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Honesty is very important, especially since your data will be used in decision-making. If you are not honest people might end up making the wrong decision using your data this might affect your company or those people that will benefit from your project. Do not be biased because you have a special interest in a particular area of your project, don't forge figures, do not misrepresent your conclusion heading just to gain the attention it will mislead people and always be honest and declare your capacity and inabilities to avoid giving people high hopes.
Is it a course?
Data needs to be collected honestly and presented honestly without any biases as this would be unethical
As stated at the beginning of this section, honesty in M&E goes beyond just avoiding lying. it is common practice for researchers to exaggerate their findings to convince the donors. This paints a n inaccurate picture about the subjects of their projects.
It's not enough to simply tell the truth in M&E. Wow, I think this has stood out for me concerning honesty, good food for thought.
This means even at the level of recruitment, the HR team should consider applicants that value honesty to join the M&E team. I am learning so much, thank you!
Ensuring findings from M & E are accurately represented is a huge risk when assessing data, without proper understanding of other factors that influences the outcome/ impact the findings can be skewed and is unlikely to present a holistic view of the situation.
Monitoring and Evaluation is all a bout honesty, otherwise if honesty is not observed the report a bout the project is biased. Every step in monitoring and Evaluation should be known to the project stakeholders.
Being honest about any limitations to you work
competence by having professional skill required
It is important to keep data as honest as possible.
Verification of data is important before it is presented.
Be transparent to the stakeholders about the teams limitations.
share your profession relations with stakeholders.
this module is very touching, honesty is the basis of any evolution
Honesty can also be related with data quality and mislead the decision makers. Unless exceptional, objective data collection and data triangulation will help to enhance honest in M&E.
An honest data presentation will tremendously help in achieving a lot in any project
Honesty in the M&E process cannot be overstated. Practicing honesty with data collection and use is beneficial to any project for two main reasons. First, honesty as operationalised by presenting accurate data helps the project team determine areas of success and those that need improvement. If data collection is done regularly, the project team is able to make timely decisions based on honest evidence. The other benefit of being honesty in the conduct data gathering and presentation involves articulating the limitations in terms of the M&E processes. By conveying what is and what is not covered in the M&E process relieves the project team from the pressure of producing evidence that is beyond what can be possibly collected based on the context of the project sites and the resources of the project team. For these reasons, it is advantageous to the project team to observe honesty in its M&E process.
honesty is an essential element in M&E, because it means every data collected will be reflecting true picture of the actual occurrence. it also help in making informed and impacting decisions because the intervention will be truly addressing the actual matter,
For me honesty is or should be the way of life, if you want to a professional in every expert of your life you should honest.
I think this is equally an important part to consider as a data collector and equally a field volunteer.
The honesty principle is not easy to implement for all; however, it should be stressed to all members involved in M&E activities that the integrity of a project's results depends on it. We aim to show the true things that are taking place on the ground regardless of what situation the project faces
honesty is an essential element in M&E, because it means every data collected will be reflecting true picture of the actual occurrence. it also help in making informed and impacting decisions because the intervention will be truly addressing the actual matter,
honesty is key in M&E because for evaluation to be accurate it has to come from true findings. otherwise it would not help in making informed decisions. again monitoring has to be truthful so that the report should also reflect true matters.
honesty in monitoring and evaluation participate to your evaluation quality
super!! i agree with this opinion
Honesty is very important in Monitoring and evaluation. Under honesty er try to be as honest as possible by: Ensuring that the data presented is accurate, ensuring that the data by M&E is oresented accurately, by declaring and sharing limitations in data collection and by declaring and sharing personal as well as professional interests
Keeping it simple and accurate and providing the limitations shows honesty in your data. Honesty is so key in data presentation as it gives realistic expectations and limits unrealistic expectations
Never compromising is part of keeping your data at an honesty level. So never compromise no matter what.
This conflict of interest happen a lot especially when there is incentives for any one who hits the program target.
Good M&E system is very important of successful program.
Some knows that not to be honest is the unethical side, but it is difficult as well to sustain their financial source if the data shown disappoint their donors. One thing to be foreseen is making decision on time to the project implementation instead of waiting until the project end.
Honesty, brings in a conflicting aspect of M and E, where organizations Will have to stand by the truth, despite their organizational needs, but it also brings in room for solving the companies limitations, by acting us a guide line for improving companies short falls in M and E.
It is very unethical to manufacture, create or fabricate data. It totals to dishonesty.
This is actually a standard to take into consideration more often. We need to be careful with biased opinions, and need to state facts, not opinions in our data collection and analysis. Also, the use of the correct words to phrase a paragraph, an outcome, a report, or similars; should be based on facts, and we should not allow to mislead on a certain topic.
This is helpful. My organization will ensure honesty in our date functions so as to get a realistic and clean date.
Being honest is essential in presenting data. We can tackle a lot of problems by just being honest.
Being honest is essential for data management. We can tackle a lot of problems by just being honest.
Being honest is essential for data management. We can tackle a lot of problems by just being honest.
Learning cultural competency is big a deal
M&E data should always be true and transparent. The importance of honesty in M&E processes cannot be over emphasized.
as a M&E officer you always have to be honesty in any situation in time of data collections and presentation of report for decision making, because honesty is the key success to your data and also to you personality as an M&E officer, changing data to make some one or organization happy is deeply dishonest and, therefore, is unethical. to do that
Interesting Principle
Interesting Principle
Honesty mean be clear in front of donor sometimes data quality is issue same time deadline is major issue that time be honest in justification its was not happen due to list if reason
we need to collect , use and present data accurately
Actually, if the honesty is not upheld from data collection to data presentation then it will be good to not waste time. It is the honesty in data management that differentiates facts from biases.
Yes, it is very important to present honestly data and results in circumstances where competition among the organization is very high.
Honesty mean be clear in front of donor sometimes data quality is issue same time deadline is major issue that time be honest in justificaation its was not happen due to list if reason
Honesty is important in data collection . Honesty starts from data collection that you state clear about that project,purpose of collecting that data and incentives if they are any. In order to get accurate data you must be honest.
To me this is an eye opener, honestly is not only what I think
in this changing environment, honesty is a luxury that most cant afford so they will resort any other way that is within their limits to achieve the goal they intend to achieve.
honest business practices build foundations of trust with colleagues, competitors, staff, customers and every other individual and entity. When employers deal honestly with their staff, employees are motivated to drive the business forward.
Honest people trust themselves. Never underestimate the life-changing power of the ability to trust yourself. Wellness – Honesty has been linked to less colds, less fatigue, less depression, and less anxiety. Less stress – Dishonesty needs to be maintained.
It allows you to resolve conflict and avoid confrontation. It can even enhance wellbeing for those around you. Yes, openness and honesty is contagious! It encourages others to share more with you in return and that mutual respect is essential for establishing a healthy work environment.
honest business practices build foundations of trust with colleagues, competitors, staff, customers and every other individual and entity. When employers deal honestly with their staff, employees are motivated to drive the business forward.
Honest people trust themselves. Never underestimate the life-changing power of the ability to trust yourself. Wellness – Honesty has been linked to less colds, less fatigue, less depression, and less anxiety. Less stress – Dishonesty needs to be maintained.
It allows you to resolve conflict and avoid confrontation. It can even enhance wellbeing for those around you. Yes, openness and honesty is contagious! It encourages others to share more with you in return and that mutual respect is essential for establishing a healthy work environment.
In data collection there is a basic principle of you get what you put in, that is to say if you put in junk you will get junk out. It is very important that as an M&E officer you are transparent with the data collection process and everything else involved in it to avoid putting in junk and getting junk out.
Also honesty goes a long way and could possibly save one from all the troubles they could encounter.
Honesty on outcomes /results or wrong interpretations,or else putting a note below collected data results is better than turning the story another way round to catch donor or to gain high expectations to our organizations when presenting data
Honesty is crucial for M&E professionals. Interesting to note that data can be misrepresented even if collected flawlessly.
I agree.
In most situations outside of the realm of M&E, people expect that personal beliefs will influence what you say. Data from M&E processes, on the other hand, is expected to be as close as possible to the pure truth. Simply not lying is not enough.
A conflict of interest happens when you or your organization might gain something useful if a certain outcome is reached.
For example, imagine an organization that receives donations from a pharmaceutical company. If they publish data that shows that one of that pharmaceutical company’s drugs is effective, their donor might be pleased with them and give them more money.
We must strive to be honest from our data collection to data analysis to data usage, as to ascertain the veracity of our data and to make it more usable for our projects and future projects while avoiding any conflict of interest that might arise.
Quoiqu'il arrive il faut savoir rester honnête et intègre enfin de garantir la qualité des données ainsi que leur fiabilité ce qui est très capital pour la suite du programme.
About being honest, means the M&E process needs to be trustful way and respectfully. Also it refers to be sure, true, strict and purposely process.
Honesty should be demonstrated throughout the M&E activity, as well as to stakeholders (beneficiaries, program staff, donors, or other groups of interested parties) and participants.
Use the data for the only purpose that you intended to. participants should be assured that their data will only be used for the intended purpose.
HONESTY: seems to be one of the major factors
Data should be honestly collected, managed, analysed and presented.
helps in accuracy
It is very ethical for you to disclose you relationship with the pharmaceutical company.
Honesty is the key to any M&E success
The most impressive part of "Honesty" in M&E is not simply to not lie. Failing here, could dramatically affect the quality of the work, even create a doubt about the data analysis outcomes. This could be a real problem for the organisation that playing the role of M&E. It is extremely important for any M&E professional to, keep in mind the standard of honesty is even higher it is for other people.
This is a great topic of being honest. I now understand why we are being asked to share findings and limitations through out the project life span. This is really an eye opener
Honesty is one of the key to success in M&E.
Ensure that the data you present is accurate. Do not tamper with data collected to build your study
Entre nous soit dit: Est-ce que les membres de la team S&E sont vraiment honnêtes? Peut-être qu'à travers ce cours, on sera honnête et on présentera des données exactes
Helps one to prepare for accurate and reliable data during presentation and then it gives a good feedback on someone wishes to show interest on field of his/her dream's
Honesty is very important in everything we do; however, it is less put into consideration in many organizations. The most critical point I think is declaring conflict of interest before the intended outcome is observed. Making sure that the data we present and collect are accurately should always be at our fingertips to avoid damaging the people we intend to use it on them.
Conflicts of interest are a possibility throughout the M&E process. The financial or intellectual interests of the program employees may conflict with the M&E if the M&E is carried out internally by program staff. There is a possibility of conflicts of interest in the case of external evaluations as well, either in the form of monetary stakes with the funding agency or other intellectual interests of the external evaluators. The M&E manager's judgment may be affected by these conflicts of interest. As a result, the outcomes could become suspect.
This very crucial in M&E
In the company I work for, there is a specialized department for collecting data and archiving it using Excel and a special program
it is good to be honest especially when you are collecting data
this shows the ethic of your data
it is possible to ignore honesty just to convene your stakeholders especially donor, but it possibly destroy the process of your project. it will sure fail on the way because you have not collected the right information and you will have no steps to follows
it is possible to ignore honesty just to convene your stakeholders especially donor, but it possibly destroy the process of your project. it will sure fail on the way because you have not collected the right information and you will have no steps to follows
Dishonesty during data collection or interpretation could do harm to the people such data was meant to help in the first place and could destroy your company's or organization's credibility. And the user of such data could provide solutions that are at variance with the needs of the population, eventually translating to the waste of limited resources.
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Honesty is keen
during the presentation you have to include implementation processes, challenges you have faced, long term strategies needed, how to achieve the targets' and achievements.
Without honesty the data can be bias and to an extension it can lead to wrong decision making.
My name is ANDREW BRIMA KAMARA
My name is ANDREW BRIMA KAMARA
My name is ANDREW BRIMA KAMARA
Risk and Assumptions very vital in project lag frame helps in bringing out the challenges and biases that we can encounter during the project implementation
Quels les critères essentiels du choix des données (Variables en études)
Quels les critères essentiels du choix des données (Variables en études)
Sharing the limitations of your M&E strategies may be hard for a data scientist who wants to achieve perfect results but it shows that we are human and we can make mistakes .
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 a key to building trust, an Honest report provides for more opportunities from funders.
honest with all data collected is a priority for all who are involve
Honesty is key in data collection as it tends to eliminate Biases.
False information leads to wrong decision-making. So, providing false data or information it is not only a crime, but also shows how bad professional we are, professionals without the sense of responsibility. The Honesty principle help us to avoid many problems.
Sadly, some think of ethics as a process that drags data collection. Honesty is a virtue in research that cannot/should not be downplayed.
We must be confident that the data which we and our entire team members supply to public or main clients are as much accurate as possible . This is because of the reason that the company honesty totally lies on that for sure for future endeavors.