Imagine that you were asked to find out factors affect lecture session attendance among
students in higher learning public institutions in Tanzania. Assume also that you have been
instructed to use observational study designwhen undertaking this study. For you to come up
with reliable and at least valid findings:
a)Which type of observational study would you adopt? why?.
b)Withvivid examples (where necessary) discussstrengths and weaknesses of
observational research
a) The type of observational study that I would adopt in this case is a cross-sectional observational study. This involves collecting data from a sample population at a specific point in time. This study design would be appropriate because it allows for the collection of data regarding lecture session attendance and factors influencing it, within a specific timeframe. It would provide a snapshot of the current situation and enable the examination of various factors that affect attendance among students in higher learning public institutions in Tanzania.
b) Strengths and weaknesses of observational research:
1. Strength: Naturalistic Observation - Observational research allows researchers to observe behavior in its natural setting without interfering or manipulating any variables. In this case, attendance at lecture sessions can be observed without any external influence, providing insights into the actual behavior of students.
2. Strength: Ecological Validity - Observational research has high ecological validity as it takes place in real-world environments, such as lecture halls, where the behavior of interest naturally occurs. This increases the generalizability of the findings to the target population of students in higher learning public institutions in Tanzania.
3. Weakness: Observer Bias - Observational research is prone to observer bias, where the researcher's own biases and perceptions may influence the interpretation of behavior. To mitigate this, multiple observers can be trained and inter-rater reliability can be established to ensure consistent and unbiased observations.
4. Weakness: Limited Control - Unlike experimental designs, observational studies lack control over variables, making it difficult to establish causal relationships between factors and attendance. For example, while observational research can identify factors such as timing of classes or distance to lecture halls, it cannot determine if these factors directly cause low attendance.
5. Strength: Cost-effective - Observational research generally requires fewer resources and is less time-consuming compared to experimental research. It allows researchers to collect data without the need for extensive equipment or experimental manipulations, making it a cost-effective method for studying lecture session attendance.
6. Weakness: Lack of Privacy - Depending on the nature of the observational study, privacy concerns may arise. It is important to obtain ethical approval and ensure the anonymity and confidentiality of the participants' data. Observational research of lecture session attendance may require consent from the institutions and students involved, which could affect the overall validity of the findings.
Overall, while observational research has its strengths and weaknesses, it can provide valuable insights into the factors that affect lecture session attendance among students in higher learning public institutions in Tanzania. By managing potential biases and ensuring ethical considerations, the findings can contribute to informing interventions and policies aimed at improving attendance rates.
Mvomero District Council has 500 employees. As a young researcher you want to extract a
sample of 100 employees from them using simple random sampling. Explain steps you will
follow to come up with this sample size.
To extract a sample of 100 employees from the 500 employees of Mvomero District Council using simple random sampling, the following steps can be followed:
1. Define the population: Identify the population of interest, which in this case is all the 500 employees of Mvomero District Council.
2. Determine the desired sample size: Decide on the desired sample size, which in this case is 100 employees. This number should be based on statistical considerations and the amount of precision required for the study.
3. Assign numbers: Assign a unique number to each employee in the population. Each employee should have an equal chance of being selected.
4. Generate random numbers: Use a random number generator (such as a software program or a table of random numbers) to select the sample.
5. Randomly select the sample: Start by selecting the first random number and choose the employee with that corresponding number from the population list. Repeat this process until you have selected the desired sample size of 100 employees. Ensure that no employee is selected more than once.
6. Validate the sample: Once the sample is selected, double-check to ensure that it truly represents a random sample. Verify that each selected employee has been chosen correctly and that no bias has been introduced.
It is important to note that the steps above assume that a complete and accurate list of all 500 employees is available. Additionally, simple random sampling assumes that the population is homogenous, meaning that there are no distinct subgroups within the population. If there are subgroups of interest, it may be necessary to use stratified random sampling to ensure representation from each subgroup.
a) In this case, the most suitable type of observational study to adopt would be a cross-sectional study design. This is because a cross-sectional study involves observing and collecting data from a population at a single point in time, which allows researchers to gather information about the factors affecting lecture session attendance at that specific time. It provides a snapshot of the situation and enables the examination of associations between variables.
b) Strengths and weaknesses of observational research:
Strengths:
1. Naturalistic setting: Observational research allows researchers to study phenomena in their natural environment, making it possible to observe actual behavior without interfering or manipulating variables.
Example: In the context of lecture session attendance, researchers can observe students in their classrooms, taking note of factors like class size, teaching methods, and the availability of resources, without altering the conditions or enforcing certain behaviors.
2. High external validity: Observational research is generally considered to have high external validity, meaning that the findings can be generalized to other similar populations or settings. This is because the study takes place in a real-world setting rather than a controlled laboratory environment.
Example: Findings from an observational study on lecture session attendance in public institutions in Tanzania can be applied to other public institutions in the country or even to similar institutions in other countries.
Weaknesses:
1. Lack of control: One major weakness of observational research is that researchers have limited control over variables. They cannot manipulate or control certain variables to establish cause-and-effect relationships as experimental designs allow.
Example: While researchers can observe factors affecting lecture session attendance, they cannot manipulate those factors to definitively establish whether they directly influence attendance.
2. Potential for observer bias: Observational studies require researchers to be present during data collection, which introduces the possibility of observer bias. This bias can occur when researchers unintentionally influence or manipulate the data due to their personal beliefs, expectations, or interpretations.
Example: If the researchers have preconceived notions that smaller class sizes positively impact attendance, they might subconsciously focus more on instances where attendance is higher in smaller classes, leading to biased findings.
3. Limited ability to establish causality: Observational research, especially cross-sectional studies, can identify associations between variables but cannot establish causality. It is difficult to confirm if observed factors directly cause changes in attendance or if other underlying factors are at play.
Example: Suppose the study finds a positive correlation between lecture session attendance and student satisfaction with teaching quality. However, without experimental manipulation, it cannot be concluded that improving teaching quality will definitively result in increased attendance.
Overall, while observational research provides valuable insights into real-world settings, it also comes with limitations that need to be considered when interpreting the findings.
a) If the goal is to study the factors that affect lecture session attendance among students in higher learning public institutions in Tanzania using an observational study design, the most appropriate type of observational study to adopt would be a cross-sectional study.
Cross-sectional studies involve observing a group of individuals at a single point in time to collect data on exposure and outcome variables. In this case, the researcher would collect data on various factors that may influence lecture session attendance (such as class size, student motivation, scheduling conflicts, distance from campus, etc.) by observing and recording attendance and gathering information through surveys or interviews.
The reason for choosing a cross-sectional study design is that it allows the researcher to obtain a snapshot of the situation at a specific time, which is useful for understanding the current factors affecting lecture attendance. It is also relatively quick and cost-effective compared to other observational study designs, making it suitable for gathering data on a large population of students.
b) Strengths and weaknesses of observational research:
Strengths:
1. Naturalistic setting: Observational studies allow researchers to observe participants in their natural environment, which provides a realistic context for understanding behavior.
2. Real-time data collection: Observational research allows for the collection of real-time data, capturing behaviors and events as they naturally occur.
3. External validity: Findings from observational studies are often generalizable to real-life situations, as they are based on real-world settings and behaviors.
4. Ethical considerations: In some cases, observational research is the only ethical option when studying certain phenomena, as manipulating variables would be unethical or impractical.
Weaknesses:
1. Lack of control: Unlike experimental studies, observational research does not involve manipulation of variables, limiting the researcher's control over confounding factors. This can make it difficult to establish causal relationships.
2. Observer bias: Observational studies rely on human observation, which is subject to personal interpretation and bias. Researchers must be careful to minimize bias through standardized protocols and training.
3. Limited ability to establish temporal sequences: Observational studies may struggle to determine the order of cause and effect because they lack the temporal control found in experimental designs.
4. Inability to infer causality: Due to the lack of experimental control and potentially confounding factors, it is challenging to establish a causal relationship between observed behaviors and outcomes.
5. Recall bias: Participants may have difficulty accurately recalling past events or providing truthful responses, leading to potential recall bias, which affects the validity of the data collected.
Overall, observational research can provide valuable insights into real-world behaviors and phenomena, but careful consideration of its limitations is necessary when interpreting the findings.