Learning Communities as Interdisciplinary Teams

Introduction

This paper presents a review and critique of the article that utilized a quasi-experimental research design. The selected study investigated the benefits of learning communities and presents three hypothesis, which stated that students might have higher average grades and retention rates, as well as completed more credits while involved in learning communities. The study utilized a longitudinal design and was performed during a two-year period.

The paper discusses its research questions, design, the collected data and the findings, as well as the validity of the measurements and approaches the authors used. It also considers the threats to internal validity and the external validity of the study. The paper analyzes the conclusions of the authors and concludes that the findings of the research are valid, and may be utilized in the other context and applied to practice.

Primary Research Questions

The selected study is aimed to analyze the learning outcomes of students who join learning communities. The authors insist that their objectives are to develop connections among first-year students, create meaningful interactions among students and professors, and adjust the curricular time to the needs of both students and teachers (Yungbluth & Waldron, 2007). The study presents three hypothesis, which can be transformed into research questions.

The first one is: Do learning community participants have higher average grades compared to other first-year students? The second research question is: Are first year retention rates higher for learning community participants? Finally, the last question is: Do learning community participants complete more course credits in their first year compared to other students?

Research Design

The research utilized a quasi-experimental, longitudinal design (Yungbluth & Waldron, 2007). According to Becker et al. (2017), in this study design, the researcher does not have the “full control over the scheduling of experimental stimuli”, which allows for an experiment (p. 86). The research included 251 participants, all of them were first-year students and members of the inaugural class; 63 of them were part of the comparison group (Yungbluth & Waldron, 2007).

The individuals involved in the study were divided into two groups; the first one presented the Science Cohort, while students of the second one enrolled in six learning communities (Yungbluth & Waldron, 2007). The equivalence between the groups was determined during preliminary testing. All of the participants had been involved in training sessions before the experiment, which included exercises on team- and community building, as well as discussions on first-year students’ learning characteristics.

Collected Data

The gathered data considered students’ grade point average (GPA) scores, as well as the completion of a credit hour, and retention rates. The authors also collected information about individuals’ gender and ethnical background. Moreover, they gathered information about the communication demands of learning communities to ensure that they met the minimum of requirements, which included at least three meetings of instructional teams during the semester, the availability of library sources, and the ability of students to interact with staff members (Yungbluth & Waldron, 2007). The data about the outcomes of learning communities based on the surveys was also collected.

The Validity and Reliability of Measurements

As mentioned above, to measure the change in students’ academic performance, Yungbluth and Waldron (2007) calculated individuals’ GPA, the completion of a credit hour, and retention rates several times during two academic years. The measurement of the first two criteria was taken after the first semester, at the end of students’ first academic year, and at the end of their second academic year.

The data about retention was calculated after the first academic year, and before and after the second one (Yungbluth & Waldron, 2007). The utilized measurements can be considered reliable and valid as the authors ensured that learning community students experienced more communication opportunities than other individuals did. To do so, the authors conducted end-of-semester and phone anonymous surveys. Moreover, they encouraged staff to participate in discussions to receive commentary on the learning community experience. It means that the authors utilized both qualitative and quantitative approach to measure the results, which proves their accuracy.

Statistical Approaches

The authors utilized several statistical approaches as they aimed to test the hypothesis and examine a relationship between several variables. To collect data, they used both qualitative and quantitative methods. The first one was involved in the assessment of students’ scores and learning outcomes, as well as the data obtained during surveys. The quantitative approach was implemented during the assessment of students’ perspectives on the changes in their performance, relationships within groups and with staff, and general learning outcomes. The utilization of several statistical methods allowed to conclude that the quasi-experimental design of the study was successful for the purposes of the research.

Appropriateness of Methods

The selected study methods may be considered appropriate to the research questions and the collected data. The primary reason for it is that the authors intended to compare the performance of two groups of students, which implied the necessity of the utilization of the qualitative approach. Moreover, the study used surveys among individuals and staff members, which involved the collection of statistical data. It is necessary to mention that the utilization of the quantitative approach was also reasonable it allowed for investigation of the benefits of communication practices within learning communities.

Threats to Internal Validity

The authors did not address threats to internal validity of the study specifically. However, they mentioned that there was a possibility of selection bias due to the fact that all students had clear career objectives and were motivated to achieve their study goals. This decision not to discuss threats to internal validity may be reasonable because, for example, the selection was controlled, there were no changes in measurement, and interfering events were not likely to occur.

However, I believe that the authors should have considered several factors that could affect the validity of the study. First, they should have examined the attrition factor, as some of the participants could have decided to stop participating in learning communities. Yungbluth and Waldron (2007) did not mention whether any of the students left the experiment. Moreover, they did not refer to maturation as a potential threat to internal validity. However, considering that the individuals could have changed their attitude towards learning, or implement different studying techniques with time as they gained more experience as students, which could have affected their learning outcomes and final scores as well.

External Validity

The external validity of the study can be considered at a high level, which means that its conclusions may be applied outside the context of the research. For example, Zacharis (2015) notes that collaborative learning may improve students’ learning outcomes. It implies that participation in learning communities may be beneficial for them.

Moreover, the authors mentioned that students’ communicative capacities and relationships with faculty members improved as well, which means that the principles of learning communities may be applied to other models aimed to improve individuals’ performance in educational institutions and other settings. It is necessary to mention that the research was conducted among the students of the same state university. However, this fact cannot potentially affect the external validity of the study as the authors ensured the high degree of variation among the participants.

Authors’ Conclusions

The authors mentioned the following conclusions associated with the implementation of learning communities. First, they stated that participants’ GPA rates were significantly higher compared to other students’ ones (Yungbluth & Waldron, 2007). The differences in retention rates were not highly evident. The study also proved that learning community students completed more college credits than those that were not involved in the initiative.

Moreover, the authors also noted that learning communities played a significant role in improving intellectual connections between individuals, the quality of their social interaction, high levels of faculty accessibility. However, they reported several challenges as well, including the negative feedback on the Uni 101 component of learning communities’ activities and the occupational status differences among staff and faculty (Yungbluth & Waldron, 2007). The authors concluded that the results indicated positive student outcomes associated with the integration of learning communities.

It is necessary to mention that the authors concluded that there were several methodological issues and limitations associated with the study. First, they pointed out the possible selection bias and the lack of stability within the campus (Yungbluth & Waldron, 2007). Second, they noted that there were expectancy effects as instructors might have expected the improvement in students’ performance and scores. Moreover, the sample size of the study implied was relatively small; the authors concluded that the replication of the research with larger samples would be necessary for the future research (Yungbluth & Waldron, 2007). Although there were some limitations to the study, the results showed that team-based learning communities could improve first-year students’ performance and experiences at universities.

The authors’ conclusions may be considered as robust as the findings of the study suggest that the current educational models may be changed to improve students’ performance by providing them with the tools for collaborative learning.

Their notes about the limitations of their research are also reasonable, as the larger sample size could have allowed for relatively different results. Yungbluth and Waldron (2007) did not conduct alternative analyses but mentioned the results of similar studies that supported their findings. For example, they noted that other investigations on the topic involved more educational institutions and had a larger scale while showing the same results. They also stated that future studies should utilize a different approach, such as random assignment, to ensure the higher quality of the results.

Conclusion

The results of the evaluation of the selected study show that although it has some limitations, its findings are relevant and can be applied to practice and within other contexts. The research indicates that individuals participating in learning communities have better performance compared to other students, as well as improve their communication skills and relationships with their team members and universities’ staff. The primary limitation of the study is the lack of authors’ consideration of the threats to internal and external validity.

References

Becker, B. J., Aloe, A. M., Duvendack, M., Stanley, T. D., Valentine, J. C., Fretheim, A., & Tugwell, P. (2017). Quasi-experimental study designs series – Paper 10: Synthesizing evidence for effects collected from quasi-experimental studies presents surmountable challenges. Journal of Clinical Epidemiology, 89, 84-91.

Yungbluth, S. C. & Waldron, V. (2007). Learning communities as interdisciplinary teams: How communication-enhancing models of instructional design improve student outcomes. Web.

Zacharis, N. Z. (2015). A multivariate approach to predicting student outcomes in web-enabled blended learning courses. The Internet and Higher Education, 27, 44-53.

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