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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;

Just be honest with your M & E processes as your accuracy determines right decisions

I need the notes to read

Throughout the whole process , Honesty is key.
it promotes trustfulness.
When reporting data, results, methods and procedures, and publication status we have to avoid the follwing:
1-fabricate
2- falsify
3- misrepresent data.

Throughout the whole process , Honesty is key.
it promotes trustfulness.
When reporting data, results, methods and procedures, and publication status we have to avoid the follwing:
1-fabricate
2- falsify
3- misrepresent data.

Throughout the whole process , Honesty is key.
it promotes trustfulness.
When reporting data, results, methods and procedures, and publication status we have to avoid the follwing:
1-fabricate
2- falsify
3- misrepresent data.

As much as collecting correct data is crucial in measuring and evaluating results and impact of an Intervention, the actual process itself should be carried out in a manner that will compel the respondent to openly share true position without fearing. The Designers for such data collection tools must consider respondent's environment and values that may likely hinder the process and ensure they are incorporated for quality data

Here there is no room for assumptions or maybe's. Just share any area that may suggest dishonesty. Ethics in M&E is very deep.

The issue of cause and effect are often difficult to prove especially in cases where there are multiple interventions taking place. Hence, it is important to disclose circumstances that may affect the results and its limitations.

How to balance the principle of "do not harm" and the principle of "honesty"? It is explained that maintaining the principle of "do not harm" can be done by, for example, not disclosing an information which may harm a particular group (i.e. not disclosing that a group of low socioeconomic is associated with a higher crime rate to politicians). To my understanding this would contrast with the principle of "honesty" when where we are required to be transparent to relevant stakeholders.

It is good to ensure that the data collected and presented is accurate and it is also too close to truth. Don't present data that is strongly worded/inaccurate because is not ethically appropriate. Before collecting any data, it is good to find out any limitation associated with your project and share it with other stake holders who are interested with your study. Share with other stakeholders the project area you think will yield positive results.

Honest is a ethical behavior within M&E is to ensure that data you present is accurate and you should not present data that you know is inaccurate, present your data accurately be clear about how your M&E process work and be honest about any limitations

I want to know about difference between honesty and completeness

I want to know about difference between honesty and completenest

My name is Daniel. This is my first attempt at Project Management. Hope it's a nice point to begin my journey. You may suggest a better place to begin.
I hope to enjoy it here and relate better with like minds.

What stood out for me is the fact that in order to ensure honesty you have to constantly check accuracy of your data.

You have to tell the truth to your respondents and avoid promising them what you can not fulfil

Honest in the m and e program is one of the fundamental principles that each member should adhere to and follow, since it leads to correct and transparent processes and outcomes

Because the data collected, managed, analysised and shared is going to inform future planing or interactions, it is therefore, cardinal that it should be a true representation of what is happening in our target population. It must be handled with much care, analysised in the same manner of care, intepreted with accuracy and presented with equal accuracy so that it does no harm to future planning and the population at large.

being honesty in M&E process is a key as it helps to measure well the success of the project

We all need to be honest with our data and the result, and we should use the accurate data in conducting data analysis. Failing to describe the limitation of the M&E strategies may lead to a weak decision about the project.

We all need to be honest with our data and the result, and we should use the accurate data in conducting data analysis. Failing to describe the limitation of the M&E strategies may lead to a weak decision about the project.

This is an amazing course

Très important

Honesty is vital for all data process from collection to data analysis aby the m and e team

Honesty is a key ethical consideration we must take into consideration when dealing with data. It will build the trust of stakeholders (participants, donors etc.) in us and in our process.

as the saying goes honesty is the best policy.
collecting honesty, accurate and transparent data helps to grow confidence and can lead transforming others through your honesty.

These are good methods!

In fact, Not every person can make part of this.

This task in fact, needs skilled people.

In order to present accurate data be honest from the start

we should keep to our words,keep our commiments, pay attention to the enviroment, stay focused, take responsibily and respect the people we work with.
Honesty brings courage and it helps develop strong connections. Also it shows the real side of people and creates trust.

we should keep to our words,keep our commiments, pay attention to the enviroment, stay focused, take responsibily and respect the people we work with.
Honesty brings courage and it helps develop strong connections. Also it shows the real side of people and creates trust.

Here the author is right about honesty, because there are several agencies that do publications but that is not accurate, even in graduation papers. Sometimes, for example, we have fixed a sample of 150 but in the field, we do not manage to reach 150 people, and when the publication, you manage to publish that there were 150 respondents it is not honestly.

It's a fantastic idea, I had to work in a research firm, I was a data analyst, he told us before the elements were analyzed it must be well cleaned so that it does not there are no missing ones and when you do the analyzes you have to be honest that here it is true and the other question is not well done. To allow you to be precise in what you are doing like analyzes and also to gain the customer's trust. So I will say in this area honesty matters more.

The "HONESTY" ethical principle issue is really critical to provide good understanding and appropriate acceptation of our conclusion. In fact, this is confident key of M&E process.

Honesty is a virtue that most be exhibited when presenting data collected in M&E. Ways to ensure hoinesty are;
Ensure that the data you present is accurate and void of intentional or unintentional mistakes or errors

Share limitations of the M&E strategies

Share areas where personal interest may arise causing conflict of interest. etc

This is one area a lot development have come short. Data is misrepresented. The norm is that outcome is now been directly to a program/project. This will continue to be so because on the one hand, recipient of grant want to show to the grantor's that there is value for their money, and on the other hand, the grantor's are demanding humongous proof from the grantee's for the money they have received. If the "showman" continue, data will continue to be represented.

exactly. the topic is relevant

Basically we should bring in other means to cushion the existing frame work

The issue of honesty have been ignored or undermined by many organizations just to get more funding or extend the duration of the project. This leading to cloning (falsifying) data towards the interest and desired outcomes. Many development workers most time falsifying data just o meet targets.

You are right but note that some organizations manipulate data falsely to meet the biased expectations of donors or international partners in order to sustain funding for extension of the project/programmes.

have had great interest in the last bit of conflict of interest. that is a challenging position to be though we have to be host to produce accurate and meaningful M&E reports

What if there are consequences attached to disclosing such information (conflict of interest) during data sharing

It is said that honesty is the best policy. Therefore, programmes must honest right from data collection to presentation.

Presenting data honestly and using only for the intended purpose should always be emphasized. Because if your respondents believe that you are trustworthy there is a high probability that we collect accurate data. realistic data can be collected if people trust our honesty.

Off course when we are talking about honesty we are traying to close a gap that insincerity will come in place when disclosing, preparing or presenting an accurate information always is the way forward and this will speak to the ethical nomenclature we most adopt for smooth and success of a program.

Off course when we are talking about honesty we are traying to close a gap that insincerity will come in place when disclosing, preparing or presenting an accurate information always is the way forward and this will speak to the ethical nomenclature we most adopt for smooth and success of a program.

So the donor gets pleased when the organization mentions their input in a project? Alright.

The issue of conflict of interest is pertinent. Most of the time people can be carried to present a partially close the truth data to please their donor without other necessary considerations but reporting the conflict of interest it's what I don't know if it has ever happened.

The issue of conflict of interest is pertinent.

The issue of conflict of interest is pertinent. Reporting conflict of interest I don't know if It has ever happened.

Honest is one of the fundamental area we all need to put in mind when collecting and presenting data at different levels. presenting false data affects the who process of data collection. As M&E experts we need to be honest when presenting our data. through honesty, our data can be trusted and references can made towards our work by different organization and good recommending can be applause to the organization which we represent.

Indeed, being truthful in your data collection process and presentation of findings is a perfect way to ensure credibility of the work. Any malicious act of doctoring evaluation findings can injure the organizational reputation in the long run.

We must be honest in data collection and analyze

Be honest - collect, use and present your data accurately

Honesty is the hallmark of M&E data representation. Conflict of interest when not disclosed in time put a doubt on the entire data collection and analysis process. M&E personnel should indicate any personal interest at the beginning of their findings. M&E data has to be presented clearly and accurately as possible.

If the honesty information is been provided, it will allow for accurate data analysis of the information. it will also give the organisation room to work out on the mistakes that where made and avoid them in future.

Honest in M&E is not just telling the truth and not laying, but in M&E, there are other dimensions to be evaluated such as: ensuring the data is accuracy before presenting it and it should be presented accurately

Honestly report data as it is from the start.
The results must be honest no what what the outcome is.
The methods and procedures must be honest that collected the data.
It is not good to falsify or distort data.
When dealing with data avoid careless and negligent mistakes carefully and critically check your data that it corresponds.

Honesty is very key in collecting, managing, analysing and presenting your data, findings should be nothing but the truth.