I need help improving my text and and use the meal plan method with no citations in the first and last sentence of the paragraph. I need the references in APA 7 style. In this section, I need to put my first theme and select several studies that clarify a similar problem of practice using some common set of activities (stakeholder meetings, data that clarify the problem over time, focus groups, needs analysis, etc.). I need to Introduce the studies by stating the Theme or Cluster that unites the studies. Then, describe each study in light of how that study clarified and defined the problem of practice. The focus should be on the explanation of the strengths and weaknesses of each study in how each study identified the problem of practice? I need to Name the Next Theme or Similarity that Unites a Cluster Based on the Problem of Practice (Replace with the Name of your Theme or Cluster) In this section, for each research article, I need to summarize the point of view of the authors and discuss the methodology (participants, methods, intervention, data collected, and data analysis). Also, presenting the findings and conclusions of the study. I need to Compare and contrast the literature that I present. If applicable, create more themes of clusters of studies

Theme 1: Factors Influencing Student Retention This theme focuses on relatively new and promising topics regarding various factors stimulating student persistence and retention, particularly in STEM and adjacent fields. Belser et al. (2018), utilizing a large dataset and rigorous statistical methods, identified several key predictors of persistence among STEM majors, including prior academic achievement, financial aid status, and engagement in extracurricular activities. This study's strength lies in its comprehensive approach and robust methodology, but it is limited by its focus on a single academic discipline and reliance on self-reported data. Various techniques are required to create effective prediction models due to the complexity of the factors impacting student retention. In another study, Sass et al. (2018) developed a structural model to predict student retention based on factors like positive and negative sacrifice, student engagement, and student satisfaction. They used a large sample to increase the probability of including a more generalized population to enhance the query's generalizability. However, the model's complexity limits its practical application (Elder, 2021). Additionally, the study's cross-sectional design makes it difficult to establish causal relationships between the identified factors and retention outcomes. One of the most critical factors in community college student success is the impact of expectations on retention rates. James (2022) investigated the role of expectations in student retention, finding that both student and institutional expectations significantly impact persistence rates. However, the qualitative nature of this study limits its generalizability and ability to capture the full range of quantitative data relevant to the issue. Similarly, Lucey (2018) focused on the role of motivation in online learning environments, highlighting the importance of motivation-enhancing policies. While this study provides valuable insights into student motivation, it is limited in scope and does not fully address the broader factors influencing student persistence across different learning modalities. Theme 2: Early Identification of At-Risk Learners and Student Retention The early identification of at-risk learners is a recurring theme within the literature on student retention in community colleges. A significant body of research underscores the potential of early identification systems to detect and address challenges that students may face before they escalate and lead to dropout. For instance, Ortiz-Lozano et al. (2023) highlighted the importance of analyzing various data points to identify vulnerable student populations and provide tailored support. Similarly, Villano et al. (2018) employed survival analysis techniques to assess the effectiveness of early-alert systems in predicting student outcomes, revealing a positive correlation between early intervention and increased retention rates. However, implementing and utilizing early identification systems effectively poses challenges for institutions. Ortiz-Lozano et al. (2023) noted the financial burden of implementing comprehensive systems and the potential difficulties in generalizing findings across different institutional contexts. Likewise, the statistical methods employed by Villano et al. (2018) may be complex for some practitioners to interpret and utilize, who lack adequate statistical and analytical skills, limiting the practical applicability of their findings (Berens et al., 2018). Despite these challenges, the research consistently underscores the importance of timely intervention for students at risk of dropping out, emphasizing the need for institutions to invest in effective early identification and support systems. The literature review on the problem of practice reveals a vast amount of information about various aspects and potential effects on student retention, emphasizing the importance of early identification. Specifically, quantitative papers such as Belser et al. (2018) and Sass et al. (2018) support the quantitative investigation of retention and the factors that affect it. On the other hand, papers with qualitative approaches, such as James (2022), underscore how Colleges should be prepared to satisfy the expectations of students by providing certain practices and policies. Even more, Ortiz-Lozano et al. (2023) and Villano et al. (2018) support this by stressing how important preventions are to ensure vulnerable learners are protected; however, the authors appear to agree that since their applications are not entirely feasible due to the presence of some concerns, etc.