Sample
The participants in the survey were recruited online from Amazon Mechanical Turk (Mturk) – a virtual crowdsourcing marketplace. However, before the recruitment process, Zhou and Zhang (2021) were required to obtain xxx IRB approval. As evidenced in the article, the screening criteria adopted targeted the college students currently studying in the U.S. To achieve the desired results, Zhou and Zhang (2021) utilized an online survey as the most appropriate data-gathering technique – they developed the online survey in Google Forms. Similarly, Amazon Mechanical Turk played a critical role in facilitating the creation of a Human Intelligence Task (HIT) which was used to complete the survey. The participants were allocated up to 30 minutes to complete the online job.
In line with the above, I believe the sample size of 62 participants is appropriate because the authors wanted to obtain answers that are precise and accurate. There was no bias introduced because the sampling strategy did not favor some outcomes over others. Similarly, the online survey was short and accessible to all the participants – they all had an equal chance of participating in the study.
Procedure
It is possible to replicate this study with the information provided. More specifically, a direct replication could be carried out but still yield the same results. One way of doing this is to carry out an online survey on high-school students to find out there overall learning process, mental health, and student support. The participants involved in the study can as well come from other countries, other than the U.S.
Data Analysis
The first type of data analysis performed in the survey article is descriptive analysis which was used to summarize data points related to the demographic information. The authors used descriptive analysis to gather basic information (mean and percentage) on each corresponding research question. Secondly, Zhou and Zhang (2021) performed a reliability analysis on all survey constructs. Lastly, inferential analyses were carried out to help understand the impact of student’s grades, genders, learning modes, and learning locations on the learning experience.
Results
The study’s findings of the study were presented – the authors simply stated the results without interpretation such as the use of percentages. More specifically, Zhou and Zhang (2021) categorized their results into two categories. The first category consisted of both the demographic and reliability results. The second category covered all the survey results related to the five research questions. In doing so, the authors managed to arrange the results in a logical sequence. In addition to this, tables and figures were used to display the results. For instance, tables were used to explain the demographic information related to the 62 participants – the tables helped simply the information that would otherwise be difficult to explain using text. Figures, on the other hand, were used to help readers visualize trends on the Overall Learning Experience scale.
Discussion
The authors provided a strong explanation of their findings by focusing exclusively on interpreting the results for the audience. Similarly, the authors while interpreting the findings, ensured they did not repeat findings in the result section. Zhou and Zhang’s (2021) discussion section gave rich information that effectively answered the research questions. Furthermore, the authors outlined their thoughts to defend their research through four major themes: Socioeconomic Impact on the Learning Community, Optimal Learning Location and Learning Mode, Improved Mental Health, and Overall Positive Learning Experience. These themes helped the authors delve deep into establishing the importance, meaning, and relevance of their results.
Limitations
As explicated in the study, the authors were not able to access students from campus due to the quarantine situation. This forced them to recruit their participants through an online survey platform. The authors further noted that they were not able to grow their sample size as they had originally anticipated. Lastly, the “variety of racial groups was limited with most participants being Asians at 66% and whites at 23%” (Zhou and Zhang, 2021, p. 16). However, these limitations did not translate to bias in results because the online ensured participants entered their responses directly into the system. In other words, the margin of error was low with this method.
Overall Thoughts of the Article
Overall, I liked the authors’ survey design, particularly the use of the Course Experience Questionnaire which consisted of 42 items. The questionnaire played a critical role in ensuring they gathered a large amount of data from a sample size of 62 participants. It offered a quick, effective, and inexpensive means of collecting data on 42 items. More specifically, the questionnaire had 6 items related to key demographic information such as age, gender, ethnicity, and family income. The remaining 36 items revolved around five major constructs as they relate to the five questions. It is important to note that the questionnaire guided Zhou and Zhang (2021) in investigating the learning experience of college students, one year after the start of school closure. I also liked how the authors utilized the Online Learning Experience Questionnaire and Well-Being Index (WHO-5) in developing the College Student Learning Experience Survey.
Reference
Zhou, J., & Zhang, Q. (2021). A survey study on US college students’ learning experience in COVID-19. Education sciences, 11(5), 248.