Algorithmic or Human Source? Examining Relative Hostile Media Effect With a Transformer-Based Framework

The relative hostile media effect suggests that partisans tend to perceive the bias of slanted news differently depending on whether the news is slanted in favor of or against their sides. To explore the effect of an algorithmic vs. human source on hostile media perceptions, this study conducts a 3 (author attribution: human, algorithm, or human-assisted algorithm) x 3 (news attitude: pro-issue, neutral, or anti-issue) mixed factorial design online experiment (<em>N</em> = 511). This study uses a transformer-based adversarial network to auto-generate comparable news headlines. The framework was trained with a dataset of 364,986 news stories from 22 mainstream media outlets. The results show that the relative hostile media effect occurs when people read news headlines attributed to all types of authors. News attributed to a sole human source is perceived as more credible than news attributed to two algorithm-related sources. For anti-Trump news headlines, there exists an interaction effect between author attribution and issue partisanship while controlling for people’s prior belief in machine heuristics. The difference of hostile media perceptions between the two partisan groups was relatively larger in anti-Trump news headlines compared with pro-Trump news headlines.

Spacing, Feedback, and Testing Boost Vocabulary Learning in a Web Application

Information and communication technology (ICT) becomes more prevalent in education but its general efficacy and that of specific learning applications are not fully established yet. One way to further improve learning applications could be to use insights from fundamental memory research. We here assess whether four established learning principles (spacing, corrective feedback, testing, and multimodality) can be translated into an applied ICT context to facilitate vocabulary learning in a self-developed web application. Effects on the amount of newly learned vocabulary were assessed in a mixed factorial design (3×2×2×2) with the independent variables Spacing (between-subjects; one, two, or four sessions), Feedback (within-subjects; with or without), Testing (within-subjects, 70 or 30% retrieval trials), and Multimodality (within-subjects; unimodal or multimodal). Data from 79 participants revealed significant main effects for Spacing [F(2,76) = 8.51, p = 0.0005, ηp2=0.18] and Feedback [F(1,76) = 21.38, p &lt; 0.0001, ηp2=0.22], and a significant interaction between Feedback and Testing [F(1,76) = 14.12, p = 0.0003, ηp2=0.16]. Optimal Spacing and the presence of corrective Feedback in combination with Testing together boost learning by 29% as compared to non-optimal realizations (massed learning, testing with the lack of corrective feedback). Our findings indicate that established learning principles derived from basic memory research can successfully be implemented in web applications to optimize vocabulary learning.

Pengaruh Probability To Audit Dan Machiavellianism Terhadap Tax Evasion

This study aims to analyze the effect of probability to audit and Machiavellianism on tax evasion behavior. There are two approaches to explain the factors that influence taxpayer behavior on compliance and tax evasion, named the economic approach (external factors) and non-economic approach which is the socio-psychological approach (internal factors). This study used a quasi-experimental design with 2x2 mixed factorial design to test the effect of probability to audit (external factors) and machiavellianism (internal factors) on tax evasion behavior. The hypothesis in this study tested by using repeated measures ANOVA. The results of this study indicate that subjects in a low probability to audit condition tend to commit tax evasion. Also, the results of this study found that there is no influence between a high-machiavellian subject and a low-machiavellian subject on tax evasion behavior. Furthermore, the results of this study found that there is interaction between probability to audit and machiavellianism on tax evasion behavior.

Anti-Immigration Media Portrayals and Latinx Well-Being

The current study examined the immediate impact of exposure to anti-immigration sentiments on the psychological well-being of Latinx young adults. A quasiexperimental, mixed-factorial design was used to analyze differences in mood, stress, ethnic identification, and motivation to take action after exposure to a video stressor across four groups: immigrants from Latin America, first-generation Latinx Americans, second-generation and up Latinx Americans, and non-Latinx, nonimmigrant, White Americans. Three hundred forty participants, ages 18–30, were randomly assigned to either an experimental condition involving an anti-immigration video or a control condition involving a multivitamin video. As hypothesized, those who viewed the anti-immigration video exhibited significantly higher levels of negative affect (p < .001; ηp2 =.06), stress (p < .001; ηp2 =.04), and motivation to take action (p < .001; ηp2 =.07) than those who viewed the multivitamin video. Additionally, Ethnicity/Generation American was associated with higher negative affect (p < .001, ηp2 =.06), stress (p = .01, ηp2 =.04), and motivation to take action (p < .001, ηp2 =.10) after video viewings, such that immigrants from Latin American countries and first-generation Latinx Americans tended to have greater levels than the other groups (pairwise comparison ps < .05). Contrary to our hypothesis, results indicated that firstgeneration Latinx Americans (p = .01) and non-Latinx, nonimmigrant participants (p < .001) experienced a significant decrease in ethnic identification after viewing the anti-immigration video. Our results indicate that, across the differing Ethnicities/Generations American, participants are impacted by anti-immigration sentiments in the media.

Achieving structured knowledge management with a novel online group decision support system

Knowledge management (KM) is a complicated process that involves socialization, externalization, combination, and internalization and requires close collaboration among the people involved. Although Nonaka proposed the SECI (Socialization, Externalization, Combination, Internalization) model and the concept of Ba, which provides a process-oriented view of knowledge creation and transfer, practicing it is rather ad hoc. COVID-19 has provided a chance for practitioners to find a new method for KM. In this study, we adapted a group problem-solving system called TeamSpirit and structured it as a Ba for the SECI model. We then compared TeamSpirit with two other implementations of Ba, email and face-to-face communication, to evaluate their effects on knowledge externalization, knowledge combination, and knowledge internalization. Then, we evaluated whether these knowledge-conversion processes could improve knowledge acquisition and intention to share knowledge. A 3 × 2 mixed factorial design experiment was conducted. The results show that (a) TeamSpirit was better than the others, and face-to-face was better than email for each of the three knowledge conversion processes (externalization, combination, and internalization) and (b) the better the team’s knowledge conversion process lead, the stronger its knowledge acquisition and knowledge-sharing intention.

Effects and Prerequisites of Self-Generation in Inquiry-Based Learning

The goal of this study is to investigate the effect of self-generation in inquiry-based learning and to identify the role of feedback. While open-ended inquiry-based learning with a high degree of self-generation requirements has long been considered optimal for facilitating effective learning, its long-run effects have been critically challenged. This study employed a 3 (learning condition) × 2 (retention interval) mixed factorial design (N = 98). An inquiry activity involving the self-generation of content knowledge with or without subsequent feedback was compared to an inquiry task in which students simply read hypotheses and data interpretations. Self-generation without feedback was subject to rereading and self-generation with feedback. However, no differences were found under the two latter conditions. An additional analysis of individual learners’ abilities revealed that different abilities (e.g., cognitive load, self-generation success) served as predictors of performance in the disparate treatments.

Agree to disagree: Examining the psychometrics of cybervetting

PurposeDue to the paucity of research on web-based job applicant screening (i.e. cybervetting), the purpose of the current study was to examine the psychometric properties of cybervetting, including an examination of the impact of adding structure to the rating process.Design/methodology/approachUsing a mixed-factorial design, 122 supervisors conducted cybervetting evaluations of applicant personality, cognitive ability, written communication skills, professionalism, and overall suitability. Cross-method agreement (i.e. the degree of similarity between cybervetting ratings and other assessment methods), as well as interrater reliability and agreement were examined, and unstructured versus structured cybervetting rating formats were compared.FindingsCybervetting assessments demonstrated high interrater reliability and interrater agreement, but only limited evidence of cross-method agreement was provided. In addition, adding structure to the cybervetting process did not enhance the psychometric properties of this assessment technique.Practical implicationsThis study highlighted that whereas cybervetting raters demonstrated a high degree of consensus in cybervetting-based attributions, there may be concerns regarding assessment accuracy, as cybervetting-based ratings generally differed from applicant test scores and self-assessment ratings. Thus, employers should use caution when utilizing this pre-employment screening technique.Originality/valueWhereas previous research has suggested that cybervetting ratings demonstrate convergence with other traditional assessments (albeit with relatively small effects), these correlational links do not provide information regarding cross-method agreement or method interchangeability. Thus, this study bridges a crucial gap in the literature by examining cross-method agreement for a variety of job-relevant constructs, as well as empirically testing the impact of adding structure to the cybervetting rating process.

Spacing, Feedback, and Testing Boost Vocabulary Learning in a Web Application

As information and communication technology (ICT) becomes more prevalent in education its efficacy in general and that of specific learning applications in particular has not been fully established yet. One way to further improve learning applications could be to use insights from fundamental memory research. We here assess whether four established learning principles (spacing, feedback, testing, and multimodality) can be translated into an applied ICT context to facilitate vocabulary learning in a self-developed web application. Effects on the amount of newly learned vocabulary were assessed in a mixed factorial design (3×2×2×2) with the independent variables Spacing (between-subjects; one, two, or four sessions), Feedback (within-subjects; with or without), Testing (within-subjects, 70% or 30% retrieval trials), and Multimodality (within-subjects; unimodal or multimodal). Data from 79 participants was analyzed and revealed significant main effects for Spacing (F[2, 76] = 8.51, p = 0.0005, η^2p = 0.18) and Feedback (F[1, 76] = 21.38, p &lt; 0.001, η^2p= 0.22), and a significant interaction between Feedback and Testing (F[1, 76] = 14.12, p = 0.0003, η^2p = 0.16). Optimal Spacing and the presence of corrective Feedback in combination with Testing together boost learning by 29% as compared to non-optimal realizations (massed learning, testing with lack of corrective feedback). Our findings indicate that established learning principles derived from basic memory research can successfully be implemented in web applications to optimize the acquisition of new vocabulary.

Efektifitas Executive Coaching Pada Tipe Kepemimpinan Transformasional Dan Transaksional

Executive coaching that considers leadership types has the potential to change behavior that can improve individual and organizational performance. This is what prompted a study to determine the effectiveness of giving executive coaching on the types of transformational and transactional leadership.The design of the study designed in this study is mixed-factorial design 2x2 between-within subject. The first factor is executive coaching which consists of two levels, namely executive coaching and no executive coaching and the second factor is the type of leadership which consists of two levels, namely transformational and transactional on proactive influence tactics rational persuasion, inspirational appeals, consultation, collaboration. The data measured or observed in this study is the sales performance of the experimental participants consisting of sales heads and key account heads in automotive multinational companies.The findings of this study indicate that this type of transformational leadership with executive coaching has proven to be more effective in improving sales head and key account head sales performance. Furthermore, this study also shows that in the type of transformational leadership, the proactive collaboration and consultation influence tactics proved to be more effective while the transactional leadership type will be more effective in proactive rational and inspirational tactics.

Share and share alike?

Purpose The growing trend for online peer-to-peer commerce has changed the way consumers purchase and exchange products and services across a wide variety of industries, including the craft beer industry. The lack of large scale distribution channels for local breweries has led to a growing market for social exchanges across the country. However, these barter systems remain more obscure compared to their mega counterparts in monetary exchange systems. The purpose of this paper is to evaluate how the set-up of online beer marketplaces impacts the perceptions of source attractiveness as moderated by the perceived risks to encourage exchange behaviors. Design/methodology/approach Using an established beer exchange community, members appraised the impact of avatar profiles in their decision-making process based on user congruity, product congruity and risk perceptions. The research was conducted using a 2×2 between subjects mixed factorial design. Findings Product attractiveness and risk perceptions influenced behavioral intentions while user attractiveness did not. This is counter to past research that emphasizes the importance of relationships in sharing economy contexts. Originality/value This research shifts the discourse for sharing economy platforms from monetizing trust to prioritizing the product. While much of the emphasis had previously been on facilitating relationships between the supplier and customers on sharing economy websites, this may indicate that there needs to be a shift to prioritizing the product.