My research paper was completed as a requirement for the Educational Statistics and Research Methods course 5013, Research Methods in Education, through the University of Arkansas’s program in Educational Technology. This paper relied on survey data collected from anonymous volunteers in order to determine if there was a statistically significant correlation between one’s ability to stay motivated through challenges and failures and one’s level of education. The hypothesis put forward was that there would be a positive correlation, indicating that those who stayed motivated despite challenges were more likely to achieve higher levels of education than those who were not motivated by challenges.

While current research has addressed many aspects of student motivation, particularly how to keep (or get) students motivated, and other studies have examined the factors that might contribute to educational achievement (usually demographic), the relationship between motivation and achievement is less articulated. In 2003, the ESRM 5013 course developed a survey in which participants rated their level of motivation, among other factors, on a Likert scale. The survey also included demographic information, such as age, gender, and education level. In the research paper, I identified those surveys which would be applicable for my research question. The total number of participants was 158. Next, I identified which statements answered applied to motivation through challenges. After averaging those scores, I created four categories of educational achievement (High school, some college, undergraduate, graduate degree). After having completed these tasks, I conducted a chi-square test in order to determine whether there was a statistically significant correlation. The chi-square result was 6.6.5. With the alpha set at .05, I would have needed a result of 12.592 to be statistically-significant. Because our score is much lower than the tabled value, our result is not statistically significant.  Therefore, we must not reject the null hypothesis, and we must conclude that there is no statistically significant relationship between level of educational achievement and motivation to learn.

In this paper, I applied many of the skills that I learned throughout the course. In particular was the determination of relevant data and the performance of statistical tests to determine validity of results and prove (or reject) hypotheses. The process also emphasized the importance and practice of receiving IRB approval when conducting research using human participants. Finally, the paper required research into previous scholarship on topics of motivation and achievement, which further enhanced my abilities in using inline databases and search engines for educational scholarship.

The practice of identifying a research question, forming a hypothesis, gathering data, and testing that data using statistics was a very enlightening experience. My previous research in Classics had involved scholarly writing, but not from the social science framework. Additionally, the integration of statistical testing was eye-opening. My own dissertation involved some statistics on Greek inscriptions and I am hesitant to return to it because I fear my application was inadequate given what I have now learned. Most pertinent however, is that this process inspired me to apply for a grant to test the correlation between students who turn in homework and their performance on assessments. As Parish Episcopal School moves toward Competency-based education, they are limiting the weight of homework in favor of summative assessments. This results in many students questioning the need to do homework at all. I plan to conduct a statistical analysis between the percentage of homework assignments a student completes and how that student performs on their assessments.