The incorporation of hands-on tasks in an online course: an analysis of a blended learning environment

This article describes the design and evaluation of a blended online/face-to-face course completed by more than 6000 learners throughout the United States of America and internationally. The educational impact was monitored using a variety of evaluation strategies. The results, in terms of achieved knowledge and overall satisfaction, indicate that a focus on online instruction combined with face-to-face, hands-on activities showed statistically significant improvement in the learners' understanding of the course material, while also validating the impact of the curriculum in their workplace. As illustrated through the blended course design, this study further showed that online learners with greater improvement in their pre- and posttest scores also exhibited significantly greater likelihood in demonstrating competency in several areas during the hands-on portion of the course. In particular, participants working in the information systems field exhibited the highest mean difference score (21.49) on the pre- and the posttests, while those working in the laboratory had the lowest (12.17). Likewise, the odds that participants who reviewed the course contents sought to further understand their job roles was 58.2 times greater for those in information systems, while it was only 19.0 times greater for laboratory staff, than those who did not review their job roles.     

Detecting Violations of Factorial Invariance Using Data-Based Specification Searches: A Monte Carlo Study

In testing factorial invariance, researchers have often used a reference variable strategy in which the factor loading for a variable (i.e., reference variable) is fixed to 1 for identification. This commonly used method can be misleading if the chosen reference variable is actually a noninvariant item. This simulation study suggests an alternative method for testing factorial invariance and evaluates the performance of the method in specification searches based on the modification index. The results of the study showed that the proposed specification searches performed well when the number of noninvariant variables was relatively small and this performance improved as sample size increased and the size of group differences increased. When the number of noninvariant variables was relatively large, however, the method rarely succeeded in detecting the noninvariant items in the specification searches. Implications of the findings are discussed along with the limitations of the study.     

A Cross-Cultural Comparison of the Effects of Source Credibility on Attitudes and Behavioral Intentions

In this article, we investigated (a) whether the commonly reported 3 dimensions of source credibility (expertise, trustworthiness, and attractiveness) are applicable to both Americans and Koreans, and (b) which of those 3 dimensions exerted more influence on the dependent variables in each country. Findings suggest that the dimensionality of source credibility was remarkably similar between the 2 samples. The influence of 3 source credibility dimensions varied by the dependent variables. Attractiveness, expertise, and trustworthiness were equally important to purchase intentions. All 3 dimensions affected involvement with the advertisement message equally. Only trustworthiness had a significant impact on attitude toward brand and brand beliefs. In terms of attitude toward the advertisement, perceived attractiveness of the endorser was more important than expertise and trustworthiness.     

Re-presenting Sport: How Instant Replay and Perceived Violence Impact Enjoyment of Mediated Sports

Several long-standing theories intersect in discussing the impact of community characteristics and of the mass media. The structural pluralism model popularized by Tichenor and his colleagues says that social structure influences how mass media operate in communities because they respond to how power is distributed in the social system, whereas the linear model says that the increasing size of a community's population leads to more social differentiation and diversity and corresponding increases in subcultures with their own beliefs, customs, and behaviors. Recently, there has been a concern about how changes in society have led to a decline in organizational activity and the network of relationships and trust that constitute “social capital.” This article examines the impact of population and diversity (using census data) on individuals’ media use, interpersonal discussion and civic engagement (measured in a national survey), and the relationship among these variables. Analysis of a structural model provides evidence that the “linear hypothesis” can be combined with structural pluralism, with size—measured by population—impacting diversity, which influences the relationships that people have with their community. Concurrently, social categories influence people's communication patterns and community relationships, and communication impacts civic engagement.     

Cultural influences on consumers' processing of advertising: A structural equation approach

This study reports a structural equation approach to the cultural differences in consumers' processing of advertising. The study hypothesized a path model for advertising processing and tested it for three different groups: Koreans, Korean‐Americans, and Caucasian‐Americans. The findings revealed that the final path patterns were different according to consumers' cultural background. Even though the influences of ad content were significant across the three different groups, prior attitudes to the brand played a more important role in Koreans' advertising processing than in Caucasian‐Americans' processing. The impact of each demographic variable also varied according to culture. The results were discussed through Hofstede's four cultural dimensions and Hall's dichotomy of high‐context versus low‐context culture.     

An integrated framework for RFID adoption and diffusion with a stage-scale-scope cubicle model: A case of Indonesia

This study presents a comprehensive framework to identify dynamic radio frequency identification (RFID) adoption and diffusion from three different perspectives: stages of adoption, levels of analysis, and domain of issues. The main concern of this study is stages of adoption, which covers three phases in respect of the maturity of the RFID project and the sophistication of business applications and RFID technology. The level of analysis involves different units of analysis beyond the organization level, including the industry- and country-level, which is lacking in the current literature. To understand dimensions of RFID issues, a strategy, technology, organization, people and environment (STOPE) based approach was applied. An extensive review of prior literature was conducted to find various RFID success factors and the Delphi method was applied to find positions of these factors within the framework. Based on the Delphi, some factors belong to early stage of adoption, and some others persist in the later stages of adoption. At the country level, factors such as RFID national policy, R&D policy and income per capita were accepted by most experts at the preliminary and intermediate stage; strategy and environment were accepted as important domains. To find practical implications of the framework, a case study of Indonesia was conducted at each level of analysis. Analytic hierarchy process (AHP) was applied to identify most important factors and important domains of issues with respect to the factors from the Delphi results. At country level, RFID policy, vision of leadership and RFID potential market are the most important factors; strategy and environment are the most important domains.     

Teaching about complex systems is no simple matter: building effective professional development for computer-supported complex systems instruction

The recent next generation science standards in the United States have emphasized learning about complex systems as a core feature of science learning. Over the past 15 years, a number of educational tools and theories have been investigated to help students learn about complex systems; but surprisingly, little research has been devoted to identifying the supports that teachers need to teach about complex systems in the classroom. In this paper, we aim to address this gap in the literature. We describe a 2-year professional development study in which we gathered data on teachers’ abilities and perceptions regarding the delivery of computer-supported complex systems curricula. We present results across the 2 years of the project and demonstrate the need for particular instructional supports to improve implementation efforts, including providing differentiated opportunities to build expertise and addressing teacher beliefs about whether computational-model construction belongs in the science classroom. Results from students’ classroom experiences and learning over the 2 years are offered to further illustrate the impact of these instructional supports.