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Students\u27 Perceptions of Effects of TikTok on Academic Performance: A Case Study at Southern Illinois University
Get PDFA Critical Book Review of the work edited by Alfred, M. V., Robinson, Petra, A., & Roumell, E.A. (Eds.) (2021). Advancing the global agenda for human rights, vulnerable populations, and environmental sustainability: Adult education as strategic partner.
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This critical book review is an overview of the work edited by Alfred, M. V., Robinson, Petra, A., & Roumell, E.A. (Eds.) (2021), Advancing the global agenda for human rights, vulnerable populations, and environmental sustainability: Adult education as strategic partner. This review introduces each author, discusses the content, and concisely evaluates the work. Alfred, Robinson, and Roumell use a global perspective to explore how adult education influences considerations for marginalized persons with low literacy levels. Further, they write that people should focus on learning, not capital gain, but also contend that one does not have to operate at the exclusion of the other. In other words, a focus on “economic development” does not necessitate neglecting “human development” (Walker, 2010, pp. 488-489). This book under review uses inclusive language, and varying demographics of society are considered. Within a similar inclusive context, this book under review argues against “stereotypes” (p. 136) and for the rights of specific sectors of people as far as the relationship between “social justice and the environment” is concerned (p. 317). Alfred, Robinson, and Roumell\u27s efforts to advance a global agenda through adult education are evident throughout the book.
Keywords: Globalization, adult education, human capital
ANALYZING THE DETERMINANTS OF INWARD, OUTWARD, AND BILATERAL FOREIGN DIRECT INVESTMENTS IN MENA COUNTRIES: THE ROLE OF TRADE OPENNESS
No full textThis dissertation delves into the dynamics of Foreign Direct Investment (FDI) in the Middle East and North Africa (MENA) region, focusing on the role of trade openness as a determinant. It consists of three chapters, each contributing to a comprehensive understanding of FDI patterns in MENA countries.The first chapter explores the determinants of inward FDI in MENA countries from 1990 to 2022, emphasizing the significance of trade openness. Employing panel data analysis and Two-Stage Least Squares (2SLS) methodology, the study reveals a positive correlation between FDI inflows and trade openness. Moreover, it identifies other influential factors such as market size, infrastructure, human capital, and government policies. By addressing the heterogeneity of trade openness across various memberships, including OPEC and WTO, this chapter provides valuable insights for policymakers and investors seeking to stimulate economic development in the MENA region. Building upon these findings, the second chapter investigates the determinants of outward FDI from MENA countries over the period 1990-2021. This chapter fills a gap in the literature by analyzing factors influencing outward investment flows. Contrary to conventional expectations, the study finds a negative relationship between trade openness and outward FDI. Additionally, it uncovers significant impacts of market size, infrastructure, industry dynamics, and tax policies. Through consideration of heterogeneity in trade openness across subsets of MENA countries, this chapter offers insights into fostering economic growth through outbound investment. In the third chapter, a gravity model approach is employed to analyze bilateral FDI flows, focusing on the impact of trade openness and Bilateral Investment Treaties (BITs). By examining annual data from 48 countries between 1990 and 2021, the study uncovers nuanced relationships between trade openness, BITs, and FDI flows. Through comprehensive analysis, it highlights the significance of investment treaties in promoting cross-border investment and provides valuable insights into bilateral FDI dynamics among countries
GROWTH AND VOLATILITY RELATIONSHIPS REEXAMINED: THE ROLE OF AGGREGATION
No full textThis dissertation studies the relationship between output growth rate and its volatility. This study sheds light on International, Regional, and Development Economics literature. In the first chapter, we revisit the relationship between output growth rate and its volatility using cross-section techniques for our panel data set from 60 countries from 1970 to 2019. In addition to the conventional volatility measurement of the standard deviation, we incorporate the higher moments, such as skewness and kurtosis, as volatility measures. Higher moments further sharpen our understanding of the volatility and growth rate relationship. We also examine the role of the irreversibility of investment, a purported proximate factor for increased volatility in theory but not applied to empirical models, on the growth rate. We find that a higher level of the irreversibility of investment tends to reduce the growth rate. In the second chapter, we examine the growth-volatility relationship covering manufacturing activities at the two-digit level in 32 countries. In particular, we conduct a comprehensive analysis to reveal the long-term relationship between output growth rate and volatility over 1970 – 2019 within countries and across sectors. We have data for each manufacturing subsector for each country over a long period. We have redefined the growth rate and volatility measures with alternative definitions such as cross-country and cross-sector across time. This offers additional advantages from an econometric perspective, as the large cross-sectional dimension is beneficial when estimating the determinants of growth rate. Moreover, our study assesses the evolution of the long-term relationship between economic sectoral growth rate and sectoral volatility over time. Overall, we find that growth rate and volatility are negatively related, with a few exceptions. The third chapter investigates the relationship between regional growth rate and volatility in U.S. state regions. We use disaggregated data for manufacturing activities over the period 1977 – 2021. We find a significant positive relationship between sectoral volatility and GDP per worker growth rate across the U.S. states regions, meaning that manufacturing volatile sectors for the U.S. are growing faster. This finding is also robust in including additional control variables in the analysis, thus confirming that volatility does not capture the effect of other potential determinants of GDP growth in the manufacturing sectors. We further examine how policy structure and geographical similarity affect regional growth rates, in which we distinguish between the Democrat and Republican Parties and Coastline and Non-Coastline states. We find that the growth rate and volatility relationship has been weaker for Democrat-leading states and geographically more open states (states with a coastline). This suggests that the growth rate and volatility relationship can be altered by having a supporting fiscal policy or having a more open economy
DEFINING CULTURALLY RESPONSIVE LEADERSHIP IN DIVERSITY AND INCLUSION MANAGEMENT: AN EXAMINATION OF SOCIOCULTURAL FACTORS ON PERCEPTIONS AND EXPECTATIONS OF LEADERSHIP
No full textThe expansion of workplace demographics in response to globalization and intersectionality has resulted in the workplace becoming increasingly diverse. Research indicates that there are both positive and negative consequences for having diverse workplaces, and the positively inclined studies emphasize how workplace diversity can provide a strategic advantage to organizations when managed effectively. Thus, scholars and organizational decision-makers have diverted their efforts towards understanding leadership and the ways that leaders manage diversity and inclusion to facilitate a climate for inclusion in the workplace. The present study aimed to identify the differences in expectations and perceptions of workplace fairness, effective leadership, and the management of diversity and inclusion between different sociocultural groups to see if they led to the applicability of various leadership behaviors in diversity-related situations. Using a multi-method design, this research assessed the perceptions and expectations of leadership and the management of diversity and inclusion in the workplace. Study One utilized an online survey design to measure the extent to which a leader was expected to be culturally responsive, a manager of diversity and inclusion, and effective. Study Two utilized a quasi-experimental design that exposed participants to DEI-related leadership scenarios where they assessed the leader’s behavior. Both studies collected the sociodemographic information of the participants. Results for Study One (N = 290) suggested that sociodemographic differences play a role in expectations of effectiveness and social justice and equity for managers, leadership effectiveness expectations for managers increase as social justice and equity expectations for managers increase, and culturally responsive leadership expectations for managers play a role in the extent that employees expect leaders to manage diversity and inclusion. Study Two (N = 448) results determined that cultural humility positively influences the relationship between leadership styles (i.e., transformational leadership, Daoist leadership, transactional leadership, and Machiavellian leadership) and the perception of leadership effectiveness. Machiavellian leadership was perceived as less socially just, culturally humble, and effective than the other leadership styles (i.e., transactional leadership, transformational leadership, and Daoist leadership); sociodemographic information was found to be mostly related to perceived leadership effectiveness; and perceived cultural humility and social justice are positively associated with leadership effectiveness. Ultimately, this study revealed the empirical significance of culturally responsive leadership behaviors in the workplace, provided evidence to show the distinct contributions of positive leadership in DEI-related situations, and emphasized the importance of considering the expectations and the demographic distribution of employees when leading to ensure organizational compliance among followers
TROPES OF IMPRISONMENT AND SOCIAL STASIS IN VICTORIAN FICTION
No full textThis dissertation concerns nineteenth-century British novelists’ representations of unachieved aspirations. Through a blend of affect theory, materialist literary criticism, and formalist analysis, I examine a particularly frustrating problem addressed by these writers: the gap between a dream of social mobility and a reality of class paralysis for many working-class people. I am interested in the tropes of imprisonment, constraint, and confinement through which Charles Dickens, Elizabeth Gaskell, Thomas Hardy, and Arthur Morrison pondered this problem. I take into account these writers’ own limitations and imperfect social-progress ideology of melioration. These metaphors highlight the exploitation of impoverished people by the very institutions purportedly meant to encourage and mobilize them. In this project, I draw on Lauren Berlant’s theory of cruel optimism, Carolyn Lesjak’s study of the depleasurization of work in the Victorian novel, and Bruce Robbins’s theory of mobility and welfare as frameworks for interpreting what Victorian middle-class fiction writers do with the lived experience of poverty
EFFECT OF INCOME AND EMPLOYMENT ON CONSUMPTION OF FOOD AND BEVERAGES IN USA BY STATES (2012-2021)
No full textIn this thesis, I examined the impact of income and employment on consumption of food and beverages in USA by states. Data from 2012 to 2021 from 50 states in USA were used. I analyzed the data using the panel regression as my baseline model. Using panel data models allowed controlling for time invariant unobserved state -specific factors that could bias the estimates. I estimated a fixed effect panel regression to examine the relationship between Income and Employment with Consumption of food and beverages . The results of the fixed effect panel regression showed that Income is significant. There was a steady change in Income elasticities from year 2012 to 2019. However, the elasticities greatly increased in 2020 and 2021. This shows that the pattern of the relationship between food consumption and Income has shifted for some reasons. From 2012 to 2019, the percentage changes in Income were greater than the percentage changes in food consumption . However, 2020 and 2021 had different outcomes from the other years. For these years, percentage changes in consumption of food and beverages were greater than those of Income. I also estimated a Random Effect Regression Using both States and Years. The results showed a positive correlation of Consumption of Food and Beverages with Income, but a negative association with Employment. This method deduced Income (X1) to be the only significant variable when ‘years’ were used as dummy variables. The two variables (Income and Employment) were significant when ‘States’ were used. Hausman test was carried out and the result suggested that the Fixed effect model is the most appropriate method to use for estimation. It was concluded that Income has a significant impact on consumption of food and beverages
Consensus for creating light weight blockchain for IoT
No full textThe utilization of blockchain technology within Internet of Things (IoT) applications presents an opportunity to eliminate the dependency on a single trusted authority, thus improving scalability and reliability. However, prevalent consensus methods employed in blockchain often come with drawbacks, including high energy consumption, substantial computational requirements, and reliance on trusted authorities. These challenges become particularly pronounced when dealing with resource-constrained IoT devices that necessitate lightweight and low-latency consensus mechanisms. In response to these considerations, trust-free probabilistic consensus methods emerge as a promising approach, enabling every node to actively participate in the consensus process and thereby enhancing the robustness of transactions compared to more rigid consensus methods. Blockchain technology has revolutionized various industries by providing a decentralized and secure platform for data storage and transactions. One of the critical components of blockchain systems is the consensus mechanism, which ensures agreement among network participants regarding the validity of transactions. Traditional consensus mechanisms, such as Proof of Work (PoW) and Proof of Stake (PoS), have significant drawbacks, including high energy consumption and susceptibility to centralization. In response to these challenges, new consensus mechanisms, such as Proof of Chance and Proof of Elapsed Work and Luck (PoEWAL), have emerged. PoEWAL is specifically engineered to address the energy and resource limitations of IoT devices, aiming to consume minimal energy, require fewer computational resources, and exhibit low latency. To assess its practical viability, we conducted experiments using the Contiki Cooja simulator, demonstrating that PoEWAL maintains low energy consumption across varying difficulty levels, thereby highlighting its feasibility in real-world IoT scenarios. Moreover, we conducted an in-depth comparative analysis of PoEWAL against established probabilistic consensus methods, including Proof of Chance, Proof of Work, Proof of Stake, Proof of Activity, Algor and, and Proof of Authority. This comprehensive evaluation considered critical factors such as energy efficiency, consensus time, and network latency. The results of this comparative study affirm that PoEWAL emerges as a well-suited consensus mechanism for implementing blockchain in IoT environments. Its performance demonstrates a balanced trade-off between energy efficiency, consensus speed, and overall network performance, positioning PoEWAL as a promising solution for addressing the unique challenges posed by IoT devices with limited resources
Iot Reliance on cloud computing and fog computing
No full textEvery day, more Internet of Things (IoT) devices and their data are appearing, which is causing problems for the traditional cloud-based architecture used for processing and storage. This traditional model might need to be supplemented with another approach to better handle future IoT applications. While many researchers have developed algorithms and models focusing on distributed architectures, these often have two main problems. First, they are usually tested in simulations rather than on real hardware, which doesn’t fully represent realworld conditions. Second, these models often distribute entire tasks rather than dividing a single task among multiple devices. The goal of this thesis is to explore the challenges of traditional architecture in the IoT context and look for gaps in current research, particularly in computing approaches. It aims to develop and test a new architecture model that allows multiple off-the-shelf hardware devices to work together on a single task. This model is assessed based on how quickly it completes tasks, how well it handles different sizes of data, and how scalable it is. The results indicate that the new system can effectively divide a single task among various devices, completing it more efficiently. Systems with multiple devices perform better in terms of task completion time and don’t have significant scalability problems. The findings also reveal that tasks divided and distributed among multiple devices are completed much faste
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