Quantitative Analysis: Online vs. Face-to-Face Math Success
This paper presents a quantitative analysis of a study by Ashby, Sadera, and McNary (2011) examining student success in a developmental intermediate Algebra course across three learning environments: online, blended, and face-to-face. The analysis covers the study's purpose, participant demographics, research design, data collection methods, and statistical techniques — including ANOVA, Tukey's HSD, and chi-square tests. The paper also evaluates threats to validity, identifies opportunities for further research, and discusses implications of the findings for e-learning platform design and instructional strategy, drawing on Transactional Distance Theory and Bloom's Taxonomy Theory.
- Study Overview and Purpose: Purpose of the developmental math comparison study
- Participants and Sample Characteristics: Demographics and enrollment of 167 algebra students
- Research Design and Data Collection: Quantitative design and controlled data gathering methods
- Statistical Analysis Methods: ANOVA, Tukey's HSD, and chi-square testing approach
- Threats to Validity and Further Research: Validity concerns and gaps for future investigation
- Implications of the Findings: E-learning models and instructional design implications
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What makes this paper effective
- The paper systematically addresses each component of a quantitative study — purpose, sample, design, data collection, analysis, validity, and implications — providing a clear and organized critique.
- It connects the study's findings back to broader debates in the literature, such as the cost-effectiveness of e-learning and the role of student self-regulation in online environments.
- The discussion of validity threats goes beyond surface-level critique by identifying specific constructs — persistence, ethnic background, gender — that remain inadequately measured in the original study.
Key academic technique demonstrated
The paper demonstrates structured quantitative article analysis, a core graduate-level skill in which the student evaluates a published study across multiple dimensions: methodological rigor, sampling strategy, statistical appropriateness, and validity. By referencing supporting literature (Arias et al., 2018; Abuhassna et al., 2020), the student situates the original study within a wider scholarly conversation rather than treating it in isolation.
Structure breakdown
The paper is divided into a summary section — covering purpose, participants, research design, data collection, and statistical analysis — followed by an analysis section that addresses future research opportunities, threats to validity, original criticism, and implications. This two-part structure mirrors the standard format for academic article critique assignments at the graduate level, separating descriptive reporting from evaluative commentary.
Study Overview and Purpose
The purpose of the selected study was to evaluate student success in a developmental math course across three different learning environments: online, blended, and face-to-face (Ashby, Sadera & McNary, 2011). By comparing outcomes across these modalities under controlled conditions, the study sought to determine whether the mode of course delivery meaningfully affects student performance in developmental education.
Participants and Sample Characteristics
Demographic data, standardized intermediate Algebra Competency test scores, and unit test grades were obtained from 167 participants enrolled in an intermediate Algebra class at a college. The participants had either passed a previous developmental course or been placed into the course directly based on their placement test scores. There was considerable variability in the sample's demographic and academic characteristics. Students included recent high school graduates as well as non-traditional returning students, with an average age of 25.5 years. The sample included 97 females, with ethnic backgrounds of 49% Caucasian and 43% African American. The sample was also split between full-time and part-time students, at 48% and 52% respectively.
Students were given the option to select their preferred learning environment, resulting in 35% enrolling in face-to-face classes, 28% in blended classes, and 38% in online classes. It was noted that online classes had the oldest participants on average and included a higher proportion of female students.
Adjustments were made for attrition, since attrition rates are particularly high at community colleges and simply retaining students through course completion was a significant challenge. Completion of unit tests and the final exam proved difficult for many students. Missing grades and exam data varied by learning environment and required statistical adjustment.
Research Design and Data Collection
The study utilized a quantitative research methodology to compare student success across the three learning environments. The research questions examined whether the learning environment affected students' success as measured by test scores, final exam performance, and course grades, and whether course performance was related to attrition. For students to be considered successful and eligible for college-level math, their success rate needed to be 70% or higher. Comparisons therefore had to account for equal course completion rates and adjust for attrition.
Data were collected from all three learning environments: online, blended, and face-to-face. Demographic information was obtained from the college database with students' prior informed consent. Because the learning environments differed structurally, measurements were carefully standardized to allow meaningful comparisons. All three groups followed the same syllabus, course content, and assignment deadlines. Measures to discourage cheating were implemented to ensure test score fairness across groups. Test questions were evaluated for comparable difficulty levels and alignment with course content and objectives. Time limits and grading rubrics were identical across all three environments.
Students in face-to-face courses completed tests using pencil and paper, while students in online and blended courses completed equivalent online versions of the same tests. Tests were scheduled over a three-day period to accommodate the different attendance and scheduling patterns across the three learning environments.
Statistical Analysis Methods
Comparisons among the three learning environments were conducted using ANOVA (Analysis of Variance). Tukey's HSD (Honestly Significant Difference) test was employed to follow up on significant main effects and to detect pairwise differences between groups. Chi-square tests were used to identify statistically significant differences between categorical variables. The significance level for all tests was set at 0.05.
References
Abuhassna, H., Al-Rahmi, W.M., Yahya, N., Zakaria, M.A.Z.M., Kosnin, A.B.M. & Darwish, M. (2020). Development of a new model on utilizing online learning platforms to improve students' academic achievements and satisfaction. International Journal of Educational Technology in Higher Education, 17. https://doi.org/10.1186/s41239-020-00216-z
Arias, J.J., Swinton, J. & Anderson, K. (2018). Online vs. face-to-face: A comparison of student outcomes with random assignment. E-Journal of Business Education and Scholarship of Teaching, 12(2), 1–23.
Ashby, J., Sadera, W.A. & McNary, S.W. (2011). Comparing student success between developmental math courses offered online, blended, and face-to-face. Journal of Interactive Online Learning, 10(3), 128–140.
Heale, R. & Twycross, A. (2015). Validity and reliability in quantitative studies. Evidence-based Nursing, 18(3), 66–67.
Saba, T. (2012). Implications of e-learning systems and self-efficiency on students' outcomes: A model approach. Human-centric Computing and Information Services, 2. https://doi.org/10.1186/2192-1962-2-6
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