Assessing the intention to use technology among pre-service teachers in Singapore and Malaysia: A multigroup invariance analysis of the Technology Acceptance Model (TAM)

This study assesses the pre-service teachers’ self-reported future intentions to use technology in Singapore and Malaysia. A survey was employed to validate items from past research. Using the Technology Acceptance Model (TAM) as a research framework, 495 pre-service teachers from Singapore and Malaysia responded to an 11-item questionnaires containing four constructs: intention to use (ITU), attitude towards computer use (ATCU), perceived usefulness (PU), and perceived ease of use (PEU). Structural equation modelling (SEM) was employed as the main method of analysis in this study. A multi-group analysis of invariance was performed on the two samples. The results show that configural and metric invariance were fully supported while scalar and factor variance invariance were partially supported, suggesting that the 11-item measure of the TAM may be robust across cultures and that the factor loading pattern and factor loadings appeared to be equivalent across the cultures examined. While all the paths in the structural model were significant, the variance accounted for in the dependent variable (ITU) was much larger in the Malaysian sample relative to the Singaporean sample.     

‘First do no harm’: Factors influencing teachers’ ability and willingness to use ICT in their subject teaching

The paper reports on a Department of Culture, Museums and Sport (DCMS) funded project which provided modest amounts of time for teachers to be freed from their classroom teaching to explore the use of information and communications technology (ICT) in their subject teaching, and to meet up together to discuss their use of new technology. The funding was sufficient to provide a day of supply cover for two groups of secondary teachers in different curriculum subjects (history and science) to meet towards the start of the academic year to discuss their use of ICT, a day of supply cover to work on their ideas and interests, and a day to meet together again towards the end of the year to share ideas and experiences.     

Predicting secondary school teachers’ acceptance and use of a digital learning environment: A cross-sectional study

In this study, secondary school teachers’ acceptance of a digital learning environment (DLE) was investigated. Questionnaires were taken on three times (T1/T2/T3) during the same school year, with the Unified Theory of Acceptance and Use of Technology (UTAUT) as theoretical framework. Next to questionnaires, user-logs were collected during the entire school year. A total of 72 teachers completed a questionnaire on at least one occasion: 64 teachers responded at T1, 41 at T2, and 55 at T3. We first investigated which factors influence teachers’ acceptance of a DLE. The main predictors of DLE acceptance were performance expectancy and social influence by superiors to use the DLE. Effort expectancy and facilitating conditions were of minor importance. We then investigated how well the amount of final observed use could be predicted, and found that at T1 about one third, at T2 about one fourth and at T3 about half of the variance in observed use was predicted by attitude, behavioral intention and self-reported frequency of use. Our study showed that to maximize use of a DLE, its usefulness should be demonstrated, while school boards or principals should strongly encourage teachers to (start to) use the DLE.     

Cultural differences in social networking site use: A comparative study of China and the United States

This research compared social networking site (SNS) use in a collectivistic culture, China, and an individualistic culture, the United States (US). Over 400 college student participants from a Southwestern University in Chongqing, China, and 490 college participants from a Midwestern University in the US completed a survey about their use of SNSs – time spent, importance and motives for use. They then rated themselves on a variety of personal characteristics, namely the Big Five Personality factors, Loneliness, Shyness and Life Satisfaction. Results revealed cultural differences in SNS use. US participants spent more time in SNS, considered them to be more important and had more friends in SNSs than did Chinese participants. Self-ratings of personal characteristics also differed in the two cultures as did the personal characteristics that predicted SNS use. In general, personal characteristics were less effective in predicting SNS use in China than in the US. Findings suggest that in collectivistic cultures the importance of the family, friends and one’s groups may be partly responsible for Chinese participants’ lesser use of SNSs, whereas in individualistic cultures the importance of self and having more but less close and enduring friendships may be partly responsible for US participants’ greater use of SNSs. Personal characteristics predicted SNS use in both cultures but were stronger predictors in an individualistic culture than in a collectivistic, consistent with the emphasis on self in the former and on family, friends and one’s groups in the latter. Future research is needed to identify whether cultural values always take precedence over personal characteristics and motives in determining behavior in the virtual world.     

Perceived risks, counter-beliefs, and intentions to use anti-/counter-terrorism websites: An exploratory study of government–citizens online interactions in a turbulent environment

This study examines the relationships between various risks, beliefs, and behavioral intentions that are related to citizens' use of anti-/counter-terrorism e-Government websites. The data was collected through two surveys within a one-year interval — before and after the Iraqi regime was expelled by the US coalition army. The results suggest that perceived privacy risk from an anti/counter-terrorism authority is the major obstacle in citizen-to-government anti/counter-terrorism information flow, while citizens' belief in the authority's domain competence greatly influences citizens' dependence on anti/counter-terrorism website information. Other findings and implications are discussed, and directions for future research are suggested.     

The role of physical representations in solving number problems: A comparison of young children’s use of physical and virtual materials

This research aims to explore the role of physical representations in young children’s numerical learning then identify the benefits of using a graphical interface in order to understand the potential for developing interactive technologies in this domain. Three studies are reported that examined the effect of using physical representations (blocks) on children’s (aged 4–8 years) strategies in a numerical partitioning task. The first study describes the role of certain perceptual and manipulative properties of the physical materials, comparing performance with paper and no materials conditions. The study demonstrated an advantage for physical materials and identified a key property reflecting strategies: whether blocks were moved individually or as a group. This finding was investigated in the second study by comparing strategies when children were asked to constrain movements to one block at a time. Significant differences were found in strategies used although differences were reduced by children moving individual blocks quickly in succession using both hands. The final study examined the effect of constraining manipulation using a graphical user interface, where on screen squares could only be moved individually. As predicted, significant differences were found for strategies used between physical and virtual conditions. The findings suggest that differences in the manipulative properties of interfaces may affect children’s numerical strategies and are discussed with respect to the design of effective interactive technologies in this domain.     

State of worksite health promotion in companies with and without Quality‐Management systems: A comparative study

The goal of comprehensive worksite health promotion (WHP) is to protect and promote the health and performance of employees. WHP principles link health‐promotion activities to existing management systems, such as Quality Management (QM), to better integrate these activities into goals and processes of the company. Accordingly, it was hypothesized that the presence of a QM system is related to increased institutionalization and scope of WHP. Swiss companies in the service sector with a certified QM system (N = 289) were compared to a random sample of service‐sector companies without QM systems (N = 334). The results show that the presence of a certified QM system is related to the quality of WHP, as companies have both a stronger institutionalization and a broader scope of WHP compared to companies without a certified QM system. The present study produced empirical evidence that QM systems might be an enhancing factor for WHP. © 2010 Wiley Periodicals, Inc.     

Microwave antennas—An intrinsic part of RF energy harvesting systems: A contingent study about its design methodologies and state‐of‐art technologies in current scenario

With the significant rise of low power embedded devices in various applications of both consumer and commercial usage, the surge for continuous power requirements has initiated promising research toward alternative sources of energy. It includes the domain of wireless power transmission, internet‐of‐things, wireless sensor nodes, machine‐to‐machine, and radio frequency identification. Thus, the overall scope of this review article is to witness microwave antennas and its implementation in RF energy harvesting system through ambient RF signals. For this reason, unified understanding of classical electromagnetism is needed; beginning with the fundamentals of RF transmission and the exploration of concepts such as Fraunhofer's Distance and Friis Transmission Equation. It is followed up by the analogy of dependency of parameters like circuit build‐up, conversion efficiencies and amount of power harvested, which is quite crucial from the rectifier point‐of‐view. For better improvisement in RF energy harvesting systems, five different cases of monopole antennas are explored with reflector surfaces such as PEC (perfect electrical conductor) and AMC (artificial magnetic conductor) integrated with the rectifier circuit. Implementation with wide diversity has proposed a generalized solution for achieving tradeoffs: polarization and pattern diversity with consistent system efficiency; leads to clean and sustainable energy for low power‐embedded devices.     

Ensemble data mining modeling in corrosion of concrete sewer: A comparative study of network-based (MLPNN & RBFNN) and tree-based (RF,CHAID, & CART) models

This research aims to evaluate ensemble learning (bagging, boosting, and modified bagging) potential in predicting microbially induced concrete corrosion in sewer systems from the data mining (DM) perspective. Particular focus is laid on ensemble techniques for network-based DM methods, including multi-layer perceptron neural network (MLPNN) and radial basis function neural network (RBFNN) as well as tree-based DM methods, such as chi-square automatic interaction detector (CHAID), classification and regression tree (CART), and random forests (RF). Hence, an interdisciplinary approach is presented by combining findings from material sciences and hydrochemistry as well as data mining analyses to predict concrete corrosion. The effective factors on concrete corrosion such as time, gas temperature, gas-phase H₂S concentration, relative humidity, pH, and exposure phase are considered as the models’ inputs. All 433 datasets are randomly selected to construct an individual model and twenty component models of boosting, bagging, and modified bagging based on training, validating, and testing for each DM base learners. Considering some model performance indices, (e.g., Root mean square error, RMSE; mean absolute percentage error, MAPE; correlation coefficient, r) the best ensemble predictive models are selected. The results obtained indicate that the prediction ability of the random forests DM model is superior to the other ensemble learners, followed by the ensemble Bag-CHAID method. On average, the ensemble tree-based models acted better than the ensemble network-based models; nevertheless, it was also found that taking the advantages of ensemble learning would enhance the general performance of individual DM models by more than 10%.