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Decision-Based Learning : An Innovative Pedagogy that Unpacks Expert Knowledge for the Novice Learner
How can we ensure that students truly benefit from the expert knowledge of their professors and tutors, and how can we enable them to put knowledge into practice?Decision-Based Learning (DBL) is an innovative instructional strategy that uncovers the 'expert blind spot' to reveal the conditional knowledge that teachers (as experts) use to reason and act within the discipline.Instruction begins by modeling an expert’s decision-making process through real-world scenarios, guiding students through the conditions that shape those decisions.Learning occurs through comparison/contrast with other possible conditions at each decision point.Concepts and procedures are learned when they are relevant to the decision.With DBL, students never have to ask, 'When does this apply?'In this book you will read stories told by faculty who have redesigned their university courses using the Decision-Based Learning pedagogy and the impact this powerful strategy can have on student learning.It should be of use to anyone teaching and designing curricula in higher education.
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MANAGEMENT ACCOUNTING: DECISION AND CONTROL - STUDY TEXT
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Engaged Decision Making : From Team Knowledge to Team Decisions
In the knowledge economy, teams play a central role in decisions made within and across organisations.The reason why teams with diverse compositions are often used is arguably their ability to develop solutions that none of their members could have produced alone.Systems design, strategy and policy development, risk management, and innovation are just a few of the areas that call for team decisions.Unfortunately, a considerable number of behavioural research studies show that teamwork is fraught with difficulties.Teams often underestimate their fallibility, struggle with conflict, or are unable to share and integrate critical information effectively.Indeed, the evidence shows that two out of three teams do not achieve their goals and half of organisational decisions – many of which are team decisions – fail. In this book, the authors draw from research in psychology, decision and systems sciences – as well as their own research and consulting work that spans more than 20 years – to show how designed interventions can enable team decision making to become rigorous, transparent, and defensible.They cover theory and practice regarding the design, delivery, and evaluation of interventions to support team decision making in situations of varied complexity.Written as an applied resource for researchers and advanced students in particular, this book offers a guide to proven interventions that enhance the process of making team decisions and increase the chances of superior team results. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
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Practicing Communication Ethics : Development, Discernment, and Decision Making
This textbook presents a theoretical framework for developing a personal standard of ethics that can be applied in everyday communication situations.This third edition focuses on how the reader’s communication matters ethically in co-creating their relationships, family, workgroups, and communities.Through an examination of ethical values including truth, justice, freedom, care, integrity, and honor, the reader can determine which values they are ethically committed to upholding.Blending communication theory, ethics as practical philosophy, and moral psychology, the text presents the practice of communication ethics as part of the lifelong process of personal development and fosters the ability in its readers to approach communication decision making through an ethical lens.This edition features new and expanded treatment of moral injury and trauma, digital communication, partisan political division, and issues related to the COVID-19 pandemic.Practicing Communication Ethics is a core textbook for communication ethics and media ethics courses.Online resources for instructors include an instructor’s manual, sample assignments, and PowerPoint slides.They are available at www.routledge.com/9781032288987.
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Is my training a wrong decision?
It's difficult to determine whether your training is a wrong decision without more context. Consider evaluating your training based on factors such as your personal goals, interests, and the potential benefits it may bring to your career or personal development. Reflect on whether the training aligns with your long-term aspirations and if it will provide you with valuable skills and knowledge. Ultimately, trust your instincts and make a decision that feels right for you.
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What is the training decision 3?
Training decision 3 involves determining the specific training methods and materials to be used in the training program. This includes selecting the appropriate training resources, such as online courses, workshops, or on-the-job training, as well as deciding on the best delivery methods, such as in-person training, virtual training, or a combination of both. Additionally, training decision 3 involves identifying the key learning objectives and outcomes for the training program, as well as assessing the training needs of the participants to ensure the training is tailored to their specific requirements.
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Is it my decision when I study?
Yes, it is ultimately your decision when you study. As an individual, you have the autonomy to choose when and how you allocate your time for studying. However, it is important to consider the expectations and requirements of your educational institution or job, as well as the impact of your study habits on your overall well-being and success. Ultimately, finding a balance between personal autonomy and external responsibilities is key to effective time management and achieving your goals.
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What is the school decision 2?
School decision 2 refers to the process of making a choice about a student's education, such as selecting a school or program for them to attend. This decision may involve considering factors such as the student's academic needs, extracurricular interests, and the resources available at different schools. It is an important decision that can have a significant impact on a student's educational experience and future opportunities.
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Algorithmic Decision Making with Python Resources : From Multicriteria Performance Records to Decision Algorithms via Bipolar-Valued Outranking Digraphs
This book describes Python3 programming resources for implementing decision aiding algorithms in the context of a bipolar-valued outranking approach.These computing resources, made available under the name Digraph3, are useful in the field of Algorithmic Decision Theory and more specifically in outranking-based Multiple-Criteria Decision Aiding (MCDA). The first part of the book presents a set of tutorials introducing the Digraph3 collection of Python3 modules and its main objects, such as bipolar-valued digraphs and outranking digraphs.In eight methodological chapters, the second part illustrates multiple-criteria evaluation models and decision algorithms.These chapters are largely problem-oriented and demonstrate how to edit a new multiple-criteria performance tableau, how to build a best choice recommendation, how to compute the winner of an election and how to make rankings or ratings using incommensurable criteria.The book’s third part presents three real-world decision case studies, while the fourth part addresses more advanced topics, such as computing ordinal correlations between bipolar-valued outranking digraphs, computing kernels in bipolar-valued digraphs, testing for confidence or stability of outranking statements when facing uncertain or solely ordinal criteria significance weights, and tempering plurality tyranny effects in social choice problems.The fifth and last part is more specifically focused on working with undirected graphs, tree graphs and forests.The closing chapter explores comparability, split, interval and permutation graphs. The book is primarily intended for graduate students in management sciences, computational statistics and operations research.The chapters presenting algorithms for ranking multicriteria performance records will be of computational interest for designers of web recommender systems.Similarly, the relative and absolute quantile-rating algorithms, discussed and illustrated in several chapters, will be of practical interest to public and private performance auditors.
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Deep Learning in Personalized Healthcare and Decision Support
Deep Learning in Personalized Healthcare and Decision Support discusses the potential of deep learning technologies in the healthcare sector.The book covers the application of deep learning tools and techniques in diverse areas of healthcare, such as medical image classification, telemedicine, clinical decision support system, clinical trials, electronic health records, precision medication, Parkinson disease detection, genomics, and drug discovery.In addition, it discusses the use of DL for fraud detection and internet of things.This is a valuable resource for researchers, graduate students and healthcare professionals who are interested in learning more about deep learning applied to the healthcare sector. Although there is an increasing interest by clinicians and healthcare workers, they still lack enough knowledge to efficiently choose and make use of technologies currently available.This book fills that knowledge gap by bringing together experts from technology and clinical fields to cover the topics in depth.
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Learning for Decision and Control in Stochastic Networks
This book introduces the Learning-Augmented Network Optimization (LANO) paradigm, which interconnects network optimization with the emerging AI theory and algorithms and has been receiving a growing attention in network research.The authors present the topic based on a general stochastic network optimization model, and review several important theoretical tools that are widely adopted in network research, including convex optimization, the drift method, and mean-field analysis.The book then covers several popular learning-based methods, i.e., learning-augmented drift, multi-armed bandit and reinforcement learning, along with applications in networks where the techniques have been successfully applied.The authors also provide a discussion on potential future directions and challenges.
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Sustainable Energy Development : A Multi-Criteria Decision Making Approach
Sustainable Energy Development: A Multi-Criteria Decision Making Approach discusses sustainable energy development, the main path for achieving carbon neutrality, and the use of multi-criteria decision making (MCDM) in assessing energy transition in both operational and socio-political forms.It proposes ways to support responsible decision making toward sustainable energy in key areas such as power distribution, household energy, and transportation.The authors have developed frameworks and tools to help choose sustainable energy options like renewable energy technologies, energy efficiency improvements, policies, and how to promote them in different communities.The book includes several case studies focused on electricity, district heating, transport sectors in the European Union (EU), and decision making in the household sector.FeaturesAnalyzes the connection between sustainable energy development and the transition toward a carbon neutral society.Compares and discusses advanced MCDM tools to support sustainable energy options.Develops new frameworks of indicators for the assessment of sustainable regional and national energy system planning, and provides practical illustrative examples in various energy sectors.Provides policy implications when promoting sustainable energy development.Presents case studies on the applications of multi-criteria tools to support sustainable energy options in different energy sectors. Readers interested in gaining insight into leading trends in energy efficiency and sustainability, such as academics, researchers, graduate students, and professionals interested in sustainable energy and energy producers, city planners, policy makers, and more, will benefit from the topics and frameworks discussed in this book.
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What is a difficult decision during training?
A difficult decision during training is often knowing when to push through physical discomfort and when to listen to your body and rest. It can be challenging to balance the desire to improve and meet training goals with the need to prevent injury and avoid overtraining. Additionally, deciding when to seek help from a coach or trainer for guidance on training adjustments can also be a difficult decision, as it requires humility and trust in someone else's expertise. Ultimately, making the right decisions during training requires a combination of self-awareness, discipline, and willingness to seek support when needed.
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What is the right decision for the school?
The right decision for the school would be to prioritize the safety and well-being of its students and staff. This may involve implementing strict health and safety protocols, such as mask-wearing, social distancing, and regular sanitization measures. Additionally, offering a combination of in-person and virtual learning options to accommodate different needs and comfort levels would be beneficial. It is important for the school to stay informed about the evolving situation and be flexible in adapting their plans accordingly to ensure the best possible learning environment for everyone.
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Is training as an automotive painter a good decision?
Training as an automotive painter can be a good decision for individuals who have a passion for working with cars and enjoy painting. It can lead to a stable career with opportunities for growth and specialization within the automotive industry. However, it is important to consider factors such as job demand in your area, potential salary, and the physical demands of the job before making a decision. Overall, if you have a genuine interest in automotive painting and are willing to put in the effort to develop your skills, it can be a rewarding career choice.
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Is training as a vehicle painter a good decision?
Training as a vehicle painter can be a good decision for individuals who have a passion for working with their hands, have an eye for detail, and enjoy working in a creative field. Vehicle painting can be a rewarding career with opportunities for growth and specialization. However, it is important to consider factors such as job availability, salary potential, and physical demands of the job before pursuing training in this field. Conducting thorough research and speaking with professionals in the industry can help individuals make an informed decision about whether training as a vehicle painter is the right choice for them.
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