Development of a general internet attitude scale and internet self-efficacy scale

The measurement of users’ attitudes towards and confidence with using the Internet is an important yet poorly researched topic. Previous research has encountered issues that serve to obfuscate rather than clarify. Such issues include a lack of distinction between the terms ‘attitude’ and ‘self-efficacy’, the absence of a theoretical framework to measure each concept, and failure to follow well-established techniques for the measurement of both attitude and self-efficacy. Thus, the primary aim of this research was to develop two statistically reliable scales which independently measure attitudes towards the Internet and Internet self-efficacy. This research addressed the outlined issues by applying appropriate theoretical frameworks to each of the constructs under investigation. First, the well-known three component (affect, behaviour, cognition) model of attitudes was applied to previous Internet attitude statements. The scale was distributed to four large samples of participants. Exploratory factor analyses revealed four underlying factors in the scale: Internet Affect, Internet Exhilaration, Social Benefit of the Internet and Internet Detriment. The final scale contains 21 items, demonstrates excellent reliability and achieved excellent model fit in the confirmatory factor analysis. Second, Bandura’s (1997) model of self-efficacy was followed to develop a reliable measure of Internet self-efficacy. Data collected as part of this research suggests that there are ten main activities which individuals can carry out on the Internet. Preliminary analyses suggested that self-efficacy is confounded with previous experience; thus, individuals were invited to indicate how frequently they performed the listed Internet tasks in addition to rating their feelings of self-efficacy for each task. The scale was distributed to a sample of 841 participants. Results from the analyses suggest that the more frequently an individual performs an activity on the Internet, the higher their self-efficacy score for that activity. This suggests that frequency of use ought to be taken into account in individual’s self-efficacy scores to obtain a ‘true’ self-efficacy score for the individual. Thus, a formula was devised to incorporate participants’ previous experience of Internet tasks in their Internet self-efficacy scores. This formula was then used to obtain an overall Internet self-efficacy score for participants. Following the development of both scales, gender and age differences were explored in Internet attitudes and Internet self-efficacy scores. The analyses indicated that there were no gender differences between groups for Internet attitude or Internet self-efficacy scores. However, age group differences were identified for both attitudes and self-efficacy. Individuals aged 25-34 years achieved the highest scores on both the Internet attitude and Internet self-efficacy measures. Internet attitude and self-efficacy scores tended to decrease with age with older participants achieving lower scores on both measures than younger participants. It was also found that the more exposure individuals had to the Internet, the higher their Internet attitude and Internet self-efficacy scores. Examination of the relationship between attitude and self-efficacy found a significantly positive relationship between the two measures suggesting that the two constructs are related. Implication of such findings and directions for future research are outlined in detail in the Discussion section of this thesis.

Repairing wireless sensor network connectivity in damaged environments

A wireless sensor network can become partitioned due to node failure, requiring the deployment of additional relay nodes in order to restore network connectivity. This introduces an optimisation problem involving a tradeoff between the number of additional nodes that are required and the costs of moving through the sensor field for the purpose of node placement. This tradeoff is application-dependent, influenced for example by the relative urgency of network restoration. In addition, minimising the number of relay nodes might lead to long routing paths to the sink, which may cause problems of data latency. This data latency is extremely important in wireless sensor network applications such as battlefield surveillance, intrusion detection, disaster rescue, highway traffic coordination, etc. where they must not violate the real-time constraints. Therefore, we also consider the problem of deploying multiple sinks in order to improve the network performance. Previous research has only parts of this problem in isolation, and has not properly considered the problems of moving through a constrained environment or discovering changes to that environment during the repair or network quality after the restoration. In this thesis, we firstly consider a base problem in which we assume the exploration tasks have already been completed, and so our aim is to optimise our use of resources in the static fully observed problem. In the real world, we would not know the radio and physical environments after damage, and this creates a dynamic problem where damage must be discovered. Therefore, we extend to the dynamic problem in which the network repair problem considers both exploration and restoration. We then add a hop-count constraint for network quality in which the desired locations can talk to a sink within a hop count limit after the network is restored. For each new problem of the network repair, we have proposed different solutions (heuristics and/or complete algorithms) which prioritise different objectives. We evaluate our solutions based on simulation, assessing the quality of solutions (node cost, movement cost, computation time, and total restoration time) by varying the problem types and the capability of the agent that makes the repair. We show that the relative importance of the objectives influences the choice of algorithm, and different speeds of movement for the repairing agent have a significant impact on performance, and must be taken into account when selecting the algorithm. In particular, the node-based approaches are the best in the node cost, and the path-based approaches are the best in the mobility cost. For the total restoration time, the node-based approaches are the best with a fast moving agent while the path-based approaches are the best with a slow moving agent. For a medium speed moving agent, the total restoration time of the node-based approaches and that of the path-based approaches are almost balanced.