Competency L

Preparation and Evidence

I avoided this competency but knew it was not the last competency I wanted to write. I avoided it because I knew I did not have enough material for this competency. A small number of my classes focused on Competency L, but the main class the comes to mind is Professor Liu's INFO 285 Applied Research Methods. For Professor Liu's class, we focused on learning about quantitative and qualitative research by engaging in a series of assignments and projects that would cultivate our understanding of the subject by using SPSS Statistics software to test our research. The main project for this course allowed us to learn how to use SPSS Statistics software in case we needed to perform tests in our research.

The main scope of my project focused on the topic of multitasking in students to test its effectiveness. Many psychologists state that the cognitive brain is not trained to perform task divisions because its structure functions as one processor and not multiple. The fact that people can switch between tasks does not mean they can multitask. Engaging in task switching can result in the loss of information as the brain attempts to make the transition between assignments. Now, with the boom of modern technology over the past decades, students are encouraged to use new technologies to advance and adapt to new learning initiatives. One of the main questions I asked during the initial stage of my research is, does multitasking enhance the learning experience or does it hinder academic success? Sources indicated that many professors felt multitasking was a distraction, while tested research declared that those who did not engage in multitasking performed exceptionally well in exams.

As I engaged in the information-gathering process, I came across many materials that focused on the study of the brain or that examined how professors test or analyze multitasking behavior. This information prompted me to focus my studies from a different angle and examine students attitudes on multitasking. One way to approach this examination would require me to use SPSS statistics and perform multiple tests, which is the evidence I present to you for this competency.

Although test research for this class was hypothetical, I took the opportunity to apply these skills to real-life situations to better understand how to measure data. I surveyed ten students in my quantitative research (INFO 285 SPSS Report), which is what I had access to at the time, and recorded their age, gender, and academic level. Next, they were asked the following questions:

• Have you enrolled in online courses, physical classes, or a combination of both?
• Have you engaged in multitasking behavior in any of these environments?

In my final paper, I described how I would utilize this survey in an academic setting to gain more results from diverse students, but for now, we will examine the results from the ten students that were surveyed.

I used a Chi-Square Statistic test using SPSS. "The Chi-Square statistic is commonly used for testing relationships between categorical variables" ("Using Chi-Square statistics in research," 2019) and this test hoped to evaluate the relationship between multitasking in diverse academic settings. This type of test is also known as the Test of Independence, which "assesses whether an association exists between the two variables by comparing the observed pattern of responses in the cells to the pattern that would be expected if the variables were truly independent of each other" ("Using Chi-Square statistics in research," 2019). For my report, I listed the following variables: age, gender, academic level, online courses, school courses, and multitasking. When I performed a crosstab reference, there were problems with the results. The age variable produced false results, indicating that multiple users were surveyed, which was not the case. My information-seeking behaviors, as Kuhlthau would describe, had me feeling dubious and overwhelmed. Being new to the subject, I was not sure where the problem lied, but I knew I had to rearrange the variables. In the next Chi-Square test, I removed certain variables and crosstab reference the variable age with the variable multitasking. I decided to crosstab these variables because I wanted to compare multitasking against different age groups. I had also considered performing a crosstab reference between variable gender and variable multitasking, but the results would not provide as many details as the variable age, or so I concluded.

For our second assignment, I performed a T-Test and a Pearson Correlation Test. In a T-Test, you examine two groups and test them against the same value to note if there exist any differences in the average value. I ran four sets of T-Tests because each time I performed a test, results were inconclusive. For the first test, I classified the independent variable as gender and in-class multitasking as the dependent variable. Then, I separated them because I wanted to compare them between my two groups, which were males and females. For any statistical test you perform, you must always ask a question which serves as the foundation of your test. The question that drove the analysis is, do you multitask during class time? This question reflects both online students and in-school students. The first T-Test did not produce any test of any kind, which had me questioning what I did wrong. Next, I decided to change the numeric values to string values, and this also provided negative results. In the third test, I reverted back to a numeric value for the independent variable and identified the groups using numerics. Again, results were inconclusive. During each examination, I was optimistic that I would produce conclusive results because I kept changing variables hoping that would solve the problem. In my final attempt, I modified the independent variable. The new independent variable would reflect the variable degree type, and the dependent variable remained as multitasking. Results were inconclusive because the numeric value was the same as the numeric value for the groups that were tested. Reflecting on these exams, I cannot help but feel detained or stuck in the information-seeking behavior life cycle. The purpose of evaluating information is to present conclusive results to your audience, and I am unable to pass the T-Test with the variables I have selected. As noted, I did not take many courses that focus on Competency L or performed assignments that test quantitative or qualitative data. From my T-Test, I hoped to gain an analysis between different genders to examine if a particular gender was more engaged in multitasking than the other gender, or if results were relatively the same. Although I could analyze collected surveys to draw conclusions, the purpose of running statistical tests is to present measurable data and analysis during research investigations.

The Pearson Correlation Test was a smoother process than the T-Test examinations. For this test, I identified two categories, Multitask_School, and Multitask_Online, which attempts to identify in what kind of setting multitasking is more prevailing. "A Pearson correlation is a number between -1 and 1 that indicates the extent to which two variables are linearly related" ("Pearson correlations: Quick introduction," 2019). The -1 and 1 are represented by variable r in the test, which examines how far apart the tested groups are from each other in a linear graph. If the variable is indicative of these values, then there is a positive correlation between the groups. The Pearson Correlation Test I performed shows that correlation exists between Multitask_School and Multitask_Online when r=1. The results indicate that the setting does not change multitasking behavior; in fact, the results are the same, so students do not have a preference in setting when they choose to engage in multitasking behavior. I believe the results for this test to be true because, in my research, I came across articles that surveyed university students, and they declared that they engage in multitasking behaviors while doing homework as much as they did in class.

For the final research paper, I did not include these samples because they do not reflect results at the university level. In the paper, I clarify that measuring quantitative and qualitative data would need to occur at the university level where I could survey multiple students in diverse universities. The instruments used to test responses will measure the following:

• Quantitative data analyzes frequency levels that provide a statistical analysis of how many times students engage with devices to view messages or check news feed notifications. Secondly, these tests will observe how class information is recorded as students multitask.
• Qualitative data provides a statistical overview of which social networking sites are popular among students.

The literature review analyzes results from the University of Connection and other studies that focused on multitasking behavior between students from the U.S and Europe, or that examined test results between students that did and did not engage in multitasking behavior while in class.

The components in my final research paper cultivate my understanding of research practices in information science. Research is designed by proposing a theory or idea to study and designing a plan that will test your theories against attained results. The research study is an ongoing investigation of behavioral patterns, in my case of multitasking behavior, to provide an analysis. Initially, the scope of this research focused on students opinion on multitasking behavior and its effects on academic success; however, as new inquiries surfaced, the scope of this research proposed new theories and concepts to examine.

Future Applications

Theoretical frameworks are necessary for information science to develop a deeper understanding of research practices. Research practices begin at an early stage when people retrieve information. The information retrieved ultimately builds a hypothesis or proposes a research problem that designs a study. To achieve results, the academic or information professional will engage with information at a personal level where the research examine their data against quantitative and qualitative tests. These tests are geared towards finding linear similarities between the subject and the product to provide conclusions on their effect on one another. Research practices and elements are instrumental in the field of library science to test new theories related to LIS or to guide scholars in their research.