Eugene V. Gallagher
- Published in print:
- 2007
- Published Online:
- September 2007
- ISBN:
- 9780195177299
- eISBN:
- 9780199785537
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195177299.003.0013
- Subject:
- Religion, Religion and Society
Students frequently come to classes about new religious movements disinclined to take them seriously as legitimate religions. Borrowing from literature about race and diversity in the classroom and ...
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Students frequently come to classes about new religious movements disinclined to take them seriously as legitimate religions. Borrowing from literature about race and diversity in the classroom and using Peter Elbow's description of methodological doubt and methodological belief as analytical tools, this chapter discusses strategies for overcoming student resistance to taking NRMs seriously as religions. It is argued that the rigorous cultivation of methodological belief as an approach to the study of NRMs offers an effective way to dissipate some negative effects of stereotypes of NRMs and develop adequate descriptions of them. Advocating a rhetorical model of teaching, the chapter provides examples of active learning assignments and offers suggestions about course design that can make the politics of representation of NRMs a continuing topic for class discussions.Less
Students frequently come to classes about new religious movements disinclined to take them seriously as legitimate religions. Borrowing from literature about race and diversity in the classroom and using Peter Elbow's description of methodological doubt and methodological belief as analytical tools, this chapter discusses strategies for overcoming student resistance to taking NRMs seriously as religions. It is argued that the rigorous cultivation of methodological belief as an approach to the study of NRMs offers an effective way to dissipate some negative effects of stereotypes of NRMs and develop adequate descriptions of them. Advocating a rhetorical model of teaching, the chapter provides examples of active learning assignments and offers suggestions about course design that can make the politics of representation of NRMs a continuing topic for class discussions.
Robert DiYanni, Anton Borst, Robert DiYanni, and Anton Borst
- Published in print:
- 2020
- Published Online:
- September 2020
- ISBN:
- 9780691183800
- eISBN:
- 9780691202006
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691183800.003.0004
- Subject:
- Education, Higher and Further Education
This chapter identifies, explains, and explores a number of strategies and techniques for active learning in the classroom. “Active learning” is a broad term for an approach to teaching that requires ...
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This chapter identifies, explains, and explores a number of strategies and techniques for active learning in the classroom. “Active learning” is a broad term for an approach to teaching that requires students to demonstrate their learning through doing things. Active learning provides an alternative to more passive forms of knowledge acquisition, such as listening to lectures. It shifts the focus from teachers to their students. Active learning offers an alternative to the transmission model of teaching and learning, in which the teacher speaks and demonstrates, while students listen and observe. With active learning, students use and apply information, principles, and concepts to scenarios, situations, and cases, whether actual or fabricated.Less
This chapter identifies, explains, and explores a number of strategies and techniques for active learning in the classroom. “Active learning” is a broad term for an approach to teaching that requires students to demonstrate their learning through doing things. Active learning provides an alternative to more passive forms of knowledge acquisition, such as listening to lectures. It shifts the focus from teachers to their students. Active learning offers an alternative to the transmission model of teaching and learning, in which the teacher speaks and demonstrates, while students listen and observe. With active learning, students use and apply information, principles, and concepts to scenarios, situations, and cases, whether actual or fabricated.
NIGEL DUNCAN and SUSAN L. KAY
- Published in print:
- 2010
- Published Online:
- January 2011
- ISBN:
- 9780195381146
- eISBN:
- 9780199869305
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195381146.003.0012
- Subject:
- Law, Public International Law
This chapter explains the limited ways in which legal ethics and professionalism are addressed in most traditional law programs and proposes more challenging goals for legal education, recognizing ...
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This chapter explains the limited ways in which legal ethics and professionalism are addressed in most traditional law programs and proposes more challenging goals for legal education, recognizing the importance of introducing students to the values underpinning the professional codes. It presents the diversity of approaches to addressing lawyer competence, ethics, and professionalism in different jurisdictions, and identifies the different ways in which clinical legal education and clinical methods may be used to address these issues. The chapter considers the advantages and disadvantages of each, and gives concrete examples of effective methods. It underpins this with the theoretical basis for such experiential learning approaches and explains how active learning can provide effective ways of encouraging moral development. It also considers the particular contribution played by the global clinical movement to developing legal ethics education.Less
This chapter explains the limited ways in which legal ethics and professionalism are addressed in most traditional law programs and proposes more challenging goals for legal education, recognizing the importance of introducing students to the values underpinning the professional codes. It presents the diversity of approaches to addressing lawyer competence, ethics, and professionalism in different jurisdictions, and identifies the different ways in which clinical legal education and clinical methods may be used to address these issues. The chapter considers the advantages and disadvantages of each, and gives concrete examples of effective methods. It underpins this with the theoretical basis for such experiential learning approaches and explains how active learning can provide effective ways of encouraging moral development. It also considers the particular contribution played by the global clinical movement to developing legal ethics education.
Masashi Sugiyama and Motoaki Kawanabe
- Published in print:
- 2012
- Published Online:
- September 2013
- ISBN:
- 9780262017091
- eISBN:
- 9780262301220
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262017091.003.0008
- Subject:
- Computer Science, Machine Learning
This chapter examines the problem of active learning. The goal of active learning is to find the most “informative” training input points so that learning can be successfully achieved from only a ...
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This chapter examines the problem of active learning. The goal of active learning is to find the most “informative” training input points so that learning can be successfully achieved from only a small number of training samples. In the active learning scenario, covariate shift—mismatch of training and test input distributions—occurs naturally occurs since the training input distribution is designed by users, while the test input distribution is determined by the environment. Thus, covariate shift is inevitable in active learning. The chapter introduces active learning methods for regression in light of covariate shift. Their mutual relation and numerical examples are also shown. Furthermore, these active learning methods are extended to the pool-based scenarios, where a set of input-only samples is provided in advance and users want to specify good input-only samples to gather output values.Less
This chapter examines the problem of active learning. The goal of active learning is to find the most “informative” training input points so that learning can be successfully achieved from only a small number of training samples. In the active learning scenario, covariate shift—mismatch of training and test input distributions—occurs naturally occurs since the training input distribution is designed by users, while the test input distribution is determined by the environment. Thus, covariate shift is inevitable in active learning. The chapter introduces active learning methods for regression in light of covariate shift. Their mutual relation and numerical examples are also shown. Furthermore, these active learning methods are extended to the pool-based scenarios, where a set of input-only samples is provided in advance and users want to specify good input-only samples to gather output values.
Sugiyama Masashi, Rubens Neil, and Müller Klaus-Robert
- Published in print:
- 2008
- Published Online:
- August 2013
- ISBN:
- 9780262170055
- eISBN:
- 9780262255103
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262170055.003.0007
- Subject:
- Computer Science, Machine Learning
This chapter, which addresses the problems of model selection and active learning in the conditional expectation framework, is organized as follows. Section 7.2 formulates a linear regression problem ...
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This chapter, which addresses the problems of model selection and active learning in the conditional expectation framework, is organized as follows. Section 7.2 formulates a linear regression problem with covariate shift. Sections 7.3 and 7.4 introduce a model selection criterion and an active learning criterion, respectively, in the conditional expectation framework and show that they are more advantageous than the full expectation methods in the context of approximate linear regression. Section 7.5 discusses how model selection and active learning can be combined. Concluding remarks and future prospects are given in Section 7.6.Less
This chapter, which addresses the problems of model selection and active learning in the conditional expectation framework, is organized as follows. Section 7.2 formulates a linear regression problem with covariate shift. Sections 7.3 and 7.4 introduce a model selection criterion and an active learning criterion, respectively, in the conditional expectation framework and show that they are more advantageous than the full expectation methods in the context of approximate linear regression. Section 7.5 discusses how model selection and active learning can be combined. Concluding remarks and future prospects are given in Section 7.6.
Masashi Sugiyama and Motoaki Kawanabe
- Published in print:
- 2012
- Published Online:
- September 2013
- ISBN:
- 9780262017091
- eISBN:
- 9780262301220
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262017091.003.0009
- Subject:
- Computer Science, Machine Learning
This chapter examines the problem of active learning with model selection. Model selection and active learning are two important challenges for successful learning. A natural desire is to perform ...
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This chapter examines the problem of active learning with model selection. Model selection and active learning are two important challenges for successful learning. A natural desire is to perform model selection and active learning at the same time, that is, we want to choose the best model and the best training input points. However, this is actually a chicken-and-egg problem since training input samples should have been fixed for performing model selection and models should have been fixed for performing active learning. The chapter discusses several compromise approaches, such as the sequential approach, the batch approach, and the ensemble approach. Using numerical examples, limitations of the sequential and batch approaches are pointed out, and the usefulness of the ensemble active learning approach is demonstrated.Less
This chapter examines the problem of active learning with model selection. Model selection and active learning are two important challenges for successful learning. A natural desire is to perform model selection and active learning at the same time, that is, we want to choose the best model and the best training input points. However, this is actually a chicken-and-egg problem since training input samples should have been fixed for performing model selection and models should have been fixed for performing active learning. The chapter discusses several compromise approaches, such as the sequential approach, the batch approach, and the ensemble approach. Using numerical examples, limitations of the sequential and batch approaches are pointed out, and the usefulness of the ensemble active learning approach is demonstrated.
Robert DiYanni, Anton Borst, Robert DiYanni, and Anton Borst
- Published in print:
- 2020
- Published Online:
- September 2020
- ISBN:
- 9780691183800
- eISBN:
- 9780691202006
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691183800.003.0009
- Subject:
- Education, Higher and Further Education
This chapter takes a look at experiential learning. The central idea of “experiential learning,” as the term suggests, is the process of learning through experience. The “learning” part requires an ...
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This chapter takes a look at experiential learning. The central idea of “experiential learning,” as the term suggests, is the process of learning through experience. The “learning” part requires an additional element: reflection. Thus, a fuller concept of experiential learning includes reflection about the learning experiences in which students participate. The teacher's responsibility is to create worthwhile educational experiences so that students will have something of value on which to reflect. Like active learning, experiential learning involves many different forms of student engagement. Experiential learning is learning by doing. In this kind of hands-on learning, students assume responsibility for their learning, taking control of both the learning experience and their reflection on it.Less
This chapter takes a look at experiential learning. The central idea of “experiential learning,” as the term suggests, is the process of learning through experience. The “learning” part requires an additional element: reflection. Thus, a fuller concept of experiential learning includes reflection about the learning experiences in which students participate. The teacher's responsibility is to create worthwhile educational experiences so that students will have something of value on which to reflect. Like active learning, experiential learning involves many different forms of student engagement. Experiential learning is learning by doing. In this kind of hands-on learning, students assume responsibility for their learning, taking control of both the learning experience and their reflection on it.
Kanamori Takafumi and Shimodaira Hidetoshi
- Published in print:
- 2008
- Published Online:
- August 2013
- ISBN:
- 9780262170055
- eISBN:
- 9780262255103
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262170055.003.0006
- Subject:
- Computer Science, Machine Learning
This chapter examines learning algorithms under the covariate shift in which training and test data are drawn from different distributions. Using a naive estimator under the covariate shift, such as ...
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This chapter examines learning algorithms under the covariate shift in which training and test data are drawn from different distributions. Using a naive estimator under the covariate shift, such as the maximum likelihood estimator (MLE), results in serious estimation bias when the assumed statistical model is misspecified. To correct this estimation bias, the chapter introduces the maximum weighted log-likelihood estimator (MWLE) with an information criterion to determine an optimal weight function for samples. It also investigates active learning in which the covariate shift is used to improve prediction, and shows that by incorporating the MWLE into active learning, one can reduce estimation bias and obtain a consistent estimator even under model misspecification.Less
This chapter examines learning algorithms under the covariate shift in which training and test data are drawn from different distributions. Using a naive estimator under the covariate shift, such as the maximum likelihood estimator (MLE), results in serious estimation bias when the assumed statistical model is misspecified. To correct this estimation bias, the chapter introduces the maximum weighted log-likelihood estimator (MWLE) with an information criterion to determine an optimal weight function for samples. It also investigates active learning in which the covariate shift is used to improve prediction, and shows that by incorporating the MWLE into active learning, one can reduce estimation bias and obtain a consistent estimator even under model misspecification.
Stephen M. Kosslyn, Robin B. Goldberg, and Teri Cannon
- Published in print:
- 2017
- Published Online:
- May 2018
- ISBN:
- 9780262037150
- eISBN:
- 9780262343695
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262037150.003.0010
- Subject:
- Education, Educational Policy and Politics
We have learned many lessons in the course of implementing the Minerva curriculum and pedagogy. One of the most striking lessons is how important it is for both faculty and students to be open to ...
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We have learned many lessons in the course of implementing the Minerva curriculum and pedagogy. One of the most striking lessons is how important it is for both faculty and students to be open to unlearning many previous assumptions and habits. For example, we have identified what we call the “illusion of learning”—which occurs when faculty and students believe that the more notes students take during a lecture, the more they have learned. Yet, the evidence is clear: Lectures are not an effective way to learn, and pale in comparison to active learning. Although active learning often takes more time than lectures and requires much more intellectual engagement from both faculty and students, it provides lasting benefits. Similarly, we have discovered that active learning requires a different view of what is an appropriate goal for in-class experiences–not information transmission and memorization but rather the internalization of skills, concepts and ways to use knowledge. In this chapter, we summarize many of the assumptions and habits that both faculty and students need to unlearn in order to learn effectively at Minerva.Less
We have learned many lessons in the course of implementing the Minerva curriculum and pedagogy. One of the most striking lessons is how important it is for both faculty and students to be open to unlearning many previous assumptions and habits. For example, we have identified what we call the “illusion of learning”—which occurs when faculty and students believe that the more notes students take during a lecture, the more they have learned. Yet, the evidence is clear: Lectures are not an effective way to learn, and pale in comparison to active learning. Although active learning often takes more time than lectures and requires much more intellectual engagement from both faculty and students, it provides lasting benefits. Similarly, we have discovered that active learning requires a different view of what is an appropriate goal for in-class experiences–not information transmission and memorization but rather the internalization of skills, concepts and ways to use knowledge. In this chapter, we summarize many of the assumptions and habits that both faculty and students need to unlearn in order to learn effectively at Minerva.
Jonathan Katzman, Matt Regan, and Ari Bader-Natal
- Published in print:
- 2017
- Published Online:
- May 2018
- ISBN:
- 9780262037150
- eISBN:
- 9780262343695
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262037150.003.0015
- Subject:
- Education, Educational Policy and Politics
When we set out to design the Active Learning Forum we had three aspirational goals in mind. First, we wanted every student to feel as though he or she is sitting next to the professor. Students are ...
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When we set out to design the Active Learning Forum we had three aspirational goals in mind. First, we wanted every student to feel as though he or she is sitting next to the professor. Students are constantly engaged in “fully active learning.” Second, we wanted the technology to disappear. We ensure that the focus is on the interactions and discussion among students and the professor; the technology fades into the background. Third, we wanted to bring the seminar back from the ether. Because we record each class, faculty can provide students with feedback on every class (and vice versa!). Students can see the history of how they do over the course of a semester, a year and eventually their entire time at Minerva. The combined result of meeting these three goals is that we can have seminars that surpass what’s possible in a traditional classroom and create better learningLess
When we set out to design the Active Learning Forum we had three aspirational goals in mind. First, we wanted every student to feel as though he or she is sitting next to the professor. Students are constantly engaged in “fully active learning.” Second, we wanted the technology to disappear. We ensure that the focus is on the interactions and discussion among students and the professor; the technology fades into the background. Third, we wanted to bring the seminar back from the ether. Because we record each class, faculty can provide students with feedback on every class (and vice versa!). Students can see the history of how they do over the course of a semester, a year and eventually their entire time at Minerva. The combined result of meeting these three goals is that we can have seminars that surpass what’s possible in a traditional classroom and create better learning
Remo Job, Lorella Lotto, and Claudio Tonzar
- Published in print:
- 2011
- Published Online:
- September 2011
- ISBN:
- 9780199794942
- eISBN:
- 9780199914500
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199794942.003.0044
- Subject:
- Psychology, Social Psychology
This chapter discusses some of the implications of the notion of psychological literacy for the design of curriculum for bachelor students of psychology in Italy. Specifically, the chapter identifies ...
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This chapter discusses some of the implications of the notion of psychological literacy for the design of curriculum for bachelor students of psychology in Italy. Specifically, the chapter identifies four features that would allow students to develop psychological literacy during their undergraduate education: a mixed competence-based and input-based approach to teaching, with an emphasis on the development of attitudes and skills; active learning methodologies, with an emphasis on students’ responsibility for their learning; activities that allow to relate to real-world situations, with an emphasis on problem solving and application of knowledge; and the value of mobility within and across countries as a bridge to cultural awareness and sensitivity. Finally, some of the consequences of considering psychological literacy a process are briefly discussed.Less
This chapter discusses some of the implications of the notion of psychological literacy for the design of curriculum for bachelor students of psychology in Italy. Specifically, the chapter identifies four features that would allow students to develop psychological literacy during their undergraduate education: a mixed competence-based and input-based approach to teaching, with an emphasis on the development of attitudes and skills; active learning methodologies, with an emphasis on students’ responsibility for their learning; activities that allow to relate to real-world situations, with an emphasis on problem solving and application of knowledge; and the value of mobility within and across countries as a bridge to cultural awareness and sensitivity. Finally, some of the consequences of considering psychological literacy a process are briefly discussed.
Masashi Sugiyama and Motoaki Kawanabe
- Published in print:
- 2012
- Published Online:
- September 2013
- ISBN:
- 9780262017091
- eISBN:
- 9780262301220
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262017091.003.0010
- Subject:
- Computer Science, Machine Learning
This chapter describes real-world applications of active learning techniques: sampling policy design in reinforcement learning and wafer alignment in semiconductor exposure apparatus.
This chapter describes real-world applications of active learning techniques: sampling policy design in reinforcement learning and wafer alignment in semiconductor exposure apparatus.
Marjorie Mayo
- Published in print:
- 2020
- Published Online:
- January 2021
- ISBN:
- 9781447343257
- eISBN:
- 9781447343301
- Item type:
- chapter
- Publisher:
- Policy Press
- DOI:
- 10.1332/policypress/9781447343257.003.0004
- Subject:
- Education, Educational Policy and Politics
This chapter focuses on varying approaches to the values, principles and practices of learning for active citizenship and social change. Government projects in UK have included active learning to ...
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This chapter focuses on varying approaches to the values, principles and practices of learning for active citizenship and social change. Government projects in UK have included active learning to promote active citizenship, such as the Take Part programmes, for example. These programmes built on the values, principles and approaches of civil society initiatives, including the experiences of the Workers Educational Association.
The chapter concludes with examples of the application of values and principles via the arts, both in Britain and internationally.Less
This chapter focuses on varying approaches to the values, principles and practices of learning for active citizenship and social change. Government projects in UK have included active learning to promote active citizenship, such as the Take Part programmes, for example. These programmes built on the values, principles and approaches of civil society initiatives, including the experiences of the Workers Educational Association.
The chapter concludes with examples of the application of values and principles via the arts, both in Britain and internationally.
Susan G. Clark
- Published in print:
- 2008
- Published Online:
- October 2013
- ISBN:
- 9780300124224
- eISBN:
- 9780300145038
- Item type:
- chapter
- Publisher:
- Yale University Press
- DOI:
- 10.12987/yale/9780300124224.003.0007
- Subject:
- Environmental Science, Environmental Studies
This chapter explains the options to improve management policy in greater Yellowstone by focusing on decision making, adopting active learning, and managing adaptively, all in the interest of ...
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This chapter explains the options to improve management policy in greater Yellowstone by focusing on decision making, adopting active learning, and managing adaptively, all in the interest of identifying and supporting common interest outcomes. Widely recognized standards for good decision making can be used to appraise the existing decision process when leaders understand that improving policy means upgrading how the decision process functions. There are many tools available to help leaders and others learn actively, among them prototyping and case-based learning, or harvesting the lessons of experience. This is a way to examine past experience, find lessons, and diffuse and adapt them to future work. There are many possible programs to convey new leadership styles and problem-solving methods for policy-making in greater Yellowstone, all of which can reinforce one another.Less
This chapter explains the options to improve management policy in greater Yellowstone by focusing on decision making, adopting active learning, and managing adaptively, all in the interest of identifying and supporting common interest outcomes. Widely recognized standards for good decision making can be used to appraise the existing decision process when leaders understand that improving policy means upgrading how the decision process functions. There are many tools available to help leaders and others learn actively, among them prototyping and case-based learning, or harvesting the lessons of experience. This is a way to examine past experience, find lessons, and diffuse and adapt them to future work. There are many possible programs to convey new leadership styles and problem-solving methods for policy-making in greater Yellowstone, all of which can reinforce one another.
ANA PAULA SALES, CHRISTOPHER CHALLIS, RYAN PRENGER, and DANIEL MERL
- Published in print:
- 2013
- Published Online:
- May 2013
- ISBN:
- 9780199695607
- eISBN:
- 9780191744167
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199695607.003.0012
- Subject:
- Mathematics, Probability / Statistics
This chapter presents a novel online learning system for classification of email texts based on particle learning for composite mixture models involving probabilistic automata. The composite mixture ...
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This chapter presents a novel online learning system for classification of email texts based on particle learning for composite mixture models involving probabilistic automata. The composite mixture structure allows specification of a joint probability model for heterogeneous collections of independent variables without requiring complex embeddings via generalized linear models or copula techniques. The chapter is organized as follows. Section 12.2 presents a hierarchical model representation of a class of probabilistic automata and derives the particle learning algorithm for obtaining parameter estimates. Section 12.3 describes a framework for semisupervised text classification problems based on a composite mixture model formulation. Section 12.4 discusses an application of the classifier to a spam detection dataset. Section 12.5 concludes with a discussion of computational considerations and future work.Less
This chapter presents a novel online learning system for classification of email texts based on particle learning for composite mixture models involving probabilistic automata. The composite mixture structure allows specification of a joint probability model for heterogeneous collections of independent variables without requiring complex embeddings via generalized linear models or copula techniques. The chapter is organized as follows. Section 12.2 presents a hierarchical model representation of a class of probabilistic automata and derives the particle learning algorithm for obtaining parameter estimates. Section 12.3 describes a framework for semisupervised text classification problems based on a composite mixture model formulation. Section 12.4 discusses an application of the classifier to a spam detection dataset. Section 12.5 concludes with a discussion of computational considerations and future work.
Naomi S. Baron
- Published in print:
- 2021
- Published Online:
- March 2021
- ISBN:
- 9780190084097
- eISBN:
- 9780190084127
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780190084097.003.0007
- Subject:
- Education, Educational Equipment and Technology
Chapter 6 draws upon what we learned in Chapters 4 and 5 to identify effective strategies for onscreen reading, with both single and multiple texts. The chapter begins by emphasizing the importance ...
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Chapter 6 draws upon what we learned in Chapters 4 and 5 to identify effective strategies for onscreen reading, with both single and multiple texts. The chapter begins by emphasizing the importance of determining reading goals, along with thinking about who the reader is, how cost factors in, the importance of active learning, and ways of applying print strategies when reading onscreen. The first set of recommendations is for young children, while the rest of the chapter looks at strategies for school-age readers. In discussing use of single texts, we consider such issues as genre, complexity, scrolling, priming a reading mindset, annotation, and concept maps. The section on reading multiple texts includes the challenge of recognizing online fake news and the potential to use skills developed when scrutinizing online documents to advance the larger civic good.Less
Chapter 6 draws upon what we learned in Chapters 4 and 5 to identify effective strategies for onscreen reading, with both single and multiple texts. The chapter begins by emphasizing the importance of determining reading goals, along with thinking about who the reader is, how cost factors in, the importance of active learning, and ways of applying print strategies when reading onscreen. The first set of recommendations is for young children, while the rest of the chapter looks at strategies for school-age readers. In discussing use of single texts, we consider such issues as genre, complexity, scrolling, priming a reading mindset, annotation, and concept maps. The section on reading multiple texts includes the challenge of recognizing online fake news and the potential to use skills developed when scrutinizing online documents to advance the larger civic good.
Jenneth Parker
- Published in print:
- 2014
- Published Online:
- May 2015
- ISBN:
- 9781447306467
- eISBN:
- 9781447311560
- Item type:
- chapter
- Publisher:
- Policy Press
- DOI:
- 10.1332/policypress/9781447306467.003.0006
- Subject:
- Political Science, Public Policy
In Chapter Six, Jenneth Parker explores ways of facilitating effective collaboration between environmental and development organisations (as social movements) to meet the political challenges of ...
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In Chapter Six, Jenneth Parker explores ways of facilitating effective collaboration between environmental and development organisations (as social movements) to meet the political challenges of global sustainability. The chapter posits a new way of thinking, using the concept of convergence as a means to facilitate the development of global equity within planetary boundaries. Convergence is based on an approach to global eco-justice that was developed during the Kyoto climate change talks by the environmental campaigner Aubrey Meyer. It combines the concept of equal rights for all citizens to use the earth's atmosphere, with a per capita allocation approach. This would mean that rich countries would contract their use of carbon, leaving poorer countries to continue to develop. Convergence would occur when equal levels of development are achieved with sustainable carbon emissions. The chapter looks at the potential of convergence to act as a ‘unifying framework’ for sustainability practitioners involved in the process of developing the new Sustainable Development Goals, as a successor to the Millennium Development Goals that ran from 2000 to 2015.Less
In Chapter Six, Jenneth Parker explores ways of facilitating effective collaboration between environmental and development organisations (as social movements) to meet the political challenges of global sustainability. The chapter posits a new way of thinking, using the concept of convergence as a means to facilitate the development of global equity within planetary boundaries. Convergence is based on an approach to global eco-justice that was developed during the Kyoto climate change talks by the environmental campaigner Aubrey Meyer. It combines the concept of equal rights for all citizens to use the earth's atmosphere, with a per capita allocation approach. This would mean that rich countries would contract their use of carbon, leaving poorer countries to continue to develop. Convergence would occur when equal levels of development are achieved with sustainable carbon emissions. The chapter looks at the potential of convergence to act as a ‘unifying framework’ for sustainability practitioners involved in the process of developing the new Sustainable Development Goals, as a successor to the Millennium Development Goals that ran from 2000 to 2015.
Vsevolod Kapatsinski
- Published in print:
- 2018
- Published Online:
- September 2019
- ISBN:
- 9780262037860
- eISBN:
- 9780262346313
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262037860.003.0005
- Subject:
- Psychology, Cognitive Psychology
This chapter reviews the main ideas of Bayesian approaches to learning, compared to associationist approaches. It reviews and discusses Bayesian criticisms of associationist learning theory. In ...
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This chapter reviews the main ideas of Bayesian approaches to learning, compared to associationist approaches. It reviews and discusses Bayesian criticisms of associationist learning theory. In particular, Bayesian theorists have argued that associative models fail to represent confidence in belief and update confidence with experience. The chapter discusses whether updating confidence is necessary to capture entrenchment, suspicious coincidence, and category variability effects. The evidence is argued to be somewhat inconclusive at present, as simulated annealing can often suffice. Furthermore, when confidence updating is suggested by the data, the updating suggested by the data may be non-normative, contrary to the Bayesian notion of the learner as an ideal observer. Following Kruschke, learned selective attention is argued to explain many ways in which human learning departs from that of the ideal observer, most crucially including the weakness of backward relative to forward blocking. Other departures from the ideal observer may be due to biological organisms taking into account factors other than belief accuracy. Finally, generative and discriminative learning models are compared. Generative models are argued to be particularly likely when active learning is a possibility and when reversing the observed mappings may be required.Less
This chapter reviews the main ideas of Bayesian approaches to learning, compared to associationist approaches. It reviews and discusses Bayesian criticisms of associationist learning theory. In particular, Bayesian theorists have argued that associative models fail to represent confidence in belief and update confidence with experience. The chapter discusses whether updating confidence is necessary to capture entrenchment, suspicious coincidence, and category variability effects. The evidence is argued to be somewhat inconclusive at present, as simulated annealing can often suffice. Furthermore, when confidence updating is suggested by the data, the updating suggested by the data may be non-normative, contrary to the Bayesian notion of the learner as an ideal observer. Following Kruschke, learned selective attention is argued to explain many ways in which human learning departs from that of the ideal observer, most crucially including the weakness of backward relative to forward blocking. Other departures from the ideal observer may be due to biological organisms taking into account factors other than belief accuracy. Finally, generative and discriminative learning models are compared. Generative models are argued to be particularly likely when active learning is a possibility and when reversing the observed mappings may be required.
Susan G. Clark
- Published in print:
- 2008
- Published Online:
- October 2013
- ISBN:
- 9780300124224
- eISBN:
- 9780300145038
- Item type:
- chapter
- Publisher:
- Yale University Press
- DOI:
- 10.12987/yale/9780300124224.003.0006
- Subject:
- Environmental Science, Environmental Studies
This chapter explains the approaches for leaders to develop skills to narrow the gap between current management policy and stated goals. Many strategies are recommended to encourage out-of-the-box ...
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This chapter explains the approaches for leaders to develop skills to narrow the gap between current management policy and stated goals. Many strategies are recommended to encourage out-of-the-box thinking, practice-based action, and active learning. Some options to improve leaders include staffing and partnerships, high-performance teams, problem-solving seminars, better understanding of the relationship between science and policy, public education and policy, and a host of other leadership-improvement techniques that have proven useful in other settings. The leaders of Yellowstone today have an opportunity, particularly the GYCC in its unique role as a high-level, interagency committee, to close this gap as effectively, efficiently, and equitably as possible. Thus, the model of a healthy greater Yellowstone ecosystem guided by enlightened management policy is a widely popular idea and leaders can build the necessary coalitions, overcome dissension, and integrate fragmentation into a vision and action that moves us all toward sustainability.Less
This chapter explains the approaches for leaders to develop skills to narrow the gap between current management policy and stated goals. Many strategies are recommended to encourage out-of-the-box thinking, practice-based action, and active learning. Some options to improve leaders include staffing and partnerships, high-performance teams, problem-solving seminars, better understanding of the relationship between science and policy, public education and policy, and a host of other leadership-improvement techniques that have proven useful in other settings. The leaders of Yellowstone today have an opportunity, particularly the GYCC in its unique role as a high-level, interagency committee, to close this gap as effectively, efficiently, and equitably as possible. Thus, the model of a healthy greater Yellowstone ecosystem guided by enlightened management policy is a widely popular idea and leaders can build the necessary coalitions, overcome dissension, and integrate fragmentation into a vision and action that moves us all toward sustainability.
Brenna Reinhart Byrd and Andrew Miles Byrd
- Published in print:
- 2020
- Published Online:
- October 2020
- ISBN:
- 9780198829874
- eISBN:
- 9780191868351
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780198829874.003.0012
- Subject:
- Linguistics, Applied Linguistics and Pedagogy, Sociolinguistics / Anthropological Linguistics
Traditionally, to even begin studying Proto-Indo-European (PIE), one must have many years of experience with one (or multiple) ancient Indo-European (IE) languages. Yet, the dwindling number of ...
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Traditionally, to even begin studying Proto-Indo-European (PIE), one must have many years of experience with one (or multiple) ancient Indo-European (IE) languages. Yet, the dwindling number of students who meet these expectations makes teaching PIE at the undergraduate level an increasingly difficult task. This chapter proposes a unique solution: instructors should teach students a constructed language (conlang) version of PIE as a precursor to discussions on the individual surviving branches and the methodologies behind historical reconstruction. This approach was developed through the synergy of the authors’ experiences teaching a conlang version of PIE to actors for the video game Far Cry Primal, teaching PIE to undergraduate students at the University of Kentucky, and previous training in language pedagogy and transformative learning.Less
Traditionally, to even begin studying Proto-Indo-European (PIE), one must have many years of experience with one (or multiple) ancient Indo-European (IE) languages. Yet, the dwindling number of students who meet these expectations makes teaching PIE at the undergraduate level an increasingly difficult task. This chapter proposes a unique solution: instructors should teach students a constructed language (conlang) version of PIE as a precursor to discussions on the individual surviving branches and the methodologies behind historical reconstruction. This approach was developed through the synergy of the authors’ experiences teaching a conlang version of PIE to actors for the video game Far Cry Primal, teaching PIE to undergraduate students at the University of Kentucky, and previous training in language pedagogy and transformative learning.