This study analyzed discussions on Reddit to explore perspectives on contemporary issues in education. Data was collected from three education-focused subreddits using Python APIs. In total, 9,697 submissions and comments were analyzed using an inductive qualitative approach and topic modeling to identify key themes. Results revealed multifaceted debates around major issues like challenges in navigating the changing landscape of education, ways to advance higher education, the goal of nurturing holistic development, and examining education from diverse perspectives. Specific topics like education funding, classroom technology, equity in access, and curriculum debates were prevalent. Findings provide insight into the complex public discourse on education, highlighting areas of consensus and debate. This analysis on Reddit presents an opportunity to understand perspectives from diverse stakeholders and promote collective understanding as education continues to evolve in a rapidly changing society.

The advent of Artificial Intelligence (AI) is set to revolutionize governance and public administration, presenting both opportunities and challenges. This paper provides a roadmap for public agencies, detailing steps from preparation to mainstream AI implementation. It proposes a skills framework encompassing technical, ethical, legal, and management aspects, supplemented by continuous training recommendations. Emphasizing a human-centric and ethical approach, it aims to foster innovative and responsible governance. Collaboration is highlighted as vital for accelerating AI adoption and equipping administrators with tools to navigate this complex yet promising landscape. The paper also addresses the equality and inclusion challenges posed by AI, particularly in bridging the divide between the Global North and Global South, using international examples from both developed and developing countries. These insights ensure a comprehensive perspective on AI integration in public administration, promoting a holistic and nuanced approach to addressing these challenges.

This chapter traces the remarkable evolution of research administration from its modest origins to its current strategic role in advancing scientific research. It provides a comprehensive overview of how the field has adapted to the changing needs of the scientific community and the increasing complexity of the research enterprise. The impact of key policy developments, such as the Bayh-Dole Act and the Belmont Report, on the professionalization of research administration is discussed, along with an examination of the current landscape, including the benefits and challenges of technological integration, the rise of specialized roles, and the increasing emphasis on compliance and accountability. The potential influence of emerging technologies, such as artificial intelligence, automation, and advanced analytics, on research administration is also investigated. Ultimately, the chapter underscores the vital role of research administrators as strategic partners in the advancement of scientific knowledge and societal progress.

The purpose of this chapter is to provide a comprehensive overview of context-rich learning, including its theoretical foundations, alignment with various instructional practices, and potential benefits and limitations. The chapter begins with a discussion of the theoretical underpinnings of context-rich learning, exploring its connections to constructivism, experiential learning, problem-based learning, and situated learning. Each section provides specific examples of how context-rich learning aligns with these theories and highlights the benefits of incorporating authentic, real-world experiences into the learning process.

Assessments, even summative, are part of the learning journey not just for the student, but for the instructors as well. In competency-based education, performance assessments (PAs) are regarded as a highly authentic method of measurement, but their complexity makes them vulnerable to construct-irrelevant variance such as group bias. A differential item functioning (DIF) study was conducted to detect potential bias in a series of information technology PA tasks in which task scenarios were identified (by SMEs) as neutral or potentially controversial, where the latter was hypothesized as more likely to trigger DIF for certain demographics. Given the variety of DIF methods available and their relative strengths and weaknesses, three common statistical methods – Mantel-Haenszel (MH), logistic regression (LR), and Lord's chi-square (LC) - were used followed by a substantive review of DIF items. Hypotheses were largely supported by the analysis and review. Discussion centers on the implication of findings for assessment strategies in education.

With the changes in societies and economies, new formats and packaging of educational products have been emerging as alternatives to the traditional degrees and certificates. Most of these offerings emerge outside higher education institutions and aim to alleviate the gap between the supply of skills and the needs of industries which had a big impact on the educational space. The authors studied approximately four hundred thousand tweets discussing educational offerings. They used a combination of topic modeling and network analysis to group topics into wider themes over the topic network. They also used word embeddings to measure semantic similarity of words related to specific educational packagings and further understand the discussion carried out on Twitter. The results of this study show how public opinion on Twitter discussed formal and non-formal educational offerings in ways that stress economic and professional advancement. Finally, the results from the word embeddings analysis revealed a need for common and clear taxonomy that differentiates between educational formats.

Programs in an online competency-based higher education (OCBHE) institute will focus on a set of skills and competencies that form a theme throughout multiple courses, where one course builds upon another in terms of increasing the strength or depth of competency. Thus, for students within a given program or major, it is ideal for scores from course assessments with overlapping content to correlate and indicate higher-order skills or competencies. The purpose of this study was to use factor analysis to test the internal and structural validity of course-level performance assessment scores for a group of courses taken as part of a data analytics program in an OCBHE institution. Moreover, the presence of program-level competencies was investigated using hierarchical factor analysis for two groups: a faster, shorter course track and a slow, longer course track. Results supported validity at the course level as well as the presence of a higher-order factor (program-level competency) for the fast course track but not the slow track.

The gap between higher education and industry is often discussed, but mitigating solutions lag behind and contribute to its widening. This chapter explores the root causes of this gap and examines the establishment of common frameworks based on skills and approaches to assessing those skills as the path forward. The perspective and needs of the industry, the learners, and higher education are discussed. Data silos to inform the educational product on skills in need by industry exist. Tools to support communicating skills in various technology solutions in the spirit of a holistic learning and employment record are emerging. Skills and competencies that populate those records must be relevant, appropriately validated, and communicated using an agreed-upon language. Selected examples of current and emerging approaches in the skills-first approach to establishing common frameworks for communication and assessment are provided to illustrate possibilities.

Performance assessments (PAs) offer a more authentic measure of higher order skills, which is ideal for competency- based education (CBE) especially for students already in the workplace and striving to advance their careers. The goal of the current study was to examine the validity of undergraduate PA score interpretation in the college of IT at a CBE online, higher education institute by evaluating (a) the transparency of cognitive complexity or demands of the task as communicated through the task prompt versus expected cognitive complexity based on its associated rubric aspect and (b) the impact of cognitive complexity on task difficulty. We found that there is a discrepancy in the communicated versus expected cognitive complexity of PA tasks (i.e., prompt vs. rubric) where rubric complexity is higher, on average, than task prompt complexity. This discrepancy negatively impacts reliability but does not affect the difficulty of PA tasks. Moreover, the cognitive complexity of both the task prompt and the rubric aspect significantly impacts the difficulty of PA tasks based on Bloom's taxonomy but not Webb's DOK, and this effect is slightly stronger for the rubric aspect than the task prompt. Discussion centers on how these findings can be used to better inform and improve PA task writing and review procedures for assessment developers as well as customize PAs (their difficulty levels) to different course levels or individual students to improve learning.

Salmonella enterica serotype Enteritidis is known as one of the most common pathogenic bacteria causing salmonellosis with humans. Most frequently, raw materials of the animal origin (eggs, chicken meat) appear as a vector in the transmission of this bacterium. Since eggs are used for the production of egg-based pasta, and due to an insufficient thermal treatment during pasta drying they can be a potential risk for the consumer’s health. Different pot herbs can be used in order to reduce potentially present pathogenic microorganisms. This paper compares a decrease of the number of Salmonella enterica serotype Enteritidis (D) ATCC 13076 and Salmonella enterica serotype Enteritidis isolated from outbreaks of salmonellosis in egg-based pasta under the influence of thymus and sweet basil essential oil. The reduction of the number achieved during process ranges from 0.5 to 1.5 log CFU/g. The results indicated that utilized oils were more effective against epidemic strain then ATCC strain. Also, thyme oil caused more significant inhibition of S. Enteritidis during production process.

Salmonella enterica serotype Enteritidis is known as one of the most common pathogenic bacteria causing salmonellosis in humans. Raw materials of animal origin (eggs, chicken meat) are frequent vectors that transmit this bacterium. Since eggs are used for the production of pasta, due to insufficient thermal treatment during pasta drying, they can be a potential risk to consumer health. Different essential oils of herbs can be used to reduce present pathogenic microorganisms. This paper compares a decrease in the number of Salmonella enterica serotype Enteritidis (D) ATCC 13076 and Salmonella enterica serotype Enteritidis isolated from outbreaks of salmonellosis in egg-based pasta under the influence of thyme and sweet basil essential oils. The results indicate that the utilized oils were more effective against the epidemic strain than the ATCC strain. In addition, thyme oil caused a more significant inhibition of Salmonella enterica serotype Enteritidis during the production process.

The focus of this chapter is the explanation of a method for allowing languages to emerge within a multi-agent system. The need for such a method tends to be in larger multi-agent systems that focus either on large domains or span across multiple domains. This method can also be adapted for interfacing multi-agent systems with humans through natural languages. Also addressed in this chapter are the necessary requirements for a multi-agent system to utilize an evolving communication system. A specification of an evolving vocabulary is presented along with an explanation of results from an experiment that contains an implementation of these specifications.

Many in IT education—following on more than twenty years of multicultural critique and theory—have integrated “diversity” into their curricula. But while this is certainly laudable, there is an irony to the course “multiculturalism” has taken in the sciences in general. By submitting to a canon originating in the humanities and social sciences—no matter how progressive or well-intentioned—much of the transgressive and revolutionary character of multicultural pedagogies is lost in translation, and the insights of radical theorists become, simply, one more module to graft onto existing curricula or, at the very least, another source of authority joining or supplanting existing canons. In this essay, we feel that introducing diversity into IT means generating this body of creative critique from within IT itself, in the same way multiculturalism originated in the critical, transgressive spaces between literature, cultural studies, anthropology and pedagogy. The following traces our efforts to develop isomorphic critiques from recent insights into multi-agent systems using a JAVA-based, software agent we’ve developed called “Izbushka.”

This chapter overviews a robotic platform developed at our Cognitive Agency and Robotics Laboratory (CARoL, n.d.) for the purpose of carrying out Interactivist-Expectative Theory of Agency and Learning (IETAL) and Multi-Agent Simulated Interactive Virtual Environments (MASIVE)-like experiments in a realistic environment. Performing IETAL and MASIVE-like experiments with a robotic agent(s) requires specialized agent(s) in a specialized environment. The solution overviewed here is done on a shoestring budget and is easy to replicate and modify.

In this chapter, we formalize the Interactivist-Expectative Theory of Agency and Learning (IETAL) agent in an algebraic framework and focus on issues of learnability based on context.