26 4.5† –0.300 –5.2†0 0.34 06.00† –0.020 –0.210 0.31 05.32†F **5.24** 12.33† 10.6†0 1.64 08.00†R2 0.06 0.14 0.12 0.02 0.09

Note: n = 300.aWomen were coded as 1 and men as 2.*p < .05. **p < .01. †p < .001.

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ENGAGING IN INFORMATION TECHNOLOGY ACTIVITIES 345

enjoys what he or she gets from being engaged inthe object and also evaluates the object positively.

Locus S–Focus I: Avoidance/hesitation. In thiscase the subject experiences that he or she con-trols the object more than the object controls himor her. At the same time, the subject focuses onrewards in the activity. However, the subject ex-periences that there is not much to receive fromthe object (absence of Locus O) as comparedwith what he or she can achieve by using skill inmanaging the object as an instrument for attain-ing goals in the external environment (Locus S).Thus the focus and locus will be incongruous be-cause the locus does not match what the objectcan offer, as compared with other possibilities.This incongruity between Locus S and Focus Iis associated with a negative evaluation and maylead to avoidance behavior and hesitation to-ward the object.

Locus O–Focus E: Frustration/anxiety. Herethe subject experiences that he or she is morecontrolled by the object than in control of theobject (Locus O). That is, the subject experi-

ences that he or she lacks skill in using the ob-ject. However, the subject focuses on externalgoals (Focus E) that can be attained only afterbecoming sufficiently skilled in using the object.Thus the subject experiences an inability tocontrol the object in a way that he or she wants(incongruity). This will be experienced as threat-ening and/or frustrating if the subject finds itdifficult to control the situation while pursuingan external goal.

Locus O–Focus E: Ambition/curiosity. Thesame combination of Locus O and Focus E maylead to a positively tuned engagement mode.This occurs when the user’s attention moves fromthe temporary unavailability of external rewardsto the possibility of improving his or her skill(more of Locus S) in order to attain the rewardsassociated with using the object. Thus, in thisengagement mode, the user has an ambition toovercome the incongruity. Our data suggest thatthis ambition and curiosity are closely related tobeing interested in learning about the objectand how it can be used.

Figure 3. Overview of the engagement modes model: Dimensions and each engagement mode. The evaluationdimension is represented in terms of positive and negative engagement modes. Bold phrases = negativeengagement modes, nonbold phrases = positive engagement modes. Focus E represents extrinsic focus ofmotivation and Focus I represents intrinsic focus of motivation on the focus of motivation dimension. Locus Orepresents locus of control within the object and Locus S represents locus of control within the subject on thelocus of control dimension.

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346 Summer 2004 – Human Factors

Engagement Modes and UserCharacteristics

It appears that different engagement modesare associated with user characteristics in inter-esting and meaningful ways. All three positiveengagement modes covaried positively withIT competence. This implies that (self-rated) ITcompetence shows up not only in the engage-ment mode that conceptually is clearly relatedto competence (efficiency/productivity) but alsoin a joyful (enjoying/acceptance) and ambi-tious (ambition/curiosity) engagement with IT.It may be noted that this pattern is compatiblewith the notion of deliberate practice as a path todeveloping one’s competence. Ericsson, Krampe,and Tesch-Römer (1993) and Ericsson (2004)claimed that joyful interaction is a natural in-gredient in developing expertise, but it is alsonecessary to have enough ambition to improveoneself to overcome the hardships associatedwith reaching high levels of competency.

As might be expected, frustration/anxietywas negatively related to IT competence. How-ever, the absence of a relationship between ITcompetence and the avoidance/hesitation en-gagement mode may be regarded as more surprising. It is reasonable to assume that fordifferent levels of competence there are differentreasons for wanting to avoid IT (e.g., frustrationis experienced when competence is low, and hes-itation is experienced when competence is high-er). As for gender, men showed higher levels ofIT competence than women did, but there wasno significant difference between men and wo-men for ambition/curiosity. Further research isneeded to investigate what these differencesdepend on.

The proportion of variance of particular en-gagement modes accounted for by user charac-teristics was low (around .10) but not negligibleif one considers the large number of peoplewho are involved in IT-related activities.

The EM Model and Flow

The EM model can be used to clarify the con-ditions for the emergence of flow as an emo-tional experience by highlighting the role ofevaluation, control, and motivation in people’sinvolvement with objects. In terms of the EMmodel, flow will occur when the subject shifts

among different engagement modes. More pre-cisely, flow may occur when the person experi-ences that he or she is in control of the object(Locus S) by meeting the requirements neededto master the object (Locus O).

However, in order for flow to occur, the mo-tivational focus presumably must be congruouswith the locus of control. That is, getting involvedin a difficult learning task (Locus O) may beexperienced as interesting and rewarding (moti-vational focus: intrinsic motivation, which iscongruous with Locus O) or as frustrating (mo-tivational focus: extrinsic motivation, which isincongruous with Locus O). Similarly, master-ing an object (Locus S) may be experienced asefficient for various external purposes (extrinsicmotivation, congruous with Locus O) or as timeconsuming and restricting (misplaced intrinsicmotivation, incongruous with Locus O).

Thus, in terms of the EM model, and also inline with our data, it seems that the flow expe-rience is built on a delicate balance betweenlocus-focus congruous engagement modes (i.e.,enjoyment/acceptance and efficiency/produc-tivity). The remaining positive engagementmode, ambition/curiosity, is needed to drive theindividual to find the appropriate balance be-tween the two congruous engagement modes.It may be noted that Ghani and Deshpande’s(1994) flow scales did not include any scales thatcould be used for differentiating among differ-ent types of motivation.

The search for balance between enjoying/acceptance and efficiency/productivity shouldlead to positive correlations between these en-gagement modes, given that this search aims atfinding sufficiently high levels on both these en-gagement modes. Indeed, fairly high positivecorrelations were found between the two congru-ous engagement modes. In addition, ambition/curiosity should be expected to be positivelycorrelated with the two congruous engagementmodes because ambition is assumed to propelthe subject to attain higher levels in those en-gagement modes. Positive correlation may alsobe expected between the two negative engage-ment modes (frustration/anxiety and avoid-ance/hesitation) because they are both morelikely to occur when the conditions for flow arenot met. All these correlations were found inthe present data.

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ENGAGING IN INFORMATION TECHNOLOGY ACTIVITIES 347

Practical Use of the EM Model

To what extent can the EM model be practi-cally useful? To answer this question, we thinkit is important to keep in mind that the EM con-cept requires that the IT user (subject), the ITapplication (object), and the perceived environ-ment be seen as a coherent system. Thus mea-sures based on the EM model should take thesesystem properties into account. More concrete-ly, we think the EM model – or, rather, futuredevelopments of the EM model – could be use-ful on three levels of generality in people’s lives.

On the most general level, the EM modelcould provide a platform for considering howIT users, IT applications, and IT environmentsshould work together to yield a balance betweenenjoyment and efficiency. This would minimizethe risk of frustration and an impoverished lifeattributable to misplaced intrinsic motivationassociated with IT-related activities. This bal-ance will be different for different individuals,depending on their skills and their motivationalfocus in relation to IT and other areas of life.Some people (perhaps the majority) may be in-terested in using IT primarily as a practical tool(Focus E, efficiency), whereas others may see ITas the meaning of their life (Focus I, enjoyment);still others may be motivated to minimize theirIT use (getting rid of Focus I, avoidance). Onemay predict that these groups will be differen-tially motivated to use and learn IT (with high-est motivation for the second group and lowestfor the third group).

Second, and more specifically, the EM modelcould provide ideas about the design of IT train-ing programs. A good training program mustprovide some fun (enjoying/acceptance engage-ment mode) and help students to find the fun,but it must also prepare them for hardships thatmust be tolerated (ambition/curiosity engage-ment mode). It must also help students find theirweak areas (lack of Locus S) as well as thoseaspects in the learning material to which theyshould give their attention (Locus O) in orderto eliminate their weak points.

Third, on a micro level, the EM model mayshed light on the monitoring of IT users’ cogni-tive styles in a specific learning situation and,as a consequence, give useful knowledge on howusers can be helped to find appropriate cogni-

tive styles when learning an IT application. Forexample, consider how IT users’ depth of infor-mation processing (i.e., concentration on theunderlying meaning of available information oron shallow surface characteristics; Craik &Lockhart, 1972) is associated with engagementmodes. It may be hypothesized that a combina-tion of the enjoying/acceptance and ambition/curiosity engagement modes is associated withdeeper information processing (seeing it as en-joyable to understand) than is the efficiency/productivity engagement mode, especially whenthis engagement mode is associated with frus-tration/anxiety. In the latter case, it may be ex-pected that IT users will be less reflective andmore likely to repeat previous mistakes insteadof going to the root of the problem when theyget stuck. Obviously, it will be of great impor-tance to know whether engagement modes arecauses (and not only effects) of cognitive styles.Knowledge of this causality may help both ITusers and IT designers to improve the condi-tions for learning IT applications.

ACKNOWLEDGMENTS

This research was supported by Grant No.1998-0239 from the Swedish Transport andCommunication Research Board.

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Henry Montgomery is a professor in the Depart-ment of Psychology at Stockholm University. Hereceived his Ph.D. in psychology in 1975 at Gothen-burg University.

Parvaneh Sharafi is a research associate in the De-partment of Learning, Informatics, Management, andEthics at the Karolinska Institute, Stockholm, Swe-den. She received her Ph.D. in psychology in 2004at Stockholm University.

Leif R. Hedman is an associate professor in the De-partment of Psychology at Umeå University. Hereceived his Ph.D. in psychology in 1978 at LundUniversity.

Date received: November 29, 2001Date accepted: February 27, 2003

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