SAMPLE RESEARCH STUDY PAPER WITH SURVEY QUESTIONNAIRE

Introduction

This paper discusses a research study conducted on college students’ technology usage and its effect on academic performance. The main goal of this study was to understand how much time college students spend using technology for recreational purposes like social media, gaming, streaming services etc. and whether that impacts their Grade Point Average (GPA). Excessive usage of technology for non-academic reasons is a concern that is often discussed both in academic and popular media. There is limited empirical research quantifying the relationship between technology usage and GPA. This study aims to fill that gap by surveying college students and analyzing the relationship between self-reported technology usage and actual GPA data.

Literature Review

Several past studies have looked at the relationship between technology usage and academic performance in college students but the findings have been mixed. Some studies found a negative correlation between non-academic technology usage and GPA (Junco, 2012; Jacobsen & Forste, 2011; Kirschner & Karpinski, 2010; Rosen et al., 2013). Other studies did not find conclusive evidence of such a relationship (Foster et al., 2015; Bowman et al., 2010; Unal & Unal, 2017). One limitation of prior research is reliance on self-reported academic performance without access to actual grade data. Self-reported grades could be prone to over-estimation and bias.

Prior studies varied in how they defined and measured technology usage. Some looked at broad categories like social media usage while others focused on specific apps or websites. They also differed in whether usage was measured in hours per day or weeks. This variation in measurement makes it difficult to compare findings across studies. The current study addresses some of these limitations by using a well-defined survey to capture self-reported technology usage across specific apps/websites and linking it to actual GPA data obtained from university records.

Hypotheses

Based on the mixed findings of prior literature but a majority showing a negative correlation, the current study hypothesized the following:

H1: Students who spend more time on technology for non-academic purposes will have lower GPAs.

H2: Increased usage of social media specifically will be negatively associated with GPA.

H3: Increased usage of streaming services/online gaming will be negatively associated with GPA.

Method

Participants
The study sample consisted of 200 undergraduate students enrolled at a public university in the Midwest region of United States. The inclusion criteria were that participants had to be currently enrolled full-time undergraduate students aged between 18-22 years.

Materials and Measures
A 28 item online survey was used to collect self-reported data from participants (see Appendix A for full survey). The survey collected following information:

Demographic information like age, gender, year of study

Self-reported cumulative GPA on a 4.0 scale

Estimated weekly hours spent on various technology activities:

Social media usage across platforms like Facebook, Instagram, Twitter etc.
Online streaming services like Netflix, Hulu, YouTube etc.
Online gaming platforms

General internet browsing and other technology usages

Survey also included validation questions to check for careless or inconsistent responding

Procedure
After obtaining IRB approval, participant recruitment emails were sent through the university registrar’s listservs for undergraduate students. The emails contained a short description of the study along with a link to the online survey hosted on Qualtrics. Participants provided informed consent and then completed the anonymous online survey which took approximately 10-15 minutes.

At the end of the data collection period, cumulative GPA data for participants was obtained through the registrar’s office with participant identifiers removed to ensure anonymity during analysis. Self-reported GPA was then compared to actual GPA data to check for accuracy. Cases with discrepancies greater than 0.5 GPA points were removed prior to analysis to reduce potential bias from inaccurately reported grades.

Analysis Plan
To test the hypotheses, bivariate correlational analysis as well as multiple linear regression was conducted in SPSS. Specifically:

Bivariate correlations were run between technology usage variables (social media, streaming, gaming, total hours) and actual GPA

Multiple linear regression analysis was performed to examine if technology usage variables predicted variance in GPA while controlling for demographic factors.

Results

Sample Characteristics
The final sample consisted of 180 participants after removing cases that failed data validity checks. The average age was 20.1 years (SD=1.3). There were slightly more women (56.7%) than men in the sample. Freshmen made up 33.3% of participants, sophomores were 29.4%, juniors 26.1% and seniors 11.1%.

The mean self-reported GPA was 3.28 (SD = 0.48) and mean actual GPA obtained from records was 3.30 (SD = 0.46), indicating minimal discrepancy between self-reported and actual grades on average.

Technology Usage Patterns
On average, participants reported spending 11.2 hours per week (SD=7.6) on technology for non-academic purposes. Breakdown of usage across different platforms/activities is shown in Table 1.

[Insert Table 1 showing means and standard deviations of estimated weekly hours spent on social media, streaming services, online gaming and total non-academic technology usage.]

Bivariate Correlations
As displayed in Table 2, bivariate correlation analysis revealed:

A small negative correlation between total weekly non-academic technology hours and actual GPA (r = -0.149, p < 0.05) A slightly stronger negative correlation between social media usage hours and actual GPA (r = -0.189, p < 0.01) No significant correlation between streaming or gaming hours and GPA [Insert Table 2 showing bivariate correlations between technology usage variables and actual GPA] Multiple Regression A multiple linear regression was conducted to examine predictive relationships between technology usage and GPA while controlling for demographic factors of age, gender and year of study. As seen in Table 3, the full model significantly predicted GPA and explained 8.2% of its variance, F(6, 173) = 2.505, p < 0.05. Specifically, higher social media usage hours significantly predicted lower GPA (β = -0.189, p < 0.05) after controlling for other variables. Total non-academic technology hours showed a weak trend of predicting lower GPA but it was not statistically significant in the full model. None of the demographic variables or other technology usage activities significantly predicted GPA. [Insert Table 3 showing results of multiple linear regression analysis with technology usage variables and demographics predicting actual GPA] Discussion The current study investigated the relationship between college students' technology usage patterns and their academic performance measured by GPA. Overall the findings provided partial support for the hypotheses. Higher total weekly hours spent on non-academic technology showed a small negative correlation with GPA, supporting H1. Increased social media usage in particular emerged as the strongest unique predictor of lower GPA even after accounting for other factors, supporting H2. No significant relationships were found between streaming or gaming activities and GPA, failing to support H3. Notably, the amount of variance explained in GPA was relatively small at around 8%, suggesting that while technology usage may play some role, students' academic achievement is determined by numerous complex factors beyond technology alone. This does not diminish the value of quantifying specific relationships observed that are consistent with findings in prior literature. The fact that social media showed the strongest link to lower grades aligns with concerns expressed by educators and researchers.