Discussion HUM670
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School
National University College *
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Course
670
Subject
Communications
Date
Apr 3, 2024
Type
docx
Pages
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Uploaded by MateScience10909
Week 1 Initial Introduction:
Proofreading is essential in the writing process to ensure clarity and accuracy in communication. However, the effectiveness of different proofreading methods remains a topic of interest. This study aims to investigate whether reading passages silently or aloud influences the detection of typographical errors. Research Problem:
The study aims to address the question: Is there a significant difference in detecting typographical errors when reading passages silently and aloud?
Hypothesis:
H1: Reading passages aloud will result in a significantly higher detection rate of typographical errors than reading silently.
Definitions:
Independent Variable (IV): The independent variable in this study is the type of proofreading performed, with two levels: 1) reading silently and 2) reading aloud.
Dependent Variable (DV): The dependent variable is the number of typographical errors detected while proofreading.
Testing the Influence of the IV on the DV:
A between-subject design will be employed to test the influence of the independent variable (reading method) on the dependent variable (typographical error detection rate). Participants will be randomly assigned to either the silent or aloud reading groups. Each participant will be given the same passage to proofread, with instructions to read it silently or aloud. The typographical errors detected by each participant will be recorded and compared between the two groups.
Qualitative Study Approach:
The approach to conducting a qualitative study would involve gathering insights and experiences from participants regarding their preferred proofreading methods and perceptions of effectiveness. This could include conducting interviews or focus group discussions to explore the nuances of proofreading practices and their impact on error detection.
Conclusion:
In summary, this study investigates the effectiveness of different proofreading methods in detecting typographical errors. By examining whether reading passages silently or aloud influences error detection rates, this research aims to provide insights that can benefit individuals engaged in written communication, such as students, professionals, and academics.
Hello, I am very excited to be taking this course. However, it also stumped me in my undergrad program. When testing, I overthink the differing methodologies, so I hope my study's assumptions prove correct. Quantitative Study Choice:
The choice to conduct a quantitative study stems from the need to quantify the potential difference in typographical error detection rates between reading passages silently and aloud. Quantitative methods allow for precise measurement and statistical analysis, which is well-suited
for testing hypotheses and identifying relationships between variables.
Correlational or Associational Study:
Given that the study aims to investigate whether there is a significant difference in error detection rates based on the proofreading method (silent vs. aloud reading), it would likely fall under the category of an associational study. This is because the study seeks to identify an association between the independent variable (reading method) and the dependent variable (error
detection rate). By comparing the error detection rates of participants who read silently with those who read aloud, the study aims to determine if there is a relationship between the two variables.
Coursebook Reading Integration:
Gliner et al. (2009) discuss the importance of random assignment in experimental design to ensure that participants are assigned to experimental conditions unbiasedly. This principle supports the study's random assignment of participants to silent or aloud reading groups.
Gliner et al. (2009) also highlight the significance of controlling for extraneous variables that could influence the dependent variable. This concept reinforces the need to control factors such as reading level, attention span, and environmental conditions to minimize their potential impact on error detection rates.
Gliner et al. (2009)discuss strategies for ensuring the validity and reliability of research findings. This could include techniques for designing measures and procedures that accurately assess the variables of interest. Applying these principles strengthens the study's credibility and the interpretation of its results.
Gliner et al. (2009) cover various statistical methods for analyzing data in quantitative research. This includes techniques for comparing means between groups, such as t-tests or analysis of variance (ANOVA), which would apply to comparing error detection rates between the silent and aloud reading groups. Gliner et al. (2009) discuss ethical considerations in research, such as obtaining informed consent and protecting participant confidentiality. Integrating these moral principles into the study design and implementation ensures that the research is conducted ethically and upholds the
rights of participants. Hypothesis and Definitions:
The hypothesis for the study could be stated as follows:
H1: There will be a significant difference in typographical error detection rates between participants who read passages silently and those who read them aloud.
Independent Variable (IV): The independent variable in this study is the method of proofreading,
with two levels: 1) reading silently and 2) reading aloud.
Dependent Variable (DV): The dependent variable is the number of typographical errors detected
while proofreading.
Reference Gliner, J. A., Morgan, G. A., & Leech, N. L. (2009). Research methods in applied settings: An integrated approach to design and analysis (2nd ed.). New York, NY: Routledge.
The relationship between the proofreading method and typographical error detection rates will be
tested using a randomized between-subjects experimental design. Participants will be randomly assigned to either the silent or aloud reading group. They will then proofread the same passage containing typographical errors, and the number of errors detected by each participant will be recorded and compared between the two groups using statistical analysis. This approach ensures a systematic investigation of the relationship while controlling for potential confounding variables.
Yes, I am open to alternatives. I would use Survey Monkey and post it on my social media platforms, allowing up to 30 people to participate. However, your idea seems more doable. I could do five v. five. I appreciate the new perspective. I will definitely go forward with the five v. five with family and
friends. Since your suggestion, I have contacted friends and family who are willing to participate. I was under the impression I needed a large number of participants. Having a smaller sample will allow for more accurate data representation.
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Overview of Research Design:
This study employs a between-subject design to examine the impact of two proofreading methods, silent and aloud, on typographical error detection rates. The research hypothesis posits that reading aloud will result in more errors detected than reading silently. The study aims to determine whether there is a significant difference in error detection rates between the two conditions.
Description of Participants and Sampling Strategies:
Participants will be recruited from San Bernardino County using convenience sampling. The study will include five participants assigned to the silent reading group and five participants assigned to the aloud reading group. This sampling strategy ensures a balanced representation of both proofreading methods within the study.
Description of Measures for Data Collection:
Data collection will involve participants reading a passage from Henry Cloud and John Townsend's book "Boundaries," which contains 230 words and eight typographical errors. Participants will be instructed to proofread the passage and identify the mistakesa. Additionally, demographic information such as gender, age, ethnicity, and education level will be collected.
Procedure for Data Collection:
Participants will receive an email containing a link to a Survey Monkey survey. They will provide consent and complete the demographic information. Depending on their assigned condition, they will read the passage silently or aloud and identify the typographical errors. There will be no time limit for completing the task, allowing participants to read at their own pace.
Plan for Data Analysis:
Data analysis will compare the mean errors detected between the silent and aloud reading groups
using a t-test with independent samples. This statistical analysis will determine if there is a significant difference in error detection rates based on the proofreading method. Additionally, the
analysis may include demographic variables as covariates to control for potential confounding factors. Since the small sample size, non-parametric tests may also be considered for analysis.
Gliner et al. (2009) emphasize the importance of selecting appropriate research designs based on the research question and objectives. My recruitment aligns with the authors because they
highlight various sampling strategies, including convenience sampling, the route I will be taking,
and how it is suitable for certain research contexts, especially when practical constraints exist.
Gliner et al. (2009) outlined principles regarding data collection procedures are tailored to the specific research objectives and variables of interest. Additionally, including demographic information aligns with the author's emphasis on gathering relevant participant characteristics to enhance the understanding of study outcomes. The authors also guide the selection of appropriate
statistical tests based on the research design and data characteristics. As outlined in the book, the consideration of demographic variables as potential covariates also reflects the authors' adherence to best practices in data analysis. Lastly, Gliner et al. (2009) acknowledge the small sample size and suggest considering non-parametric tests for analysis. They state it is a cautious approach and recommend assessing the appropriateness of statistical assumptions and selecting alternative methods when necessary, especially in studies with limited sample sizes.
I am trying to have as diverse a sample as possible, and I would love to have older and younger generations as well as at least one on each side whose second language is English.
Since we last spoke, I have changed my method section to reflect that first week's discussion. As well as find more relevant articles I may be able to utilize. Thank you for all your input!
Measure: The primary measure used in this study is the passage from Henry Cloud and John Townsend's book "Boundaries," which contains 230 words and eight typographical errors. These errors consist of either the deletion or addition of a letter, altering the appearance of the original word.
Plan for organizing data:
Data Collection: Participants will read the provided passage and identify typographical errors. The errors identified by each participant will be recorded.
Data Entry: The identified errors from each participant will be entered into a spreadsheet.
Coding: Each error will be coded based on its type (e.g., deletion, addition) and location within the passage.
Grouping: Data will be organized based on the proofreading method employed by participants (reading silently or aloud).
Data Cleaning: The data will be checked for errors or inconsistencies and cleaned accordingly before analysis.
Data Analysis: Statistical analysis will be conducted to compare the error detection rates between
the two groups (silent reading vs. reading aloud).
Plan for analyzing data:
Descriptive Statistics: Calculate the mean, median, mode, and standard deviation for each group's error detection rates. Utilize descriptive statistics to summarize and describe the data collected from your study. Gliner, Morgan, and Leech (2009) emphasized the importance of descriptive statistics in providing a clear and concise summary of the data, including measures of
central tendency (e.g., mean) and variability (e.g., standard deviation). This will help to understand each group's overall error detection rates and identify any patterns or trends.
Comparative Analysis: Perform inferential statistical tests (e.g., t-test, chi-square test) to compare the error detection rates between the silent reading and reading aloud groups. Conduct a
comparative analysis to determine if there are significant differences in error detection rates between the two proofreading methods. According to Gliner, Morgan, and Leech (2009), inferential statistics, such as t-tests or analysis of variance (ANOVA), can be used to compare means between groups. This statistical approach will allow to assess whether any observed differences in error detection are statistically significant.
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Subgroup Analysis: Consider conducting subgroup analyses to explore potential differences in error detection based on demographic variables such as age, gender, or education level. Gliner, Morgan, and Leech (2009) highlighted the importance of subgroup analyses in identifying potential moderators or factors that may influence the relationship between the independent and dependent variables.
Qualitative Analysis: Optionally, analyze any qualitative data collected during the study, such as participant feedback or comments on their proofreading experience. Gliner, Morgan, and Leech (2009) discussed various qualitative analysis techniques, such as thematic or content analysis, which can provide valuable insights into participants' experiences and perceptions.
Exploratory Analysis: Explore any potential patterns or trends in error detection rates within each group.
Reliability and Validity Checks: Assess the reliability of error detection within each group by examining inter-rater agreement. Validity checks should be considered by comparing participants' error detection with known correct answers.
Bias Checks: Investigate potential biases in error detection based on participant demographics (e.g., age, gender, education level) or other factors (Gliner, Morgan, & Leech, 2009).
Thank you for your feedback on my research proposal. I appreciate your guidance and suggestions for improvement. Based on your comments, I have made revisions to address the issues you raised.
Bias Checks and Reliability:
I have removed bias checks from the methodology section, as I acknowledge that reliability and face validity may be compromised due to the absence of a standardized instrument. Per your recommendation, I have cited insights from our coursebook, "Research Methods in Applied Settings: An Integrated Approach to Design and Analysis" by Gliner, Morgan, and Leech (2009),
to support this decision.
Statistical Analysis:
For the statistical analysis, I used a t-test to compare the error detection rates between the two proofreading methods. This decision is justified by the coursebook's emphasis on inferential statistics for comparing means between groups. I have omitted ANOVA as per your instruction.
Demographic Differences and Sample Size:
I have noted your concern regarding the small sample size and have refrained from conducting analyses for demographic differences. Subgroup analysis has been limited to overall and specific types of error detection, which aligns with your recommendation.
Data Collection and Subgroup Analysis:
Regarding data collection, I will track the number of errors detected and the specific errors marked by participants. This information will inform the subgroup analysis, allowing for a more comprehensive examination of error detection strategies.
Thank you for the feedback. I greatly appreciate it. I must admit I am feeling uncertain about the methodology section of the research.