Semantic Systems and Visual Tools to Support Environmental Communication

Given the intense attention that environmental topics such as climate change attract in news and social media coverage, scientists and communication professionals want to know how different stakeholders perceive observable threats and policy options, how specific media channels react to new insights, and how journalists present scientific knowledge to the public. This paper investigates the potential of semantic technologies to address these questions. After summarizing methods to extract and disambiguate context information, we present visualization techniques to explore the lexical, geospatial, and relational context of topics and entities referenced in these repositories. The examples stem from the Media Watch on Climate Change, the Climate Resilience Toolkit and the NOAA Media Watch—three applications that aggregate environmental resources from a wide range of online sources. These systems not only show the value of providing comprehensive information to the public, but also have helped to develop a novel communication success metric that goes beyond bipolar assessments of sentiment

Semantic enrichment for enhancing LAM data and supporting digital humanities. Review article

With the rapid development of the digital humanities (DH) field, demands for historical and cultural heritage data have generated deep interest in the data provided by libraries, archives, and museums (LAMs). In order to enhance LAM data’s quality and discoverability while enabling a self-sustaining ecosystem, “semantic enrichment” becomes a strategy increasingly used by LAMs during recent years. This article introduces a number of semantic enrichment methods and efforts that can be applied to LAM data at various levels, aiming to support deeper and wider exploration and use of LAM data in DH research. The real cases, research projects, experiments, and pilot studies shared in this article demonstrate endless potential for LAM data, whether they are structured, semi-structured, or unstructured, regardless of what types of original artifacts carry the data. Following their roadmaps would encourage more effective initiatives and strengthen this effort to maximize LAM data’s discoverability, use- and reuse-ability, and their value in the mainstream of DH and Semantic Web

Semantic enrichment for enhancing LAM data and supporting digital humanities. Review article

With the rapid development of the digital humanities (DH) field, demands for historical and cultural heritage data have generated deep interest the data provided by libraries, archives, and museums (LAMs). In order to enhance LAM data’s quality and discoverability while enabling a self-sustaining ecosystem, “semantic enrichment” becomes a strategy increasingly used by LAMs during recent years. This article introduces a number of semantic enrichment methods and efforts that can be applied to LAM data at various levels, aiming to support deeper and wider exploration and use of LAM data in DH research. The real cases, research projects, experiments, and pilot studies shared in this article demonstrate endless potential for LAM data, whether they are structured, semi-structured, or unstructured, regardless of what types of original artifacts carry the data. Following their roadmaps would encourage more effective initiatives and strengthen this effort to maximize LAM data’s discoverability, use- and reuse-ability, and their value in the mainstream of DH and Semantic Web

Connectivisim theory to develop english listening skills on senior students at Monte Olivo High School Academic period 2021 -2022

Analyze the Connectivism theory for the development of English listening skills on senior students at Monte Olivo High School.Learning theories understand how people acquire different types of knowledge and describe methods to make understanding clear. Assuming that in this research work are described five learning theories that were used to reach the main objectives. They are Behaviorism learning theory; it is based on the stimulus-response scheme and is based on objective and experimental procedures. It determines that learning is based on human behavior change and modifies behavior through stimulation, response, and reinforcement. This research is supported by the Connectivism learning theory, it is one of the most important theories in the present research because it uses technology as an important role in society. Furthermore, their technological tools helped create the proposal's creation activities, which is useful for students in their education in the digital age. In the globalized world acquiring a second language is important because it allows people to relate to different labor branches. Language acquisition involves structures, rules, and representation. The capacity to use language successfully requires one to acquire a range of tools including phonology, morphology, syntax, semantics, and an extensive vocabulary. This research is focused on listening skills, language is one of the essential parts, because it allows students not only to understand but also to imitate sounds and to be understood more clearly, in addition to being able to understand the speakers of the language. It refers to the capacity for listening comprehension and, as we mentioned at the beginning, it allows us to imitate sounds and improve precision when speaking. The reason for the importance of Listening is that when people are babies and children, they only identify the phonemes of their own language and do not consider the others, because it does not resemble what they were used to since they were born.Licenciatur

Mentorship and Teacher Retention: Analysis of Beginning Special Education Teachers’ Experiences in Minnesota

Beginning special education teachers each year enter their classrooms with high expectations and best-practice strategies they are eager to employ. Related literature affirmed, however, that they are quickly faced with what Charlotte Danielson (1999) described as a “sink or swim in the deep end of the pool” culture (p. 251-7) as they grapple with the needed sudden transition from theory to practice. Done well, effective mentoring can become the bridge between preservice learning and classroom experience and guide beginning special education teachers toward a deeper and more impactful teaching practice. This study’s purpose was to explore facets of new special education teacher mentorship supports in Minnesota to better understand what constituted effective mentoring program supports for new special education teachers in the profession. The study also endeavored to explore the influence of these supports on beginning special education teachers’ plans to remain in the field. The results of this study are intended to supplement the gap in the literature related to the influence of effective mentorship on special education teacher retention rates in Minnesota and to provide greater insight into how mentorship was provided, what that mentorship consisted of, and who provided it to beginning special education teachers in our state. The significance of this study was supported by four primary factors: 1) the growth of induction/mentoring programs across the United States, 2) the continued high attrition rate of special education teachers and the need to retain them in the field, 3) the limited research on the issues to be investigated, and 4) the recommendations from previous research. Therefore, this study researched specific themes of mentorship to better understand what constituted effective mentoring program supports for beginning special education teachers in Minnesota and to explore the influence on beginning special education teachers’ plans to remain in the profession. Mandlawitz, (2003) reported that the first three years of teaching represent a critical time-period for understanding and affecting the attrition rate of special education teachers. As such, this study focused solely on beginning special education teachers in their first three years of teaching. The findings of the study indicated that there was an apparent disconnect between what beginning special education teachers found helpful and what they were actually being provided in terms of mentorship support delivery. Further, there appeared to be a disconnect between what content beginning teachers found helpful and what they were actually being provided. There also appeared to be a shift from year one to year two in terms of the reported supports that were most beneficial. Ultimately, findings of the study indicated that provision of positive and meaningful mentorship experience in year one, year two, and year three of teaching special education had a positive impact on beginning teacher retention rates on the short- and long-term

A two-stage framework for designing visual analytics systems to augment organizational analytical processes

A perennially interesting research topic in the field of visual analytics is how to effectively develop systems that support organizational knowledge worker’s decision-making and reasoning processes. The primary objective of a visual analytic system is to facilitate analytical reasoning and discovery of insights through interactive visual interfaces. It also enables the transfer of capability and expertise from where it resides to where it is needed–across individuals, and organizations as necessary. The problem is, however, most domain analytical practices generally vary from organizations to organizations. This leads to the diversified design of visual analytics systems in incorporating domain analytical processes, making it difficult to generalize the success from one domain to another. Exacerbating this problem is the dearth of general models of analytical workflows available to enable such timely and effective designs. To alleviate these problems, this dissertation presents a two-stage framework for informing the design of a visual analytics system. This two-stage design framework builds upon and extends current practices pertaining to analytical workflow and focuses, in particular, on investigating its effect on the design of visual analytics systems for organizational environments. It aims to empower organizations with more systematic and purposeful information analyses through modeling the domain users’ reasoning processes. The first stage in this framework is an Observation and Designing stage, in which a visual analytic system is designed and implemented to abstract and encapsulate general organizational analytical processes, through extensive collaboration with domain users. The second stage is the User-centric Refinement stage, which aims at interactively enriching and refining the already encapsulated domain analysis process based on understanding user’s intentions through analyzing their task behavior. To implement this framework in the process of designing a visual analytics system, this dissertation proposes four general design recommendations that, when followed, empower such systems to bring the users closer to the center of their analytical processes. This dissertation makes three primary contributions: first, it presents a general characterization of the analytical workflow in organizational environments. This characterization fills in the blank of the current lack of such an analytical model and further represents a set of domain analytical tasks that are commonly applicable to various organizations. Secondly, this dissertation describes a two-stage framework for facilitating the domain users’ workflows through integrating their analytical models into interactive visual analytics systems. Finally, this dissertation presents recommendations and suggestions on enriching and refining domain analysis through capturing and analyzing knowledge workers’ analysis processes. To exemplify the generalizability of these design recommendations, this dissertation presents three visual analytics systems that are developed following the proposed recommendations, including Taste for Xerox Corporation, OpsVis for Microsoft, and IRSV for the U.S. Department of Transportation. All of these systems are deployed to domain knowledge workers and are adopted for their analytical practices. Extensive empirical evaluations are further conducted to demonstrate efficacy of these systems in facilitating domain analytical processes

Conceptual and Procedural Instruction: Mathematical Teaching Approaches And Strategies In An Urban Middle School

The purpose of this qualitative research study is to describe which methods and strategies can help to improve students’ achievement in mathematics in under resourced urban middle schools. The significance of this study is to develop math instructional skills in urban schools that can help bridge the achievement gap between urban underperforming schools and suburban achieving schools. Urban mathematics educators are content-ready and state-certified, but they lack certain key techniques and strategies that will help teachers succeed and students learn effectively and efficiently. Two questions were answered in this survey: in answer to the first question, the educators characterized conceptual and procedural math teaching methods, while in answer to the second question, the instructors answered questions on teaching strategies and pedagogies that help improve the quality of math instruction at the middle school level. Twelve math educators were asked eleven, semi structured, face-to-face questions. The conceptual framework supporting this research includes professional development schools, project-based learning, and transformational leadership. The conclusions that were drawn after the study can be categorized into three parts: First, the educators who were surveyed believe that conceptual learning is characterized as teaching students to apply the math concepts and theories that they have learned. Secondly, procedural learning is associated with the memorization of math facts and formulas. Lastly, certain practices ensure quality math instruction, including positive behavior intervention support, professional development, professional learning communities, response to intervention, teacher professional development schools, using curriculum maps and pacing guides, the use of technology in the classroom and using project-based learning methods

Needs assessment and future foresight report on Citizen Science

Through its potential to bridge science, society, and policy, Citizen Science is in a unique position to help generate responsible research, innovations, and policies in relation to societal challenges. While there are resources provided to researchers and practitioners on how to tap into the potential of Citizen Science, the knowledge and skills needs of the citizens, citizen science practitioners and many other social actors to achieve such participation is frequently overlooked. Needs assessment & future foresight report of the Erasmus+ project “Digital Citizen Science: Network, transfOrm, groW” aims to address this gap via providing insights concerning citizens’ behaviours, motivations, and change signals on Citizen Science at the European level. The report captures and delivers on the needs assessment research and findings, that is generated via futures design principles.Erasmus+ project title: Digital Citizen Science NOW: Network, transfOrm , groW 2021-1-DE02-KA220-ADU-00003535