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This paper aims to present the finding of a practical lab assessment used to evaluate students’ mastery of Ohm’s law. The researchers used an approach combining different instruction types and lab formats to examine whether this combination produced a unique effect on students’ performance. This multifaceted approach provided evidence about how assessment design could affect students’ lab performance. The study also discussed various strategies that could guide instructors and curriculum designers about how to incorporate lab tasks into their curriculum to facilitate students’ mastery of subject content.

This study was a quantitative experiment that used a factorial repeated measures design. The design allowed the researchers to measure participants’ task scores and time across different treatment conditions, hence enabling the effects of lab format and instructional type to be observed. All participants were recruited through the convenience sampling strategy.

The results suggested that there was a statistically significant difference in the time taken to complete the task. However, no statistically significant difference was recorded in the participants’ task scores. Overall, it appeared that participants performed better in the simulation-based labs with expository instructions.

The current study contributes to the body of knowledge on the effect of lab format and instructional type on students’ performance in lab-based assessments. The results presented here may also help instructors to determine the most appropriate form of lab formats and instruction types to be used in an electronics course.

The primary objective of the current study is to examine the impact that the size of a police department and workload on a department have on response time. Secondarily, the authors look at the effect that incident-level factors such as the severity of a call for service (CFS) and community-level factors such as ethnic diversity have on police response time.

The current study examined CFSs data collected over a three-year period and organizational information from 26 police departments in Northeast Texas, as well as community-level information. In order to measure the effect of organizational variables, community factors and incident-level variables on police response time, the authors employed the use of hierarchical linear models (HLMs).

The results of hierarchical linear modeling indicated that incident-level factors and police department size are significant predictors of response time.

There are two primary limitations: first, there were a lack of available organizational structure correlates such as age and differentiation. Second, the primary data set had a significant number of incomplete or repeating cases, thereby limiting the accuracy of the current study’s analysis.

The most unique aspect of this manuscript is that it examines how organizational factors affect police response time. Numerous studies analyzed determinants of police response time such as incident- and community-level factors, but the importance of organizational factors has not been analyzed.

This study aims to examine the influence of destination awareness, cognitive and affective image, risk perception and past visitation on the intention to visit a tourist destination (a medium-sized city) in the next 12 months.

Partial least squares structural equation modeling was adopted to examine the data collected from 714 domestic holidaymakers.

Results demonstrate that awareness, cognitive and affective image, past visitation, perceived risk of traveling and perceived risk in international versus domestic travel are key factors; safety concerns enhance the cognitive image and perceived safety of the destination, but increase the perceived risk of traveling; and perceived social risk increases the perceived risk of traveling.

Data collection from only one country limits the generalizability of the conclusions.

Conclusions allow gaining new insights regarding communication strategies in general, during and post-pandemic times.

Using a consolidated and empirical approach, this study provides a better understanding of the role of perceived risk and its effects on cognitive and affective image and travel intention. For instance, to the best of the author’s knowledge, it is the first study to consider the effects of social risk in the pandemic context. It also offers insights into the mediating effect of destination image and the moderating effects of perceived risk and past visitation.

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

While many researchers have investigated the adoption and usage of online learning in different settings, one area that has yet to be examined thoroughly, particularly in the context of online learning in Yemen, is the self-efficacy role. The purpose of this paper is to extend the Delone and McLean information system success model by incorporating a self-efficacy construct as an antecedent to user satisfaction and actual usage to predict student performance.

Questionnaire survey method was used to collect primary data from 448 students in nine public universities in Yemen. The six constructs in the proposed model were measured using existing scales. The data analysed using confirmatory factor analysis and structural equation modelling via AMOS.

Three main results were revealed, namely that overall quality (system, information and service quality) and self-efficacy have a positive impact on user satisfaction and actual usage; that actual usage significantly predicts user satisfaction; and that both user satisfaction and actual usage have a positive impact on student performance.

First as the study population were students from nine public universities, it excluded academics and administrative staff. Second, the study depends on self-reported measures to test the proposed research model. This is because getting objective data about the performance was not probable due to the issue of privacy.

The findings of this study can be a guideline for Yemeni higher education institutions to develop efficient and effective plans to improve the performance of education institutions, and train and develop student ability to use online learning. Additionally, it highlights the areas that university management needs to concentrate on, namely information systems (IS) tools that will contribute to higher student enrolment, address the lack of infrastructure and improve the quality of education outcomes, things which represent Yemen’s main challenges in the higher education sector.

This paper adds to the existing literature of IS by combining overall quality, self-efficacy, actual usage and user satisfaction to predict performance impact of online learning among students in nine public universities in Yemen. Furthermore, the predictive power of the proposed model has a higher ability to explain and predict performance impact compared to those obtained from some of the previous studies.

This study's purpose is to propose an integrated model based on expectation-confirmation model (ECM), task-technology fit (TTF) model, and updated DeLone and McLean information system (IS) success model to examine whether quality factors and TTF as antecedents to physician beliefs can affect physicians' continuance intention of the cloud-based hospital information system (HIS) and performance impact.

Sample data for this study were collected from physicians at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 305 (61.0 percent) usable questionnaires were analyzed using structural equation modeling in this study.

This study verified that physicians' perceived information quality, system quality, general technical support service quality, and cloud storage service quality all positively caused their PU, confirmation, and perceived TTF in the cloud-based HIS, which together explained their satisfaction with the system, and subsequently led to their continuance intention of the system and performance impact.

First, IS-related and cloud-related quality factors are simultaneously taken into consideration within this study's research model, and empirical results reveal deep insights into quality evaluation in the field of physicians' cloud-based HIS continuance intention. Next, this study contributes to an understanding of TTF in explaining physicians' cloud-based HIS continuance intention that is difficult to explain with only their utilitarian perception of the system, and places emphasis upon physicians' perception of performance impact greatly driven by their perceived TTF and continuance intention of the system, thus the results can shed light on antecedents and outcome of physicians' cloud-based HIS continuance intention.

The purpose of this paper is to examine the roles of task-technology fit (TTF), learning-technology fit (LTF) and cognitive absorption (CA) in determining medical professionals’ cloud-based electronic learning (e-learning) system continuance intention and performance outcomes and evaluate whether medical professionals’ perceived impact on learning can affect their perceived impact on tasks within medical institutions.

Sample data for this study were collected from medical professionals at six hospitals in Taiwan. A total of 600 questionnaires were distributed, and 373 (62.2%) usable questionnaires were analyzed using structural equation modeling in this study.

In this study, medical professionals’ perceived TTF and LTF as antecedents to their cloud-based e-learning continuance intention and performance outcomes were validated, and medical professionals’ perceived impact on learning had a positive effect on their perceived impact on tasks. Synthetically speaking, this study’s results strongly support the research model with all hypothesized links being significant.

It is particularly worth mentioning that this study introduces a new construct, “LTF,” to conceptualize, define and measure it, and further contributes to the application of capturing both expectation–confirmation model and CA (i.e. an intrinsic motivator) for completely explaining medical professionals’ perceived TTF and LTF as external variables to their cloud-based e-learning continuance intention and performance outcomes.

This study's purpose is to propose a hybrid model based on expectation-confirmation model (ECM) and technology acceptance model (TAM) to examine whether organizational users' perceived task-technology fit (TTF) in cloud enterprise resource planning (ERP) as an antecedent to user beliefs can directly and indirectly affect their continuance intention of cloud ERP and individual performance.

Sample data for this study were collected from end users of cloud ERP working in companies in Taiwan. A total of 500 questionnaires were distributed in the 50 sample companies, and 355 (71.0%) usable questionnaires were analyzed using structural equation modeling in this study.

This study showed that organizational users' perceived TTF contributed positively to their perceived usefulness, confirmation and perceived ease of use of cloud ERP, which in turn directly and indirectly led to their satisfaction with cloud ERP, continuance intention of cloud ERP and individual performance; that is, this study's findings strongly supported the research model integrating ECM, TAM and TTF model with all hypothesized links being significant.

This study contributes to an understanding of the TTF model in explaining organizational users' cloud ERP continuance intention that is difficult to explain with only their utilitarian perceptions of cloud ERP. Further, it is especially worth mentioning that this study places considerably more emphasis upon organizational users' individual performance greatly driven by their perceived TTF in cloud ERP and continuance intention of cloud ERP. Thus, this study's empirical evidence on incorporating ECM, TAM and TTF model can significantly enhance better understanding of the outcomes for cloud ERP continuance intention and shed light on the possible formulation of a richer post-adoption model.

The internet technology becomes an essential tool for individuals, organizations, and nations for growth and prosperity. The purpose of this paper is to integrate the DeLone and McLean IS success model with task-technology fit (TTF) to explain the performance impact of Yemeni Government employees.

Questionnaire survey method was used to collect primary data from 530 internet users among employees within all 30 government ministries-institutions in Yemen. The four constructs in the proposed model were measured using existing scales. The data analysis starts with initial exploratory factor analysis, then confirmatory factor analysis and lastly structural equation modeling via AMOS.

The results showed that the proposed integrated model fits the data well. Findings of the multivariate analysis demonstrate four main results. First, actual usage has a strong positive impact on user satisfaction, TTF, and performance impact. Second, user satisfaction has a great influence on performance impact. Third, TTF has a strong positive impact on user satisfaction and performance impact. Fourth, both user satisfaction and TTF mediate the relationship between the actual usage and performance impact.

The public sector in Yemen contains three parts: Yemeni prime minister, Yemeni ministries, and government agencies. This study focuses only on the Yemeni employees among Yemeni ministries; hence the results are not necessarily generalizable. Moreover, there are biases when the researcher measures the actual Internet usage variable through asking a participant about their opinion regarding their usage because these are generally found to differ from the true score of system usage.

The findings should be very useful for the Yemeni Government in presenting the importance of information technology effects on individual efficiency and effectiveness. Therefore, the information from these findings should encourage and support the formation of future policy at the organizational level and national level. If the government utilizes these findings by setting up strategies to promote internet usage, this may, in turn, improve professional practice, personal development, and quality of working life.

This paper adds to the existing literature of information systems by combining actual technology usage, user satisfaction, and TTF to predict performance impact within the organizations. Furthermore, this study proposed a second-order model of performance impact in order to increase the power of explaining the output by the model, which contains four first-order constructs: process, knowledge acquisition, communication quality, and decision quality. The predictive power of the proposed model has a higher ability to explain and predict performance impact compared to those obtained from some of the previous studies.

Online learning has evolved into a necessary means of learning because of its capability to enhance the education quality with minimum resources and infrastructure. Nevertheless, while academics have studied the espousal and use of online learning in various settings, the effect of compatibility and transformational leadership (TL) still remains to be seen, with regards to the Yemeni context. The purpose of this paper is to forward the Delone and Mclean Information System (IS) success Model by integrating compatibility and TL constructs as precursors to user contentment and actual use for estimating performance of students.

The questionnaire technique was utilised for gathering primary data from 448 students in nine state-funded Yemeni universities. The six variables in the recommended framework were gauged utilising current scales. Data analysis was done by deploying structural equation modelling through SmartPLS 3.0.

The outcomes encompassed three key results: overall quality (data, system and service quality), compatibility and TL have a favourable effect on user satisfaction and actual use; actual use considerably estimates user satisfaction; and user satisfaction and actual use have a favourable effect on performance of students.

Because the research populace comprised students from nine state-funded universities, it did not include administrative and academic staff. Furthermore, as the study was cross-sectional, it studied the variables at a single point of time. Attaining experience in utilising online learning would transform the convictions of students, and this cannot be traced through a cross-sectional scrutiny. Moreover, the research relies upon self-testified measures for ascertaining the recommended research model. The reason behind this is that obtaining objective information regarding performance was not likely because of the privacy concern.

Despite the fact that Yemen is a low-income emerging nation with inadequate resources (World Development Indicators, 2017), it can capitalise on online-based learning that provides the advantage of excellent education and that too with limited supplies (Dokhan and Akkoyunlu, 2016; Yang et al., 2016). Additionally, online learning can enhance administration and communication, empower learning anywhere and anytime, and endorse fairness of education.

This study supplements the existing studies on information systems by blending overall quality, compatibility, TL, actual use and client satisfaction for estimating the effect of online learning among students from nine state-funded Yemeni universities. Moreover, the recommended model’s predictive prowess has a higher capability to elucidate and estimate the performance effect as against those acquired from few of the previous studies.