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Zoekresultaten (16)

HBO/WO

MBO

1 februari 2021

Example of an analysis of a policy network

What is actor analysis? If you want to solve a complex problem or design a new policy it is important to know the playing field and to know who your friends are and who are the foes. You have to know the concerns and issues of other actors and you may need to take those into account when designing a strategy for problem solving. Who has the power to block your plans and whom you need to incorporate or involve in your work to generate social support for your policy or project. For effective policy analysis and policy design it is important to systematically explore the socio-political environment you are operating in. How to explore and map these social and political playing field for policy making is exactly what we will learn to do in this part of the course.

Website

Bert Enserink

1 februari 2021

Actor analysis, step 4

Step 4: Making an inventory of the problem formulations of the different actors by looking at their interests, objectives and perceptions. Concepts are defined, it is discussed how to do in-depth research and how to present the actor information in an chart and table. This means an elaboration and in depth research of the interests, objectives and means. There is need to do additional research: policy documents, annual reports, consulting experts in the field, interviewing spokespersons. Definition of objectives and interests is also defined in this chapter: Interests = fundamental objectives. Why actors want to achieve a specific goal. Deeply embedded in our personal values. Relatively stable over time. Objectives = goals that an actor wants to achieve in a concrete situation Perception = our worldview. Largely based on selective information and our social background and influenced by peer pressure. At the end of this step: make an overview table where you can see in one glance all the actors, their interests, objectives, the problem as they perceive it, its causes, the preferred solutions and their means.

Website

Bert Enserink

8 mei 2018

13-02: Applied research - micro lecture DECISION MAKING AND RESEARCH QUESTIONS

In this micro lecture the following items will be explained regarding this lecture: Clarifying the relationship between empirical research, decision making and design Empirical research questions are often asked in the context of decisionmaking and design ‘How to’ questions can be ‘broken up’ into empirical research questions

Website

Henk van der Kolk

8 mei 2018

01-05: Research question - micro lecture DECISION MAKING AND RESEARCH QUESTIONS

In this micro lecture the following items will be explained regarding this lecture: Clarifying the relationship between empirical research, decision making and design. Empirical research questions are often asked in the context of decisionmaking and design. 'How to' questions can be 'broken up ' into empirical research questions

Website

Henk van der Kolk

8 mei 2018

03-14: Theory - ASSIGNMENT 1: WHAT IS EMPIRICAL RESEARCH?

In this assignment the following items will be discussed: In this assignment, you will practice with all aspects of the wheel of science, you will also familiarize yourself with the basic aspects of decision making and with the relationship between decision making and research.

Document

Henk van der Kolk

8 mei 2018

14-03: Philosophy of science- ASSIGNMENT 1: WHAT IS EMPIRICAL RESEARCH?

In this assignment the following items will be explained regarding this assignment: In this assignment, you will practice with all aspects of the wheel of science, you will also familiarize yourself with the basic aspects of decision making and with the relationship between decision making and research.

Document

Henk van der Kolk

8 mei 2018

13-03: Applied research- ASSIGNMENT 1: WHAT IS EMPIRICAL RESEARCH?

In this assignment the following items will be explained regarding this assignment: In this assignment, you will practice with all aspects of the wheel of science, you will also familiarize yourself with the basic aspects of decision making and with the relationship between decision making and research

Document

Henk van der Kolk

8 mei 2018

01-13: Research question - Assignment 1: What is empirical research

In this micro lecture the following items will be explained regarding this lecture: Assignmet 1: What is empirical research

Document

Henk van der Kolk

14 mei 2023

ChatGPT-and-Artificial-Intelligence-in-higher-education-Quick-Start-guide

Advies van Unesco over inzet van AI in onderwijs.

Wo, HboDocument

Unesco

17 september 2024

Dynamic data processing: Recursive least-squares

This book is a follow-up on Adjustment theory. It extends the theory to the case of time-varying parameters with an emphasis on their recursive determination. Least-squares estimation will be the leading principle used. A least-squares solution is said to be recursive when the method of computation enables sequential, rather than batch, processing of the measurement data. The recursive equations enable the updating of parameter estimates for new observations without the need to store all past observations. Methods of recursive least-squares estimation are therefore particularly useful for applications in which the time-varying parameters need to be instantly determined. Important examples of such applications can be found in the fields of real-time kinematic positioning, navigation and guidance, or multivariate time series analysis. The goal of this book is therefore to convey the necessary knowledge to be able to process sequentially collected measurements for the purpose of estimating time-varying parameters. When determining time-varying parameters from sequentially collected measurement data, one can discriminate between three types of estimation problems: filtering, prediction and smoothing. Filtering aims at the determination of current parameter values, while smoothing and prediction aim at the determination of respectively past and future parameter values. The emphasis in this book will be on recursive least-squares filtering. The theory is worked out for the important case of linear(ized) models. The measurement-update and time-update equations of recursive least-squares are discussed in detail. Models with sequentially collected data, but time-invariant parameters are treated first. In this case only the measurement-update equations apply. State-space models for dynamic systems are discussed so as to include time-varying parameters. This includes their linearization and the construction of the state transition matrix. Elements from the theory of random functions are used to describe the propagation laws for linear dynamic systems. The theory is illustrated by means of many worked out examples. They are drawn from applications such as kinematic positioning, satellite orbit determination and inertial navigation.

Open (Access) Tekst Boek

Peter Teunissen