Interface agents as social models for female students: The effects of agent visual presence and appearance on female students’ attitudes and beliefs

The current work investigates the use of interface agents as anthropomorphic social models to influence young women’s negative beliefs and low self-efficacy regarding engineering. Experiment 1 focused on the impact of agent model visual presence vs. voice alone for changing the women’s beliefs. Based on literature on human social models we hypothesized that the visual presence of the interface agent would result in more positive attitudes toward engineering and greater self-efficacy than the presence of a human voice alone. Experiment 2 focused on the impact of model appearance-related characteristics for changing the women’s beliefs. Previous work with human social models suggests that people are more persuaded by models that are similar to them. Therefore, models that were young, female, and “cool” were predicted to be more effective in influencing young women’s attitudes. In accordance with our hypothesis, results revealed that participants who interacted with the visible agents reported significantly greater utility for engineering, greater self-efficacy, and greater interest in engineering-related fields than those who interacted with a human voice. In addition, the agent models that were similar to the young women tended to be the most effective for positively influencing the women’s stereotypes and self-efficacy.     

The impact of general and specific performance and self-efficacy on learning with computer-based concept mapping

When students learn a new and challenging task, for which they have very limited corresponding personal or vicarious experiences to refer, it is important to understand how their self-efficacy beliefs evolve during the course of sequential lessons; how they differ in the way their general learning performance and self-efficacy influence their ratings of task-specific self-efficacy and performance; and, how such differences may result in different learning outcomes and motivations for learning. By examining a group of 66 students engaged in learning to construct good concept maps with computer software, this study revealed several important findings on these questions. Students generally tended to initially overestimate their ability to successfully carry out the required task. They also varied in the way their general self-efficacy and performance were associated with their task-specific self-efficacy and performance. And, these differences did appear to be associated with different learning outcomes and motivations for learning. These results indicate that investigating individual differences in students’ patterns of association between general and specific performance and their self-efficacy may lead to a better understanding of how students differ in their levels of motivation and outcomes when learning a new and challenging task.     

Understanding knowledge management system usage antecedents: An integration of social cognitive theory and task technology fit

The factors influencing KMS usage are of major concern to the MIS community. Among the diverse theories employed to help understand this is task technology fit (TTF), which considers the needed technological characteristics of the task as a major factor determining usage. This theory, however, ignores the personal cognition dimension, which has been found to affect the use of an IS. By integrating TTF and social cognitive theory (SCT), we attempted to determine the key factors affecting KMS usage in IT, the organizational task, and personal cognition. Through a survey of 192 KMS users, task interdependence, perceived task technology fit, KMS self-efficacy, and personal outcome expectations were found to have substantial influences on KMS usage. Among the key factors, KMS self-efficacy was found to be especially important as it was substantially and positively correlated to perceived task technology fit, personal and performance-related outcome expectations, and KMS usage.     

Effects of a collaborative annotation method on students’ learning and learning-related motivation and affect

Two studies tested the effectiveness of a web-based collaborative annotation system (Hy-Lighter) for learning comprehension, and learning-related affect and motivation. In an undergraduate course setting, students (N = 27) in study 1, (1) highlighted and annotated selected articles, and (2) highlighted and annotated selected articles and reviewed peer highlights and annotations. In a graduate course setting, students (N = 40) in study 2, (1) highlighted and annotated selected articles, and (2) highlighted and annotated selected articles and reviewed peer highlights and annotations. Control groups in both studies read a hard copy of the articles -without using HyLighter and engaging in its associated annotation practices. The main dependent variables included: (a) performance on quizzes, and (b) a number of affective and motivational variables related to reading assignments and academic success. Although not statistically significant, summative assessment scores were higher for students using HyLigther relative to the ones exposed to conventional instruction. HyLighter use also seemed to be associated with more positive affect in undergraduate students relative to their graduate counterparts. Somewhat equivocal findings between the two studies were attributed to the differential implementation of the software in and outside of the classroom. Recommendations for optimal use and desired outcomes were advanced.     

Assessing the effects of self-efficacy and competence on individual satisfaction with computer use: an IT student perspective

To explore the determinants of the success of applying computing technology to computer-related work, this study proposed a theoretical model that adopts individual satisfaction as a surrogate for the success of computer learning. Based on social cognitive theory (SCT) and competence-related literature, this study considered self-efficacy, computer competence, and near-term and long-term consequences as the determinants of individual satisfaction with computer use. The research model was tested using a questionnaire survey of 367 IT-related senior undergraduate students in five colleges. The empirical results identified self-efficacy as a strong and positive antecedent of competence, and confirmed the positive effects of self-efficacy on perceived consequences. Additionally, computer competence was found to affect individual satisfaction with computer use directly and indirectly. Moreover, perceived consequences influenced individual satisfaction more than did competence. Overall, this study provided empirical results involved theoretical explanations for understanding the effects of self-efficacy and competence on computer learning behavior. The limitations of the present study were discussed for researchers and practitioners.     

Computer mediated communication for social and academic purposes: Profiles of use and University students’ gratifications

The present study approaches the Internet as a social space, where university students make use of computer mediated communication (CMC) applications, i.e. e-mail, instant messaging and social network sites, in order to satisfy social and academic needs. We focus on university students, because they represent one of the most avid groups of CMC users and additionally, because they are expected to carry their perceptions of media with them into the work place and their social life. In order to investigate this issue, we conducted an empirical research using, as a target group, a sample of students from a specific Greek University. Grounded in the “uses and gratifications” perspective, we investigated the various profiles of CMC use by students along with (a) the students’ perceptions about social and academic usefulness of CMC applications, (b) the extent up to which these perceptions are correlated with students’ prior experience with the use of CMC applications, and (c) how both of these factors can predict the frequency of present use of CMC for social or academic purposes respectively. The results reveal that although these three CMC applications constitute “functional alternatives” (media that satisfy similar needs) they are different to the degree of their “functionality” for the gratification of social and academic needs. Furthermore, the degree of CMC use by students is not correlated with the years of CMC experience, but with the profile of use that students dynamically adopt according to their daily needs and preferences. The results provide evidence for the current CMC use by university students and can be useful for the implementation of further academic policies regarding CMC use in Higher Education settings.     

Testing alternative models of individuals’ social media involvement and satisfaction

This study extends the Technology Acceptance Model 3 (TAM 3) within the context of the rapidly evolving area of social media. Since social media requires the user’s active participation and processing of information as well as the creation of user-generated content, this timely study introduces the two relevant constructs of social media involvement and social media satisfaction that are associated with TAM 3. This study then develops three alternative conceptual models and empirically validates each of them using datasets obtained from the United States and Saudi Arabia. The LISREL analysis results show that the Dual Mediation Impact model is the best-fit model for both datasets. Further, the results show that a user’s social media involvement and social media satisfaction are dual mediators of the TAM 3 factors on social media usage intention. While the two country data show some differences in the strength of the relationships in the Dual Mediation Impact model, the identified model provides a common framework for global use. Implications and future research directions are discussed.     

Building surrogate models for engineering problems by integrating limited simulation data and monotonic engineering knowledge

The use of surrogate models to replace expensive computations with computer simulations has been widely studied in engineering problems. However, often only limited simulation data is available when designing complex products due to the cost of obtaining this kind of data. This presents a challenge for building surrogate models because the information contained in the limited simulation data is incomplete. Therefore, a method for building surrogate models by integrating limited simulation data and engineering knowledge with evolutionary neural networks (eDaKnow) is presented. In eDaKnow, a neural network uses an evolutionary algorithm to integrate the simulation data and the monotonic engineering knowledge to learn its weights and structure synchronously. This method involves converting both limited simulation data and engineering knowledge into the respective fitness functions. Compared with the previous work of others, we propose a method to train the surrogate model by combining data and knowledge through evolutionary neural network. We take knowledge as fitness function to train the model, and use a network structure self-learning method, which means that there is no need to adjust the network structure manually. The empirical results show that: (1) eDaKnow can be used to integrate limited simulation data and monotonic knowledge into a neural network, (2) the prediction accuracy of the newly constructed surrogate model is increased significantly, and (3) the proposed eDaKnow outperforms other methods on relatively complex benchmark functions and engineering problems.     

A step toward STEP-compatible engineering data management: the data models of product structure and engineering changes

In an iterative design process, there is a large amount of engineering data to be processed. Well-managed engineering data can ensure the competitiveness of companies in the competitive market. It has been recognized that a product data model is the basis for establishing engineering database. To fully support the complete product data representation in its life cycle, an international product data representation and exchange standard, STEP, is applied to model the representation of a product. In this paper, the architecture of an engineering data management (EDM) system is described, which consists of an integrated product database. There are six STEP-compatible data models constructed to demonstrate the integratibility of EDM system using common data modeling format. These data models are product definition, product structure, shape representation, engineering change, approval, and production scheduling. These data models are defined according to the integrated resources of STEP/ISO 10303 (Parts 41-44), which support a complete product information representation and a standard data format. Thus, application systems, such as CAD/CAM and MRP systems, can interact with the EDM system by accessing the database based on the STEP data exchange standard.     

Individual and team annotation effects on students’ reading comprehension,critical thinking,and meta-cognitive skills

Many students enter college without the needed skills to be successful. Colleges and universities are seeking instructional interventions to address these needs. Various classes are leveraging web-based social media to provide new instructional technologies that will help students learn. This paper reports on two studies related to the potential of online social annotation for improving teaching and learning in second-semester Freshman English classes. The approach, referred to as the Social Annotation Model-Learning System (SAM-LS), combines various instructional strategies, team-based learning, and a social annotation computer-supported collaborative learning tool, HyLighter, to increase student engagement with selected essays and with classmates. SAM-LS stimulates students to actively monitor their thoughts and compare them to both peers and the instructor (or domain experts). Study 1 showed no significant difference between the SAM-LS approach and a control; however, results appear to be related to confounding factors. Study 2 showed that students achieve better outcomes on measures of reading comprehension and meta-cognitive skill, but not critical thinking, when SAM-LS activities include small team collaborations. The two studies suggest future directions for research and development of SAM-LS and the HyLighter tool.     

“It doesn’t matter what you are!” Explaining social effects of agents and avatars

Empirical studies have repeatedly shown that autonomous artificial entities, so-called embodied conversational agents, elicit social behavior on the part of the human interlocutor. Various theoretical approaches have tried to explain this phenomenon: According to the Threshold Model of Social Influence (Blascovich et al., 2002), the social influence of real persons who are represented by avatars will always be high, whereas the influence of an artificial entity depends on the realism of its behavior. Conversely, the Ethopoeia concept (Nass & Moon, 2000) predicts that automatic social reactions are triggered by situations as soon as they include social cues. The presented study evaluates whether participants´ belief in interacting with either an avatar (a virtual representation of a human) or an agent (autonomous virtual person) lead to different social effects. We used a 2 × 2 design with two levels of agency (agent or avatar) and two levels of behavioral realism (showing feedback behavior versus showing no behavior). We found that the belief of interacting with either an avatar or an agent barely resulted in differences with regard to the evaluation of the virtual character or behavioral reactions, whereas higher behavioral realism affected both. It is discussed to what extent the results thus support the Ethopoeia concept.     

The role of perceived social capital and flow experience in building users’ continuance intention to social networking sites in China

The long-term development of social networking sites (SNSs) relies on their users’ continuance of use. This paper tested the role of perceived social capital and flow experience in driving users to continue using SNSs based on the expectation–confirmation model of information systems continuance. Using data from online surveys of social networking sites users in China, the proposed model was tested by using the Partial Least Squares (PLSs) technique. The results show that perceived bridging and bonding social capital have different role in building users’ satisfaction and continuance intention: perceived bridging social capital has remarkable influence on users’ satisfaction and continuance intention, but perceived bonding social capital has none. Flow experience has influence on users’ satisfaction but none on continuance intention. In addition, gender has impact on users’ continuance intention.     

Team shared mental model as a contributing factor to team performance and students’ course satisfaction in blended courses

The purpose of the study was to examine how team shared mental model (SMM), team performance, and students’ course satisfaction change over time and how Team-SMM affects team performance and students’ course satisfaction. Forty-eight preservice teachers from two undergraduate blended courses participated in this study. The data were obtained via two online questionnaires (shared mental model instrument and Course Satisfaction Scale) administered throughout Spring 2010. Data analysis was conducted using repeated measures ANOVA and multiple linear regression techniques. Results indicated that Team-SMM and students’ course satisfaction changed slightly over time but the change was not statistically significant. Team performance increased significantly over the courses. Additionally, attitudes towards teammates and task were closely linked with effective team performance and students satisfaction. In the early stage of the courses, general team knowledge, resource, and environment explained a significant amount of variance in students’ course satisfaction.     

Learning secondary mathematics with technology: Exploring the complex interrelationship between students’ attitudes,engagement, gender and achievement

The aim of this study was to investigate the complex relationship between students’ mathematics confidence, confidence with technology, attitude to learning mathematics with technology, affective engagement and behavioural engagement, achievement, gender and year level. The participants were secondary students from state co-educational schools in Metropolitan Athens, Greece. Gender differences as well as differences between year levels and the resulting clusters of students were investigated by using a MANOVA. It was found that boys expressed more positive views towards mathematics and more positive views towards the use of technology in mathematics, compared to girls. It was also found that high achievement in mathematics was associated with high levels of mathematics confidence, strongly positive levels of affective engagement and behavioural engagement, high confidence in using technology and a strongly positive attitude to learning mathematics with technology. Low levels of mathematics achievement was associated with low levels of mathematics confidence, strongly negative levels of affective engagement and behavioural engagement, low confidence in using technology, and a negative attitude to learning mathematics with technology.     

The relationships among the Big Five Personality factors,self-esteem,narcissism, and sensation-seeking to Chinese University students’ uses of social networking sites (SNSs)

It has been suggested that personality factors are related to an individuals’ use of social networking sites (SNSs). The present research explores the relationships between the Big Five Personality factors, narcissism, self-esteem, and sensation seeking and individuals’ use of specific features of SNS. Self-reports were collected from 265 SNS users from a university in China. Regression analyses revealed that personality factors play an important role in how SNS are used. Specifically, extraverts are more likely to use the communicative function of SNS including status update, comment, and adding more friends. Neurotic are more likely to use the feature of status update as a way of self-expression. Agreeable individuals tend to make more comments on others’ profiles. Individuals with high self-esteem are more likely to comment on others’ profiles. Users scoring high on openness and sensation seeking are more likely to play online games on SNS. Narcissistic users are more likely to upload their attractive photos on SNS and tend to use update status more frequently for self-presentation. Gender also played an important role in predicting types of SNS use. Males reported more SNS friends and were more likely to play online games than were females, who were more likely to upload self-photos and update their status.     

Identification of Wiener models for dynamic and steady‐state performance with application to solid oxide fuel cell

This work is concerned with identification of Wiener models (a linear dynamic part connected in series with a nonlinear dynamic one). A neural network with one hidden layer is used as the nonlinear block of the model, two network configurations are considered. For model identification three algorithms are described. In the first case model accuracy only in transient conditions is considered, only the dynamic data is used for model training. In the next two algorithms model accuracy in both transient and steady‐state conditions is considered, dynamic and steady‐state data sets are used. The steady‐state model errors are taken into account by an additional term in the minimized cost‐function or by additional inequality constraints. For comparison of discussed algorithms and model structures, identification of a Wiener model of a solid oxide fuel cell (SOFC) process is considered. It is shown that the best results are obtained by the algorithm 2 which minimizes at the same time both dynamic and steady‐state model errors, additional constraints used in the algorithm 3 are computationally quite demanding.     

Robustness analysis framework for computations associated with building performance models and immersive virtual experiments

Building performance models (BPMs) have been used to simulate and analyze building performance during design. While extensive research efforts have made to improve the performance of BPMs, little attention has given to their robustness. Uncertainty is a crucial factor affecting the robustness of BPMs, in which such effect needs to be quantified through a suitable approach. The paper offers a robustness analysis framework for BPMs by using perturbation techniques to simulate uncertainty in input datasets. To investigate the efficacy of the framework, a generative adversarial network (GAN)-based framework was selected as a case study to analyze light switch usages in a single-occupancy office simulated using an immersive virtual environment (IVE). The robustness of the GAN was analyzed by comparing differences between a baseline (i.e., a BPM obtained from the GAN trained on a non-perturbed dataset) and BPMs obtained from the GAN trained on perturbed datasets. Overall, the robustness of the GAN significantly reduced when the training datasets were perturbed by using structured transformation techniques. The GAN remained relatively robust when the training datasets were perturbed by using an additive perturbation. Additionally, the sensitivity of the GAN involves different magnitudes corresponding to different levels of perturbed input datasets. The study suggests that the perturbation analysis is effective for investigating data uncertainty affecting the robustness of BPMs.     

Kei-Tying teens: Using mobile phone e-mail to bond, bridge, and break with social ties—a study of Japanese adolescents

This paper examines the extent to which Japanese adolescents use mobile phone e-mail to bond, bridge, and break with their social ties. Although existing literature shows that adolescents use mobile phone e-mail to bond with intimate strong ties, the fluid nature of social networks during adolescence suggests that mobile phone e-mail may also be used to bridge to new ties and to break with old ties. Drawing on a stratified random sample survey of 501 high school students living in Tokyo, we find that mobile phone e-mail is used both to bond and bridge, but not to break with ties. We also find that the intensity with which Japanese adolescents use mobile phone e-mail is more fundamentally a result of bridging than bonding. These findings apply both to typical users and heavy users.     

Effect of guard‐ring on the DC and high‐frequency performance of deep‐submicrometer metal oxide semiconductor field effect transistor

The influence of guard‐ring (GR) on the direct current (DC) and high‐frequency performance of deep‐submicrometer metal oxide semiconductor field effect transistors (MOSFETs) is investigated in this study. MOSFETs with four different GRs are fabricated using 90 nm complementary metal oxide semiconductor (CMOS) process, and a detailed comparative study on their device performances is performed. A united DC and small signal equivalent circuit model that takes into the effect of GR is developed. A set of simple, but efficient formulas provide a bidirectional bridge for the S parameters transformation between devices with different GRs. The corresponding model parameters for MOSFETs with different GRs are determined from S parameter on‐wafer measurement up to 40 GHz. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:259–267, 2014.