Research Project

by Daniel Lobo. Daniel Lobo, a PhD Student in Sociology at UC Berkeley, discusses his journey from growing up in the urban working class to making it to Harvard College and UC Berkeley. He credits his mentors who were able to see him in a way that he could not see himself as the keys to his success. This gift, the power to see others for who they are and who they could be, animates his research and teaching, including on the NSF-IUSE project.

by Mingfeng Xue. Hierarchical Linear Modeling (HLM) is an extension of linear models, which offers an approach to analyzing data structures with nested levels. This blog elucidates HLM's significance over traditional linear regression models, particularly in handling clustered data and multilevel predictors. Illustrated with an example from educational research, the blog demonstrates model implementation and interpretation steps. It showcases how HLM accommodates both independent variables from different levels and hierarchical structure data, providing insights into their impacts on the outcome variable. Recommended resources further aid readers in mastering HLM techniques.

by Leah Lee. Large-scale geographic data over time on insect diversity can be used to answer important questions in Entomology. Open-source, open-access citizen science platforms like iNaturalist generate huge amounts of data on species diversity and distribution at accelerating rates. However, unstructured citizen science data contain inherent biases and need to be used with care. One of the efforts to validate big data from iNaturalist is to cross-check with systematically collected data, such as museum specimens.

by Farnam Mohebi. As an aspiring leading researcher, I find the full-cycle research methodology crucial for transforming initial curiosities into organized studies and research products. This approach begins with thorough observation, leads to theory and hypothesis development and experimentation, and concludes with synthesizing findings into coherent narratives. It's beneficial for researchers of all backgrounds, enhancing the depth and impact of their work. By embracing this method, researchers comprehensively understand each stage and its contribution to the broader research context and can lead the process of converting an initial unspecified research idea to a streamlined research study and product. This systematic approach is particularly effective in complex studies, fostering thorough, investigative, and innovative research processes.