COMMUNICATION MANAGEMENT IN DISTANCE LEARNING SCALE VALIDATION

<sec> <title>BACKGROUND</title> Medical graduate education increasingly uses blended and online delivery, although students' academic self-regulation may be shaped by different motivational and cognitive processes across learning contexts, with emotional factors potentially playing a complementary role. Understanding how these mechanisms operate and whether their structural relationships differ between online/blended and face-to-face formats can inform targeted educational supports. </sec> <sec> <title>OBJECTIVE</title> The present investigation developed and tested a comparative causal model of academic self-regulation among medical graduate students in online/blended versus face-to-face programs. We examined how key motivational constructs (eg, academic self-efficacy, task value, future orientation, perfectionism, and academic help-seeking), positive achievement emotions, and cognitive factors (cognitive academic engagement and need for closure) relate to academic self-regulation, and whether these relationships differ by learning context. </sec> <sec> <title>METHODS</title> The design was cross-sectional, comparative causal modeling. Participants were master’s-level students at Shahid Beheshti University of Medical Sciences enrolled in either face-to-face (population n=1554; sample n=310) or blended/online (population n=449; sample n=205) programs selected using cluster sampling. Data were collected using validated instruments measuring academic self-regulation (Bouffard scale), academic self-efficacy (Midgley et al), academic engagement (Schaufeli &amp; Bakker), multidimensional perfectionism (Frost), academic help-seeking (Ryan &amp; Pintrich), task value (Pintrich), future orientation (Seginer), need for closure (DeBacker &amp; Crowson), and achievement emotions (AEQ; Pekrun et al). Data were analyzed using path analysis/structural equation modeling. Model fit was evaluated using χ²/df, CFI, GFI, AGFI, and RMSEA. Direct, indirect, and total effects were estimated for each group, and comparative interpretation focused on effect patterns and explained variance. </sec> <sec> <title>RESULTS</title> The hypothesized causal model reached an acceptable fit in both face-to-face and blended/online groups (χ²/df approximately &lt;3; CFI/GFI/AGFI in the acceptable range; RMSEA approximately 0.02–0.05). In both groups, most of the specified direct effects reached statistical significance, while the indirect effects of exogenous variables on academic self-regulation through intermediate constructs were supported overall. Cognitive academic engagement and academic self-efficacy were important proximal predictors of academic self-regulation. The need for closure had a negative direct effect with regard to academic self-regulation. However, a previously specified direct effect from need for closure to self-regulated learning strategies could not be retained in the final revised model. In both cohorts, the indirect pathway from positive achievement emotions to academic self-regulation via cognitive engagement was not supported, indicating that positive emotions alone were insufficient to increase self-regulation through cognitive engagement. The model explained a substantial proportion of variance in academic self-regulation in both groups—being approximately 0.44 in face-to-face and 0.46 in blended/online students—indicating comparable overall explanatory power across learning contexts. </sec> <sec> <title>CONCLUSIONS</title> A comparative causal model integrating motivational, emotional, and cognitive pathways provided an adequate explanation of academic self-regulation among medical graduate students in both face-to-face and blended/online formats. Findings highlight the central role of cognitive engagement and academic self-efficacy as proximal levers for supporting self-regulation across contexts. The lack of a supported indirect effect from positive emotions to self-regulation via cognitive engagement suggests that emotional experiences may not be enough unless they are accompanied by cognitively engaged learning behaviors. Considering motivational and cognitive mechanisms that together shape self-regulation within different delivery modes, educational interventions in medical graduate programs should focus on strengthening self-efficacy beliefs and cognitively engaged learning practices. </sec>

background music on social media engagement, focusing on the roles of event relevance, lyric resonance, and the origins of AI-generated singers, along with the mediating effects of audience interpretation and emotional resonance. To wit, this study provided important practical insights into how AI-modified music improves users' cognitive and emotional engagement, fostering a stronger connection between content creators and their audiences.As AI becomes increasingly embedded in our communication practices, individuals must develop new coping and adaptation strategies to navigate these environments. This special issue also explored the various ways people adjust to the presence of AI in their lives, including the strategies they use to manage the complexities and challenges associated with AI-MC. Grassini (2023) developed and validated the AI Attitude Scale (AIAS-4), a measure designed to evaluate public perceptions of AI. The authors highlighted the importance of digital literacy and critical thinking skills in coping with AI-MC. As users improve their understanding of the capabilities and limitations of AI, they become better equipped to navigate such systems and mitigate potential negative effects.Additionally, the integration of AI in smart speakers, which use voice interaction to provide services, poses potential risks to user privacy due to the continuous collection of voice data. Feng (2024) explored the factors influencing privacy boundary management among smart speaker users. The author identified that personalization positively influences privacy disclosure and boundary linkage but negatively affects privacy control. Privacy concerns have a negative impact on privacy disclosure and boundary linkage, while positively influencing privacy control.It showed that users with higher privacy concerns are less likely to disclose information and more likely to adopt strict privacy controls. Higher levels of privacy literacy are associated with reduced privacy disclosure and boundary linkage, and increased privacy control. These findings have significant implications for the design and regulation of smart speakers and similar AI-driven devices.The rise of chatbots and similar tools has transformed the way humans interact with information technology. Lee and Hahn (2024) investigated a crucial aspect of human-chatbot interaction: the perception of mind in chatbots. The study found that users who implicitly perceive chatbots as having human-like minds are more likely to perceive the chatbots' messages to be effective, particularly when the chatbots provide emotional support. Users who explicitly attribute humanlike minds to chatbots also perceive the chatbots' messages as more effective, regardless of whether the support received is informational or emotional. These findings have significant implications for the design of social support chatbots.Human-machine interactions are characterized by a complex interplay of psychological factors, including perception, emotion, and cognition. This issue investigated the psychological dynamics of these interactions, examining how individuals perceive and respond to AI systems.For example, Liu, Wang, and Yu (2023) investigated how the labeling of Artificial Intelligence Generated Content (AIGC) affects users' perceptions of automated news using electroencephalography (EEG) to measure brain activity. The study found that AIGC labeling significantly reduces the perceived trustworthiness of both descriptive (fact-based) and evaluative (opinion-based) news. This suggests that transparency cues, like AIGC labeling, nudge users to critically evaluate the quality of the information presented. EEG results indicated higher delta, theta, alpha, and beta Power Spectral Densities (PSDs) when AIGC labeling was present, signifying increased cognitive load and attention. These findings demonstrate the importance of transparency in AI-generated news, while the labeling of AIGC is found to not only help in maintaining journalistic integrity but also enhances users' cognitive engagement, prompting them to process information more critically.In addition, one of the key findings from this special issue is the importance of subjective perceptions in shaping user attitudes toward AI (Tao, Gao & Yuan, 2023;Liu, Wang & Yu, 2023;Feng, 2024;Inju Lee & Sowon Hahn, 2024). The research shows that users are more likely to accept and trust AI systems that exhibit a degree of autonomy and intelligence. However, there is also evidence of the "uncanny valley" effect, where highly realistic AI can evoke discomfort and unease. This issue explored these psychological dynamics, providing insights into how designers can create AI systems that are both effective and user-friendly. At the same time, the issue highlighted the potential risks and challenges associated with AI-MC. For example, concerns were expressed about the privacy and security of user data, as well as the potential for AI systems to perpetuate biases and stereotypes. In addition, the issue examined the broader societal implications of AI, including the impact on employment, social inequality, and the digital divide.This special issue offers a comprehensive exploration of the psychological dynamics and outcomes of AI-mediated communication. The studies presented provide important insights into how AI systems are reshaping human interaction, with significant implications for individuals, organizations, and society at large. As we navigate the complexities of an AI-driven world, developing a nuanced understanding of these systems and their impact on our lives is essential for our daily life.

Evaluating the impact of internet communication quality in human resource management on the productivity of construction projects

With the expansion of industrialisation and rapid development of economy in China, migration of the rural population to the urban areas in seek of employment has resulted in changes in the family structure and increased number of left-behind children (LBC) in China. Numerous studies on LBC have concluded the critical issues among the children related to their overall well- being and their performance at school. The current study aimed to investigate the impact of emotional, cognitive and behavioural engagement of the LBC on the academic achievement of the left behind children. Quantitative research method was used and the sample were 186 left- behind children in Henan Province, China. To measure school engagement, the instrument developed by Finlay (2006) was used. Correlation and hierarchical multiple regression analyses were conducted to examine the relationship between the various predictors and academic achievement. The findings concluded that emotional, cognitive and behavioural engagement of the LBC at school were significantly correlated with academic achievement. The hierarchical regression findings concluded that emotional engagement (&amp;beta;= .268; t= 3.593, p&amp;lt;0.000, cognitive engagement (&amp;beta;= .245; t= 3.284, p&amp;lt;0.000 and care takers (&amp;beta;= .132; t= 2.009, p&amp;lt;0.05) were significant predictors of academic achievement of the LBC.

Background: Facebook has been acknowledged as an alternative media in supporting traditional learning activities. However, its potential in enhancing students’ cognitive engagement on flipped-classroom’ activities is still not much known. This study aims to measure undergraduate medical students’ cognitive engagement changes after joining an ocular trauma flipped-classroom’ Facebook group.Methods: This pre-experimental study was involving 45 third-year undergraduate medical students of Muhammadiyah Surabaya' University who were joining the ocular trauma flipped-classroom' Facebook group. Three cognitive engagement variables were measured before students were joining the group and after the flipped-classroom’ face to face session ended. Finally, metrics data of the group members’ activities, which had been collected using Facebook Insight, used to shown changes between the active and passive user.Results: All users’ (n = 45) cognitive engagement were rising significantly after join the Facebook group (motivation, p = 0,000; self-directed learning readiness, p = 0,000; knowledge towards ocular trauma topic, p = 0,000). Increase in average active user knowledge was 11.09 points higher than passive users. Self-efficacy aspect of the students’ learning motivation and self-management aspects of the students’ self-directed learning readiness were the most increased sub-components.Conclusion: Facebook group has the potential to improve students’ cognitive engagement on ocular trauma’ flipped classroom.

Boarding school students must participate in online learning due to the COVID-19 pandemic. Student engagement is an important aspect that must be considered in online learning. This study aims to determine: (1) the level of student engagement of boarding school students, (2) to investigate the effect of simultaneous behavioral engagement, emotional engagement, and cognitive engagement on learning achievement, and (3) to determine the relationship between behavioral, emotional and cognitive engagement with learning achievement, (4) to measure the relative and effective contribution of behavioral, emotional and cognitive engagement on learning achievement. This research is quantitative research with an ex post facto type. 182 boarding school students participated in this study. The data collection instrument used is the engagement scale from Fredricks &amp; McCloskey. Data processing using descriptive and inferential statistics. The inferential test used is multiple linear regression and Pearson correlation. This study’s results indicate a significant influence between behavioral, emotional, and cognitive engagement on the learning achievement. The influence of these three variables on learning achievement is 46.7%. While the results of the correlation test showed that there is a significant relationship between the variables of behavioral, emotional, and cognitive engagement in learning achievement.

Understanding cultural systems in online learning with voluminous data, such as the engagement of students and teachers, has proven to be challenging. This predicament catalyzed the need for an emerging methodology to assess learning and complex thinking in online environments using statistical tools to analyze qualitative data. Quantitative Ethnography (QE) blends qualitative and quantitative approaches and uses statistical tools in analyzing qualitative data. This study advanced Epistemic Network Analysis (ENA), a QE tool, to analyze the engagement of teachers and students in online research courses of six groups of students. Observation of synchronous classes and asynchronous activities was carried out, 4,137 utterances were coded, and network models of engagements were generated. The findings show that the ENA engagement models among teachers and students in synchronous and asynchronous sessions differed significantly, with the teachers giving more frequent and varied feedback during synchronous classes. The network models of engagement in synchronous classes reveal the co-occurrence of students’ cognitive engagement and teachers’ feedback. When students try to connect with the lesson, they are given corrective feedback, and when they extend their understanding of the content, they are given affective feedback. On the other hand, when students are given prompts during asynchronous sessions, they try to connect. When they simply agree, they are given informative-procedural feedback, and when they emancipate their understanding, they receive affective feedback. This study illuminates the methodological advantages of ENA as an ethnographic tool that mixes qualitative and quantitative approaches in understanding cultural systems and processes in online education.

The purpose of this study was to investigate the validity of exploratory factor analysis (EFA) study on the work attributes of pharmaceutical sales executives in Nigeria using confirmatory factor analysis (CFA), and furthermore to evaluate the relative importance of the work attributes. An analytical study design used a 13-item, 5-point Likert scale questionnaire administered to 226 pharmaceutical sales executives using a simple random sampling method. Data analysis using the Statistical Package for Social Sciences (SPSS) and Analysis of Moment Structures (AMOS) with a significance level set at p&lt;0.05. The measurement model was evaluated using the maximum likelihood method. Model fit criteria measures for CFA were satisfactory (CMIN/df=2.297; NFI=0.017; TLI=0.905; CFI=0.950; RMSEA=0.064). The study showed that the most dominant attribute was involvement in community education programs with a regression coefficient of 0.892, and the least was limited access to customers (0.446). Convergent validity measures were acceptable. Divergent validity can be enhanced by including more items. The study confirmed the validity of the EFA study outcomes obtained from the previous research work. The purpose of this study was to investigate the validity of exploratory factor analysis (EFA) study on the work attributes of pharmaceutical sales executives in Nigeria using confirmatory factor analysis (CFA), and furthermore to evaluate the relative importance of the work attributes. An analytical study design used a 13-item, 5-point Likert scale questionnaire administered to 226 pharmaceutical sales executives using a simple random sampling method. Data analysis using the Statistical Package for Social Sciences (SPSS) and Analysis of Moment Structures (AMOS) with a significance level set at p&lt;0.05. The measurement model was evaluated using the maximum likelihood method. Model fit criteria measures for CFA were satisfactory (CMIN/df=2.297; NFI=0.017; TLI=0.905; CFI=0.950; RMSEA=0.064). The study showed that the most dominant attribute was involvement in community education programs with a regression coefficient of 0.892, and the least was limited access to customers (0.446). Convergent validity measures were acceptable. Divergent validity can be enhanced by including more items. The study confirmed the validity of the EFA study outcomes obtained from the previous research work.

This study examines the effectiveness of gamified learning environments in improving grammar mastery and engagement among Jordanian secondary school EFL learners in Saudi Arabia. The research aims to explore the impact of gamification on learners' cognitive, emotional, and behavioral engagement while addressing the challenges faced in grammar instruction within this educational context. A quantitative experimental research design was employed, involving 120 students divided into an experimental group (exposed to a gamified grammar intervention) and a control group (taught using traditional methods). Data were collected through pre-tests, post-tests, and engagement questionnaires. Statistical analyses, including ANCOVA and effect size evaluation, were conducted to determine the impact of gamification on grammar proficiency and student engagement. The results indicate a significant improvement in grammar mastery among students in the gamified learning environment, with a 41.91% increase in proficiency compared to 13.41% in the control group. The experimental group also demonstrated higher scores in behavioral, emotional, and cognitive engagement, confirming that gamification enhances both learning outcomes and student motivation. Effect size analysis revealed a large impact of gamification on grammar achievement and engagement levels. This study provides empirical evidence supporting gamified learning as an effective strategy for enhancing grammar acquisition in EFL contexts. The findings highlight the role of gamification in fostering engagement and improving learner performance, suggesting that it can serve as a transformative approach in language education. The study offers valuable insights for educators, curriculum developers, and policymakers, emphasizing the need to integrate gamification into EFL instruction. By incorporating game-based elements, teachers can create a more engaging and effective learning environment, potentially improving long-term grammar retention and student motivation. Additionally, cultural considerations should be taken into account when implementing gamified learning to ensure its effectiveness across diverse educational settings.

Abstract: Feedback can play a pivotal role in learning but is only effective when students use it. However, the use of feedback varies greatly from student to student and these differences must be explained. Hence, the construct receptivity to instructional feedback (RIF) was introduced to assess students’ attitudes towards and engagement with human-provided feedback in multiple English-speaking countries. However, RIF scales have not yet been used in computer-based assessment contexts nor in German-speaking countries; their application is thus limited. This study examined an adapted and translated RIF scale using confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM). We capitalized on data sets comprising German-speaking university ( N = 464) and secondary school ( N = 1,207) students. The bifactor-CFA model showed a good model fit and revealed a general receptivity factor alongside the four specific factors: experiential attitudes, instrumental attitudes, cognitive engagement, and behavioral engagement with feedback. Scalar measurement invariance allowed for cross-gender and educational level comparisons. The relationships with broader personality characteristics were consistent with other contexts, thus indicating discriminant validity. General receptivity, cognitive engagement, and experiential attitudes positively correlated with GPA, suggesting convergent validity. Results support the stability of the RIF scale’s adaptation and translation. Assessment implications are discussed.

The current research aims to define the role of job engagement in achieving organizational excellence, as the job engagement variable, depending on the (Rich, 2010) model, included the dimensions (cognitive engagement, emotional engagement, physical engagement), while organizational excellence the researcher relied on the model (Baldrige, 2011- 2012) dimensions (organization leadership, strategic planning, customer focus, information and method of analysis, human resources, operations management, business results),These variables have been studied in the Directorate of Residency Affairs, which is one of the specialized directorates in the Iraqi Ministry of Interior, and the research was relied on the questionnaire as a main tool for measurement and data collection, relying on the method of random sample in its distribution, as it included (45) questions, as well as the method of the personal interview. To support the results of the questionnaire and achieve the greatest degree of realism in data collection, the sample included (206) individuals out of a total of (400) and were selected according to the sample calculation formula (Stephen Thompson) and were distributed directly to the respondents as (190) were retrieved and the number of the questionnaires were valid for analysis. Statistical (180) questionnaires, and in order to analyze the research data, the researcher used ready-made statistical programs (SPSS v.25 AMOS v.25), and among the most important statistical methods used in the analysis are "Alpha Cronbach scale, Spearman-Brown correlation coefficient, confirmatory factor analysis, the mean." Arithmetic, standard deviation, coefficient of variation, relative importance, Pearson correlation coefficient, simple regression coefficient, multiple linear regression. The research reached a number of results and recommendations, including that the Iraqi Residency Affairs Directorate showed interest in organizational excellence, so it directed job engagement to enhance it well in addition to directing emotional absorption, cognitive engagement and physical engagement directly to improve the required organizational excellence, as these results were in conformity with the hypotheses, Where there is a statistically significant relationship between job engagement and organizational excellence.

Rationale of Study – The emergence of the Internet has unlocked immense prospects for distance learning. One of the prospects is Web 3.0 tools, a web platform that enables its users to read, write and execute content. Previous studies established the use of Web 3.0 tools in higher education but this author knows of no studies on the use of Web 3.0 tools for knowledge management by distance learners in Nigeria. Therefore, this paper examines distance learners’ knowledge conversion using the SECI knowledge management model and identifies appropriate Web 3.0 tools used in each quadrant.Methodology – A descriptive research design was used for this study. Qualitative data was collected from 16 distance learners from the Distance Learning Centre, the University of Ibadan using interviews. The respondents were purposively selected from the faculties of Arts, Education, Science, and Social Sciences.Findings – The distance learners at the University of Ibadan went through the four quadrants of knowledge conversion in the course of their distance learning programmes in accordance with the SECI knowledge conversion model. They use Web 3.0 tools such as Google Classroom, WhatsApp, Google Hangout, Facebook, E-library, Semantic Search Engines, and Open Educational Resources, and Google Drive in the four quadrants of SECI knowledge conversion.Implications – The findings of the study confirmed that Web 3.0 tools are germane to distance learners’ knowledge conversion activities.Originality – This study has a prodigious value because it is the first study to examine the usage of Web 3.0 tools in knowledge conversion by distance learners in Nigeria

&nbsp; &nbsp; The present paper sought to confirm factors that are relevant to board role performance in Uganda and&nbsp; &nbsp; &nbsp; as a corollary empirically tested the relationship between individual dimensions of the model of board&nbsp; &nbsp; role performance. The study was cross-sectional and correlational and the analysis was conducted&nbsp; using Structural Equation Modelling (SEM) with Analysis of Moment Structures (AMOS) software on a&nbsp; sample of 128 service firms in Uganda. Findings indicate that a four-dimensional model of board role&nbsp; performance was determined to be the best fitting model for Ugandan service firms. From the results&nbsp; we do claim, that board role performance causes the scores observed on the measured variables of&nbsp; boundary spanning, effective partnership, environmental scanning and control of the organization. The&nbsp; measured variables are the individual dimensions of the model of board role performance. The present&nbsp; study provides one of the few studies that have analysed with confirmatory factor analysis (CFA) using&nbsp; AMOS to test board role performance measurement model and provides a benchmark for Uganda&rsquo;s&nbsp; service firms wishing to leverage performance of their boards. However, using cross-sectional data&nbsp; does not allow for testing of the process aspect of the model; still, it provides evidence that the model&nbsp; can stand empirical tests of the four elements of the model. Additional research should examine the&nbsp; process aspects of board role performance and also test our model in predicting firm financial&nbsp; performance. The model in this paper might improve the quality of board role performance and apply to&nbsp; other sectors of Uganda&rsquo;s firms to avert the problem of ineffective boards as evidenced by consistent&nbsp; firm failures in Uganda. By improving the quality of board role performance, boards will demonstrate&nbsp; their relevance in company direction and improvement of company value to the benefit of all&nbsp; stakeholders.&nbsp; &nbsp; Key words: Board role performance, service firms, analysis of moment structures (AMOS), Uganda.

The size of the group is an important subject to discuss, especially in light of the challenges that appear with the trend toward large institutions with large student bodies in higher education, including the quality of student integration and the quality requirements that higher education must meet in light of the high qualifications demanded by the world of employment. In this study, we examine the effect of learning-group size on students’ cognitive and behavioral engagement. In a quantitative approach, a questionnaire survey is used to collect data from 234 students at the Hassan II University in Casablanca. The purpose of this research is to demonstrate the influence of group size on students’ cognitive and behavioral engagement. The participants were separated into 140 students in large groups and 94 small groups. A questionnaire measured the impact of group size on participants’ cognitive and behavioral engagement and had a Cronbach’s alpha value of 0.9. According to the study’s findings, group size should be taken into account because it affects most factors related to cognitive and behavioral engagement. To increase student involvement and boost their academic achievement, it is advised that more empirical research should be done in order to develop pedagogical strategies to control this difference much better.

TQM and TPM are widely used performance improvement techniques employed by manufacturing organisations. They are employed world over for achieving customer satisfaction, reliability, productivity, market share, profitability and even survival. The study highlights the gain in business performance that can be obtained if TQM is supported by TPM in a manufacturing organisation. The study uses the confirmatory factor analysis (CFA) approach using structural equation modelling (SEM) in analysis of moment structures (AMOS 20.0) software to employ the inter-relationship among TQM and TPM variables. Using AMOS 20.0 software, TPM model and the transfusion of TQM-TPM model were constructed and the statistical data of the model fit values before and after modification indices were compared. Among the models, it was found that the SEM_TQM-TPM model fits the collected data better, which implies that the synergistic relationship of TQM and TPM paradigms can help Indian manufacturing industries to achieve good performances in terms of customer satisfaction, reliability, productivity, market share, profitability and even product quality, product cost and maintenance initiatives.