4,233 research outputs found
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The Role of Interactive Web Broadcasts in Fostering Distance Learning Studentsâ Engagement with Practical Lab and Fieldwork
Practical work in science and technology disciplines is crucial for studentsâ understanding and mastery. For educators who teach those disciplines at a distance and for students who learn remotely, this endeavour may be challenging.
The study presented in this thesis investigates the use of Interactive Web Broadcasts (IWBs) in five undergraduate practical science and technology modules at The Open University. The study examines the reasons for using IWBs, as well as the strategies and types of interactions that staff and students use to engage and interact with one another. The study gathered perspectives from academics (n=18); associate lecturers (n=10); technical production team (n=3); students (n=88), and an external guest expert about the purposes, strategies and motivations of participating in IWBs. The study used a qualitatively mixed-methods design. An adapted protocol of Flandersâs Interaction Analysis Categories was used to analyse the interaction patterns in the web broadcast transcripts and text-chat logs, and a discourse analysis coding scheme was applied to analyse the text-chat. Student online questionnaires were administered towards the end of the modules to capture the student perceptions of IWBs. Student interviews and staff focus groups were also conducted to gain a fuller picture of experiences of using and engaging with IWBs.
Findings show that the purposes and aims of using IWBs are to facilitate student engagement, foster a sense of community, and demonstrate an authentic practice of the sciences in real-world contexts. The communicative strategies were primarily affective and met studentsâ interests and expectations. The IWBs mitigated feelings of isolation that are common in distance education environments. IWBs had positive impacts on professional teaching practices and fostered collegiality and collaboration among staff. The findings are relevant to other distance and traditional campus-based universities that teach practical science and technology, those who teach online using synchronous technology-mediated systems, and those who are interested in student engagement and practical work
Traffic Prediction using Artificial Intelligence: Review of Recent Advances and Emerging Opportunities
Traffic prediction plays a crucial role in alleviating traffic congestion
which represents a critical problem globally, resulting in negative
consequences such as lost hours of additional travel time and increased fuel
consumption. Integrating emerging technologies into transportation systems
provides opportunities for improving traffic prediction significantly and
brings about new research problems. In order to lay the foundation for
understanding the open research challenges in traffic prediction, this survey
aims to provide a comprehensive overview of traffic prediction methodologies.
Specifically, we focus on the recent advances and emerging research
opportunities in Artificial Intelligence (AI)-based traffic prediction methods,
due to their recent success and potential in traffic prediction, with an
emphasis on multivariate traffic time series modeling. We first provide a list
and explanation of the various data types and resources used in the literature.
Next, the essential data preprocessing methods within the traffic prediction
context are categorized, and the prediction methods and applications are
subsequently summarized. Lastly, we present primary research challenges in
traffic prediction and discuss some directions for future research.Comment: Published in Transportation Research Part C: Emerging Technologies
(TR_C), Volume 145, 202
The Protection of Student Data Privacy in Wisconsin School Board Policies
American schools have increasingly adopted technology resources to fulfill their educational obligations. These tools are for instruction, communication, and storing and analyzing student information. Student data can be directory information, enrollment records, achievement data, and student-created products. This increased utilization began with the passage of No Child Left Behind in 2001, and the COVID-19 pandemic led to more educational technology use of student data. Districts turned to third-party vendors for assistance with data systems and virtual learning resources. Before, during, and after the pandemic, stakeholders were concerned about information security and the students\u27 privacy. School leaders looked to federal regulations to ensure appropriate and legal practices for student data use. The Family and Educational Rights and Privacy Act (FERPA) was implemented in 1974, and the growth of educational technology and digitization of student information has moved beyond the original guidance of the regulation. District leaders also looked to state laws, but Wisconsin statutes provide little guidance. These leaders rely on their local board policies to ensure they benefit from educational technology while protecting the privacy of their students. I utilized the methodological approach of document analysis and the contextual integrity privacy framework to understand how Wisconsin districts address student data privacy in local board policies. In addition, I examined how federal regulations are addressed and the role of leadership in policy implementation. Findings from this study indicate differences for districts using a policy consultation service. These policies address federal regulations and account for the use of data by modern educational technology. The leadership activities required for student data privacy align with previous research for effective educational leadership. These findings show the need for local policies to address federal regulations for student privacy in the context of educational technology utilization
Development of linguistic linked open data resources for collaborative data-intensive research in the language sciences
Making diverse data in linguistics and the language sciences open, distributed, and accessible: perspectives from language/language acquistiion researchers and technical LOD (linked open data) researchers. This volume examines the challenges inherent in making diverse data in linguistics and the language sciences open, distributed, integrated, and accessible, thus fostering wide data sharing and collaboration. It is unique in integrating the perspectives of language researchers and technical LOD (linked open data) researchers. Reporting on both active research needs in the field of language acquisition and technical advances in the development of data interoperability, the book demonstrates the advantages of an international infrastructure for scholarship in the field of language sciences. With contributions by researchers who produce complex data content and scholars involved in both the technology and the conceptual foundations of LLOD (linguistics linked open data), the book focuses on the area of language acquisition because it involves complex and diverse data sets, cross-linguistic analyses, and urgent collaborative research. The contributors discuss a variety of research methods, resources, and infrastructures. Contributors Isabelle BarriĂšre, Nan Bernstein Ratner, Steven Bird, Maria Blume, Ted Caldwell, Christian Chiarcos, Cristina Dye, Suzanne Flynn, Claire Foley, Nancy Ide, Carissa Kang, D. Terence Langendoen, Barbara Lust, Brian MacWhinney, Jonathan Masci, Steven Moran, Antonio Pareja-Lora, Jim Reidy, Oya Y. Rieger, Gary F. Simons, Thorsten Trippel, Kara Warburton, Sue Ellen Wright, Claus Zin
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
RAPID: Enabling Fast Online Policy Learning in Dynamic Public Cloud Environments
Resource sharing between multiple workloads has become a prominent practice
among cloud service providers, motivated by demand for improved resource
utilization and reduced cost of ownership. Effective resource sharing, however,
remains an open challenge due to the adverse effects that resource contention
can have on high-priority, user-facing workloads with strict Quality of Service
(QoS) requirements. Although recent approaches have demonstrated promising
results, those works remain largely impractical in public cloud environments
since workloads are not known in advance and may only run for a brief period,
thus prohibiting offline learning and significantly hindering online learning.
In this paper, we propose RAPID, a novel framework for fast, fully-online
resource allocation policy learning in highly dynamic operating environments.
RAPID leverages lightweight QoS predictions, enabled by
domain-knowledge-inspired techniques for sample efficiency and bias reduction,
to decouple control from conventional feedback sources and guide policy
learning at a rate orders of magnitude faster than prior work. Evaluation on a
real-world server platform with representative cloud workloads confirms that
RAPID can learn stable resource allocation policies in minutes, as compared
with hours in prior state-of-the-art, while improving QoS by 9.0x and
increasing best-effort workload performance by 19-43%
Academic integrity : a call to research and action
Originally published in French:L'urgence de l'intĂ©gritĂ© acadĂ©mique, EÌditions EMS, Management & socieÌteÌ, Caen, 2021 (ISBN 978-2-37687-472-0).The urgency of doing complements the urgency of knowing. Urgency here is not the inconsequential injunction of irrational immediacy. It arises in various contexts for good reasons,
when there is a threat to the human existence and harms to others. Today, our knowledge based civilization is at risk both by new production models of knowledge and by the shamelessness
of knowledge delinquents, exposing the greatest number to important risks. Swiftly, the editors respond to the diagnostic by setting up a reference tool for academic integrity.
Across multiple dialogues between the twenty-five chapters and five major themes, the ethical response shapes pragmatic horizons for action, on a range of disciplinary competencies:
from science to international diplomacy. An interdisciplinary work indispensable for teachers, students and university researchers and administrators
2023-2024 Lynn University Academic Catalog
The 2023-2024 Academic Catalog initially published as a web-only document.
The Department of Marketing and Communication created a PDF version, which is available for download here.https://spiral.lynn.edu/accatalogs/1052/thumbnail.jp
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