L'auteur discute un modele a cinq facteurs de la personnalite qu'il confronte a d'autres systemes de la personnalite et dont les correlats des dimensions sont analyses ainsi que les problemes methodologiques

Personality structure: emergence of the five-factor model

Much previous research has established that perceived ease of use is an important factor influencing user acceptance and usage behavior of information technologies. However, very little research has been conducted to understand how that perception forms and changes over time. The current work presents and tests an anchoring and adjustment-based theoretical model of the determinants of system-specific perceived ease of use. The model proposes control (internal and external--conceptualized as computer self-efficacy and facilitating conditions, respectively), intrinsic motivation (conceptualized as computer playfulness), and emotion (conceptualized as computer anxiety) as anchors that determine early perceptions about the ease of use of a new system. With increasing experience, it is expected that system-specific perceived ease of use, while still anchored to the general beliefs regarding computers and computer use, will adjust to reflect objective usability, perceptions of external control specific to the new system environment, and system-specific perceived enjoyment. The proposed model was tested in three different organizations among 246 employees using three measurements taken over a three-month period. The proposed model was strongly supported at all points of measurement, and explained up to 60% of the variance in system-specific perceived ease of use, which is twice as much as our current understanding. Important theoretical and practical implications of these findings are discussed.

/pdf/determinants-of-perceived-ease-of-use-integrating-control-10opxseq0g.pdf

Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model

This paper discusses the role of individuals' beliefs about their abilities to competently use computers (computer self-efficacy) in the determination of computer use. A survey of Canadian managers and professionals was conducted to develop and validate a measure of computer self-efficacy and to assess both its impacts and antecedents. Computer self- efficacy was found to exert a significant influence on individuals' expectations of the outcomes of using computers, their emotional reactions to computers (affect and anxiety), as well as their actual computer use. An individual's self-efficacy and outcome expecta- tions were found to be positively influenced by the encouragement of others in their work group, as well as others' use of computers. Thus, self-efficacy represents an important individual trait, which moderates organizational influences (such as encouragement and support) on an individual's decision to use computers. Understanding self-efficacy, then, is important to the successful implementation of systems in organizations. The existence of a reliable and valid measure of self-efficacy makes assessment possible and should have implications for organizational support, training, and implementation.

https://www.jstor.org/stable/pdfplus/249688.pdf

Computer self-efficacy: development of a measure and initial test

A model, based on Bandura's Social Cognitive Theory, was developed to test the influence of computer self-efficacy, outcome expectations, affect, and anxiety on computer usage The model was tested using longitudinal data gathered from 394 end users over a one-year interval Significant relationships were found between computer self-efficacy and outcome expectations, and between self-efficacy and affect and anxiety and use Performance outcomes were found to influence affect and use, while affect was significantly related to use Overall, the findings provide strong confirmation that both self-efficacy and outcome expectations impact on an individual's affective and behavioral reactions to information technology

Social cognitive theory and individual reactions to computing technology: a longitudinal study

E-learning is emerging as the new paradigm of modern education. Worldwide, the e-learning market has a growth rate of 35.6%, but failures exist. Little is known about why many users stop their online learning after their initial experience. Previous research done under different task environments has suggested a variety of factors affecting user satisfaction with e-Learning. This study developed an integrated model with six dimensions: learners, instructors, courses, technology, design, and environment. A survey was conducted to investigate the critical factors affecting learners' satisfaction in e-Learning. The results revealed that learner computer anxiety, instructor attitude toward e-Learning, e-Learning course flexibility, e-Learning course quality, perceived usefulness, perceived ease of use, and diversity in assessments are the critical factors affecting learners' perceived satisfaction. The results show institutions how to improve learner satisfaction and further strengthen their e-Learning implementation.

http://water-msc.org/en/knowledge_base/successful_e_learning.pdf

What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction

Assessing computer anxiety: Development and validation of the Computer Anxiety Rating Scale

The recent growth of computer technology has been accompanied by an increasing number of individuals who are anxious or intimidated by computers. The current study was designed to test a cognitive model of computer anxiety, where computer anxiety is seen as a function of internal dialogue, underlying meaning systems, behavioral acts, and behavioral outcomes when working on a computer. The Self-Statements About Computers (SSAC) checklist was empirically developed to assess thoughts or internal dialogue associated with anxiety and computer use, as well as the meaning of those thoughts for the individual. Analyses revealed that high computer-anxious subjects had lower expectations of performance and reported more debilitative thoughts during an actual computer task. They also reported higher levels of anxiety during this computer interaction, had more bodily sensations, and took longer to complete the task. In addition, high computer-anxious individuals reported less computer experience and mechanical interest, and higher levels of math anxiety. These results support the proposed cognitive model of computer anxiety and suggest directions for clinical intervention.

Cognitive factors in computer anxiety

The Interpersonal Style Inventory and the Personality Research Form were administered to 327 adolescents in order to test hypotheses with regard to the second-order factors that they share in common. The 37 scale scores were intercorrelated and factored by the principal axes method and rotated to an oblique solution. The seven correlated factors were interpreted as Impulse Control, Extraversion-Introversion, Autonomy, Level of Socialization, Achievement Motivation, Liking New Experience, and Adventure Seeking. These confirmed four of the hypothesized factors.

Luanne A. Knight

Papers

Assessing computer anxiety: Development and validation of the Computer Anxiety Rating Scale

Cognitive factors in computer anxiety

Higher-order factors assessed by the ISI and PRF.