Masters Degrees (Computer Science and Informatics)
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Browsing Masters Degrees (Computer Science and Informatics) by Subject "Computer anxiety"
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Item Open Access Comparing the sensor glove and questionnaire as measures of computer anxiety(University of the Free State, 2014-01) Nkalai, Tlholohelo Stephania; De Wet, L.English: A vast amount of literature regarding computer anxiety exists. Consequently, a number of researchers have discovered different definitions for computer anxiety. Regardless of the numerous definitions, several researchers agree that computer anxiety involves emotional ‘fear’ or ‘apprehension’ when interacting or anticipating interaction with computers. Subsequently, some individuals who experience computer anxiety avoid using computers. This situation is undesirable because these days it is almost always a necessity for people to use computers in the workplace. It is therefore important to extensively investigate computer anxiety including measures which can be implemented to mitigate it. Different findings about computer anxiety regarding the correlates: gender, age, computer ownership, educational attainment and computer experience, exist. For example, while some research findings state that females experience higher levels of computer anxiety than males, other research findings assert that males experience computer anxiety more than the females. The contradictory findings regarding the correlates of computer anxiety could be attributed to the fact that most of the research studies which investigated computer anxiety relied solely on existing computer anxiety questionnaires. Using questionnaires exclusively poses various limitations which include relying on the ‘subjective’ responses of the participants. This research study incorporated another measurement of computer anxiety in addition to an existing computer anxiety questionnaire named Computer Anxiety Rating Scale. This additional measurement was performed using an instrument that measured physiological signals of a participant. The instrument is called an Emotion RECecognition system (EREC). It measures skin temperature and skin resistance and heart rate. Apart from the mentioned two, other data collection methods were used which are pre-test and post- test self-developed questionnaires, observations and interviews. With various measurements incorporated in this study, computer anxiety was investigated taking into consideration the following research questions: To what extent does a sensor glove add value in measuring computer anxiety during usability testing when compared to anxiety questionnaires and observations? To what extent is computer anxiety influenced by age, gender, computer experience, educational attainment, and ownership of a personal computer according to the anxiety questionnaire and the sensor glove? From the findings of the study in relation to the first research question, it can be concluded that the sensor glove does not add value. Instead, the sensor glove may add value when measuring stress. This means that although the EREC sensor glove measures skin conductance, changes in skin conductance may indicate changes in stress levels rather than anxiety levels. Regarding the second research question, it can be concluded that computer anxiety was not influenced by age, gender, computer experience, educational attainment, and ownership of a personal computer according to the anxiety questionnaire and the sensor glove.Item Open Access Some psychological and biographical predictors of computer proficiency: an analysis of the potential of a novice to become a good computer user(University of the Free State, 2006-08-22) Burger, Andries Johannes; Blignaut, P. J.; Huysamen, G. K.English: As a result of the proliferation of computers throughout the business world, more and more demands are placed on workers to develop computer skills. There are a variety of training methods by means of which workers can obtain these much-needed skills. It is nevertheless true that with identical training methods, it is quite likely that different people will end up with different computer abilities. It was thus the primary objective of this study to investigate the role that certain biographical, psychological and cognitive variables play in the prediction of computer proficiency. The variables that were included as possible predictors were personality type, learning style, general anxiety, three-dimensional perceptual ability (spatial 3D), numerical ability, computer attitude, grade 12 final examination mark and mathematical ability. The se condary objective of this study was to determine whether computer attitude and its three components (computer anxiety, computer liking and computer confidence) were influenced by computer experience. Culture was taken into account as a moderator variable in both the primary and secondary studies. To ensure that all the research participants were on the same level of computer literacy, only students enrolled for the basic computer literacy course at the University of the Free State were used in the study. Because the research was used to develop predictor formulas for computer proficiency, the research participants were tested early in February 2003, before the introductory computer literacy course commenced. This was to ensure that the participants’ attitudes, abilities and feelings regarding computers were assessed prior to their exposure to computers. The only test that was repeated (on the same students) towards the end of the semester course was the so-called Computer Attitude Scale (CAS). Apart from measuring a person’s attitude towards computers, the test also contains sub-tests that measure computer anxiety, computer liking and computer confidence. The researcher needed these retest scores to determine whether users’ computer attitude, as well as the three mentioned components, had changed as more computer experience was gained. The primary study resulted in the formulation of two formulas which can be used to predict the computer proficiency of white and black students enrolled for an introductory computer literacy course. The prediction formula for the white students is made up of six variables – grade 12 final examination mark, computer confidence, the learning modes of abstract conceptualisation (AC) and concrete experience (CE), mathematical ability and the conscientiousness (C) domain of personality. The prediction formula for the black students is also made up of six variables – spatial 3D, the L, Q3 and Q4 scores of the IPAT Anxiety Scale, computer confidence and the learning mode of abst ract conceptualisation (AC). It was thus found that different variables predict the computer proficiency of white and black students. The only variables that are shared by both formulas are computer confidence and the learning mode of abstract conceptualisation (AC). In contrast with previous research on the topic, a negative relationship between computer attitude and computer experience was found in the secondary study. The statistical results indicated that as the students gained more experience on computers their computer confidence and computer liking decreased while their computer anxiety increased. As these three constructs are the components of computer attitude, it was not surprising that computer attitude also decreased. Computers play an integral role in the lives of many individuals and therefore the improvement of computer skills is a continuous and important process. This study provided valuable inputs by identifying predictors of computer proficiency for students enrolled in an introductory computer literacy course.