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Honesty is a the 2nd ethical principle.The researcher while in monitoring and evaluation process should gather data using accuracy which means should minimise the errors .Also from that the M&E should represented accurately in using a sample size which is standard.The conflict of interest should be listed promoting to the research participants rights.

les biais dans la collecte des données sont t'elles aussi liées à l'honnête?

well! they are some professional in ME whose taken thier work seriously

Honesty play important as a team that presented important data.

Ensure your data are accurate and always share your limitations

Honesty is the most important virtual in data collection and M&E in general. This helps build the confidence of the community and they will be able to trust you and give you the information you will need

INTERM OF ETHICS PRINCIPLES

1. DO NOT HARM
2. HONESTY
   3)COMPETENCE
   I HAVE DISCOVERED THAT MOSTTLY BRINGS NICE AND PRESENTABLE DATA OBTAINED FROM THE FIELD

Most of the time the conflict of interest part is never shared, this causes serious challenges with our M & E data.

Honesty is the most important virtual in data collection and M&E in general. This helps build the confidence of the community and they will be able to trust you and give you the information you will need.

Integrity is also very important in data collection because it helps in building confidence of your participants.

Honesty is the most important virtual in data collection and M&E in general. This helps build the confidence of the community and they will be able to trust you and give you the information you will need.

Integrity is also very important in data collection because it helps in building confidence of your participants.

This is a very cardinal principle if goals of an organization, especially those of achieving a reduction in some effect, prevalence of disease, teenage pregnancies among others, or attaining an increase in an area of productivity. I wish this could be a daily lesson to bring to the attention of all M&E professionals.
This quality also requires that an M&E professional have a heart to the attianment of the objectives otherwise selfish ambitions may clog program attainment.

Honesty is trying to collect use data and present that data accurately without any limitation to his or her work. At this stage you are not suppose to have conflict of interest.

Honesty
As a principle in data collection and reporting , honesty presents a true view of the information collected. A number of steps can be considered in ensuring this happens;
-ensuring accuracy of data presented

• Ensuring the correct representation of the information collected
  -sharing the limitations of M&E strategies
  Honesty plays a crucial role as it forms the basis of integrity of the data collected

For me, I have find that conducting DDM or PDM internally also show bias as the employee themselves are how implement and monitor

Honesty is a thing we all need to show at all time

I agreed with you

Honesty is a virtue and one of the qualifications for Monitoring and Evaluation. Hon datandata collections ensures that the data you present is accurate, ensures that your findings are accurately represented, ensures that your limitations are considered and ensures that your conflict of interest is included if present.

one of the thing that I knew before reading this part is honest the fact being mostly practice to our beloved ones but the interesting part now honest is even in M&E when collecting and follow all the process you must be honest with your data during the presentation or representation to avoid uncertain or bias to the people that will read the information

Honesty means collect and present accurate data. Data should be accuratecollected and presented. In addition, this principle tells us to share limitations and conflict of interest.

I concure with you. Honesty principle obidience is crucial for M&E profesionals

Yes. It is true.

Yes it is true.

M&E must collect, use and present data accurately. They must be clear about how their M&E processes work and be honest about any limitations to their work.

In Cambodia, EMIS data rescores are from two ministries; such: ministry of planning and ministry of education, youth and sport so how about other country? Moreover, in Cambodia there is providing skilled professional services, too; that's why should have a vast array of M&E tools available for data collection, management and analysis. The most special, collecting data team and M&E team should ensure that you have the cultural and technical skills to carry out M&E processes so need to know about mapping stakeholder needs, storing data securely and designing surveys because culture skill allow us to work safely. Lastly, should decline to run M&E processes that you are not equipped to do well and still continually improve your skills.

How can we solve if there is problem with data quality and this is rush time to prepare the Education congress?

How can we motivate people to love working on data collection? Especially; lady

Honesty is are essential values ​​to ensure the success of a business

Honesty is a way of life, which should be seen and practiced not just personally but professionally.

Great examples in the course content, I suggest everyone to read them carefully.

Honesty is a way of life, which should be seen and practiced not just personally but professionally.

Fo perform excellently well in M&E, continuous improvement in oneself and in team, by investing in learning, can't be overemphasized.

I LEARN MORE ABOUT ETHICS,An example of an ethical issue, CAN YOU GIVE ME MORE LIGHT PLEASE

Hi Everyone,
Is honesty not counter productive when using control groups in an experiment to test the effectiveness of a system. E.g. If Aisha and her team in the assignment for module 1 have to tell the students which group they belong too, would the results not be biased? I need clarity on this please.

Honesty is one of the bases of the M&E Ethics basically Collect, use and present your data accurately. Be clear about how your M&E processes work and be honest about any limitations to your work.

Honesty is about truth and reality on M&E results. It includes:-
Expressing limitations of your M&E or any thing which can interfere or which is believed or will be perceived to interfere the outcome.

Presenting the real data which was collected.

Beside the draw backs of digital data collection tools, i still find it helpful to shift to digital data collection methods

Sharing the limitations of my M&E strategies and sharing possible areas of conflict of interest are the areas that caught my attention. This means that during the M& E design, one should think deep of all the limitations and possible conflict of interest. This may even affect the rigor with with data is collected knowing well that one does not want to bring one's bias into the system.

Honesty in Data collection plays an important role as it involves truthfulness or trustworthiness. It is important to ensure that the collected data is truthful and no additions are added to it. o e to ensure that the values or figure indicated, standards used or Measurement scare or tool are accurate,

to ensure that conflicts of interest arise, some organizations can decide to doctor the data...

once data is doctored, it becomes possible to maintain a certain status quo...

objectivity is very essential in m&e...

very true. some retraining or refresher courses may be very helpful here...

this make it difficult to have a fair evaluation of a project...

with honesty, accountability becomes possible...

this is one way which can help ensure that a project becomes self-sustaining even when funding ends...

this is a very trick situation, but a balance must be reached...

It very important to acknowledge the truth that data falsification is a crime everywhere! In order to abide by the second ethical principle "Honesty" the easiest way to to present accurate data. The moment we are truthful about how collect and record our data then we are indeed aiming at producing positive results.

Some of the key ethical considerations are avoiding conflicts of interest, maintaining independence of judgement, maintaining fairness, transparency, full disclosure, privacy and confidentiality, respect, responsibility, accountability, empowerment and sustainability. There are several ethical frameworks in public health, but none focusing on the monitoring and evaluation process. There is a need to institutionalise the ethical review of M&E proposals.

This is serious challenge with many projects, especially government projects. In most cases serving as an M&E person for a donor funded project implemented by a government ministry or agency, in this case you might be intimidated to present project to donors that are not realistic.

Most people always want things to favor them but this shouldn't be the case with the M&E professional. Remember that our career has critical moral issues, because whatever we do or present has greater effect on the larger society.

In addition to the Do No Harm, another ethical principle for the data collection activity concerns with the issue of reliability. Data and information for M & E deserves high level of reliability which means that data and information needs to be accurate and properly represented when it comes to dissemination, reporting or usage with the findings. To ensure the data reliability, it is very important that honesty is practiced fully through the process of data collection, analysis and dissemination or reporting. Honesty also means transparency in this context. For example, if there is any limitations and potential conflict of interests associating with the M & E work, such concerns need to be available and if necessary, communicated to all stakeholders. Low level of honesty means there is limited reliability with the M & E activity.

In addition to the Do No Harm, another ethical principle for the data collection activity concerns with the issue of reliability. Data and information for M & E deserves high level of reliability which means that data and information needs to be accurate and properly represented when it comes to dissemination, reporting or usage with the findings. To ensure the data reliability, it is very important that honesty is practiced fully through the process of data collection, analysis and dissemination or reporting. Honesty also means transparency in this context. For example, if there is any limitations and potential conflict of interests associating with the M & E work, such concerns need to be available and if necessary, communicated to all stakeholders. Low level of honesty means there is limited reliability with the M & E activity.

In addition to the Do No Harm, another ethical principle for the data collection activity concerns with the issue of reliability. Data and information for M & E deserves high level of reliability which means that data and information needs to be accurate and properly represented when it comes to dissemination, reporting or usage with the findings. To ensure the data reliability, it is very important that honesty is practiced fully through the process of data collection, analysis and dissemination or reporting. Honesty also means transparency in this context. For example, if there is any limitations and potential conflict of interests associating with the M & E work, such concerns need to be available and if necessary, communicated to all stakeholders. Low level of honesty means there is limited reliability with the M & E activity.

Clearly brief and concise .One shouldn't go to the extremes just to please donors and readers .strive to report the truth.

Este curso é uma continuação do anterior, planeamento em monitoria e avaliação. Pós é uma grande valia

To ensure that you're abiding by the honest principal, You must ;
Ensure you present accurate data.
Present your findings accurately.
Share limitations of your M&E strategies.
Share any areas you may have conflict of interest.

Honesty above all!

Honesty is a virtue and in its application to data, it is necessary to work with some degree of honesty.
If data is provided honestly and evaluated honestly, the outcome will be what any organization hoped for.
Its detrimental to hoard data that could impact positively on the decision of an organization.
Equally, adjusting data to one's favour is harmful towards achieving organizational objectives.

You most be honest in all your dealings, this will enable stakeholders to gain confidence on you

An evaluator needs to be aware of any bias the project team might have and actively work with them to ensure that bias does not influence how the data is presented. Training on identifying unconscious bias for all team members would be helpful in this regard.

Honesty helps to collects and present data accurately and be clearly about M&E process also be honestly helps to provide the valid information which will helps us in the process of data analysis

The whole point of M&E is to be able to assess a problem and then try to solve that problem, and in this regard, honesty is really key because without that, M&E changes to something else.

To deal with incomplete data, there are several statistical methods which deal with missing data. These methods should be used appropriately depending on the type of data. They make data clean and easy to manage and analyze.

honestly is very important because it ensure that the data present is accurate .This is why M&E professionals go to extreme lengths to ensure that their data is honestly and transparently collected, managed, analyzed and presented.

Conflict of interest should be clearly stated to avoid any form of bias. Accuracy should be continually maintained without making any assumptions for every question asked even if it is being repeated.
all limitations to the study need to be clearly stated to avoid any form of untruthfulness.

Interesting. It is save to say the accuracy of your data relies on how honest the collection process and presentation is. This should shove off any doubt about the credibility of the data.

Research becomes compromised when it is handled in a dishonest and unprofessional manner. I therefore really appreciate the emphasis on honesty

I have learned that honesty is very key in every aspect of life. imagine using an inaccurate and dishonest data for record that might affect an organization and even affect the country at large. not too many people are honest enough to admit their limitations of their M&E strategies. that is when the conflict of interest comes in.

M&E processes must be clear for all actors involved in project. Confusing and lying reduce data accuracy

Honesty is very important of the human society.

The standard of honesty is higher for M& E professionals than it is for other people as Data from M & E is expected as close as possible to the pure truth. This is why M & E professionals go to extreme lengths to ensure that their data is honestly and transparently collected , managed ,analyzed and presented.

In order to abide by the principle of honesty ,the M & E team may:

1. Ensure that the data presented is accurate
   2.Ensure the findings from M & E are accurately presented
   3.Share the limitations of M & E strategies

Being honest is one thing which makes many people to be trustworthy

honesty is top in the m and e realm it is important that data collected are properly collected and accurately documented also sight your limitations strategies

This is really an essential part. It is always important to be honest do not make things unrealistic or too over rated.

One lie would be lead to another lie so it is essential to follow the honesty although it would place in odd often.

For honesty we need to present accurate data accurately ,at least share the limitations we passed through and have or share a conflict of interest if there is.

Dishonesty is really not good and it should be avoided. however, how will one deal with a colleague that likes to lie on reports?

Honesty is the best policy, while collecting your data always check the accuracy of your data

Simply not lying is not enough. I believe it is essential to share the ethics with the teams involved in the M&E processes to ensure there is ethical adherence at every level of handling data and respondents.

The issue of honesty as being spoken about in this course is very important. I have seen from reading through this Module 1: "Honesty" is useful in carrying out any M and E activity in the field. There are a few reasons outlined below to indicate why the issue of honesty is key:
-if you want to maintain the credibility of your entity and yours in getting future contract, you need to keep the standard of honesty
-If you want to maintain accurate data that can be used for future action or actitivaties, you need to keep the standard of honesty... etcetera.

Honesty in data representation presents the best opportunity to validate data collection. My biggest lesson here is despite the need to elaborate on your successes, there is always a window for exercising discipline when reporting attribution,

The importance of honesty is fundamental for Monitoring and evaluation professionals becase the standard is higher. Thus, honesty must be practised and maintained as a priority.

Second principle of ethics one must be honest to ensure that the data you present is accurate.
Ensure that findings from your m and e are accurately represented

Honest is the second principle of ethics.
Ensure that the data you present is accurate.
Ensure that findings of your m and e accurately represented.
Share limitation of your m and e strategies

during data collection, analysis use and presentation , honesty is key principle. it ensures that accurate data is collected, used for decision making and also for presentation purposes. no one should manipulate the data to suit their personal interest or please the sponsor/donor.

I would like to discuss about Honesty while writing a proposal , becuase many donors will requst creterias to fund a project/program , and the organizations will work hard to prepare the propsoal and support it with data collected during their previous projects , here they might choose to use a part of the data they have in order to fullfill the creteria and get the fund, and this part pf the data could be tailored specially for that purpose, is that ethical ? and how can an organization use their data in this case ?

I think, Term "Integrity" is more relevant in regard to the listed items above

Honesty in a major component in M&E professional, but sometimes we are forced to bend the truth to impress the donor. And most of the time we are simply being honest on the results that won’t cause any impact.

Il faut être honnête dans le processus du collecte au partage des données, la confidentialité doit être respectée.

Lying is always difficult to defend all times. Honesty is all a data collector, an analyst need to present facts.

Oftentimes, honesty is one of the most renowned ethical principles necessary in all works of life. However, it is unique as essential in monitoring and evaluation. Honesty in M&E entails that staff present accurate data. Reports should accurately represent our findings and our limitations always shared. We must try to avoid conflict of interest.

honesty and bias are the backbone of any m&e exercise. they either make or break

honesty minimizes bias, promote accountability and transparency

Honesty is ensuring that whatever data presented has transparency , this is surety that data presented is accurate and can give prove on the services provided. limitations should be shared incase there were challenges encountered that giving inaccurate data .Accurate and quality data should be enhanced even if there is a conflict of interest on favoring a certain party.

Really nice about honesty because if honestly not collect organize and use our data, it is difficult for mand evaluation team

Exactly we have to avoid it to be a best m and evaluation expert

I appropriate above the messages. We have principle might seem simple and self evident.

Honesty is a key ethical principle in M&E.
Presenting data as it is is important.

How does one ensure that participants provide honest information during data collection?

Honesty is the best policy especially when qualitative data is involved.
Organizations should be careful especially when interests are at play.

Honesty is also very critical in M & E, as accuracy determines and influences right decisions.
Thus there is a need to ensure;