Exploring People’s resistance

to the Active User Paradox

including personality traits

An investigation of the relationship between

people’s resistance to the Active User

Paradox and the role of geekism, need for

cognition and computer anxiety

Bachelorthesis

Wiebke Stöhr

s1340182

June 2015

University of Twente

Department of Behavioral Science

Human Factors & Engineering (HFE)

Examination Committee

Dr. Martin Schmettow

Dr. Matthijs Noordzij

Table of Contents

Abstract………………………………………………………………………………………3

Samenvatting………………………………………………………………………………...4

1. Introduction……………………………………………………………………………...5

2. Method…………………………………………………………......................................9

2.1 Participants…………………………………………………………………………....9

2.2 Apparatus…………………………………………………………………………….10

2.3 Procedure…………………………………………………………………………….11

2.4 Personality measures………………………………………………………………...11

2.5 AUP measures………………………………………………………………………..12

2.6 Research Design……………………………………………………………………..21

2.7 Data analysis…………………………………………………………………………22

3. Results…………………………………………………………………………………...22

3.1 Demographics………………………………………………………………………...22

3.2 Descriptives…………………………………………………………………………..23

3.3 Hypothesis testing…………………………………………………………………....26

4. Discussion…………………………………………………………………………….....28

4.1 Limitations…………………………………………………………………………...34

4.2 Future Research………………………………………………………………………35

4.3 Conclusion……………………………………………………………………………35

References

Appendix

3

Abstract

The following study aimed at exploring people’s resistance to the Active User Paradox (AUP)

with regard to several personality traits. Hypotheses were formulated relying on the

personality traits geekism, need for cognition and computer anxiety and their association with

the AUP. Therefore, this study tries to unravel the AUP through focusing on personality traits

that could influence people’s resistance to the AUP.

To assess people’s resistance to the AUP, an experiment was carried out that measures

the effort that people invest to solve tasks on an explorative- and challenge seeking level. The

experiment consisted of several tasks that had to be solved using the graphical program GIMP

and the Word processor WORD. To gather data about the personality traits geekism, need for

cognition and computer anxiety of the participants, several questionnaires were used. 28

respondents participated in this study. The data were analyzed using correlation analyses

between people’s resistance to the AUP and the personality traits.

The results imply that there is a moderate to strong association between people’s

resistance to the AUP and a high level of need for cognition. Furthermore, people’s resistance

to the AUP was positively associated with geekism and negatively associated with computer

anxiety. This study can serve as a starting point for further investigations on the AUP and

personality traits.

4

Samenvatting

Het doel van deze studie is het verkennen van de relatie tussen het „Active User

Paradox“ (AUP) en verschillende karaktereigenschappen. Daarbij wordt vooral gekeken naar

de mate aan weerstand die mensen kunnen bieden aan het AUP afhankelijk van verschillende

karaktereigenschappen zoals geekism, need for cognition en computer anxiety. Hypothesen

werden ontwikkeld om de relaties tussen deze karaktereigenschappen en het AUP te

onderzoeken.

Om de weerstand van de respondenten tegen het AUP te meten wordt een experiment

uitgevoerd. Daarbij moeten de respondenten verschillende taken aan de computer doorlopen.

Deze moeten worden opgelost met het grafiek programma GIMP of het Woord programma

WORD. Om de weerstand tegen het AUP te meten wordt gekeken hoeveel moeite mensen

besteden aan het oplossen van deze taken met het oog op hun exploratief- en uitdagend gedrag.

Op basis van deze observaties wordt later een som voor het AUP berekent. Deze som wordt

dan op hun relatie tot de karaktereigenschappen geekism, need for cognition en computer

anxiety onderzoekt. De data voor de karaktereigenschappen worden via vragenlijsten

verzameld. Deze moeten de respondenten invullen zodat hun score voor de desbetreffende

schaal kann worden berekend. De data van het AUP en de karaktereigenschappen werden dan

geanalyseerd met correlatie analyses.

De resultaten wijzen erop dat er een sterke positieve associatie bestaat tussen de

weerstand die mensen kunnen bieden aan het AUP en need for cognition. Verder werd er een

positieve associatie gevonden tussen het AUP en geekism en een negatieve associatie tussen

het AUP en computer anxiety. Deze resultaten geven inzicht in hoeverre de karakter van een

mens zijn weerstand tegen het AUP kan bepalen. Dit kann als aanknopingspunt voor verder

onderzoek fungeren.

5

1. Introduction

The 21st century is dominated by a growing market of new technologies and innovations.

Technology pioneers of this century like Steve Jobs or Mark Zuckerberg have driven this

progress nearly to its optimum and the research on technology still continues. Researchers are

continuously busy making systems more efficient through upgrading old functions or adding

new functions to a system. These rising changes of technology present people with the

challenge of dealing with always becoming complexer systems (O'Brien, 2007).

Concentrating on the development of new innovations, progressive technologies and

complexer systems, engineers often forget the users. Are the users really prepared for the

challenges of new complexer technologies?

There are observations of users that are not able to deal with the ever-growing supply

of new systems and functions. Several user studies done at the IBM User Interface institute in

the early 1980s showed that users do not read manuals but start using new software

immediately (Nielsen, 1998). Out of these observations, Carroll and Rosson (1987)

introduced the “paradox of the active user” (AUP). This paradox deals with the fact that users

immediately get active starting to use a new software without making any effort to read its

manual first or go through other learning processes to save time and get their task done

quickly. The paradox that arises out of this fact is that users would save more time in the long

term as they would take some time learning about the software first so that they can optimize

the operation of the new software (Carroll & Rosson, 1987). But is this paradox applying to

all users?

There are indications for individual differences between users in dealing with new and

complex technologies (Schmettow, Noordzij, & Mundt, 2013). What is it for example that

made Steve Wozniak (co-founder of Apple) able to invent a new software system while some

people are not even able to handle this system?

Some people seem to be better at operating complex systems than others and this gives

the impression that those people must have special abilities. From this assumption derives the

concept of “geekism” which states that some people, called geeks, are more computer

enthusiast than others, (Schmettow & Drees, 2014) and therefore appreciate the intellectual

effort to master a technical system (Schmettow et al., 2013). These and other characteristics of

the so-called geeks could explain why some people are capable of dealing with complex

computer systems while others are not. Therefore, it may help to unravel the active user

paradox. But before investigating on the active user paradox and the concept of geekism,

these terms need to be clarified.

6

The active user paradox

The active user paradox was established by Carroll and Rosson (1987) in an age where the

computer was becoming a “powerful and sophisticated information processing technology”

(Carroll & Rosson, 1987) in the everyday life of people. Carroll and Rosson (1987) describe

this period as a paradigm shift in people's way of thinking of computers. As people in earlier

times have still been thinking of computers as helping machines to do things for them, people

nowadays think of computers as machines that will think for us due to technological

development. Therefore, people got increasingly problems with computer use. Carroll and

Rosson (1987) pick up 2 problems and describe them as true paradoxes: (1) people have

considerable trouble learning to use computers and (2) their skills tend to asymptote at

relative mediocrity. These problems arise from conflicting motivational and cognitive

strategies. The production bias is responsible for the motivational paradox and the

assimilation bias for the cognitive paradox. The production bias describes the problem that

people want to produce output which let them focus on their work but at the same time

reduces their motivation to spend time on learning about the system they use to produce

output. Therefore, they use old known procedures, regardless of their inefficacy. On the other

hand, the assimilation bias derives because of the fact that “people apply what they already

know to interpret new situations” (Carroll & Rosson, 1987). Carroll and Rosson (1987)

describe these as “fundamental properties of learning” that arise to new users as well as to

experienced users. Due to the authors, these problems arise because people do not have

enough knowledge to act but do it anyway and strike out into the unknown. They ignore what

is not known to them and interpret what there can be interpreted, no matter how. The active

user paradox appears in a “learning-to-use-a-computer situation” (Carroll & Rosson, 1987)

where users just try out things and try to relate what they already know to what is going on

instead of reading instructions or manuals that would simplify the operation with an unknown

system or function. The authors made suggestions for interface design to overcome the

obstacles of this paradox.

Bhavnani and Bonnie (2000) support these findings in their paper by mentioning that

“several studies […] have shown that despite experience, many users with basic command

knowledge do not progress to an efficient use of applications.”. This shows that even users

with experience can not overcome that obstacle. The authors mention explanations for the

inefficient use of IT based problems under 2 broad categories: (a) efficient strategies not

known and (b) efficient strategies are known but not used. Category a can be compared to the

production bias, mentioned by Carroll and Rosson (1987), which also states that people stick

7

to old known strategies by learning a new system or application instead of learning about new

efficient strategies while category b shows similarities to the assimilation bias. However,

Bhavnani & John (2000) conclude that users must learn an intermediate layer of knowledge

that lies between the layers of tasks and tools as task and tool knowledge is not sufficient.

They suggest that “the cost of learning and applying efficient strategies can be easily

addressed by proper strategic instruction.”

Fu & Gray (2004) also addressed the paradox of the active user by mentioning that

“past experiences of procedures influence future choice of procedures”. As the major factors

affecting those future choices, the name “(1) frequency of use, (2) effectiveness (or accuracy),

and (3) efficiency (or speed)” (Fu & Gray, 2004). In a more general manner, they state the

principle of stability as a possible explanation affecting future choices. From their analyses,

the authors conclude that people choose to use suboptimal procedures even when they

apparently had knowledge of better procedures so that they do not follow the normative

principle of rationality but more a principle of past choices that have shown stability in

frequency, effectiveness and efficiency.

Carter et al. (2011) also pick up the frequency of past use as a possible factor that

prevent users from the efficient use of complex applications. The authors link this factor with

the concept of habit that has an inhibitory influence on user's efficiency. They link the factor

computer anxiety to their concept of habit that inhibits user's willingness to innovate with IT-

based routines. In contrast, the authors mention the concept of “IT mindfulness” as being a

success factor for the efficient use of IT based routines. This concept is linked to computer

self-efficacy, meaning the belief of one's capability to use the computer (Sam, Othman, &

Nordin, 2005). The authors take the work of Carroll and Rosson (1987) into consideration

while linking the production bias to their concept of “IT mindfulness” and the assimilation

bias to their concept of “habits”. The concept of habits is linked to computer anxiety, which

has been defined as “a fear of computers when using one, or fearing the possibility of using a

computer” (Barbeite & Weiss, 2004) due to affective responses such as “as a reaction of fear

and apprehension, intimidation, hostility, and worries that one will be embarrassed” (Heinssen

et al., 2987). This could be an important factor in people's ability to learn computer skills and

use computers. This assumption is further supported by Sam et al. (2005) who stated that

“lower computer anxiety levels could be important factors in helping people learn computer

skills”. To summarize the findings of Carter et al. (2011), computer anxiety is expected to

have a negative impact on an individual’s propensity to innovate and IT mindfulness is

expected to have a positive impact on this propensity. The authors go even further in

8

suggesting that “individuals who are not predisposed toward novelty seeking or novelty

producing behavior are more susceptible for production bias” (Carter et al., 2011). To be

novelty seeking and novelty producing are characteristics we also found in the concept of

need-for-cognition (Cacioppo & Petty, 1982). As the concept of IT mindfulness shows many

similarities to the concept of need-for-cognition, that will be investigated during this study in

association with the AUP, it is not of great importance for this study. We will concentrate on

the concept of computer anxiety instead that could be worth investigating in association with

geekism as a possible predictor for people’s resistance to the AUP. But first, we should take a

closer look at the concept of geekism.

Geekism

As mentioned earlier by Carter et al. (2011) IT mindfulness is linked to the concept of need

for cognition (Cacioppo & Petty, 1982) as both state an individual's predisposition toward

novelty seeking and novelty producing behavior. With the need for cognition-scale, Cacioppo

and Petty (1982) sought to identify differences among individuals in their tendency to engage

in and enjoy thinking. Their analyses revealed that the need-for-cognition scale can give

information on “people's tendency to enjoy complex problem-solving activities”. Schmettow

(2013) describes geekism with people’s need to explore that leads them to a better

understanding of technology. Furthermore, Schmettow (2013) argued that the “tendency to

enjoy intellectual challenges must be a precondition for geekism.”. This means that only

people scoring high on the need-for cognition-scale, can be called geeks. Therefore, the need

for cognition scale can serve as an instrument to measure geekism. Additionally, Schmettow

(2013) introduces the concept of geekism under the assumption that those people are

computer enthusiast. This trait can be measured by a newly constructed Gex scale and can

also serve as an indicator of geekism. Besides, it would be interesting to investigate to which

extent computer anxiety, as mentioned by Carter et al. (2011) and Sam et al. (2005), is linked

to the concept of geekism.

Next to the mentioned concept of geeks, there is also another by O'Brien (2007) who

speaks of “gifted geeks” in terms of computer technology talent. O'Brien interviewed

technological involved people to get to know what characteristics of giftedness they show and

how these help them operating with technological systems effectively.

An implicit test of Users experience by Schmettow et al. (2013) showed that people

identified as geeks have different associations with Computers than others. They associate

computers with exploration and intellectual mastery (Schmettow & Drees, 2014; Schmettow,

9

Noordzij, & Mundt, 2013) which could lead to the assumption that geeks have a stronger

intrinsic motivation to learn complex IT functions. This could also mean that they have higher

cognitive abilities. White et al. (1997) suggest that cognitive style affects programming

performance and that high cognitive abilities must be available for effective programming.

Regarding these studies, there are reasons to believe that the abilities that characterize

geeks are associated with an effective strategy use of complex computer systems. This could

indicate that there is a relation between geekism and the AUP. It must be investigated if geeks

can overcome the active user paradox due to their special abilities and resources or if they are

also prone to the active user paradox. Additionally, when dealing with geekism, the concept of

Need-for-cognition should be taken into consideration. It seems to be associated with geekism

and the AUP. Furthermore, there seems to be an association between computer anxiety and

geekism that could also influence the AUP. It should be clarified to which extent computer-

anxiety influences this association. Out of these investigations, the following hypotheses can

be drawn.

1. A high score on the Geekism Index is positively related to people's resistance to the

AUP.

2. A high score on the NCS is positively correlated to people's resistance to the AUP.

3. A High score on the Computer Anxiety Rating scale is correlated to people's

resistance to the AUP.

2. Method

The purpose of the experiment is to explore people's resistance to the AUP with regard to

certain character traits. To assess people's resistance to the AUP, several tasks were invented

with the aim of measuring the effort that people invest to deal with the tasks. To assess

people's resistance to the AUP, it will be analyzed to what extent people show challenging-

and explorative behavior people during the tasks.

Additionally, the participant's tendency for the character traits geekism, Need-for-cognition

and computer anxiety will be assessed with the help of questionnaires. Later, it will be tested

if there are associations between these character traits and people's resistance to the AUP.

2.1 Participants

For this study, a sample of N=28 participants is chosen. The only necessary condition

participants must fulfill is having at least basic experience with computers and used Microsoft

10

Paint or a comparable graphics program at least once. Persons with color blindness can not

participate. The sample is composed of German participants. To find participants, the

convenience sampling technique will be used. This means that participants are selected

because of their convenient accessibility and proximity to the researcher. As additional

recruiting strategy, the Sona system will be used. It is an online platform where registered

students can choose from a pool of research studies at which study they want to participate.

For their participation they get creditpoints that are a necessary condition for their Bachelor's

degree. Besides, the researcher will search for participants himself through asking friends or

family members for their collaboration.

2.2 Apparatus

For the execution of the experiment, the used computer must be prepared with the necessary

software. Therefore, GIMP, Word and Morae recorder must be installed.

GIMP is a graphical program, comparable to Photoshop, which will be used for the

execution of the tasks. The tasks are composed of several pictures showing different colored

objects like circles, stars and lines. In the instruction form, the participants will be asked to

change the objects, for example to change the color of certain objects, or to erase certain

objects. This is only possible through using the tools of GIMP which means that the

participants have to take a closer look at the graphical program to get used to the functions

and procedures of GIMP.

One further software that is needed for the experiment is the writing processor WORD.

It is needed for further tasks where the participants have to modify certain words of an

available text (e.g. change the colour or letterstyle, underline the words, make them bold).

Therefore, they must use the functions of WORD. These tasks and also the GIMP tasks have

the purpose to challenge the participants and to see how they deal with these challenges on an

explorative- and challenge seeking level. These insights into the participant’s behavior will

later function as a way for assessing the participant’s resistance to the AUP.

The key element of this experiment is the Morae Recorder. It is a video software that it

used to record the participants while they are busy carrying out the tasks. The researcher will

use these videos later for the behavior- and event coding of the participant’s actions. Only

through this qualitative analysis, the researcher can come to a conclusion of the participant’s

resistance to the AUP. Therefore, a scoring guide was constructed. The apparatus will be

described in detail during the further procedure.

11

2.3 Procedure

At the beginning of the experiment, the participants will be informed about what they

can expect and then asked to give their informed consent. After they have signed the informed

consent, the experiment can start. Therefore, the participants receive the printed instructions.

At first, they have to carry out three tasks by using the graphical program GIMP.

Therefore, the participants get a tool guide where the function of every available tool is

described shortly. The participants are free to use every available tool to solve the task as

good as possible. However, they must explore how to deal with these tasks through using the

available tools.

After that, they have to do six tasks using the writing software WORD. There are free

to use every function that is offered by WORD but there is no help guide provided as with the

GIMP task. Again, the participants must explore how to deal with these tasks through using

the available functions of WORD by themselves. During the whole experiment, the

participants are allowed to ask technical questions but the researcher will not answer

questions about the tasks.

After the participants have finished the tasks on the computer, the questionnaires will

be given to them by pen and paper and they are asked to fill them in. After finishing the

questionnaires, the experiment ends and the participants will be informed about the purpose of

the experiment by the researcher.

2.4 Measurement of Personality traits

Different questionnaires will be used to test the personality traits of the participants with

regard to their need for cognition, their predisposition for geekism and their level of computer

anxiety.

To test the need for cognition, the need-for-cognition scale of Cacioppo & Petty (1982)

will be used. For testing the predisposition for geekism, the GEX scale, developed by Sander

and Schmettow (2013), will be used and to test the amount of computer-anxiety of a person,

the Computer Anxiety Rating Scale 'CARS' of Heinssen et al. (1987) will be used.

2.4.1 Geekism Index (GEX)

The Gex scale was invented by Sander and Schmettow (2013) to identify people that show

intellectual abilities when it comes to the use and interaction of technological products. These

people could be identified as geeks. With the GEX scale, peoples' tendency for geekism will

be measured. People who score high on the scale, are meant to have a high predisposition for

12

geekism. The questionnaire consists of 15 items that should be answered using a 5 point

Likert-scale. The items cover important aspects of geekism like “understanding of technology”

etc. (Schmettow & Drees, 2014) as it is assumed that geeks have a drive to understand

technical systems, modify and play with them (Schmettow et al., 2013).

The reliability of the scale is α=.96 (Sander and Schmettow, 2013). Sander and Schmettow

(2013) measured the construct validity of the scale through correlational measures with a

scale measuring Material-Possession-Love MPL, a scale measuring the Need for Cognition

and an implicit test measuring geekism. The convergent validity was estimated as acceptable

with a significant correlation between the implicit test and the geekism scale (r=0.53).

2.4.2 Need for cognition scale (NCS)

The need-for-cognition scale was developed by Cacioppo and Petty (1982). As the name

already indicates, it measures to what extent people are willing to explore and learn new

things. The scale consists of 18 items that must be answered with the help of a 7 point-Likert

scale. A high score means a high need for exploration and learning new things while a low

score indicates a low need for learning new things and being explorative. The reliability of the

scale is α=.77 and it appears to be valid as it correlates with relevant constructs (Cacioppo and

Petty, 1982). Additionally, a moderate correlation between NCS and the GEX can be found

(r=.357), indicating that the NCS and the GEX scale measure similar concepts ( Sander and

Schmettow, 2013).

2.4.3 Computer Anxiety Rating Scale (CARS)

The Computer Anxiety Rating Scale (CARS) was found by Heinssen, Glass & Knight (1987)

to measure the amount of computer anxiety that can be seen as a result of people’s “fear and

apprehension, intimidation, hostility, and worries that one will be embarrassed, look stupid, or

even damage the equipment”. Higher scores on the scale indicate higher levels of computer

anxiety. The scale consists of 19 items that have to be rated on a 5 point Likert Scale.

The reliability of the CARS is α=.87 and it was validated by founding correlations with other

relevant constructs like Computer Attitudes scales and fear thermometers (trait, math and text

anxiety) (Heinssen et al., 1987).

2.5 Measurement of people’s resistance to the AUP

The purpose of the experiment is to measure the tendency of individuals to be influenced by

the Acive User Paradox (AUP) when they are confronted with repetitive computer tasks. This

13

AUP tendency is ten related to the personality traits of need for cognition, geekism and

computer anxiety. The tendency of the user to fall for the AUP will be assessed on an

explorative and challenging level. In the following paragraph, the tasks of the experiment will

be described.

2.5.1 Tasks

GIMP

The participant has to fulfill three tasks with the graphical program GIMP as described in the

instructions form.

Task 1

In the first task, the participant sees a picture of stars and circles where the stars are red

colored and the circles blue. The participant gets the instruction to remove all objects with a

red color. After finishing that, the participant gets four more of the same pictures but the

colors of the objects have changed. For each picture, the participant has the same task which

is to remove objects with a particular color. He is free to use all the tools he likes.

Figure 1. Gimp Task

Task 2

In the second task, the participant gets a picture with circles and stars again. This time it is his

task to change the color of particular objects, for example to color all blue objects green. After

finishing this task with the first picture, the participants gets four more pictures where the

14

objects remain the same but the colors have changed. The participant has for each picture the

same task which is to change the color of particular objects. He is free to use all the tools he

likes.

Task 3

In the third task, the participant gets a picture of stars and circles again but this time, there are

also lines between the objects in the picture. His task is to remove all lines in the picture

without damaging the objects. After finishing this task for the first picture, the participant gets

four similar pictures where only the color of the objects has changed but he has to carry out

the same task. He is free to use all the tools he likes. An illustration of this task can be found

in the appendix.

WORD

After finishing the tasks with GIMP, the participant has to carry out six more tasks within

Word. Therefore, the participant gets a text of the sun, retrieved from Wikipedia, which is

divided into five paragraphs and where several words are marked blue.

Figure 2. Word Task

Task 1-5

The first task of the participant is to change all marked words in the first paragraph so that

they are underlined, bold, written in the font type “Times New Roman” and red colored.

15

In the following four tasks, the user has to format the marked words of the following parts in

the same way as in the first task except for the fact that the color in which he should change

the words changes for each paragraph.

Task 6

In the sixth and last task, the participant has to change all titles of the text, so that there are

bold, written in the font type Times New Roman, font size 12 and black colored. Additionally,

the participant has to add a numbering for each title (e.g. “1. First paragraph”).

2.5.2 Scoring

The scoring procedure starts with a qualitative analysis of the user's behavior through the

video recording. These results will then be transformed into quantitative scores to make the

AUP measurable. In the following paragraph, the scoring procedure will be described in detail.

Behavior Coding

At first, the video recordings will be evaluated. Having a look at the video recordings, the

researcher can identify in which way the participant has tried to solve the tasks. The

researcher will assess these video observations through behavior- and event coding. Starting

point is a classification system with a certain structure. Here, the methods the participant uses

are noted as well as the time it takes and the parameters used. An example of such a scoring

table can be seen in the following table 1.

Table 1. Example of a Scoring Table

Participant Task Subtask Observation Time Duration Methods Parameter

3 2 1 1 00:02:03 00:00:57 RH DU

3 2 2 2 00:03:00 00:00:40 ER DU

3 2 3 3 00:03:42 00:00:04 BF SP

3

…

2

…

4

…

4

…

00:03:47

…

00:00:04

…

BF

…

SP

…

Operator Characteristics

With the help of a coding schema, the methods that the participant has used will be evaluated

on the basis of five characteristics: the specificity, the difficulty, the complexity, the delayed

16

feedback and the parameter demands. Each method that is used will be analyzed on the basis

of these characteristics to calculate the AUP scores later. For each method (operator), it will

be evaluated if the particular characteristic is low, moderate or high. As the scoring of the

operators can be very subjective, all operator characteristics were scored by three raters and

the inter rater reliability was assessed. The final results of the evaluation of these operator

characteristics can be seen in table 2. In the following paragraph, the operator characteristics

will be described shortly.

The specificity of a method is defined by the amount of tasks that can be solved with it

and the amount of different objects that can be manipulated with it. An example of a tool with

a low specificity is the eraser as it can be used for almost all tasks and all objects of the

experiment. More specifically, it can be said that the eraser can be used for all tasks where the

participant must erase certain objects or parts. Additionally, the eraser can be applied to all

objects. In contrast, a tool with a high specificity is the invert selection as the user can only

modify certain objects by using this tool. Besides, this tool can only be used for specific tasks

of the experiment. In summary, it can be said that the specificity of a tool can give an insight

into the user’s mind with regard to the AUP as it shows if the participants choose to use

suboptimal procedures, affected through following a principle of past choices that have shown

stability or if they are more explorative following a principle of rationality that would predict

the use of a more specific tool (Fu & Gray, 2004). Tools with high specificity often lead to

time-saving solutions while it takes more time to solve the tasks when using tools with low

specificity. It is assumed that people, who show a higher resistance to the AUP, tend to choose

a time-saving method.

The difficulty of a method is defined by the expected required experience of the user

with the method or similar operators as well as the expected frequency of use. For example,

the eraser tool of Gimp is defined as a method with a low difficulty as it is easy to use and

most people are familiar to it. Many people recognize the function of the tool when they see

the picture of the eraser or they have already used a similar tool with another graphical

program. Additionally, it is easy to use as the participants just need to press the mouse and

then click on the area they wants to erase. Most tools that are easy to use are not as efficient as

tools that are a bit more difficult to use. Therefore it is assumed that people who choose tools

with a higher difficulty, want to solve the task more efficiently and faster and are therefore

less prone to fall for the AUP. Besides, participants who choose for a more difficult method,

show challenge-seeking behavior which leads to a higher resistance of the AUP. People, who

choose a more difficult tool, invest more time to explore how it works in the beginning but in

17

the end they normally save time as they can solve the task with such a tool faster and more

efficiently. In this way, participants can overcome the production bias as described by Carroll

& Rosson (1987), which increases their resistance to the AUP.

The complexity of a method is defined by the amount of available options or

parameters. For example, the color select tool is defined as a tool with a moderate complexity

as the participant can change some parameters to make that tool working more efficiently. The

more complex a tool is, the more functions of the tool can be changed and the more efficient

the tool can be made. This means that people can solve the task more efficiently if they

choose a tool with a high complexity as they can better adjust the functions of the tool so that

it fits with the tasks. The pencil for example is a tool with a high complexity as people can

adjust several parameters of the tool like the color, size, etc. Therefore, they can make the tool

more precise. However, they have to invest more effort at the beginning with the adjusting of

the parameters than they would have to invest in a simple tool but in the end, the result will be

better. Bhavnani and Bonnie (2000) have shown that despite experience many users with

basic knowledge do not make us of the most efficient applications and they suggest that this

results of not knowing the most efficient strategy or the users know them but do not use them.

Therefore, we suggest that people who explore with complex tools get to know the most

efficient strategy and are assumed to have a higher resistance to the AUP than people who

show less explorative behavior.

The delayed feedback describes that a visual change is not directly visible in the file,

or a preview window after each click. All tools of GIMP are characterized as having a low

delayed feedback as the participant can see the change directly after each click. For example

when he uses the bucket fill tool to change the color of an object, he directly sees the

changing color when he presses with the bucket fill tool on the object so that an object that

was originally green turns into red for example. All tools of GIMP have a low delayed

feedback so that the mental effort necessary to imagine what change would be triggered by

using a certain tool is very low. This is different when using the word processor WORD as

participants first had to adjust certain parameters after they could see the changes. It is

assumed that people who show great levels of mental effort as supposed for geeks

(Schmettow & Passlick, 2013) could imagine a visual change even it is not directly visible in

the file easily. This helps them operating with technological systems (O’Brien, 2007).

Therefore, dealing with delayed feedback seemed to increase people’s resistance to the AUP.

Parameter demands are defined by the necessity to change parameters (good defaults,

change recommended, change required). To solve certain tasks it is required to change the

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parameters of the tools, for example when the participants have the instruction to change the

color of certain objects. Then, they have to adjust the color of the tool they use. Therefore, the

pencil tool is an operator with moderate parameter demands as people must choose a new

foreground color when using it and also could change the tool size or effects. Contrary to the

pencil, the Cut selection tool has low parameter demands as there are no changes necessary

when using it. People just have to press the del key or select the edit>cut function in the

program to delete an object. No parameter changes are needed. Tools with high Parameter

demands are more difficult to use as they have a higher complexity and can thus be regarded

as tools that support challenge-seeking and explorative behavior. This leads to the supposition

that participants who use these tools and get used to the parameter demands can overcome the

production- and assimilation bias (Carrol & Rosson, 1987) resulting in a higher resistance of

the AUP.

To summarize these operator characteristics in association with the AUP, it can be said

that Persons who are assumed to have a high resistance to the AUP are more likely use and

explore operators (tools) with high specificity, difficulty, complexity, parameter demands and

delayed feedback. This is linked to the supposition that people who are less prone to the AUP

show more willingness to search for methods that might increase their task efficiency and

effectiveness than others, even if this would require additional cognitive effort.

Table 2. Scoring Table Operator Characteristics

Method

ID

Operator Description Specifity Difficulty Complexity Delayed

feedback

Paramter

demands

CU Cut

selection

The participant

presses the del key or

selects edit>cut. This

deletes the currently

selected area.

high low low low low

IS Invert

selection

The participant

presses select>invert.

This inverts the

currently selected

area.

high low low low low

PE Pencil The participant

optionally selects a

new foreground color

and a tool size, keeps

the mouse button

pressed and moves the

mouse arrow over an

object.

low low high low medium

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PA Paintbrush The participant

optionally selects a

new foreground color

and a tool size, keeps

the mouse button

pressed and moves the

mouse arrow over an

object.

low low high low medium

ER Eraser The participant

optionally selects a

tool size, keeps the

mouse button pressed

and moves the mouse

arrow over an object

low low high low medium

RS Rectangle

select

The participant

presses and pulls the

mouse to select in area

in form of a rectangle

medium low high low low

ES Ellipse

select

The participant

presses

and pulls the mouse to

select an area in form

of

an ellipse.

medium low high low low

FS Fuzzy

Select

The participant

optionally

modifies the threshold

and selects an area

with a

similar color by

clicking

on it.

medium medium high low medium

Exploratory Behavior

Besides the scoring of operators, exploratory behavior will also be assessed as it is assumed

that a low AUP tendency expresses itself in the willingness to explore the system more deeply.

On the one hand, this can be assessed by the methods and tools the participant users, on the

other hands explorative behavior can be seen in additionally procedures the participant does.

Three operators are categorized as indicating exploratory behavior: Look up function (LF),

Read Handout (RH) and Undo (U).

LF is an operator that shows explorative behavior as it indicates that the participant

invests effort to look up a certain function. This is explorative behavior that can make a

difference in user’s resistance to the AUP.

The operator RH is characterized as an indicator to measure to what extent the

20

participant is willing to invest time to read about the functions of the program. He gets the

opportunity to read the provided handout that describes the different functions of the tool. The

time he invests and the frequency he makes use of this help, are an indicator of his explorative

behavior.

The operator U is defined as explorative behavior as it indicates that the user himself

recognizes that it is better to undo a previously issued function. This self-knowledge is a first

step to self-improvement, meaning that the participant searches for a better way to solve the

task which shows highly explorative behavior.

The scoring and summary of these functions can be looked up in the following table.

Table 3. Scoring table Exploratory behavior

Operator ID Operator Description Parameters

LF Look up function user opened help system

to find out

about a specific

function. This is

scored per viewed

function.

Duration

RH Read handout User reads the provided

handout

Duration, function

U Undo User undoes a

previously issued

function

Scoring Parameters for Operators

Operators might be used with the default parameters when the parameter demands are not

high, as well as when the parameters were already modified before. As the use of default

parameters needs less cognitive effort, modification of parameters is also coded as noted in

table 4.

Default use (DU) means that the user uses a method without changing parameters.

This suggests that the participant does not invest much effort.

If the participant Sets parameters (SP) for a method, it indicates that he invests more

effort and therefore shows higher cognitive abilities that could protect him from falling for the

AUP.

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Table 4. Scoring Table Parameters

Parameter ID Parameter Description

DU Default use User uses a method

without changing

parameters

SP Set parameters User sets new parameters

for a method

AUP scores

Relevant variables to calculate these AUP resistance measures are: set parameter amount,

method diversity, read handout duration, undo amount, mean specifity, mean difficulty, mean

complexity, mean delayed feedback and the mean parameter demands. The scoring procedure

for these variables was already described above (see table 2,3 and 4).

Two summary scores will be calculated out of these variables through standardizing

the z-scores of the Challenging- and Explorative behavior and calculating the mean scores. As

a result, we have two variables measuring people's resistance to the AUP:

1. Exploratory behavior: persons with low propensity for AUP should show stronger

urge to find out the possibilities of the system.

2. Challenge seeking: persons with a low tendency for AUP should show a stronger will

to master the task in the most appropriate way, which is observed as choice of more

specific, complex and difficult to use functions.

2.5 Research Design

For this study, a mixed method design is chosen that will be carried out under two different

conditions: with manipulation and without manipulation. In the manipulation condition, the

researcher will not tell the participants that they have to perform the same tasks several times.

To guarantee that the participants do not know that they have to carry out several tasks, every

task is written on a new page in the handbook. The participants were told that they have to

turn over a page after they have finished a task. In the other condition, the participants are

aware of the fact that they have to do several tasks. Therefore, all the tasks are written on one

page so that the users can see how many tasks they have to carry out.

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2.6 Data Analysis

The following Data Analysis is based on a sample of N=28 respondents and gives an insight

into the relationship between personality scores and user's tendency to fall for the Active User

Paradox. The variables that are used for this analysis are the 3 Personality Scales (GEX, NCS,

Computer Anxiety), and the Challenge seeking and explorative behavior variables that

represent the tendency to fall for the AUP. For every respondent these 5 scores were obtained.

It appears that there was no significant variance for the WORD tasks so that these scores were

not relevant for the experiment. Therefore, the AUP scores are only calculated on the basis of

the GIMP tasks.

The AUP scores were calculated through using the following variables: set parameter

amount, method diversity, read handout duration, undo amount, mean specificity, mean

difficulty, mean complexity, mean delayed feedback and the mean parameter demands. After

scoring these variables, the scores were z-standardized and then average scores for

exploratory behavior and challenge seeking behavior are calculated on a range from -1 to 1.

This means that people’s resistance to fall for the AUP can be measured on a challenge

seeking- and an explorative behavior level so that these 2 variables calculated for the

measurement of the AUP.

With the 3 personality variables and the 2 AUP variables, an explorative analysis was

carried out first to get an overview of the distribution of the personality variables (GEX, NCS,

Anxiety) as well as the AUP variables (Challenge seeking, Explorative behavior). Besides, a

descriptive analysis of the 5 variables gives information about the demographic data.

After that, the consistency of the scales was tested through a reliability analysis.

Therefore, for each scale Cronbach’s alpha was calculated.

To test the hypotheses the correlations between the GEX, NCS, Anxiety scale and the

AUP variables are calculated with the correlation coefficient r.

3.Results

The results show the composition of the sample, as well as the distributions of the variables

and confirm some of the drawn hypotheses through showing correlations. The findings are

listed below.

3.1 Demographics

30 respondents participated in the study. As the following table shows, the sample consisted

of 16 female and 12 male respondents as the data of 2 respondents was not usable. The

average age was 23 years, ranging from 19 to 30 (SD=2.33).

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Table 5. Demographic Data

Percent M (SD)

Age 22.68 (2.33)

Gender

Male 42.9

Female 57.1

Note: M=Mean SD=Standarddeviation

3.2 Descriptives

With regard to their expertise, many participants rated their expertise with graphical programs

as low (M=2.53) while many described themselves as experts with Microsoft Word (M=4.25)

on a scale ranging from 0 to 5. The self-assessment of the expertise level for graphical

programs of the participants was very low (M=3.61) . The mean scores for people’s expertise

of certain graphical programs are listed in the table below.

Table 6. Descriptives Expertise

Min Max M (SD)

Exp_Microsoft_Paint 2 4 2.53 (0.69)

Exp_Adobe_Photoshop 1 5 1.82 (0.98)

Exp_MacPaint 1 3 1.11 (0.42)

Exp_GIMP 1 3 1.21 (0.49)

Exp_Paintbrush 1 2 1.11 (0.31)

Exp_Microsoft Word 2 5 4.25 (0.52)

Exp_Graphical programs 0 9 3.61 (1.91)

The mean scores of the personality scores indicate that the participants tend to have a

moderate tendency towards Geekism as the scores are at the middle of the scale (M=.01) and

also towards NCS (M=.12) while most of the participants seem not to be computer anxious

(M=-.38). Considering the AUP scores, people tend not to fall for the AUP as they have

challenge seeking behavior (-.01) while a moderate number of participants show explorative

behavior (M=.01).

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Table 7. Descriptives character traits and AUP

M (SD)

GEX .01 (0.29)

NCS .12 (0.28)

CompAnx - .38 (0.25)

AUP_explore .01 (0.41)

AUP_challenge - .01 (0.28)

Figure 3. Distribution of the variables

Through splitting the variables by gender, it can be seen that the the average score for com-

puter anxiety was much lower for men (M=-0,50) than for women (M=-0,29). Furthermore,

mainly men scored high on the GEX scale (M=0,15) while women scored very low (M=-0,16)

showing not as strong tendencies towards geekism as men. Additionally, men also scored

much higher on the NCS scale (M=0,16) than women who scored at the center of the scale

(.01). On the explorative level of the AUP, men scored much higher (M=0,15) than women

(M=-0,17) showing that men showed much more explorative behavior than women. On the

25

challenge-seeking level of the AUP variable, both genders scored below the center of the

scale. These results can be seen in table and are illustrated in figure 5.

Table 8. Descriptives Variables, splitted by gender

Gender Min Max M(SD)

female CompAnx -.74 .11 -.29(.22)

GEX -.46 .32 -.16(.18)

NCS -.44 .46 .01(24)

AUP_explore -.51 .24 -.17(.20)

AUP_challenge -.41 .46 -.01(.21)

male CompAnx -.79 .08 -.50(.25)

GEX -.67 .65 .15(.35)

NCS -.22 .61 .16(.30)

AUP_explore -.49 1.92 .15(.62)

AUP_challenge -.44 .85 -.05(.39)

Figure 4. Variables splitted by gender

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3.3 Hypotheses testing

The hypotheses were tested through calculating correlations with the correlation coefficient r.

Table 9. Correlations

Gex NCS ComAnx AUP_explore AUP_challenge

Gex r 1 .55** -.73** .20 .25

NCS r .55** 1 -.43* .12 .49**

ComAnx r -.73** -.43* 1 -.20 -.24

AUP_explore r .20 .12 -.20 1 .10

AUP_challenge r .25 .49** -.24 .10 1

* p<0,05

** p<0,01

At first, the hypothesis concerning geekism was investigated. The hypothesis states that a

high score on the geekism index is positively correlated with people’s tendency to resist the

AUP. A positive correlation between AUP_explore (r=.20) and geekism was found as well as

between AUP challenge and geekism (r=.25). These results indicate that people who score

high on geekism show explorative and challenge seeking behavior. However, we cannot

confirm this relation with sufficient certainty (p=0.31; p=.21). Besides, it should be noted that

geekism correlates positively (r=.55) and with strong certainty (p<0.01) with NCS, indicating

that these concepts share some similarities.

Figure 5. Correlation between Geekism and AUP

27

The second hypothesis that NCS is positively related with people’s resistance to the AUP was

tested. Here, a moderate to strong positive correlation between the AUP_challenge and NCS

was found (r=0,49) which can be predicted with strong certainty (p=.008). This means that

people with a high need for cognition tend to resist the AUP due to their challenge seeking

behavior. A weaker correlation was found between NCS and AUP_explore (r=.12). This leads

to the conclusion that people who score high on NCS show some kind explorative behavior

that increases their resistance to the AUP. We cannot confirm this relationship with high

certainty (p=.55).

Additionally, there was a strong negative correlation found between computer anxiety and

geekism (r=-.73) and a moderate negative correlation with NCS (r=-.43). These relationships

can be predicted with great certainty and prove that people scoring high on geekism and NCS

show only low computer anxiety.

Figure 6. Correlation between NCS and AUP

28

Finally, the third hypothesis, computer anxiety is negatively correlated with people’s

resistance to the AUP, was tested. This hypothesis was confirmed through finding a negative

correlation between AUP_explore (r=-0.20) and computer anxiety as well as between

AUP_challenge and computer anxiety (r=-0.24). This would lead us to the assumption that

people with great computer anxiety are not resistant to the AUP while low computer anxiety

can be seen as a predictor for high resistance to the AUP. But, we cannot predict this

relationship with great certainty (p=.31; p=.24).

Figure 7. Correlation between Computer anxiety and AUP

4. Discussion

The aim of the study was to investigate the relationship between people’s resistance to the

AUP and certain personality traits. The main results of the statistical analysis suggest that

people who score high on need-for-cognition have a better resistance to the AUP with regard

to their challenge-seeking behavior than others. This relationship can be predicted with great

certainty. Furthermore, a positive association between geekism and people’s resistance to the

AUP was found as well as a negative relation between Computer anxiety and people’s

29

resistance to the AUP but we can not be certain of these relationships.

In an overall assessment of the study, it can be said that the observations of the

experiment confirm the findings of Caroll and Rosson (1987). During the execution of the

tasks, we observed the production and assimilation bias as described by Caroll and Rosson

(1987). The production bias was observed when people want to solve the task but stick to old

known procedures instead of exploring new ones that would offer more effective and faster

ways of solving the tasks. This is described as motivational paradox (1987) as people want to

produce output but do not show the motivation to explore an efficient and fast way to produce

this output. This behavior was observed during a task where participants should remove

certain objects and used the eraser tool which is very time consuming while other more

effective tools like the color select and delete tool could be used. However, participants

preferred using the eraser tool as it was well known to them and easy to use. Even when they

had to solve many more tasks under the same schema, most participants stick to the old

known procedure and used the eraser.

Additionally, the assimilation bias (Carroll and Rosson, 1987) was observed in these

situations where people only apply what they already know to handle new situations. Carrol

and Rosson (1987) describe this phenomenon as a cognitive paradox where people interpret

situations from what they already know. For example, not many participants made the effort

to read in the provided handout about the functions of unknown tools. They rather stick into

the unknown and just try what is known to them. Consequently, most of them used the eraser

tool for removing objects which is not very effective. The observations show that these biases

appear when people do not invest enough effort to solve the task which leads them into

situation where they tend to fall for the AUP.

Out of these observations, we came to the conclusion that explorative- and challenge

seeking behavior, could increase people’s resistance to the AUP. Therefore we measured

people’s resistance to the AUP on an explorative- and challenge seeking level and looked at

associations with certain personality traits. In the following, the findings for each hypothesis

are described separately in more detail.

The first hypothesis (A high score on the geekism Index is positively related to

people's resistance to the AUP.) can not be confirmed with certainty by the results of the data

analysis. Considering contemporary literature, it was expected that there is a relationship

between geekism and the AUP. Due to Schmettow & Passlick (2013) geeks can be defined as

computer users with “the strong urge and endurance to understand the inner workings of a

30

computer system” which leads to a great affinity with the technological aspects of computers.

Furthermore, Schmettow (2013) argued that the “tendency to enjoy intellectual challenges

must be a precondition for geekism.”. These characteristics seem to be related to the Active

User Paradox as Carroll and Rosson (1982) assume that people who tend to fall for the AUP

do not make enough effort to read a manual first or try out new functions even if this would

help getting the task done faster and in a more efficient way. The intellectual abilities that are

supposed to be present at geeks place when it comes to technological computer aspects could

matter in this affair as they could increase the geeks resistance to the AUP. Therefore, it was

expected that geekism would have a positive impact on people’s resistance to the AUP.

Although a weak to moderate positive relation between geekism and the AUP for explorative

behavior and the AUP for challenge seeking behavior was found, we can not be very certain

of this relation.

One possible reason for this result may be fact that the sample did not cover many

people that could be characterized as geeks. Although the average score for geekism was

nearly in the middle of the scale (M=0,008), the variance shows that some people scored

much higher (see figure 4), indicating that the sample consisted of some people with geek

tendencies. Some scores were even above 0,5 which would show a strong predisposition for

geekism. Therefore it can be concluded that most of the participants scored at the middle of

the scale while some scores indicate strong geekish tendencies. This leads to the conclusion

that the sample contains participants that could be identified as geeks although this number

may be very low (see figure 4). Obviously, mainly male people could be regarded as geeks

because females mainly scored below average on the GEX scale (M=-0,15) while males

scored above average (M=0,15) (see table 4). This could lead to the assumption that a sample

with only male participants could have changed the results as stronger tendencies towards

geekism could have appeared so that the relationship may become stronger and of greater

certainty.

To find another explanation why the relationship between geekism and the AUP was

weak and not certain, we could have a closer look at the concept of geekism as it is a

relatively new concept and not much investigated yet. Therefore, we will take a comparable

concept of Carter (2011) into consideration that also seems to be linked to the AUP.

The GEX questionnaire is divided into 3 subscales that are motivational states,

values/attitudes and the behavior of Geeks (Sander & Schmettow, 2013). Carter et al. (2011)

present the concept of IT-mindfulness which has many similarities to the concept of Geeks,

although it seems to be more specific. With IT mindfulness Carter (2011) describes

31

consciousness awareness for the content and context of IT based routines that allow the user

to be flexible finding new ways of doing. Having a look at Carters conceptualization of IT

mindfulness, we come to know that he described it as a characteristic of people composed out

of four cognitive domains: 1) novelty producing, 2) novelty seeking 3) flexibility and 4)

engagement with the current situation (Carter et al., 2011). This classification is different from

that one of the geekism scale as carter divides his concept into 4 cognitive domains that are

more precise than those of the GEX scale. For example, the GEX subscale ‘motivational state’

is very broad while Carter has already defined the kinds of motivational states that are typical

for this population more clearly in categories as “novelty producing” and “novelty seeking”.

Here, he already makes a clear statement which kind of motivational states belong to people

with IT mindfulness. Furthermore, Carter also specifies the subcategory called “behavior” at

the GEX scale more clearly in his framework as he limits it to “flexibility within different

contexts”. The fourth category “engagement” of Carters framework may also be seen as a

further specialization of the subscale “attitude”. On its overall implications, the author

suggests that high levels of IT mindfulness reflect a tendency towards novelty seeking

behavior in the use of IT which could be positively related to an individual’s ability to deal

with IT applications in their work routines and therefore can be linked to the AUP. This could

lead to the assumption that the concept of IT mindfulness may be a better predictor for

people’s resistance to the AUP than geekism. However, after the comparison of the two

concepts, I come to the conclusion that the concept of IT mindfulness may be easier to

measure as it is more specified while it may be more difficult to measure the concept of

geekism as it is more complex. This does not imply that the concept of IT mindfulness is the

better one just because it is easier to measure. The concept of geekism comprises much more

different elements under his subscales than the concept of IT mindfulness which does not

have such a big scope due to its limited subcategories. This leads to the conclusion that the

concept of geekism may be broader but therefore it captures more people that could be

categorized as potential geeks than the concept of IT mindfulness captures people that could

be categorized as IT mindful. For the assessment of the relation between geekism and the

AUP, this means that the concept of geekism may be a better predictor for the AUP than the

concept of IT mindfulness. However, it must be noticed that there are no studies available

testing the concept of IT mindfulness regarding the AUP.

Besides the possibility that the concept could be decisive for the results, the possibility

that other variables influence the result must be taken into consideration. Having a look at the

rating for graphical expertise where participants should judge their capabilities themselves, it

32

is conspicuous that most participated rated themselves with a very low number. On a scale

from 0 to 10, the average score was M=3, 61(1,91). This could either indicate that most

participants are not familiar with graphical programs or they underrate their abilities. If the

latter was the case, then another variable would come into play: Self Confidence or rater self-

efficacy. As Carter (2011) stated: “unless confidence is tempered by a degree of uncertainty,

openness to new information is likely to inhibited.”, meaning that low self-confidence or self-

efficacy leads people to not being open for the processing of new information so that they do

not spend much effort to solve tasks. This could inhibit people’s explorative and challenge

seeking behavior and may be one further explanation why the results were not significant.

Regarding the second hypothesis (A high score on the NCS is positively correlated to

people's resistance to the AUP.), it is confirmed with great certainty by the results of the

statistical analysis. We found a moderate to strong positive correlation between Need for

Cognition and people’s resistance to the AUP on the challenge seeking level (r=.489). As need

for cognition measures the “tendency to engage in and enjoy thinking” (Cacioppo & Petty,

1982) or in other words degree to which people tend to engage in elaborative thought, it can

be assumed that people who score high on this dimension enjoy challenging activities. This is

associated with the assumption that persons with a low tendency for the AUP should show a

stronger will to master the task in the most appropriate way, which is observed as choice of

more specific, complex and difficult to use functions. This could explain why Need for

cognition and the AUP score for the challenge-seeking variable correlate. It can be concluded

that people who score high on the NCS scale have a higher resistance to the AUP with regard

to their challenge seeking qualities.

On the other hand, NCS did not show a strong correlation with the explore variable of

the AUP. It can be established that people who score high on the NCS scale did not show

many signs of explorative behavior that would be relevant to resist the AUP. However, during

the study we observe participants who showed explorative behavior. For example, when one

participant did not find the tool to color all blue objects green as demanded in the instruction

form, he discovered that he could use green stickers to cover the objects. He uses a green

sticker that had the form of a plant to cover all blue objects with that sticker. Here, the

participant showed very explorative behavior.

However, other variables may also be of great importance. One variable that is also

mentioned by Carter et al. (2011) is computer anxiety. Due to Carter, “someone who is overly

anxious is even more likely to be committed to a particular course of action“. Anxiety about

33

the implications of computer use such as the loss of important data or fear of other possible

mistakes could play an important role why people do not show explorative behavior. This

variable was further investigated within the following third hypothesis.

The third hypothesis (A High score on the Computer Anxiety Rating scale is

negatively correlated to people's resistance to the AUP.) can not be confirmed with certainty

by the results of the data-analysis. However, there was a negative correlation found between

Computer anxiety and people’s resistance to the AUP. It could be expected that computer

anxiety is negatively associated with challenge-seeking and explorative behavior as anxiety

about the implications of computer use such as the loss of important data or fear of other

possible mistakes could inhibit people’s choices. Many participants told during the tasks that

they are scared to do something wrong and after the tasks some participants also reported that

they did not explore a lot or try new tools as they were scared to make mistakes. Some

participants were also scared that it would take too much time to read the handbook or explore

with new functions even if they were told that they have enough time. These statements

would confirm the third hypothesis that a high level of computer anxiety leads to lower

resistance to the AUP as participants were not explorative or challenge seeking when they

were scared to do something wrong. This observation is confirmed through a weak negative

correlation with the AUP variables explore and challenge seeking.

Furthermore, it should be noticed that computer anxiety correlated strongly negative

with geekism. This relationship can be predicted with strong certainty (p<0,01). This leads to

the assumption that people who score high on the CARS have low tendencies towards

geekism. Consequently, geeks show low levels of computer anxiety meaning that one factor

that could influence the positive correlation between geekism and people’s resistance to the

AUP may be the level of computer anxiety.

One further negative correlation of which we can be very certain was found between

computer anxiety and NCS. This correlation shows that a high level of computer anxiety

inhibits people’s ability to explore things and this agrees with the findings about the AUP

which shows that low levels of NCS inhibit people’s resistance to the AUP.

Out of these findings it can be assumed that computer anxiety is a moderator variable

for predicting the relation between geekism and people’s resistance to the AUP and NCS and

people’s resistance to the AUP.

Within the framework of Carter (2011), computer anxiety is also related to the

concept of habit. Carter (2011) states that computer anxiety leads people to rely on well-

34

known procedures. This is connected to the assimilation bias that was described by Caroll and

Rosson (1982) where people stick to well-known procedures when confronted with an IT

problem instead of using advances in technology which would offer more efficient and faster

ways to deal with the problem. This leads the authors to the assumption that “habit is

negatively associated with an individual’s predisposition to create new applications of IT in

their work routines” (Carter et al., 2011) or in other words to fall for the AUP. The feeling of

anxiety when people get confronted with IT problems seems to have a negative influence on

flexible and adaptive behavior and therefore on habits because people who are very anxious

are more likely to stick with a particular course of action. So, the concept of computer anxiety

could be further invented and connected to habits to find significant results.

4.1 Limitations

The study at hand has several limitations and weak points. In the following, these will be

discussed.

At first, it should be said that the sample was composed only of psychology students

what could have limited the results. It could be the case that psychology students do not want

to invest too much effort in the exploration and operation of a graphical program as they

probably could not use this knowledge any further. Therefore, they maybe do not want to

spend much time with these matters as it would not help them during their further study. This

could explain why we did not observe much explorative behavior. It could be better to include

students from graphical or technical studies as they would probably like to explore more with

graphical programs. On the other hand, we probably found no variance within the word tasks

as students have to work with Word Processors like Word a lot, for example for their

homework or other academic assignments. Therefore, students are very familiar with the

functions of Word and this explains why almost all participants used the same procedures to

solve the tasks. Therefore, the results of the Word tasks could not help us predicting people’s

resistance to the AUP. Probably, the results would show greater variance with another

population that is not so trained with Word as students.

Secondly, the gender ratio could be decisive for the results. Especially when it comes

to IT based procedures, men tend to have a better understanding than women. This agrees

with the finding that mainly male participants scored high on geekism while female

participants scored low on geekism. Maybe the results would be of greater certainty if the

sample had only consisted of male participants as they show stronger tendencies towards

35

geekism which was found to be a positive predictor for people’s resistance to the AUP.

Thirdly, the translation of the Computer Anxiety Scale may have influence the results.

It was translated from its original language English into German by the researcher. As some

terms were outdated, it was hard to translate them into German as this could change their

meaning. For example, the first item “I feel insecure about my ability to interpret a computer

printout” was changed into “Ich fühle mich unsicher im Bezug auf meine Fähigkeit einen

Computer Ausdruck zu interpretieren”. The word “computer printout” is hard to translate and

not up-to-date so it turned out that many participants did not know how to interpret this item

in the right way. So, they often asked what was meant by this item. However, it is hard to

change words so that they appear recent without changing the meaning.

Fourthly, the AUP assessment could be improved.. The formulation of the instructions

could be made clearer, for example when the instruction says “color all blue objects green”,

this does not exclude that the background could also be colored green but there are no clear

scoring patterns for those special cases yet. What could be emphasized positively is that the

images of the GIMP tasks contain one object which was harder to color than the other ones.

Having tasks of varying difficulty could show differences in participant’s abilities.

4.2 Future Research

This study is only a first step in the investigation of personality traits and people’s resistance

to the AUP. Within this study, only the character traits geekism, Need for Cognition and

Computer Anxiety were investigated. Obviously, other variables could be of great importance

when it comes to people’s resistance to the AUP. Carter et al. (2011) have presented a helpful

framework to unravel the Active User Paradox. This framework shows similarities to geekism

and need for cognition and could give interesting implications for further research in this area.

4.3 Conclusion

In summary, this study successfully investigated the relation between certain personality traits

and the AUP. A significant positive relation was found between Need for Cognition and the

AUP, meaning that people with a high level of Need for Cognition tend to resist the AUP

better than others. One further certain relation was found between computer anxiety and

geekism as well as between Computer anxiety and NCS. This gives the impression that

computer anxiety functions as moderator variable in the relationships between geekism and

the AUP and NCS and the AUP. Additionally, there were correlations found between geekism

and the AUP and Computer Anxiety and the AUP but we can not be certain of these relations.

Considering these results, it can be concluded that users differ in how much effort they invest

36

to resist the AUP as users with a high need for cognition invest more than others and could

resist the AUP better.

Although there were no significant relations found between geekism and Need for

Cognition and the AUP, this does not necessarily mean that there are no relations. It has been

established that several limitations could have influenced the results and thus further research

is necessary to gain a more secure evidence base for the results.

37

References

Barbeite, F. G., & Weiss, E. M. (2004). Computer self-efficacy and anxiety scales for an

internet sample: Testing measurement equivalence of existing measures and

development of new scales. Computers in Human Behavior, 20, 1–15.

doi:10.1016/S0747-5632(03)00049-9

Bhavnani, S. K., & John, B. E. (2000). The Strategic Use of Complex Computer Systems.

Human-Computer Interaction, 15, 107–137. doi:10.1207/S15327051HCI1523_3

Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and

Social Psychology. Doi:10.1037/0022-3514.42.1.116

Carroll, J. M., & Rosson, M. B. (1987). Paradox of the active user. In J. M. Carroll (Ed.),

Interfacing Thought (pp. 80–111). MIT Press. Retrieved from

http://portal.acm.org/citation.cfm?id=28451

Carter, M., Clements, J. a, Thatcher, J., & George, J. (2011). Unraveling the “ paradox of the

active user ”: Determinants of individuals ’ innovation with it- based work routines.

AMCIS 2011 Proceedings. Retrieved from

http://aisel.aisnet.org/amcis2011_submissions/41

Fu, W. T., & Gray, W. D. (2004). Resolving the paradox of the active user: Stable suboptimal

performance in interactive tasks. Cognitive Science, 28(6), 901–935.

doi:10.1016/j.cogsci.2004.03.005

Heinssen, R. K., Glass, C. & Knight L. (1987). Assessing Computer Anxiety: Development

and Validation of t he Computer Anxiety Rating Scale. Computers in Human behavior ,

3, 49-59

Nielsen, J. (1998). Paradox of the Active User. Nielsen Norman Group. Retrieved from

http://www.nngroup.com/articles/paradox-of-the-active-user/

O’Brien, B. (2007). Gifted geeks: The emergence and development of computer technology

talent. University of Kansas. Retrieved from

http://gradworks.umi.com/32/67/3267198.html

38

Sam, H. K., Othman, A. E. A., & Nordin, Z. S. (2005). Computer self-efficacy, computer

anxiety, and attitudes toward the Internet: A study among undergraduatesin Unimas.

Educational Technology and Society, 8, 205–219.

Schmettow, M., & Drees, M. (2014). What drives the geeks ? Linking computer enthusiasm to

achievement goals. In Proceedings of BCS HCI 2014 - Sand, sea and Sky – Holiday

HCI. Southport, UK.: BCS Learning and Development Ltd.

Schmettow, M., & Keil, J. (2013). Development of an Implicit Picture Story Exercise

Measuring Personal Motives for the Interaction with Technical Products. University

of Twente.

Schmettow, M., Noordzij, M. L., & Mundt, M. (2013). An implicit test of UX: Individuals

Differ in What They Associate with Computers. In CHI ’13 Extended Abstracts on

Human Factors in Computing Systems on - CHI EA '13 (pp. 2039 – 2048). New York,

New York, USA: ACM Press. doi:10.1145/2468356.2468722

Schmettow M. & Passlick, F. (2013). Being Geek – An attempt at building a theory of

geekism. University of Twente

Schmettow, M. & Sander, N. (2013). The construction and evaluation of a questionnaire

measuring geekism. University of Twente.

White, G. L., Ph, D., Sivitanides, M. P., & Marcos, S. (1997). A Theory of the Relationships

between Cognitive Requirements of Computer Programming Languages and

Programmers ’ Cognitive Characteristics, 13(1), 59–66.

39

Appendix

Appendix 1. Gimp Task 3

40

GW.07.130 EINWILLIGUNG NACH AUFKLÄRUNG

Appendix 2. Experiment Material (German version) and Experiment Material (Dutch Version)

including the questionnaires GEX, NCS and CARS

Ich, …………………………………………………………….. (Name des Respondenten)

willige ein, an einer Untersuchung mitzumachen, die durchgeführt wird von

Julian Ebelhäuser & Wiebke Stöhr

Ich bin mir bewusst, dass die Teilnahme an dieser Untersuchung freiwillig ist. Ich kann meine

Teilnahme jederzeit beenden und die Daten, die sich aus der Untersuchung ergeben,

zurückbekommen oder löschen.

Die folgenden Punkte wurden mir erklärt:

1. Das Ziel dieser Untersuchung ist es Einsicht in die Nutzungsmöglichkeiten von

Nutzeroberflächen von Programmen zu bekommen.

2. Meine Aufgabe wird es sein, unterschiedliche Fragebögen auszufüllen und

verschiedene Aufgaben mit den Programmen GIMP und Microsoft Word auszuführen.

Die gesamte Untersuchung wird ungefähr 120 Minuten dauern. Am Ende wird der

Untersucher erklären, worum die Untersuchung ging.

3. Teilnahme an dieser Untersuchung sollte keinen Stress oder Unbehagen hervorrufen.

4. Die Daten, die sich aus der Untersuchung ergeben, werden anonym verarbeitet und

können darum nicht mit meinem Namen in Verbindung gebracht werden.

5. Der Untersucher wird alle weiteren Fragen zur Untersuchung jetzt oder im weiteren

Verlauf beantworten.

Für eventuelle Beschwerden über diese Untersuchung können Sie sich an die Schriftführerin

der ethischen Kommission der verhaltenswissenschaftlichen Fakultät der Universität Twente

Frau J. Rademaker wenden. (Telefon: 053-4894591; e-mail:j.rademaker@utwente.nl,

Postfach 217, 7500 AE Enschede).

Unterschrift Untersucher: …………………………………… Datum: …………………..

Unterschrift Respondent: …………………………………… Datum: …………………..

41

Geschlecht:___________

Alter: ___________

Bitte ankreuzen, wie oft du die folgenden Programme bisher benutzt hast. (nur ein Kreuz pro

Zeile)

noch nie selten manchmal oft täglich Microsoft Paint O O O O O

Adobe Photoshop O O O O O

MacPaint O O O O O

GIMP O O O O O

Paintbrush O O O O O

Wie bewertest du deine bisherige Erfahrung mit Grafikprogrammen allgemein auf einer Skala

von 0 (überhaupt keine Vorkenntnisse) bis 10 (sehr viel Erfahrung)?

___________

42

Aufgabenteil 1 (GIMP)

1)

Öffne die Datei task 1 version 1.

Entferne alle roten Objekte im Bild, versuche die anderen Objekte so wenig

wie möglich zu beschädigen.

Speichere das Bild.

2)

Öffne die Datei task 1 version 2.

Entferne alle grünen Objekte im Bild, versuche die anderen Objekte so wenig

wie möglich zu beschädigen.

Speichere das Bild.

3)

Öffne die Datei task 1 version 3.

Entferne alle violetten Objekte im Bild, versuche die anderen Objekte so we-

nig wie möglich zu beschädigen.

Speichere das Bild.

4)

Öffne die Datei task 1 version 4.

Entferne alle blauen Objekte im Bild, versuche die anderen Objekte so wenig

wie möglich zu beschädigen.

Speichere das Bild.

5)

43

Öffne die Datei task 1 version 5.

Entferne alle grünen Objekte im Bild, versuche die anderen Objekte so wenig

wie möglich zu beschädigen.

Speichere das Bild.

Sind alle Aufgaben bis hier abgeschlossen, so wende dich an den Experimentleiter.

44

Aufgabenteil 2 (GIMP)

1)

Öffne die Datei task 2 version 1.

Wähle einen grünen Farbton und färbe alle blauen Objekte im Bild in dieser

Farbe ein.

Speichere das Bild.

2)

Öffne die Datei task 2 version 2.

Wähle einen blauen Farbton und färbe alle orangenen/braunen Objekte im

Bild in dieser Farbe ein.

Speichere das Bild.

3)

Öffne die Datei task 2 version 3.

Wähle einen roten Farbton und färbe alle gelben Objekte im Bild in dieser

Farbe ein.

Speichere das Bild.

4)

Öffne die Datei task 2 version 4.

Wähle einen grünen Farbton und färbe alle pinken/violetten Objekte im Bild

in dieser Farbe ein.

Speichere das Bild.

5)

Öffne die Datei task 2 version 5.

45

Wähle einen blauen Farbton und färbe alle braunen Objekte im Bild in dieser

Farbe ein.

Speichere das Bild.

Sind alle Aufgaben bis hier abgeschlossen, so wende dich an den Experimentleiter.

46

Aufgabenteil 3 (GIMP)

1)

Öffne die Datei task 3 version 1.

Entferne alle Balken, versuche die roten Kreise und Sterne so wenig wie mög-

lich zu beschädigen.

Speichere das Bild.

2)

Öffne die Datei task 3 version 2.

Entferne alle Balken, versuche die blauen Kreise und Sterne so wenig wie

möglich zu beschädigen.

Speichere das Bild.

3)

Öffne die Datei task 3 version 3.

Entferne alle Balken, versuche die grünen Kreise und Sterne so wenig wie

möglich zu beschädigen.

Speichere das Bild.

4)

Öffne die Datei task 3 version 4.

Entferne alle Balken, versuche die gelben Kreise und Sterne so wenig wie

möglich zu beschädigen.

Speichere das Bild.

5)

Öffne die Datei task 3 version 5.

47

Entferne alle Balken, versuche die orangenen Kreise und Sterne so wenig wie

möglich zu beschädigen.

Speichere das Bild.

Sind alle Aufgaben bis hier abgeschlossen, so wende dich an den Experimentleiter.

48

Aufgabenteil 4 (Microsoft Word)

Das geöffnete Textdokument enthält Text von Wikipedia.org. Hyperlinks im Text sind mit

blauer Schriftfarbe gekennzeichnet.

1) Verändere alle Hyperlinks im ersten Absatz, sodass sie unterstrichen, fett, in

der Schriftart Times New Roman und mit roter Schriftfarbe formatiert sind.

2) Verändere alle Hyperlinks im zweiten Absatz, sodass sie unterstrichen, fett, in

der Schriftart Times New Roman und mit grüner Schriftfarbe formatiert sind.

3) Verändere alle Hyperlinks im dritten Absatz, sodass sie unterstrichen, fett, in

der Schriftart Times New Roman und mit gelber Schriftfarbe formatiert sind.

4) Verändere alle Hyperlinks im vierten Absatz, sodass sie unterstrichen, fett, in

der Schriftart Times New Roman und mit orangener Schriftfarbe formatiert sind.

5) Verändere alle Hyperlinks im fünften Absatz, sodass sie unterstrichen, fett, in

der Schriftart Times New Roman und mit violetter Schriftfarbe formatiert sind.

6) Verändere alle Textüberschriften, sodass sie fett, in der Schriftart Times New

Roman, in der Schriftgröße 12 und in schwarzer Schriftfarbe formatiert sind. Füge au-

ßerdem eine Nummerierung (z.B. "1. First paragraph") hinzu.

7) Speichere das Textdokument.

Nach Fertigstellung der obigen Aufgaben bitte umblättern.

49

Bitte ankreuzen, wie oft du Microsoft Word bisher benutzt hast. (nur ein Kreuz)

noch nie selten manchmal oft täglich

O O O O O

Auf den nächsten Seiten folgen drei Fragebögen. Fülle diese bitte aus.

50

Geben sie für jede Aussage an, in wie fern sie auf Sie zutrifft.

Ich würde komplizierte Probleme einfachen

Problemen vorziehen.

Völlig un-

zutreffend

O O O O O O O Trifft voll

und ganz

zu

Ich trage gerne die Verantwortung für eine

Situation, die sehr viel Denken erfordert.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Denken entspricht nicht dem, was ich unter Spaß verstehe.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Ich würde lieber etwas tun, das wenig Denken

erfordert, als etwas, das mit Sicherheit meine

Denkfähigkeit heraus fordert

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Ich versuche, Situationen vorauszuahnen und zu vermeiden, in denen die Wahrscheinlichkeit

groß ist, dass ich intensiv über etwas nachden-

ken muss.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Ich finde Befriedigung darin, angestrengt und stundenlang nachzudenken.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Ich denke nur so viel, wie ich muss. Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Ich denke lieber über kleine, alltägliche Vorhaben nach, als über langfristige.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Ich mag Aufgaben, die, wenn ich sie einmal erlernt habe, wenig Nachdenken erfordern.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Die Vorstellung, mich auf mein Denkvermögen

zu verlassen, um es zu etwas zu bringen,

spricht mich an.

Völlig un-

zutreffend

O O O O O O O Trifft voll

und ganz

zu

Die Aufgabe, neue Lösungen für Probleme zu finden, macht mir wirklich Spaß.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Ich finde es nicht sonderlich aufregend, neue Denkweisen zu lernen.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Ich habe es gern, wenn mein Leben voller kniffliger Aufgaben ist, die ich lösen muss.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Abstrakt zu denken reizt mich. Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Ich würde lieber eine Aufgabe lösen, die Intelligenz erfordert, schwierig und bedeutend

ist, als eine Aufgabe, die zwar irgendwie

wichtig ist, aber nicht viel Nachdenken erfor-

dert.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Wenn ich eine Aufgabe erledigt habe, die viel geistige Anstrengung erfordert hat, fühle ich

mich eher erleichtert als befriedigt.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Es genügt, dass etwas funktioniert, mir ist es egal, wie oder warum.

Völlig

unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Normalerweise denke ich intensiv über Sachen nach, selbst wenn diese mich nicht

persönlich betreffen.

Völlig unzutreffend

O O O O O O O Trifft voll

und ganz

zu

Die folgenden Aussagen enthalten Begriffe wie “Computer“ oder „technische Apparate“. Bitte denken Sie dabei auch an Laptops, Smartphones, Tablets und andere technische Geräte. Falls Ihnen eine Frage unklar ist, oder sie aus anderen Gründen keine Antwort geben können oder wollen, lassen Sie diese Frage einfach unbeantwortet.

1 Ich möchte verstehen, wie

Computerteile oder Software funktionieren.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

2 Wenn jemand Hilfe mit dem Computer braucht, versuche ich so gut wie möglich zu helfen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

3 Privatsphäreeinstellungen am Computer oder im Internet ist sehr wichtig für mich.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

4 Komplizierte Vorgänge mit technischen Geräten schrecken mich ab.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

5 Ich habe schon einmal technische Geräte zweckentfremdet oder modifiziert.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

6 Objektivität ist wichtig für mich.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

7 Ich habe nicht das Gefühl, viel Kontrolle über meine technischen Geräte zu haben.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

8 In meiner Freizeit verbringe ich nicht mehr Zeit am Computer oder anderen technischen Geräten als andere Menschen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

18

Wenn ich mir ein neues Computergerät kaufe, ist mir die Leistung wichtiger als die äußere Erscheinung.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

19

Es motiviert mich, technische Geräte zu optimieren oder an meine Wünsche anzupassen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

20

Ich habe schon einmal ein Projekt oder eine Arbeit von mir frei ins Internet gestellt, bzw. würde dies tun.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

21

Ich denke es gibt Menschen, die mich einen Computerfreak nennen würden.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

22

Das Innenleben technischer Geräte oder das Programmieren von Software interessiert mich nicht.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

23

Ich vermeide die erweiterten Optionen meiner technischen Geräte.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

24

Ich teile gerne meine Ideen und Projekte mit anderen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

25

Herausfordernde Aufgaben an technischen Geräten reizen mich.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

26

Ich verfüge über ein großes Wissen, was Computergeräte betrifft (Hardware/Software).

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

27

Ich versuche so wissenschaftlich wie möglich an Dinge heranzugehen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

9 Ich bin interessiert an technischen Produkten, welche vielseitig einsetzbar sind.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

10

Ich investiere viel Zeit und Mühe damit, Dinge mit Computergeräten/Software auszuprobieren.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

11 Es ist wichtig, dass sich jeder Gedanken macht, was er ins Internet hochläd und was nicht.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

12

Ich eigne mir gerne Wissen bezüglich technischen Geräten (Hardware/Software) an.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

13

Ich habe schon des Öfteren technische Geräte geöffnet, um zu sehen, wie diese von innen aussehen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

14

Mir ist es wichtig, dass Menschen freien Zugang zu meinen Projekten oder Arbeiten haben.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

15

Mir gefällt es, technische Geräte genau so steuern zu können, wie ich es möchte.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

16

Technische Geräte verwende ich teilweise anders als vorhergesehen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

17

Ich finde es toll, dass sich Computerbenutzer gegenseitig bei Problemen helfen, z.B. auf Webforen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

28

Viele Einstellungsmöglichkeiten an technischen Geräten finde ich abschreckend.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

29

Wenn es Probleme mit technischen Geräten gibt, muss mir meistens jemand anderes helfen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

30

Ein technisches Produkt muss für mich schön aussehen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

31

Ich mag technische Geräte, die sehr viele verschiedene Funktionen haben.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

32

Ich investiere viel Zeit und Mühe damit, Dinge mit Computergeräten/Software auszuprobieren.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

33

Ich achte sehr bewusst auf den Umgang meiner eigenen Daten bezüglich der Privatsphäre.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

34

Mein Studium/meine Arbeit hat viel mit der Technik von Computern oder mit Software zu tun

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

Geben Sie für jede Aussage an, inwiefern sie auf Sie zu trifft.

1. Während des Arbeitens mit Computerprogrammen bewerkstellige ich nur die Aufga-

ben, die für mich in der Situation relevant sind.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

2. Es stört mich, wenn ich mit einem bestimmten Computerprogramm eine Aufgabe

nicht gelöst bekomme.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

3. Während des Arbeitens mit dem Computer benutze ich nur die Funktionen die mir

beim Lösen einer Aufgabe helfen

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

4. Ich bin frustriert wenn ich für das Lösen einer Aufgabe mehr als ein Programm benö-

tige.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

5. Bei der Verwendung von Computerprogrammen ist es mir wichtig, meine Aufgaben

auf möglichst geschickte Art und Weise zu lösen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

6. Bei der Verwendung von Computerprogrammen ist es mir wichtig, schnell und ein-

fach zu Ergebnissen zu kommen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

7. Je schneller ich eine Aufgabe mit einem Computerprogramm bewerkstelligen konnte,

desto zufriedener bin ich.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich vollkommen zu

Entscheide für jede der folgenden Aussagen ob du Ihr zustimmst oder nicht und gebrauche dafür die

folgende 5 Punkte Skala. Die Skala reicht von „Ich stimme zu“ bis „Ich stimme nicht zu“. Fülle

eine Zahl von 1-5 neben die Statements ein, die deine Haltung zu dem Statement am besten

widerspiegelt.

Ich stimme zu Ich stimme nicht zu

1 2 3 4 5

1. Ich fühle mich unsicher im Bezug auf meine Fähigkeit einen Computerausdruck zu

interpretieren.

2. Ich freue mich darauf während meiner Arbeit einen Computer zu benutzen.

3. Ich denke nicht, dass ich dazu fähig wäre eine Computerprogrammer Sprache zu

erlernen.

4. Die Herausforderung etwas über Computer zu lernen ist sehr aufregend für mich.

5. Ich bin zuversichtlich, dass ich mir auch anspruchsvolle Computerfähigkeiten

aneignen kann.

6. Jeder kann lernen einen Computer zu bedienen, wenn er geduldig und motiviert ist.

7. Lernen mit Computern umzugehen ist wie eine neue Fähigkeit zu erlernen – Je mehr

du übst, desto besser wirst du.

8. Ich habe Angst davor, dass ich vom Computer abhängig werde und mein logisches

Denken vernachlässige, wenn ich damit Computer zu viel benutze.

9. Ich bin mir sicher, dass ich mit der Zeit und Übung so gut im Umgang mit Computer

werde, wie ich es im Umgang mit anderen technologischen Geräten bin.

10. Ich fühle mich dazu im Stande, mit den Fortschritten die sich im Computerbereich ereignen

umgehen zu können.

11. Ich mag es nicht mit Maschinen zu arbeiten die schlauer scheinen als ich.

12. Ich fühle mich nicht wohl dabei, Computer zu benutzen.

13. Ich habe Schwierigkeiten damit, die technischen Aspekte von Computern zu

verstehen.

14. Es macht mir Angst daran zu denken, dass ich dafür verantwortlich sein könnt könnte

eine große Datenmenge auf dem Computer zu löschen durch das Drücken der falschen

Taste.

15. Ich weigere mich einen Computer zu benutzen weil ich Angst habe Fehler zu machen,

die ich dann nicht korrigieren kann.

16. Du musst ein Genie sein um alle Fähigkeiten des Computers zu verstehen.

17. wenn ich die Möglichkeit bekäme, würde ich gerne mehr über den Computergebrauch

lernen.

18. Ich meide Computer, weil sie mir nicht vertraut sind und mich einschüchtern.

19. Ich finde, dass Computer sowohl in Bildungseinrichtungen als auch im Arbeitsfeld

notwendig sind.

Ik, …………………………………………………………….. (naam proefpersoon)

stem toe mee te doen aan een onderzoek dat uitgevoerd wordt door

Julian Ebelhäuser & Wiebke Stöhr

Ik ben me ervan bewust dat deelname aan dit onderzoek geheel vrijwillig is. Ik kan mijn

medewerking op elk tijdstip stopzetten en de gegevens verkregen uit dit onderzoek terugkrijgen,

laten verwijderen uit de database, of laten vernietigen.

De volgende punten zijn aan mij uitgelegd:

1. Het doel van dit onderzoek is inzicht te krijgen in hoe interfaces van programma's gebruikt kunnen worden.

2. Er zal van mij gevraagd worden om verschillende vragenlijsten in te vullen en verschillende taken met de programma's GIMP en Microsoft Word uit te voeren. Het hele onderzoek zal ongeveer 120 minuten duren. Aan het einde van het onderzoek zal de

onderzoeker uitleggen waar het onderzoek over ging.

3. Er behoort geen stress of ongemak voort te vloeien uit deelname aan dit onderzoek. 4. De gegevens verkregen uit dit onderzoek zullen anoniem verwerkt worden en kunnen daarom

niet bekend gemaakt worden op een individueel identificeerbare manier. 5. De onderzoeker zal alle verdere vragen over dit onderzoek beantwoorden, nu of gedurende

het verdere verloop van het onderzoek.

Voor eventuele klachten over dit onderzoek kunt u zich wenden tot de secretaris van de Commissie

Ethiek van de faculteit Gedragswetenschappen van de Universiteit Twente, mevr. J. Rademaker

(telefoon: 053-4894591; e-mail:j.rademaker@utwente.nl, Postbus 217, 7500 AE Enschede).

Handtekening onderzoeker: …………………………………… Datum: …………………..

Handtekening proefpersoon: …………………………………… Datum: …………………..

GEÏNFORMEERDE TOESTEMMING GW.07.130

Geslacht:___________ Leeftijd: ___________

AUB aankruisen hoe vaak je de volgende programma's tot nu toe gebruikt hebt (maar een kruis per regel)

nooit zelden soms vaak dagelijks

Microsoft Paint O O O O O

Adobe Photoshop O O O O O

MacPaint O O O O O

GIMP O O O O O

Paintbrush O O O O O

Hoe beoordeel je jouw kennis van grafiek programmas op een schaal van 0 (helemaal geen voorkennis) tot

10 (heel veel kennis)?

___________

Opgaven onderdeel 1 (GIMP)

1)

Open het bestand task 1 version 1.

Verwijder alle roode objecten in de afbeelding, probeer hierbij andere objecten mogelijk

weinig te beschadigen.

Sla het bestand op.

2)

Open het bestand task 1 version 2.

Verwijder alle groene objecten in de afbeelding, probeer hierbij andere objecten mogelijk

weinig te beschadigen.

Sla het bestand op.

3)

Open het bestand task 1 version 3.

Verwijder alle violette objecten in de afbeelding, probeer hierbij andere objecten mogelijk

weinig te beschadigen.

Sla het bestand op.

4)

Open het bestand task 1 version 4.

Verwijder alle blauwe objecten in de afbeelding, probeer hierbij andere objecten mogelijk

weinig te beschadigen.

Sla het bestand op.

5)

Open het bestand task 1 version 5.

Verwijder alle groene objecten in de afbeelding, probeer hierbij andere objecten mogelijk

weinig te beschadigen.

Sla het bestand op.

Als je alle opgaven tot hier hebt afgesloten, dan informeer de experiment leider.

Opgaven onderdeel 2 (GIMP)

1)

Open het bestand task 2 version 1.

Kies een groene kleur en maak alle blauwe objecten in de afbeelding groen.

Sla het bestand op.

2)

Open het bestand task 2 version 2.

Kies een blauwe kleur en maak alle oranje/bruine objecten in de afbeelding blauw.

Sla het bestand op.

3)

Open het bestand task 2 version 3.

Kies een roode kleur en maak alle gele objecten in de afbeelding rood.

Sla het bestand op.

4)

Open het bestand task 2 version 4.

Kies een groene kleur en maak alle pinke/violette objecten in de afbeelding groen.

Sla het bestand op.

5)

Open het bestand task 2 version 5.

Kies een blauwe kleur en maak alle bruine objecten in de afbeelding blauw.

Sla het bestand op.

Als je alle opgaven tot hier hebt afgesloten, dan informeer de experiment leider.

Opgaven onderdeel 3 (GIMP)

1)

Open het bestand task 3 version 1.

Verwijder alle streepjes in de afbeelding. Probeer hierbij de roode rondjes en sterren

mogelijk weinig te beschadigen.

Sla het bestand op.

2)

Open het bestand task 3 version 2.

Verwijder alle streepjes in de afbeelding. Probeer hierbij de blauwe rondjes en sterren

mogelijk weinig te beschadigen.

Sla het bestand op.

3)

Open het bestand task 3 version 3.

Verwijder alle streepjes in de afbeelding. Probeer hierbij de groene rondjes en sterren

mogelijk weinig te beschadigen.

Sla het bestand op.

4)

Open het bestand task 3 version 4.

Verwijder alle streepjes in de afbeelding. Probeer hierbij de gele rondjes en sterren

mogelijk weinig te beschadigen.

Sla het bestand op.

5)

Open het bestand task 3 version 5.

Verwijder alle streepjes in de afbeelding. Probeer hierbij de oranje rondjes en sterren

mogelijk weinig te beschadigen.

Sla het bestand op.

Als je alle opgaven tot hier hebt afgesloten, dan informeer de experiment leider.

Opgaven onderdeel 4 (Microsoft Word)

Het geopende test bestand bevat een tekst van Wikipedia.org. Hyperlinks in de tekst zijn in blauw

gemarkeerd.

1) Verander alle hyperlinks in de eerste alinea, zodat ze onderstrepen, vet, in het lettertype Times

New Roman en met een roode kleur geformatteerd zijn.

2) Verander alle hyperlinks in de tweede alinea, zodat ze onderstrepen, vet, in het lettertype Times

New Roman en met een groene kleur geformatteerd zijn.

3) Verander alle hyperlinks in de derde alinea, zodat ze onderstrepen, vet, in het lettertype Times

New Roman en met een gele kleur geformatteerd zijn.

4) Verander alle hyperlinks in de vierde alinea, zodat ze onderstrepen, vet, in het lettertype Times

New Roman en met een oranje kleur geformatteerd zijn.

5) Verander alle hyperlinks in de vijfde alinea, zodat ze onderstrepen, vet, in het lettertype Times

New Roman en met een violette kleur geformatteerd zijn.

6) Verander alle opschriften zodat ze vet, in de lettertype Times New Roman, in tekengrootte 12 en

zwarte kleur geformatteerd zijn. Voeg verder een numering (b.v. "1. First paragraph") toe.

7) Sla het text bestand op.

Als je alle opgaven tot hier hebt afgesloten, sla dan om naar de volgende bladzijde.

AUB aankruisen hoe vaak je Microsoft Word tot nu toe hebt gebruikt (maar een kruis)

nooit zelden soms vaak dagelijks

O O O O O

Op de volgende pagina's vind je enkele vragenlijsten. Vul deze AUB in.

In hoeverre zijn de onderstaande uitspraken op jou van toepassing?

Als ik moet kiezen heb ik liever een

ingewikkeld dan een simpel probleem.

Helemaal

niet op mij

vvan

O O O O O O O Helemaal

wel op mij

van probleem. van toepassing van toepassing

Ik ben graag verantwoordelijk voor een situatie

Helemaal niet O O O O O O O Helemaal wel situatie waarin veel nagedacht moet worden.

op mij van toe-

passing

op mij van toe-

passing

Nadenken is niet iets dat ik doe voor m’n plezier.

Helemaal niet op mij

van

O O O O O O O Helemaal wel op mij

van van toepassing van toepassing

Ik doe liever iets waarbij weinig nagedacht hoeft

Helemaal niet O O O O O O O Helemaal wel nagedacht hoeft

te worden dan iets waarbij mijn denkvermogen zeker op de proef wordt

gesteld.

op mij

van toe-passing

op mij

van toe-passing

Ik probeer situaties te vermijden waarin de kans

Helemaal niet O O O O O O O Helemaal wel de kans groot is dat ik diep over iets moet nadenken.

op mij

van toe-

passing

op mij

van toe-

passing

Iets langdurig en nauwgezet afwegen

geeft mij voldoening.

Helemaal

niet op mij

van

O O O O O O O Helemaal

wel op mij

van van toepassing van toepassing

Ik denk alleen zoveel als nodig is. Helemaal niet op mij

van

O O O O O O O Helemaal wel op mij

an van toepassing van toepassing

Ik denk liever na over kleine dagelijkse dingen Helemaal niet O O O O O O O Helemaal wel dingen dan over lange-termijn zaken. op mij

van toe-passing

op mij

van toe-passing

Ik hou van taken waarbij weinig nagedacht hoeft

Helemaal niet O O O O O O O Helemaal wel nagedacht hoeft te worden als ik ze eenmaal geleerd heb.

op mij van toe-

passing

op mij van toe-

passing

Het idee dat je op je verstand moet

vertrouwen om top te bereiken spreekt mij aan.

Helemaal

niet op mij van

O O O O O O O Helemaal

wel op mij van mij aan. van toepassing van toepassing

Ik geniet echt van een taak waarbij je met

nieuwe oplossingen voor ppproproblemen moet komen.problemen

moet komen.

Helemaal

niet op mij van

O O O O O O O Helemaal

wel op mij van problemen moet komen. van toepassing van toepassing

Het leren van nieuwe manieren om te denken

vind ik niet erg boeiend.

Helemaal

niet op mij van

O O O O O O O Helemaal

wel op mij van van toepassing van toepassing

Ik vind het prettig als mijn leven gevuld is met puzzels die ik moet

oplossen.

Helemaal niet op mij

van

O O O O O O O Helemaal wel op mij

van oplossen. van toepassing van toepassing

Abstract denken is een bezigheid

die mij aanspreekt.

Helemaal

niet op mij

van

O O O O O O O Helemaal

wel op mij

van van toepassing van toepassing

Ik heb liever een taak die intellectueel, moeilijk en belangrijk is, dan een taak die

enigszins belangrijk

Helemaal niet op mij

van

O O O O O O O Helemaal wel op mij

van die enigszins belangrijk is, maar waarbij je niet veel hoeft na te denken.

van toepassing van toepassing

Als ik een taak heb voltooid de veel mentale Helemaal niet O O O O O O O Helemaal wel inspanning heeft gevergd ben ik eerder opgelucht dan voldaan.

op mij van toe-

passing

op mij van toe-

passing

Ik vind het voldoende wanneer iets

blijkt te werken: hoe of waarom het precies werkt

Helemaal

niet op mij van

O O O O O O O Helemaal

wel op mij van waarom het precies werkt

interesseert me niet. van toepassing van toepassing

Gewoonlijk denk ik uitgebreid na over

zaken, zelfs wanneer ze mij niet persoonlijk aangaan.

Helemaal

niet op mij van

O O O O O O O Helemaal

wel op mij van niet persoonlijk aangaan. van toepassing van toepassing

De volgende stellingen bevatten vaak woorden zoals computer of technische

apparaten. Denk hierbij ook aan laptops, smartphones, tablets en andere

technische apparaten.

Als jij een vraag niet begrijpt of geen antwoord kan of wil geven, vul het niet

uit.

Ik wil begrijpen hoe computer(onderdelen)/Software werken.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Als er iemand hulp nodig heeft met computers, probeer ik zo goed mogelijk te helpen.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Privacy(-instellingen) op de computer of internet zijn er belangrijk voor mij.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Gecompliceerde taken met technische apparaten schrikken mij af.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik heb al eens technische apparaten gebruikt voor dingen waarvoor ze niet bedoeld zijn, of ze aangepast.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Objectiviteit is belangrijk voor mij. Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik heb niet het gevoel veel controle over mijn technische apparaten te hebben.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

In mijn vrije tijd breng ik niet meer tijd door met computers/technische apparaten dan andere mensen.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Wanneer ik nieuwe technische producten koop is het technische vermogen belangrijker voor mij dan het uiterlijk.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Het motiveert mij technische apparaten te optimaliseren of aan te passen aan mijn wensen.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik heb al eens projecten/werkstukken van mij gratis online gezet of zou dit doen.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik denk dat er mensen zijn die mij computerfreak zouden noemen.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Het binnenwerk van technische apparaten en/of het programmeren van software interesseert mij niet.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik vermijd de geavanceerde opties van mijn technische apparaten.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik vind het leuk mijn projecten en ideeën met andere mensen te delen.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Uitdagende opgaven met de computers prikkelen mij.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik heb veel kennis over computers (Hardware/Software).

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik probeer dingen zo wetenschappelijk mogelijk te benaderen.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik ben geïnteresseerd in technische producten die meervoudig inzetbaar zijn.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

ik investeer veel tijd en moeite dingen met mijn computerapparaten/Software uit te proberen

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Het is belangrijk dat mensen nadenken over wat ze op internet zetten en wat niet

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik vergaar graag kennis over technische apparaten (Hardware/Software)

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik heb er al vaker computer open gemaakt om te kijken hoe het er van binnen uitziet

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Het is belangrijk voor mij dat mensen vrij toegang tot mijn projecten en werken hebben

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik hou ervan de computer zo te besturen zoals ik het wil

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Technische apparaten gebruik ik soms anders dan bedoeld.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik vind het geweldig dat computergebruikers elkaar helpen bij problemen (Forums, websites).

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Veel instellingen aan technische apparaten vind ik afschrikkend

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Als ik problemen met technische apparaten heb moet ik meestal hulp zoeken.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Een technisch product moet er mooi uitzien.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik hou van computers met veel verschillende functies

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik investeer veel tijd en moeite om dingen met computerapparaten/software uit te proberen.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Ik ga bewust om met mijn data en gegevens met betrekking tot mijn privacy.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

Mijn studie/werk heeft veel met computers en techniek te maken.

Helemaal niet op mij van toepassing

O O O O O O O Helemaal wel op mij van toepassing

In hoeverre zijn de onderstaande uitspraken op jou van toepassing?

1. Als ik met computerprogramma’s werk los ik alleen maar taken op, die voor me in deze situatie relevant

zijn.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich voll-kommen zu

2. Ik stoor me eraan, als ik met een bepaalde computerprogramma een taak niet op de gewenste manier

kan oplossen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich voll-kommen zu

3. Tijdens het werken met een computer gebruik ik alleen functies die daadwerkelijk helpen om een taak

op te lossen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich voll-kommen zu

4. Ik raak gefrustreerd als ik voor het oplossen van een computer gerelateerde taak meer dan een

programma nodig heb.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich voll-kommen zu

5. Voor me is het belangrijk dat als ik computerprogramma’s gebruik, ik mijn taak zo knap mogelijk kan

oplossen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich voll-kommen zu

6. Voor mij is het belangrijk, dat als ik computerprogramma’s gebruik, ik zo snel mogelijk en op een

makkelijke manier resultaten kan verkrijgen.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich voll-kommen zu

7. Hoe sneller ik een taak met een computerprogramma kan oplossen, hoe meer ben ik er mee tevreden.

Trifft auf mich überhaupt nicht zu

O O O O O O O Trifft auf mich voll-kommen zu

Appendix 3. Computer Anxiety Rating Scale (CARS), Original Version

Appendix 4. Computer Anxiety Rating Scale (CARS), German Version

Entscheide für jede der folgenden Aussagen ob du Ihr zustimmst oder nicht und gebrauche dafür die

folgende 5 Punkte Skala. Die Skala reicht von „Ich stimme zu“ bis „Ich stimme nicht zu“. Fülle

eine Zahl von 1-5 neben die Statements ein, die deine Haltung zu dem Statement am besten wider-

spiegelt.

Ich stimme zu Ich stimme nicht zu

1 2 3 4 5

1. Ich fühle mich unsicher im Bezug auf meine Fähigkeit einen Computerausdruck zu

interpretieren.

2. Ich freue mich darauf während meiner Arbeit einen Computer zu benutzen.

3. Ich denke nicht, dass ich dazu fähig wäre eine Computerprogrammer Sprache zu erlernen.

4. Die Herausforderung etwas über Computer zu lernen ist sehr aufregend für mich.

5. Ich bin zuversichtlich, dass ich mir auch anspruchsvolle Computerfähigkeiten aneignen kann.

6. Jeder kann lernen einen Computer zu bedienen, wenn er geduldig und motiviert ist.

7. Lernen mit Computern umzugehen ist wie eine neue Fähigkeit zu erlernen – Je mehr du übst,

desto besser wirst du.

8. Ich habe Angst davor, dass ich vom Computer abhängig werde und mein logisches Denken

vernachlässige, wenn ich damit Computer zu viel benutze.

9. Ich bin mir sicher, dass ich mit der Zeit und Übung so gut im Umgang mit Computer werde, wie

ich es im Umgang mit anderen technologischen Geräten bin.

10. Ich fühle mich dazu im Stande, mit den Fortschritten die sich im Computerbereich

Ereignen umgehen zu können.

11. Ich mag es nicht mit Maschinen zu arbeiten die schlauer scheinen als ich.

12. Ich fühle mich nicht wohl dabei, Computer zu benutzen.

13. Ich habe Schwierigkeiten damit, die technischen Aspekte von Computern zu verstehen.

14. Es macht mir Angst daran zu denken, dass ich dafür verantwortlich sein könnt könnte eine

große Datenmenge auf dem Computer zu löschen durch das Drücken der falschen Taste.

15. Ich weigere mich einen Computer zu benutzen weil ich Angst habe Fehler zu machen, die ich

dann nicht korrigieren kann.

16. Du musst ein Genie sein um alle Fähigkeiten des Computers zu verstehen.

17. wenn ich die Möglichkeit bekäme, würde ich gerne mehr über den Computergebrauch lernen.

18. Ich meide Computer, weil sie mir nicht vertraut sind und mich einschüchtern.

19. Ich finde, dass Computer sowohl in Bildungseinrichtungen als auch im Arbeitsfeld

notwendig sind.

Appendix 4. Syntax

DESCRIPTIVES VARIABLES=Gender Age /STATISTICS=MEAN STDDEV MIN MAX. FREQUENCIES VARIABLES=Gender /ORDER=ANALYSIS. DESCRIPTIVES VARIABLES=exp_Microsoft_Paint exp_Adobe_Photoshop exp_MacPaint exp_GIMP exp_Paintbrush exp_graphical_programs exp_Microsoft_Word /STATISTICS=MEAN STDDEV MIN MAX.

DESCRIPTIVES VARIABLES=Gex NCS CompAnx AUP_explore AUP_challenge

/STATISTICS=MEAN STDDEV MIN MAX.

EXAMINE VARIABLES=Gex NCS CompAnx /COMPARE VARIABLE /PLOT=BOXPLOT /STATISTICS=NONE /NOTOTAL /MISSING=LISTWISE.

CORRELATIONS

/VARIABLES=Gex NCS CompAnx AUP_explore AUP_challenge

/PRINT=TWOTAIL NOSIG

/MISSING=PAIRWISE.

EXAMINE VARIABLES=AUP_explore AUP_challenge /COMPARE VARIABLE /PLOT=BOXPLOT /STATISTICS=NONE /NOTOTAL /MISSING=LISTWISE.