Attitudes toward Computer, Computer Anxiety and Gender as determinants of Pre-service Science, Technology and Mathematics Teachers’ Computer Self-efficacy

The study investigated attitudes towards computer and computer anxiety as determinants of computer self-efficacy among 2100 pre-service science, technology and mathematics (STM) teachers from the University of Lagos of Nigeria using the quantitative research method within the blueprint of the descriptive survey design. Data collected were analysed using the descriptive statistics of percentages, mean, and standard deviation and inferential statistics of independent samples t-test, Pearson product moment correlation coefficient and multiple regression analysis. Finding revealed significant correlations between computer attitudes, computer anxiety and computer self-efficacy. Gender differences in attitude toward computer, computer self-efficacy and computer anxiety among pre-service STM teachers were significant. Affective component, perceived control component, and perceived usefulness component, behavioural intention component, gender, and computer anxiety made statistically significant contributions to the variance in pre-service STM teachers’ computer self-efficacy. The study recommended among others that academic institutions should pay more attention to this computer anxiety and adopt proper ways of reducing the computer anxiety, so that positive e-learning experiences can be created for pre-service STM teachers

Behavioural intention to use ICT in teaching science among lecturers in Nigerian Polytechnic

Nigeria is investing in information and communication technology (ICT) to improve students’ learning outcome and the quality of education. However, based on research literature, the use of computer in the teaching of science by lecturers is underutilised. Therefore, the study was conducted to investigate the intention to use computer in teaching science among lecturers in North Eastern Polytechnic. The study aimed at examining the relationship between perceptions, attitude, and other factors responsible for lecturer’s behavioural intention towards the use of computer in teaching science. A quantitative design followed by supporting interview was used to execute the study and address the research objectives. Two hundred and sixty-nine (269) lecturers were selected from a population of 715 lecturers. Quantitative data were obtained from the Technology Acceptance Model (TAM) inventory and the validated questionnaire was used in the study. The data were analysed using Structural Equation Modelling (SEM). Qualitative data were obtained using semi-structured interview protocol to facilitate interviews with five participants who were purposefully selected for this phase of the study. The qualitative phase of the study aimed at exploring important factors responsible for the intention to use ICT in science teaching. The findings showed the significance of perceived ease of use on perceived usefulness, perceived ease of use, and perceived usefulness are significant on attitude while perceived usefulness and attitude are significant on behavioural intention. Perceived ease of use was moderately significant towards behavioural intention against the TAM model. The moderators such as gender, age, and teaching experience showed influence on perceived ease of use, perceived usefulness, and attitude toward behavioural intention. Suggestions were made to provide incentives for lecturers who practise ICT and Trainings, workshops, and professional development courses should be provided to train lecturers on incorporating ICT in their teachings

HABIT: Horse Automated Behaviour Identification Tool: a position paper

HABIT (Horse Automated Behaviour Identification Tool) is an Animal Computer Interaction (ACI) project, on the interdisciplinary boundary between equitation science and computer science. HABIT will automate the analysis and recognition of horse-to-horse and horse-to-human behaviours, as observed in unconstrained / ad-hoc video. A horse-to-horse dyad video dataset will be compiled, illustrating exemplar behaviours. Behavioural signatures will be manually identified from video. Next, a system will be developed and trained to recognise these signatures. The tool will then be evaluated, when applied to both horse-to-horse and horse-to-human video clips. In the study of animal behaviour, an ‘ethogram’ is a set of comprehensive descriptions of the characteristic behaviour patterns of a species. HABIT is potentially the first step towards the ‘automated ethogram’. This project provides a welfare-orientated approach to evaluating horse behaviours. When horses are handled, trained or ridden, HABIT will help ensure that these experiences occur within the natural repertoire of equine behaviours. There is also scope to engage and educate the public about horse behaviours; both for general interest and to raise welfare-awareness. Additionally, automation could play an important methodological role in animal-centred design by reducing human biases during the requirements and evaluation processes

HABIT: Horse Automated Behaviour Identification Tool: a position paper

HABIT (Horse Automated Behaviour Identification Tool) is an Animal Computer Interaction (ACI) project, on the interdisciplinary boundary between equitation science and computer science. HABIT will automate the analysis and recognition of horse-to-horse and horse-to-human behaviours, as observed in unconstrained / ad-hoc video. A horse-to-horse dyad video dataset will be compiled, illustrating exemplar behaviours. Behavioural signatures will be manually identified from video. Next, a system will be developed and trained to recognise these signatures. The tool will then be evaluated, when applied to both horse-to-horse and horse-to-human video clips. In the study of animal behaviour, an ‘ethogram’ is a set of comprehensive descriptions of the characteristic behaviour patterns of a species. HABIT is potentially the first step towards the ‘automated ethogram’. This project provides a welfare-orientated approach to evaluating horse behaviours. When horses are handled, trained or ridden, HABIT will help ensure that these experiences occur within the natural repertoire of equine behaviours. There is also scope to engage and educate the public about horse behaviours; both for general interest and to raise welfare-awareness. Additionally, automation could play an important methodological role in animal-centred design by reducing human biases during the requirements and evaluation processes

Differences in intention to use educational RSS feeds between Lebanese and British students: A multi‑group analysis based on the technology acceptance model

Really Simple Syndication (RSS) offers a means for university students to receive timely updates from virtual learning environments. However, despite its utility, only 21% of home students surveyed at a university in Lebanon claim to have ever used the technology. To investigate whether national culture could be an influence on intention to use RSS, the survey was extended to British students in the UK. Using the Technology Adoption Model (TAM) as a research framework, 437 students responded to a questionnaire containing four constructs: behavioral intention to use; attitude towards benefit; perceived usefulness; and perceived ease of use. Principle components analysis and structural equation modelling were used to explore the psychometric qualities and utility of TAM in both contexts. The results show that adoption was significantly higher, but also modest, in the British context at 36%. Configural and metric invariance were fully supported, while scalar and factorial invariance were partially supported. Further analysis shows significant differences between perceived usefulness and perceived ease of use across the two contexts studied. Therefore, it is recommended that faculty demonstrate to students how educational RSS feeds can be used effectively to increase awareness and emphasize usefulness in both contexts

Critical review of the e-loyalty literature: a purchase-centred framework

Over the last few years, the concept of online loyalty has been examined extensively in the literature, and it remains a topic of constant inquiry for both academics and marketing managers. The tremendous development of the Internet for both marketing and e-commerce settings, in conjunction with the growing desire of consumers to purchase online, has promoted two main outcomes: (a) increasing numbers of Business-to-Customer companies running businesses online and (b) the development of a variety of different e-loyalty research models. However, current research lacks a systematic review of the literature that provides a general conceptual framework on e-loyalty, which would help managers to understand their customers better, to take advantage of industry-related factors, and to improve their service quality. The present study is an attempt to critically synthesize results from multiple empirical studies on e-loyalty. Our findings illustrate that 62 instruments for measuring e-loyalty are currently in use, influenced predominantly by Zeithaml et al. (J Marketing. 1996;60(2):31-46) and Oliver (1997; Satisfaction: a behavioral perspective on the consumer. New York: McGraw Hill). Additionally, we propose a new general conceptual framework, which leads to antecedents dividing e-loyalty on the basis of the action of purchase into pre-purchase, during-purchase and after-purchase factors. To conclude, a number of managerial implementations are suggested in order to help marketing managers increase their customers’ e-loyalty by making crucial changes in each purchase stage

Physically Embedded Genetic Algorithm Learning in Multi-Robot Scenarios: The PEGA algorithm

We present experiments in which a group of autonomous mobile robots learn to perform fundamental sensor-motor tasks through a collaborative learning process. Behavioural strategies, i.e. motor responses to sensory stimuli, are encoded by means of genetic strings stored on the individual robots, and adapted through a genetic algorithm (Mitchell, 1998) executed by the entire robot collective: robots communicate their own strings and corresponding fitness to each other, and then execute a genetic algorithm to improve their individual behavioural strategy. The robots acquired three different sensormotor competences, as well as the ability to select one of two, or one of three behaviours depending on context ("behaviour management"). Results show that fitness indeed increases with increasing learning time, and the analysis of the acquired behavioural strategies demonstrates that they are effective in accomplishing the desired task

Expressive Logics for Coinductive Predicates

The classical Hennessy-Milner theorem says that two states of an image-finite transition system are bisimilar if and only if they satisfy the same formulas in a certain modal logic. In this paper we study this type of result in a general context, moving from transition systems to coalgebras and from bisimilarity to coinductive predicates. We formulate when a logic fully characterises a coinductive predicate on coalgebras, by providing suitable notions of adequacy and expressivity, and give sufficient conditions on the semantics. The approach is illustrated with logics characterising similarity, divergence and a behavioural metric on automata

Approximations of Algorithmic and Structural Complexity Validate Cognitive-behavioural Experimental Results

We apply methods for estimating the algorithmic complexity of sequences to behavioural sequences of three landmark studies of animal behavior each of increasing sophistication, including foraging communication by ants, flight patterns of fruit flies, and tactical deception and competition strategies in rodents. In each case, we demonstrate that approximations of Logical Depth and Kolmogorv-Chaitin complexity capture and validate previously reported results, in contrast to other measures such as Shannon Entropy, compression or ad hoc. Our method is practically useful when dealing with short sequences, such as those often encountered in cognitive-behavioural research. Our analysis supports and reveals non-random behavior (LD and K complexity) in flies even in the absence of external stimuli, and confirms the "stochastic" behaviour of transgenic rats when faced that they cannot defeat by counter prediction. The method constitutes a formal approach for testing hypotheses about the mechanisms underlying animal behaviour.Comment: 28 pages, 7 figures and 2 table