This is a presentation held by IEA DSM Task 24 Operating Agent, Dr Sea Rotmann in Graz, October 13, 2014. It presents some of the main findings of Dr Ruth Mourik's Subtask 3 report 'Did you behave as we designed you to?'.
Building Web Scale Apps with Docker and Mesos by Alex Rukletsov (Mesosphere)Docker, Inc.
Operating apps at web scale has become the new normal, but has been out of reach for most companies. Join us as we show you how to deploy and manage your Docker containers at scale. See how easy it is to build highly-available, fault-tolerant web scale apps using Docker with the Mesos cluster scheduler. Docker plus Mesos is a new way to scale applications. Together they give you capabilities similar to Google’s Borg, the Googleplex’s secret weapon of scalability and fault tolerance.
Your employees want a bigger piece of the pie. You want to attract and retain top talent while motivating employees to perform at their best. In this webinar, PayScale and BambooHR experts guide you to create a compensation plan that's a win/win for both you and your employees.
Building Web Scale Apps with Docker and Mesos by Alex Rukletsov (Mesosphere)Docker, Inc.
Operating apps at web scale has become the new normal, but has been out of reach for most companies. Join us as we show you how to deploy and manage your Docker containers at scale. See how easy it is to build highly-available, fault-tolerant web scale apps using Docker with the Mesos cluster scheduler. Docker plus Mesos is a new way to scale applications. Together they give you capabilities similar to Google’s Borg, the Googleplex’s secret weapon of scalability and fault tolerance.
Your employees want a bigger piece of the pie. You want to attract and retain top talent while motivating employees to perform at their best. In this webinar, PayScale and BambooHR experts guide you to create a compensation plan that's a win/win for both you and your employees.
Six Sigma ReportHammettSix Sigma DMAIC Project Report Templa.docxwhitneyleman54422
Six Sigma Report
HammettSix Sigma DMAIC Project Report Template
Comments
· The following template provides guidelines for preparing a Six Sigma written certification project report. Subheadings and length of each section will obviously vary based on your findings and writing style. For a complete sample report using the template, see “Sample Project Report”.
· The information in your report should follow the Six-Sigma Problem Solving Methodology DMAIC. This includes a description of the project, key points in the problem-solving process, and detailed support for your conclusions and any recommendations. Reports should be approximately 10-12 double-spaced pages (excluding appendices), including tables and figures.
· Some general guidelines for grammar and format are provided for your reference at the end.
· Some information contained in this template is repetitive across sections. However, since different audiences will read your report to various degrees of depth, we believe that it is essential to repeat certain information. Ultimately, you should produce a high quality, professionally-presented report that has sufficient detail to help other Six Sigma practitioners utilize and build upon your project findings.
Title of Report
Submitted to:
Name, Title
Department/Organization
Address (optional)
Prepared by:
Name, Title
Department/Organization
Address (optional)
Date Submitted
Note: Do not put a page number on your title page. Begin numbering the pages with the Executive Summary.
Executive Summary
The Executive Summary presents the major information contained in the report. Its readers are typically managers who need a broad understanding of the project and how it fits into a coherent whole. These readers do not need or want a detailed understanding of the various steps taken to complete your project. Therefore, the Executive Summary allows readers to learn the gist of the report without reading the entire document, to determine whether the report is relevant to their needs, or to get an overview before focusing on the details. We consider writing a concise (typically one-page) and comprehensive executive summary a critical element of a Six Sigma project report. TheExecutive Summary should NOT include terms, abbreviations, or symbols unfamiliar to the reader. Readers should understand the content of the Executive Summary without reading the rest of the report.
The Executive Summary should include a problem statement, summary of approach used, and major project findings and recommendations.
· Problem Statement / Description
· Concisely describe the problem (few sentences).
· Identify the time period of the problem
· Quantify the degree of the problem and its impact on the business (if possible).
Example: During the past year, the average # of incoming calls with complaints per card-year has increased by 20%. These additional calls have resulted in additional staffing and facility costs of ~$100K per year. This proj.
Foods Case Study
What to cover
Executive summary
Define Phase
Measure Phase
Analyze phase
Improve phase
Control Phase
Conclusion
1. Executive Summary
In December 2008, the company began to receive heavy surcharge from local authorities because of their poor water quality, mainly due to an excess of biological waste entering the sewer system.
Biological Oxygen Demand (BOD) The amount of oxygen needed by bacteria to decompose all the solid wastes in wastewater. Accounted for 74% of the resulting fees. The total bill for poor water quality reached $204,000 in 2009.
A six-sigma team was tasked to extremely reduce the BOD, after 6 months they reached 70% with a goal of 95%.
2. Define Phase
Project Charter
Project NameBOD Reduction at Kahiki FoodsCommencement DateSep, 2009Project SponsorKahiki FoodsCompletion DateDec, 2010Expected Hard Cost Reduction$195,000Expected % Reduction95%
Project Mission
The main objectives are:
Intense reduction in solid waste entering floor drains.
Increase output at different plant processes.
Green initiative for the organization.
$195,000 hard cost reduction.
Problem Statement
Per local authorities BOD levels shouldn’t exceed 250mg/L
Kahiki had BOD waste levels of 3864mg/L, 1546% higher than upper spec limit
The source of the waste was obviously originating from inefficient floor drain management
6
Goal Statement
At least a 50% BOD reduction in 6 months and establishing a sustainable system able of reaching the goal of 95% reduction.
Process map
SIPOC map
8
3. Measure Phase
The waste removal system doesn't meet the spec.
Process Capability Charts
Measurement Plan
Demand Analysis
Metrics Used To Determine Water Quality
Biological Oxygen Demand (BOD)
Total Suspended Solids (TSS)
Total Kjeldahl Nitrogen (TKN)
BOD Process Capability Charts
TSS Process Capability Charts
Measurement Plan
N/B In any area of concern, should there be a negative response on any unit, the unit is rendered incomplete and therefore a defect.
13
Data Collection Challenges
System changed in 2007.
Standard sampling schedule 3 site visits/year moved to monthly.
Data collection visibility most critical points came from cleanup shift.
The above assessment was done by five individuals who were, one hired external expert, two quality assurance officers at the state government, while two are community professionals. MSA is an experimental process and require more views from different quotas of different levels of understanding to make independent judgments on quality (McCarty, 2005).
14
4. Analyze Phase
5 Why Analysis.
FMEA.
Gap analysis.
Fishbone diagram.
Hotspot heat map.
Regression Analysis.
Benchmarking.
5 Why Analysis
Plant Floor Drain Hotspot Heat Map
5. Improve phase
Improved Solid/Liquid Separation.
Reducing Waste Creation.
Employee Training.
Best Practice Identification.
WAP Committee: A "Waste Awareness Program“.
Error Proofing: Adding visual S ...
The tasks You are assumed to be one of the software consultants .docxsarah98765
The tasks
You are assumed to be one of the software consultants appointed to shoulder the system analysis responsibilities in, the project outlined in, the case study. You will plan and manage the project as well as investigate and document its system requirements. You will produce a report that discusses this project based on your understanding of it and the related investigation results through the tasks below.
Task 1:
Approaches to Systems Development • How would you go about developing Hospital Information System? Compare different Software Development approaches to consider the best suited for developing HIS. • Justify the choice of your selected approach to systems development.
Task 2: Systems Requirements • What are the primary functional requirements for the system in the case study? List and discuss
Length: 2000 words
these requirements. • What are the non-functional requirements for the system in the case study? List and discuss these non-functional requirements. Justify the choice of your non-functional requirements
Task 3: Project Cost Benefit Analysis • Discuss your project Cost Benefit Analysis (CBA). CBA should focus the following two main points: a. To determine if an investment (or decision) is sound, ascertaining if – and by how much – its benefits outweigh its costs; and b. To provide a basis for comparing investments (or decisions), comparing the total expected cost of each option with its total expected benefits. • Provide an excel spread sheet with details in a Project Cost Benefit Analysis.
Task 4:) Project Schedule • Show a work breakdown structure and a project schedule as a Gantt Chart. Explain both of them and discuss how they relate to each other.
• Given the system goals, requirements, and scope as they are currently understood, is the project schedule reasonable? Why or why not?
Task 5: System Information Requirement Investigation Techniques • Who are the stakeholders involved? • Explain your choice of the 3 most useful investigation techniques. • Justify the usefulness of these 3 investigation techniques.
Information Systems Analysis and Design
Assessment - Systems Development
Lecturer: Lecturer Name
Tutor: Tutor Name
Prepared by:
Student Name
Student Number
Table of Contents (TOC)
Insert a word generated table of contents here
How to create a table of contents in Microsoft Word
1. Apply the built-in Heading styles to the headings in your text.
2. In Word 2007 and Word 2010: References > Table of Contents > choose an option from the menu.
1. Introduction
Add your contents here.
Note: In this section, you provide a clear definition of the aims of this report. You also identify the project objectives. Explain all findings in the reporting document.
2. Approach to Systems Development
Please add your contents here. There are many approaches to Systems development such as Water fall SDLC, Agile, RAD JAD. etc. You need to clearly explain which .
Here is a presentation to New Zealand stakeholders of the completed findings of the International Energy Agency's DSM Programme's Task 24 Phase 1 called 'Closing the Loop - Behaviour Change in DSM: From Theory to Practice'
Is just moving IT from CapEX to OpEx a huge benefit?
Does “IT as a cloud commodity services” changes IT Role and Responsibility?
How do you get a real overall lower TCO?
With a growth in interest in ‘big data’ as electric grids evolve and data sources become more common and more productive, there needs to be a discussion of the management of data in a secure manner, and the role of analytics to provide information and have ‘meaning’. This paper looks at a number of challenges that are beginning to be faced, and opportunities to ensure that the Future Grid is secure. Challenge 1 is the management of ‘big data’, which may provide value if appropriately viewed and analyzed; Challenge 2 is the management of security, for both data and systems which use the data; Challenge 3 is the need for appropriate urgency in analysis and action; Challenge 4 is to understand the meaning of the data and associated analyses, but also to understand the limits of our understanding.
TierPoint white paper_How_to_Position_Cloud_ROI_2015sllongo3
Traditional ROI calculators do an ineffective job of measuring the value of cloud services. This white paper serves as a guide to calculating cloud ROI using seven metrics you may not have considered.
Our Task 24 talk presenting the exciting CHS hospital building manager pilot at the Behavior, Energy & Climate Change conference in Sacramento, October 2017
This workshop followed the Energy Cultures conference and was designed to showcase how different models of understanding behaviour worked in practice, how to better use storytelling and how to collectively design a behavioural intervention.
Six Sigma ReportHammettSix Sigma DMAIC Project Report Templa.docxwhitneyleman54422
Six Sigma Report
HammettSix Sigma DMAIC Project Report Template
Comments
· The following template provides guidelines for preparing a Six Sigma written certification project report. Subheadings and length of each section will obviously vary based on your findings and writing style. For a complete sample report using the template, see “Sample Project Report”.
· The information in your report should follow the Six-Sigma Problem Solving Methodology DMAIC. This includes a description of the project, key points in the problem-solving process, and detailed support for your conclusions and any recommendations. Reports should be approximately 10-12 double-spaced pages (excluding appendices), including tables and figures.
· Some general guidelines for grammar and format are provided for your reference at the end.
· Some information contained in this template is repetitive across sections. However, since different audiences will read your report to various degrees of depth, we believe that it is essential to repeat certain information. Ultimately, you should produce a high quality, professionally-presented report that has sufficient detail to help other Six Sigma practitioners utilize and build upon your project findings.
Title of Report
Submitted to:
Name, Title
Department/Organization
Address (optional)
Prepared by:
Name, Title
Department/Organization
Address (optional)
Date Submitted
Note: Do not put a page number on your title page. Begin numbering the pages with the Executive Summary.
Executive Summary
The Executive Summary presents the major information contained in the report. Its readers are typically managers who need a broad understanding of the project and how it fits into a coherent whole. These readers do not need or want a detailed understanding of the various steps taken to complete your project. Therefore, the Executive Summary allows readers to learn the gist of the report without reading the entire document, to determine whether the report is relevant to their needs, or to get an overview before focusing on the details. We consider writing a concise (typically one-page) and comprehensive executive summary a critical element of a Six Sigma project report. TheExecutive Summary should NOT include terms, abbreviations, or symbols unfamiliar to the reader. Readers should understand the content of the Executive Summary without reading the rest of the report.
The Executive Summary should include a problem statement, summary of approach used, and major project findings and recommendations.
· Problem Statement / Description
· Concisely describe the problem (few sentences).
· Identify the time period of the problem
· Quantify the degree of the problem and its impact on the business (if possible).
Example: During the past year, the average # of incoming calls with complaints per card-year has increased by 20%. These additional calls have resulted in additional staffing and facility costs of ~$100K per year. This proj.
Foods Case Study
What to cover
Executive summary
Define Phase
Measure Phase
Analyze phase
Improve phase
Control Phase
Conclusion
1. Executive Summary
In December 2008, the company began to receive heavy surcharge from local authorities because of their poor water quality, mainly due to an excess of biological waste entering the sewer system.
Biological Oxygen Demand (BOD) The amount of oxygen needed by bacteria to decompose all the solid wastes in wastewater. Accounted for 74% of the resulting fees. The total bill for poor water quality reached $204,000 in 2009.
A six-sigma team was tasked to extremely reduce the BOD, after 6 months they reached 70% with a goal of 95%.
2. Define Phase
Project Charter
Project NameBOD Reduction at Kahiki FoodsCommencement DateSep, 2009Project SponsorKahiki FoodsCompletion DateDec, 2010Expected Hard Cost Reduction$195,000Expected % Reduction95%
Project Mission
The main objectives are:
Intense reduction in solid waste entering floor drains.
Increase output at different plant processes.
Green initiative for the organization.
$195,000 hard cost reduction.
Problem Statement
Per local authorities BOD levels shouldn’t exceed 250mg/L
Kahiki had BOD waste levels of 3864mg/L, 1546% higher than upper spec limit
The source of the waste was obviously originating from inefficient floor drain management
6
Goal Statement
At least a 50% BOD reduction in 6 months and establishing a sustainable system able of reaching the goal of 95% reduction.
Process map
SIPOC map
8
3. Measure Phase
The waste removal system doesn't meet the spec.
Process Capability Charts
Measurement Plan
Demand Analysis
Metrics Used To Determine Water Quality
Biological Oxygen Demand (BOD)
Total Suspended Solids (TSS)
Total Kjeldahl Nitrogen (TKN)
BOD Process Capability Charts
TSS Process Capability Charts
Measurement Plan
N/B In any area of concern, should there be a negative response on any unit, the unit is rendered incomplete and therefore a defect.
13
Data Collection Challenges
System changed in 2007.
Standard sampling schedule 3 site visits/year moved to monthly.
Data collection visibility most critical points came from cleanup shift.
The above assessment was done by five individuals who were, one hired external expert, two quality assurance officers at the state government, while two are community professionals. MSA is an experimental process and require more views from different quotas of different levels of understanding to make independent judgments on quality (McCarty, 2005).
14
4. Analyze Phase
5 Why Analysis.
FMEA.
Gap analysis.
Fishbone diagram.
Hotspot heat map.
Regression Analysis.
Benchmarking.
5 Why Analysis
Plant Floor Drain Hotspot Heat Map
5. Improve phase
Improved Solid/Liquid Separation.
Reducing Waste Creation.
Employee Training.
Best Practice Identification.
WAP Committee: A "Waste Awareness Program“.
Error Proofing: Adding visual S ...
The tasks You are assumed to be one of the software consultants .docxsarah98765
The tasks
You are assumed to be one of the software consultants appointed to shoulder the system analysis responsibilities in, the project outlined in, the case study. You will plan and manage the project as well as investigate and document its system requirements. You will produce a report that discusses this project based on your understanding of it and the related investigation results through the tasks below.
Task 1:
Approaches to Systems Development • How would you go about developing Hospital Information System? Compare different Software Development approaches to consider the best suited for developing HIS. • Justify the choice of your selected approach to systems development.
Task 2: Systems Requirements • What are the primary functional requirements for the system in the case study? List and discuss
Length: 2000 words
these requirements. • What are the non-functional requirements for the system in the case study? List and discuss these non-functional requirements. Justify the choice of your non-functional requirements
Task 3: Project Cost Benefit Analysis • Discuss your project Cost Benefit Analysis (CBA). CBA should focus the following two main points: a. To determine if an investment (or decision) is sound, ascertaining if – and by how much – its benefits outweigh its costs; and b. To provide a basis for comparing investments (or decisions), comparing the total expected cost of each option with its total expected benefits. • Provide an excel spread sheet with details in a Project Cost Benefit Analysis.
Task 4:) Project Schedule • Show a work breakdown structure and a project schedule as a Gantt Chart. Explain both of them and discuss how they relate to each other.
• Given the system goals, requirements, and scope as they are currently understood, is the project schedule reasonable? Why or why not?
Task 5: System Information Requirement Investigation Techniques • Who are the stakeholders involved? • Explain your choice of the 3 most useful investigation techniques. • Justify the usefulness of these 3 investigation techniques.
Information Systems Analysis and Design
Assessment - Systems Development
Lecturer: Lecturer Name
Tutor: Tutor Name
Prepared by:
Student Name
Student Number
Table of Contents (TOC)
Insert a word generated table of contents here
How to create a table of contents in Microsoft Word
1. Apply the built-in Heading styles to the headings in your text.
2. In Word 2007 and Word 2010: References > Table of Contents > choose an option from the menu.
1. Introduction
Add your contents here.
Note: In this section, you provide a clear definition of the aims of this report. You also identify the project objectives. Explain all findings in the reporting document.
2. Approach to Systems Development
Please add your contents here. There are many approaches to Systems development such as Water fall SDLC, Agile, RAD JAD. etc. You need to clearly explain which .
Here is a presentation to New Zealand stakeholders of the completed findings of the International Energy Agency's DSM Programme's Task 24 Phase 1 called 'Closing the Loop - Behaviour Change in DSM: From Theory to Practice'
Is just moving IT from CapEX to OpEx a huge benefit?
Does “IT as a cloud commodity services” changes IT Role and Responsibility?
How do you get a real overall lower TCO?
With a growth in interest in ‘big data’ as electric grids evolve and data sources become more common and more productive, there needs to be a discussion of the management of data in a secure manner, and the role of analytics to provide information and have ‘meaning’. This paper looks at a number of challenges that are beginning to be faced, and opportunities to ensure that the Future Grid is secure. Challenge 1 is the management of ‘big data’, which may provide value if appropriately viewed and analyzed; Challenge 2 is the management of security, for both data and systems which use the data; Challenge 3 is the need for appropriate urgency in analysis and action; Challenge 4 is to understand the meaning of the data and associated analyses, but also to understand the limits of our understanding.
TierPoint white paper_How_to_Position_Cloud_ROI_2015sllongo3
Traditional ROI calculators do an ineffective job of measuring the value of cloud services. This white paper serves as a guide to calculating cloud ROI using seven metrics you may not have considered.
Our Task 24 talk presenting the exciting CHS hospital building manager pilot at the Behavior, Energy & Climate Change conference in Sacramento, October 2017
This workshop followed the Energy Cultures conference and was designed to showcase how different models of understanding behaviour worked in practice, how to better use storytelling and how to collectively design a behavioural intervention.
Dr Aimee Ambrose, IEA DSM Task 24 UK expert, gave this fascinating presentation on principal agent issues in private sector landlords in New Zealand vs the UK
We were lucky to have Dr Katy Janda, from Oxford University, at our Swedish Task 24 workshop. She presented her findings on green leases in Australia and the UK
IEA DSM Task 24 on behaviour change presented their latest findings and exciting new work in Phase 2 to the Queensland Government on December 18, 2016.
Dr Sea Rotmann, Task 24 Operating Agent, gave a very in-depth presentation on everything energy & behaviour change from the many findings of Phase I of the Task to an audience of policymakers, researchers, community leaders and industry in Toronto, on May 27, 2015.
Barry Goodchild, of Sheffield Hallam University, gave this presentation on the theory of storytelling in urban planning at the IEA DSM Task 24 workshop on behaviour change in Graz, October 14, 2014.
This presentation was given by IEA DSM Task 24 Operating Agent, Dr Sea Rotmann at the Task 24 workshop in Graz, October 13, 2014. It describes the many different ways storytelling is being used in Task 24, some learnings and successes.
Corinne Moser, one of our Swiss IEA DSM Task 24 national experts from ZHAW, gave a presentation on the Subtask 2 Swiss Case Study called the '2000 Watt Society' in our October 13, 2014 Graz workshop.
Aimee Ambrose, our UK IEA DSM Task 24 expert from Sheffield Hallam University, gave a great Pecha Kucha presentation on their EcoHome case study in our workshop in Graz, October 13, 2014.
Henrik Karlstrøm, our Norwegian IEA DSM Task 24 expert, presented the amazing Finnfjord case study which shows that even the most polluting of industries can turn into good news stories. As told to the IEA DSM Task 24 workshop in Graz, Austria October 13, 2014.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptxRASHMI M G
Abnormal or anomalous secondary growth in plants. It defines secondary growth as an increase in plant girth due to vascular cambium or cork cambium. Anomalous secondary growth does not follow the normal pattern of a single vascular cambium producing xylem internally and phloem externally.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
The Evolution of Science Education PraxiLabs’ Vision- Presentation (2).pdfmediapraxi
The rise of virtual labs has been a key tool in universities and schools, enhancing active learning and student engagement.
💥 Let’s dive into the future of science and shed light on PraxiLabs’ crucial role in transforming this field!
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
BREEDING METHODS FOR DISEASE RESISTANCE.pptxRASHMI M G
Plant breeding for disease resistance is a strategy to reduce crop losses caused by disease. Plants have an innate immune system that allows them to recognize pathogens and provide resistance. However, breeding for long-lasting resistance often involves combining multiple resistance genes
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...
Evaluating Behaviour Change
1. IEA DSM Implementing Agreement
Subtasks of Task XXIV
Task 24
‘Subtask 3- monitoring and
evaluating ‘behaviour’ change
Dr Sea Rotmann,
Graz Task 24 workshop, October 14, 2014
2. SubtaSskusb otf aTsaksks XXIV
5- Social Media Expert platform
1- Helicopter
view of models,
frameworks,
contexts, case
studies and
evaluation
metrics
2-
In depth
analysis in
areas of
greatest need
(buildings,
transport,
SMEs, smart
metering)
3-
Evaluation tool
for
stakeholders
4-
Country-specific
recommen-dations,
to do’s
and not to do’s
3. SubtaSskusb otf aTsaksks XXIV
5- Social Media Expert platform
1- Helicopter
view of models,
frameworks,
contexts, case
studies and
evaluation
metrics
2-
In depth
analysis in
areas of
greatest need
(buildings,
transport,
SMEs, smart
metering)
3-
Evaluation tool
for
stakeholders
4-
Country-specific
recommen-dations,
to do’s
and not to do’s
3-
Evaluation tool for
stakeholders
4. subtask III -
Subtask I - Pre mHiesleic fooprt Tera sOkv XerXvIiVew
evaluation
WHAT IS A SUCCESSFUL LONG-TERM
BEHAVIOUR CHANGE OUTCOME TO YOU?
3
5. Subtask I - Pre mHiesleic fooprt Tera sOkv XerXvIiVew Subtask III: Outputs
indicators19 such as number of installed installations or KWh saved potentially are not even
a real proxy; minor savings might involve most intensive behaviour changes whilst major
savings might have been the result of a relatively isolated behaviour change, e.g. buying
and installing a new heating system or LED lighting. 20
x A last point is that if only modelled savings are calculated, and real savings are not meeting
these calculations, the uptake and acceptance of the involved technologies, e.g. passive
houses, or services such as energy performance contracting will face serious problems
(Batey, Mourik and Garcia 2013).
x See below an illustrative picture that demonstrates quite clearly why a proxy such as
savings or KWh reduction is unable to explain the why and how of behaviour change.
4
6. Subtask I - Pre mHiesleic fooprt Tera sOkv XerXvIiVew Subtask III: Outputs
indicators19 such as number of installed installations or KWh saved potentially are not even
a real proxy; minor savings might involve most intensive behaviour changes whilst major
savings might have been the result of a relatively isolated behaviour change, e.g. buying
and installing a new heating system or LED lighting. 20
x A last point is that if only modelled savings are calculated, and real savings are not meeting
these calculations, the uptake and acceptance of the involved technologies, e.g. passive
houses, or services such as energy performance contracting will face serious problems
(Batey, Mourik and Garcia 2013).
x See below an illustrative picture that demonstrates quite clearly why a proxy such as
savings or KWh reduction is unable to explain the why and how of behaviour change.
4
7. Subtask I - Pre mHiesleic fooprt Tera sOkv XerXvIiVew Subtask III: Outputs
- Individual evaluation and monitoring metrics for each domain in
the Subtask I Monster/Wiki, plus separate report
indicators19 such as number of installed installations or KWh saved potentially are not even
a real proxy; minor savings might involve most intensive behaviour changes whilst major
savings might have been the result of a relatively isolated behaviour change, e.g. buying
and installing a new heating system or LED lighting. 20
x A last point is that if only modelled savings are calculated, and real savings are not meeting
these calculations, the uptake and acceptance of the involved technologies, e.g. passive
houses, or services such as energy performance contracting will face serious problems
(Batey, Mourik and Garcia 2013).
x See below an illustrative picture that demonstrates quite clearly why a proxy such as
savings or KWh reduction is unable to explain the why and how of behaviour change.
4
8. Subtask I - Pre mHiesleic fooprt Tera sOkv XerXvIiVew Subtask III: Outputs
- Individual evaluation and monitoring metrics for each domain in
the Subtask I Monster/Wiki, plus separate report
- An overview and some recommendations on monitoring and
evaluation can be found in Subtask III report ‘Did you behave as
we designed you intdoicat?or’s19 such as number of installed installations or KWh saved potentially are not even
a real proxy; minor savings might involve most intensive behaviour changes whilst major
savings might have been the result of a relatively isolated behaviour change, e.g. buying
and installing a new heating system or LED lighting. 20
x A last point is that if only modelled savings are calculated, and real savings are not meeting
these calculations, the uptake and acceptance of the involved technologies, e.g. passive
houses, or services such as energy performance contracting will face serious problems
(Batey, Mourik and Garcia 2013).
x See below an illustrative picture that demonstrates quite clearly why a proxy such as
savings or KWh reduction is unable to explain the why and how of behaviour change.
4
9. Subtask I - Pre mHiesleic fooprt Tera sOkv XerXvIiVew Subtask III: Outputs
- Individual evaluation and monitoring metrics for each domain in
the Subtask I Monster/Wiki, plus separate report
- An overview and some recommendations on monitoring and
evaluation can be found in Subtask III report ‘Did you behave as
we designed you to?’
indicators19 such as number of installed installations or KWh saved potentially are not even
a real proxy; minor savings might involve most intensive behaviour changes whilst major
savings might have been the result of a relatively isolated behaviour change, e.g. buying
and installing a new heating system or LED lighting. 20
- There will also x be A last point a methodological is that if only modelled savings are calculated, review and real savings based are not meeting
these calculations, the uptake and acceptance of the involved technologies, e.g. passive
on ‘Beyond
kWh’ which will feed houses, or services such as energy performance contracting will face serious problems
(Batey, Mourik into and Garcia Subtask 2013).
IX
x See below an illustrative picture that demonstrates quite clearly why a proxy such as
savings or KWh reduction is unable to explain the why and how of behaviour change.
4
10. subtask III -
evaluation metrics
Subtask I - Pre mHiesleic fooprt Tera sOkv XerXvIiVew
Conventional monitoring of smart metering success More systemic monitoring of smart metering
5
success
x !"#$%&'()''*#+&,'#%,%&*'+!-'(&')%%-$+./'
0!,%&)+.%*'0!*,+11%-'
x 1(+-'*20),'3%&'.10%!,''
x !"#$%&'()',0#%*'.10%!,*'1((/%-'+,',2%'
)%%-$+./'3&(40-%-'
x +..%3,+!.%'+!-'+,,0,"-%*',(5+&-*'*#+&,'
#%,%&*'
x 61%.,&0.0,7'.(!*"#3,0(!'(4%&'+'7%+&'
x 1%4%1'()',%.2!(1(87'+))0!0,7'.(!.%&!0!8',2%'
"*%'()',2%',%.2!0.+1')%%-$+./'%9"03#%!,'
x +11'()',2%'0**"%*'10*,%-'1%),:'+!-',2(*%'
#%!,0(!%-'"!-%&'*7*,%#0.'&%,&()0,,0!8'
#(!0,(&0!8'31"*;
x <%&*(!+1'#(,04+,0(!',('3+&,0.03+,%'0!',2%'
.(#3%,0,0(!'
x =.,"+1'%!%&87>&%1+,%-'$%2+40("&*'
x ?%.%!,'3"&.2+*%*'0!'%!%&87',%.2!(1(80%*'
@10/%'%!%&87'%))0.0%!,'$(01%&*:'!%5'
50!-(5*:',%.AB'
x C2%'0!)(&#+,0(!'1%4%1'(!'%!%&87'%))0.0%!.7'
+!-'&%!%5+$1%'%!%&87'*("&.%*'
x D("&.%*'(!'0!)(&#+,0(!'(!'%!%&87'0**"%*'
x =,,0,"-%*'(!'%!%&87'+!-'.10#+,%'
3&(,%.,0(!'0**"%*'
x 6*,0#+,0(!'()',2%'1%4%1'()'(5!'%!%&87'.(*,*'
x $"01-0!8'()'.+3+.0,7:''
x .&%+,0(!'()'%!8+8%#%!,'
x ."*,(#%&'*%!,0#%!,:''
x 3+&,0.03+,0(!'0!'(,2%&'%!%&87'%))0.0%!.7'
3&(8&+#*'
x )%%10!8'()'.(!,&(1'@(4%&'%!%&87'$011*:',2%'
2(#%:'%!%&87B'
x 1%4%1'()'"!%#31(7#%!,:''
x 1%4%1'()'0110,%&+.7'
x E!,%&!%,'3%!%,&+,0(!'&+,%'
'
12. Life seemed easy…
What is it?
• Monitoring: measuring progress and achievements
and production of planned outputs
• Evaluation: structured process of assessing success in
meeting goals and reflect on learnings. Explicitly
places a value judgement on the data and information
gathered in an intervention
6
13. Life seemed easy…
What is it?
• Monitoring: measuring progress and achievements
and production of planned outputs
• Evaluation: structured process of assessing success in
meeting goals and reflect on learnings. Explicitly
places a value judgement on the data and information
gathered in an intervention
Why do it the way we do now?
Establish effect of policies
Assess need for improvements
Assessing value for money
Contribution to evidence base for effectiveness of
behavioral interventions at population level
6
14. Life seemed easy…
What is it?
• Monitoring: measuring progress and achievements
and production of planned outputs
• Evaluation: structured process of assessing success in
meeting goals and reflect on learnings. Explicitly
places a value judgement on the data and information
gathered in an intervention
Why do it the way we do now?
Establish effect of policies
Assess need for improvements
Assessing value for money
Contribution to evidence base for effectiveness of
behavioral interventions at population level
How to do it…….???
6
17. It’s getting challenging…
• Evaluation team often not included in design
• Often not even part of the programme…
7
18. It’s getting challenging…
• Evaluation team often not included in design
• Often not even part of the programme…
• Evaluation usually is only a snapshot at end or just after
7
19. It’s getting challenging…
• Evaluation team often not included in design
• Often not even part of the programme…
• Evaluation usually is only a snapshot at end or just after
• Often insufficient benchmarking
7
20. It’s getting challenging…
• Evaluation team often not included in design
• Often not even part of the programme…
• Evaluation usually is only a snapshot at end or just after
• Often insufficient benchmarking
• Not longitudinal, sustainability/rebound often not assessed
7
21. It’s getting challenging…
• Evaluation team often not included in design
• Often not even part of the programme…
• Evaluation usually is only a snapshot at end or just after
• Often insufficient benchmarking
• Not longitudinal, sustainability/rebound often not assessed
• No insight in formation of networks supporting lasting
change
7
22. It’s getting challenging…
• Evaluation team often not included in design
• Often not even part of the programme…
• Evaluation usually is only a snapshot at end or just after
• Often insufficient benchmarking
• Not longitudinal, sustainability/rebound often not assessed
• No insight in formation of networks supporting lasting
change
• Mismatch between needs of project managers s/h it is
aimed at
7
23. It’s getting challenging…
• Evaluation team often not included in design
• Often not even part of the programme…
• Evaluation usually is only a snapshot at end or just after
• Often insufficient benchmarking
• Not longitudinal, sustainability/rebound often not assessed
• No insight in formation of networks supporting lasting
change
• Mismatch between needs of project managers s/h it is
aimed at
• Large-scale M&E of actual behaviour too costly
7
24. It’s getting challenging…
• Evaluation team often not included in design
• Often not even part of the programme…
• Evaluation usually is only a snapshot at end or just after
• Often insufficient benchmarking
• Not longitudinal, sustainability/rebound often not assessed
• No insight in formation of networks supporting lasting
change
• Mismatch between needs of project managers s/h it is
aimed at
• Large-scale M&E of actual behaviour too costly
• Modeling or self-reported (at best)
7
25. It’s getting challenging…
• Evaluation team often not included in design
• Often not even part of the programme…
• Evaluation usually is only a snapshot at end or just after
• Often insufficient benchmarking
• Not longitudinal, sustainability/rebound often not assessed
• No insight in formation of networks supporting lasting
change
• Mismatch between needs of project managers s/h it is
aimed at
• Large-scale M&E of actual behaviour too costly
• Modeling or self-reported (at best)
• ‘proxies’, such as savings or even better: cost
7
effectiveness
26. It’s getting challenging…
• Evaluation team often not included in design
• Often not even part of the programme…
• Evaluation usually is only a snapshot at end or just after
• Often insufficient benchmarking
• Not longitudinal, sustainability/rebound often not assessed
• No insight in formation of networks supporting lasting
change
• Mismatch between needs of project managers s/h it is
aimed at
• Large-scale M&E of actual behaviour too costly
• Modeling or self-reported (at best)
• ‘proxies’, such as savings or even better: cost
7
effectiveness
• Proxies = NOT actual behaviour change, only about value
for money etc
27. It’s getting challenging…
• Evaluation team often not included in design
• Often not even part of the programme…
• Evaluation usually is only a snapshot at end or just after
• Often insufficient benchmarking
• Not longitudinal, sustainability/rebound often not assessed
• No insight in formation of networks supporting lasting
change
• Mismatch between needs of project managers s/h it is
aimed at
• Large-scale M&E of actual behaviour too costly
• Modeling or self-reported (at best)
• ‘proxies’, such as savings or even better: cost
7
effectiveness
• Proxies = NOT actual behaviour change, only about value
for money etc
• No participatory process or feedback loops in the
traditional M&E
29. To make life more difficult..
We increasingly value interventions that are:
• tailored,
• multidisciplinary,
• varied interventions,
• qualitative and iterative,
• systemic,
• and have outcomes beyond the duration of project and beyond energy
8
30. To make life more difficult..
We increasingly value interventions that are:
• tailored,
• multidisciplinary,
• varied interventions,
• qualitative and iterative,
• systemic,
• and have outcomes beyond the duration of project and beyond energy
And at the same time we judge the ‘behaviour’ of policymakers
who demand for simple, focused, quantitative and up-scaled
evaluations defining success in efficiency and effectiveness
terms.
8
31. To make life more difficult..
We increasingly value interventions that are:
• tailored,
• multidisciplinary,
• varied interventions,
• qualitative and iterative,
• systemic,
• and have outcomes beyond the duration of project and beyond energy
And at the same time we judge the ‘behaviour’ of policymakers
who demand for simple, focused, quantitative and up-scaled
evaluations defining success in efficiency and effectiveness
terms.
But how could M&E look like that is:
8
32. To make life more difficult..
We increasingly value interventions that are:
• tailored,
• multidisciplinary,
• varied interventions,
• qualitative and iterative,
• systemic,
• and have outcomes beyond the duration of project and beyond energy
And at the same time we judge the ‘behaviour’ of policymakers
who demand for simple, focused, quantitative and up-scaled
evaluations defining success in efficiency and effectiveness
terms.
But how could M&E look like that is:
Relevant to end-users, ‘cost effective’, doable, lasting actual behavioral
change, formation of networks, focusing on alignment, and processes
underpinning that change?
8
34. What now?
• No unified way of designing and M&E interventions
• Different disciplinary approaches have different methods
and foci of M&E, all pertinent to what they aim
9
35. How do different behavioural
models/disciplines evaluate?
1. Economic theory: individuals’ behaviours are seen as (semi-)
rational decisions that are made through cost-benefit calculations.
II. Psychological theory: the individual also takes a central
role; however, it is increasingly acknowledged that this individual
also operates as part of a collective e.g. by imitating the behaviour
of important others. Many psychological approaches view decision
making of an individual as a mental calculation aimed at making
choices; these calculations are informed by both emotion and cold
calculus.
III. Sociological theory: they put more emphasis on the
importance of the social nature of energy use and to the abilities of
people to participate in change in ways that fit their own contexts
and concerns. The central focus is on social practices, individuals
move into the background.
10
36. How do different behavioural
models/disciplines evaluate?
Intervention goals and evaluation methodologies commonly used in interventions underpinned by
the three disciplines discussed above are shown in the table below (this is not an extensive list, it
is aimed at highlighting foci and differences).
Goals 14 Methodologies Remarks (e.g. about causal
11
relationships)
Economic perspectives
Outputs
Cost-efficiency and
effectiveness
Units, and proxies e.g.
number of participants,
home insulated,
technologies installed, KWh
saved etc.
Labels
Modelling
Surveys
Experiments
Randomised control trials
Presence of cause Æ effect
relationship.
Aim is to meet a priori set goals
Monitoring and evaluation often
only for duration of
implementation, no longer term
Psychological perspectives
Outputs
Cost-efficiency and
effectiveness
Behavioural changes
Surveys
self-reported behavioural
changes
structured interviews
randomised control trials
Surveys to identify behavioural
determinants like motivations,
attitudes, etc.
Cause-effect relationships:
Effect on individuals of a
particular incentive, via e.g.
awareness, attitude, behaviour.
Interfering variables like social
context often not taken into
account
Sociological perspectives
Outputs and Outcomes
Cost-efficiency and
effectiveness
Learning about what works,
when, where, who, how
(long) and why
Learning about
interdependencies
Learning about co-shaping
and reshaping
User accounts
Time diaries
Cultural probes
In-depth open interviews
Analysis of fit of interventions
with daily life
measuring real, not modelled
energy consumption
Context & mechanism/conditions
produce an outcome.
Direct cause-effect relationships
hard to establish because of
interdependencies that cannot
be analysed separately.
14 We will also insert a column on the underlying processes - how does an intervention work, admittedly typically at the individual
level (what changed in people's understanding, motivations, attitudes)!
38. What now?
• Perhaps more fruitful to focus on learning processes*?
1. Single loop = instrumental, focused on short-term
learning about effectiveness in meeting goals/
outcome focused
12
39. What now?
• Perhaps more fruitful to focus on learning processes*?
1. Single loop = instrumental, focused on short-term
learning about effectiveness in meeting goals/
outcome focused
2. Double loop = process oriented, focused on the
how and why, long-term learning
12
40. What now?
• Perhaps more fruitful to focus on learning processes*?
1. Single loop = instrumental, focused on short-term
learning about effectiveness in meeting goals/
outcome focused
2. Double loop = process oriented, focused on the
how and why, long-term learning
*Based on work by Prof Chrys Argyris, Psychological and Organisational Development
12
41. Single vs double-loop
learning
Single-loop learning involves connecting a strategy for action with a result. Eg, if an action we take yields
results that are different to what we expected, through single-loop learning, we will observe the results,
automatically take in feedback, and try a different approach. This cyclical process of applying a new strategy
to achieve an expected or desired outcome may occur several times and we may never succeed. Running out of
strategies may push us to re-evaluate the deeper governing variables that make us behave the ways we do. Re-evaluating
and reframing our goals, values and beliefs is a more complex way of processing information and
involves a more sophisticated way of engaging with an experience. This is called double-loop learning and
looks at consequences from a wider perspective.
13
2.
51. Way forward?
M and E of single-loop learning doable to undertake and fine for low-hanging
fruit and non-habitual change. Sees behavioural change interventions
more or less as linear cause and effect relationships (A+B=C:
Intervention A targeted on group B will cause the intended Change C)
15
52. Way forward?
M and E of single-loop learning doable to undertake and fine for low-hanging
fruit and non-habitual change. Sees behavioural change interventions
more or less as linear cause and effect relationships (A+B=C:
Intervention A targeted on group B will cause the intended Change C)
A change of focus amongst policymakers and funders towards allowing
experimentation with more systemic and messy real life interventions
that do not provide easily quantifiable and scalable information is a big
transition. It demands amongst others that policymakers appreciate that
these systemic interventions cannot be evaluated in terms of cause and
effect, but are the outcome of a complex process.
15
53. Way forward?
M and E of single-loop learning doable to undertake and fine for low-hanging
fruit and non-habitual change. Sees behavioural change interventions
more or less as linear cause and effect relationships (A+B=C:
Intervention A targeted on group B will cause the intended Change C)
A change of focus amongst policymakers and funders towards allowing
experimentation with more systemic and messy real life interventions
that do not provide easily quantifiable and scalable information is a big
transition. It demands amongst others that policymakers appreciate that
these systemic interventions cannot be evaluated in terms of cause and
effect, but are the outcome of a complex process.
Double-loop learning much more difficult but more relevant to our aims…? We
15
want to focus on:
54. Way forward?
M and E of single-loop learning doable to undertake and fine for low-hanging
fruit and non-habitual change. Sees behavioural change interventions
more or less as linear cause and effect relationships (A+B=C:
Intervention A targeted on group B will cause the intended Change C)
A change of focus amongst policymakers and funders towards allowing
experimentation with more systemic and messy real life interventions
that do not provide easily quantifiable and scalable information is a big
transition. It demands amongst others that policymakers appreciate that
these systemic interventions cannot be evaluated in terms of cause and
effect, but are the outcome of a complex process.
Double-loop learning much more difficult but more relevant to our aims…? We
15
want to focus on:
• Interaction
55. Way forward?
M and E of single-loop learning doable to undertake and fine for low-hanging
fruit and non-habitual change. Sees behavioural change interventions
more or less as linear cause and effect relationships (A+B=C:
Intervention A targeted on group B will cause the intended Change C)
A change of focus amongst policymakers and funders towards allowing
experimentation with more systemic and messy real life interventions
that do not provide easily quantifiable and scalable information is a big
transition. It demands amongst others that policymakers appreciate that
these systemic interventions cannot be evaluated in terms of cause and
effect, but are the outcome of a complex process.
Double-loop learning much more difficult but more relevant to our aims…? We
want to focus on:
• Interaction
• Participation quality
15
56. Way forward?
M and E of single-loop learning doable to undertake and fine for low-hanging
fruit and non-habitual change. Sees behavioural change interventions
more or less as linear cause and effect relationships (A+B=C:
Intervention A targeted on group B will cause the intended Change C)
A change of focus amongst policymakers and funders towards allowing
experimentation with more systemic and messy real life interventions
that do not provide easily quantifiable and scalable information is a big
transition. It demands amongst others that policymakers appreciate that
these systemic interventions cannot be evaluated in terms of cause and
effect, but are the outcome of a complex process.
Double-loop learning much more difficult but more relevant to our aims…? We
want to focus on:
• Interaction
• Participation quality
• Learning by doing and doing by learning
15
57. Way forward?
M and E of single-loop learning doable to undertake and fine for low-hanging
fruit and non-habitual change. Sees behavioural change interventions
more or less as linear cause and effect relationships (A+B=C:
Intervention A targeted on group B will cause the intended Change C)
A change of focus amongst policymakers and funders towards allowing
experimentation with more systemic and messy real life interventions
that do not provide easily quantifiable and scalable information is a big
transition. It demands amongst others that policymakers appreciate that
these systemic interventions cannot be evaluated in terms of cause and
effect, but are the outcome of a complex process.
Double-loop learning much more difficult but more relevant to our aims…? We
want to focus on:
• Interaction
• Participation quality
• Learning by doing and doing by learning
• Aligning
15
58. Way forward?
M and E of single-loop learning doable to undertake and fine for low-hanging
fruit and non-habitual change. Sees behavioural change interventions
more or less as linear cause and effect relationships (A+B=C:
Intervention A targeted on group B will cause the intended Change C)
A change of focus amongst policymakers and funders towards allowing
experimentation with more systemic and messy real life interventions
that do not provide easily quantifiable and scalable information is a big
transition. It demands amongst others that policymakers appreciate that
these systemic interventions cannot be evaluated in terms of cause and
effect, but are the outcome of a complex process.
Double-loop learning much more difficult but more relevant to our aims…? We
want to focus on:
• Interaction
• Participation quality
• Learning by doing and doing by learning
• Aligning
• Iteration
15
59. Way forward?
M and E of single-loop learning doable to undertake and fine for low-hanging
fruit and non-habitual change. Sees behavioural change interventions
more or less as linear cause and effect relationships (A+B=C:
Intervention A targeted on group B will cause the intended Change C)
A change of focus amongst policymakers and funders towards allowing
experimentation with more systemic and messy real life interventions
that do not provide easily quantifiable and scalable information is a big
transition. It demands amongst others that policymakers appreciate that
these systemic interventions cannot be evaluated in terms of cause and
effect, but are the outcome of a complex process.
Double-loop learning much more difficult but more relevant to our aims…? We
want to focus on:
• Interaction
• Participation quality
• Learning by doing and doing by learning
• Aligning
• Iteration
• Can or should one central body do this?
15
60. Way forward?
M and E of single-loop learning doable to undertake and fine for low-hanging
fruit and non-habitual change. Sees behavioural change interventions
more or less as linear cause and effect relationships (A+B=C:
Intervention A targeted on group B will cause the intended Change C)
A change of focus amongst policymakers and funders towards allowing
experimentation with more systemic and messy real life interventions
that do not provide easily quantifiable and scalable information is a big
transition. It demands amongst others that policymakers appreciate that
these systemic interventions cannot be evaluated in terms of cause and
effect, but are the outcome of a complex process.
Double-loop learning much more difficult but more relevant to our aims…? We
want to focus on:
• Interaction
• Participation quality
• Learning by doing and doing by learning
• Aligning
• Iteration
• Can or should one central body do this?
• Or do we need user generated content? A decentralised collective
15
participatory M&E?
61. change both the contents and context of the intervention. It will change the way how stakeholders
frame problems, solutions and their own role. Double-loop learning is seen as a process in which
learning is an important Way precondition for systematic forward?
transitions to take place.
Indicators that focus on double-loop learning can be used to evaluate DSM interventions and to
see whether they contribute to long-term, broader and more lasting changes (Breukers at al.
2009). In the table below single- and double-loop learning and their main indicators are shown.
Learning/evaluation Type of measurement/evaluation
Single-loop learning Efficiency indicators:
- Cost-effectiveness
- Goals reached (within given time and allocated budget)
Effectiveness indicators:
- Reaching the intended goals
- Lowering the total energy consumption
Double-loop learning Process indicators:
- Realizing a network of the intermediary filled with a heterogeneous set
of actors
- Interaction and participation by the target group (so that they can learn
about their own behaviour and consequences for energy consumption)
- Interaction and participation with a diverse set of stakeholders since
the design phase
- Learning as an explicit aim of the intervention
- Record new lessons for future interventions
- Making use of lessons that are learned during previous interventions
perspectives of intermediaries before and after a intervention
changes in assumptions, norms and beliefs
Content indicators:
- Alignment of the expectations of the stakeholder
- Learned lessons during the intervention are translated into
(re)designs.
- Improving the capacity of own or similar organizations to perform
successful DSM interventions
16
29 refs
- Creation of new networks and institutions that support the newly
formed behaviour and its outcomes
- Lasting changes (behavioural change)
Table 2: Indicators for evaluating successful learning processes (Breukers et al, 2009)
62. How to evaluate different levels
This applies to both habitoual fan d bonee-off hor oane-vshoit boehauviourr. ?See the figure below for an
overview of the types of behaviour interventions can target:
Figure 1: behaviour spectrum, retrieved from Breukers & Mourik 2013
We differentiate between one-shot behaviours that are performed rarely and consciously e.g.
investing in energy efficiency improvements. Habitual behaviour is more frequent, e.g. the
showering, changing the settings of the thermostat. Lasting changes in namely habitual behaviour
will continuously lead to energy savings. According to Breukers et al (2009), in this definition of
effectiveness, an energy DSM intervention is highly effective when it has reached its goals and/or
has had a positive effect on reducing the total energy consumption and when it has led to lasting
behavioural change and energy savings in the target group. Evaluating this lasting effectiveness
is, however, a major challenge, as will be discussed in the next section.
Efficiency is usually measured in 17
terms of cost-effectiveness, which compares the inputs and
outputs of a DSM intervention. These cost-effectiveness calculations can be made from various
Effectiveness is based on changing habitual behaviours which
will lead to ongoing energy savings. This is very difficult to
undertake. Efficiency is usually measured in terms of cost-effectiveness,
which compares the inputs and outputs of a DSM
intervention.
64. Some conclusions
• more negotiable and flexible practice of monitoring with a
mix of both quantitative and qualitative indicators
18
65. Some conclusions
• more negotiable and flexible practice of monitoring with a
mix of both quantitative and qualitative indicators
• become smart about identifying end users to work with,
and approach these selected end users with more qualitative
methods to understand the, where, when, whom, how and
why
18
66. Some conclusions
• more negotiable and flexible practice of monitoring with a
mix of both quantitative and qualitative indicators
• become smart about identifying end users to work with,
and approach these selected end users with more qualitative
methods to understand the, where, when, whom, how and
why
• methods can be interviews, house tours, diary exercises
and unobtrusive health and eg temperature monitoring. This
can help cluster different behaviour types that can explain
variations between end users
18
67. Some conclusions
• more negotiable and flexible practice of monitoring with a
mix of both quantitative and qualitative indicators
• become smart about identifying end users to work with,
and approach these selected end users with more qualitative
methods to understand the, where, when, whom, how and
why
• methods can be interviews, house tours, diary exercises
and unobtrusive health and eg temperature monitoring. This
can help cluster different behaviour types that can explain
variations between end users
• don’t be afraid to tell stories and anecdotes. Perceptions of
success can be more important than actual measures of kWh
savings...
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68. Storytelling to evaluate impact?
An effective way to also report on the learning process is to focus explicitly on
the learning stories which are in essence a process of co-design and dialogue and
retrace replicable elements in these learning stories to allow for a more
successful delivery of comprehensive EE DSM interventions (Moezzi and Janda
2014). Storytelling is an effective dialogue and evaluation tool, it allows for
multiple perspectives and creates a deeper appreciation for the fact that there is
not one truth. It allows to move beyond the presented and pretended objectivity
of a more quantitative approach. It not only allows for different morals to be
discussed, it almost demands it, we are all aware of the almost inherited right of
stories to have multiple interpretations depending on the reader, so instead of
either accepting or opposing a story, readers are encouraged to try to
understand a story and its multiple interpretations. Through the telling of stories
the listeners and presenters learn, also about negative and unintended
consequences. But they also learn to experience bad experiences as learning and
turning points in a story, with the aim to do better next time.
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69. Or: how to evaluate the impact of
storytelling?
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