Sample research proposal program evaluation

In order also to correctly identify the areas of interest, a sample will be used to spear head the evaluation process, with this being a small section selected to help carry out a given process Kapur and Sawena The sample selected will mainly constitute the inhabitants in Kathmandu slum, to help ascertain whether the program helped reduce deaths and child mortality and morbidity.

There are various data collection methods which will be used during the evaluation including a surveys, interviews, use of questionnaires and document reviews. Surveys should be used given the geographical attribute of the area. This data collection method will be composed of sets of questions that evaluators and program participants will use to collect data. It will be structured in a way to contain both structured and unstructured question and response options. This will give the participant an option and enable the evaluator to accommodate both open and closed-ended questions, to allow as much as possible quantity of data to be collected.

Interviews will be used to collect data from the slum inhabitants through a one-to-one interview approach. In this case, an in-depth interview will be used to collect diverse information concerning the program, which encourages openness and courage thereby ensuring that an extensive coverage on the achievements and limitations of the program are gathered.

Questionnaires refer to a collection of sets of questions administered to participants, in that they give their responses based on the questions Holmes et al. It is a useful approach for collecting straight forward data and should specifically be used in collecting data with straight forward answers.

In this instance, it will be used to gather data on deaths before and after the program was launched. The program evaluation process should also involve a review of existing documents to help gather data related to the program.

The sample documents that should be considered in this stage include minutes, reports and other surveillance data to enable evaluators to make an informed decision. The document also allows evaluators to check on the progress and to ascertain whether decisions and improvements were made based on report findings. The evaluator should use the descriptive approach to perform data analysis by recording the number of participants involved and how various health cases have been resolved successful upon implanting the program.

This is because the approach considers various variables in a population, which are helpful in presenting the summary of the findings Wells To analyze the number of mothers that the program has had an impact in, the frequency distribution should be used to record the cases handled, and successes of the program. In this case, a table needs to be used to record the statistics. The frequency distribution should be used to record the average number of cases handled from the start of the year.

This gives a summary of the successful cases, based on the objectives of the program, and helps summarize the data through average. To compute success in terms of cases handled, the process should use the case attributes. The computation should give a picture on the successful cases.

It should also give the number of child births per the , cases. The above methodology should be used in the evaluation. This is because it evaluates the program based on certain quantifiable attributes. It is easier to record the cases involved, solved and unsolved in numerical form which given establishes whether the program achieves its objectives.

In addition to this, the methodology also uses a combination of data collection methods which helps gather in-depth data necessary to help in the computation process, and also gives statistical figures regarding the outcomes of the evaluation.

On the other hand, various documents reviewed in the process helps give accountability regarding the program, and also reduces mis-presetation of data which may be hidden from the external evaluators. The intended evaluation should have various checks to safeguard data collected from respondents and other participants. It is important to include this attribute to foster credibility and validity of data collected.

In this, credibility as a concept is involved with ensuring that collected data is accurate and the findings depict the actual state Parker This ensures that the data collected gives the correct measurement on the intended attribute.

The credibility aspect should be instilled through certain safeguards such as use of reliable sources and data verification. Data reliability is an important aspect that should be considered to maintain data credibility. This needs to be conducted by interviewing specific participants such as mothers, rather than the project stakeholders.

In doing so, reliable data would be collected since there is likelihood that other parties may forge data in favor of some stakeholders. Data verification remains an important aspect as it helps ascertain that given data is verifiable, in that collected data by the use of certain gadgets represent the true picture of the situation, which also ensures that data is accurate and not duplicated.

These safeguards ensure that data collected is credible, valid and can be used to evaluate the program to produce the correct findings. Blumenthal, Daniel S, Ralph J. DiClemente, Ronald L. Braithwaite, and Selina A. Butterfoss, Frances D. Coalitions and Partnerships in Community Health. Hickey, Joanne V, and Christine A. New York: Springer Pub.

Co, Research Methods in the Biosciences. Oxford: Oxford University Press, Kothari, C R. Kapur, Jagat N, and H C. Kapur and H. New Delhi: Chand, Orton, Stephen N, Anne J. Menkens, and Pamela Santos. Sudbury, Mass: Jones and Bartlett Publishers, Pitney, William A, and Jenny Parker. Champaign, IL: Human Kinetics, Thomas, R M. Thousand Oaks, Calif: Corwin Press, Wells, Michael K. Conduct focus groups with pre-service teachers at the end of every semester. Districts will hire additional qualified math specialists from their own communities to support mathematics teachers at the district level.

Construct a logic model—graphic model of the program over time including resources, inputs, expected outcomes. This document provides a conversation piece between evaluators and other stakeholders to examine and critique the progress of the program.

Communication with program staff about model implications. Two to three days 2. Background reading — external evaluator needs to get up to speed on the components of this program, similar programs, and research indicators Three to five days 3. Visit NMSU and districts in the field to help with data collection, sample the climate of the program, and communicate with team members. This would take place both in the fall and spring and involve travel and time spent in New Mexico as well as reflection time to report on and communicate back with New Mexico team.

Ten days 4. This would take place both in the fall and spring and involve travel and time spent in New Mexico as well as reflection time back in Texas to report on and communicate back with New Mexico team. Conferencing with New Mexico team by phone as well as preparation and reflection on the meetings.

Two days per year 6. Decide if you are going to do an internal assessment with your staff, or if you want to hire outside expertise to conduct your evaluation. Foundations often allow nonprofits to designate percent of the total project budget for evaluation. Determine Goals. Before you design your evaluation, consider the reasons to do it. Quantitative or Qualitative? Decide if you will use quantitative or qualitative methods for your data collection, or what combination of the two types you will use.

Develop a good description of these methods and why you're using them. Integrate the Evaluation. Make sure the evaluation component of your proposal connects with the proposal's objectives and methods. If those targets and methods are measurable and time-specific, the evaluation will be easier to design. Keep Checking. Ask yourself these questions as you develop the evaluation section of your proposal:.

Actively scan device characteristics for identification. Use precise geolocation data. Select personalised content. Create a personalised content profile.