Engineering – Page 2 – UROP Spring Symposium 2021

Engineering

Eye tracking to determine cognitive load during programming practice

Novice programmers need scaffolded instruction to maximize their ability to learn how to program. Parsons problems are an increasingly popular solution. These problems require learners to place mixed-up code blocks in the correct order to solve a problem. We are conducting think-aloud sessions and a within-subjects experiment to understand the efficiency and cognitive load of solving adaptive Parsons problems versus writing the equivalent (isomorphic) code. We are also investigating the impact of prior programming experience on students’ experiences and changes in students’ self-efficacy. This study will report on cognitive load and self-efficacy ratings before and after the task for the two problem times. We expect students to exhibit greater learning gains on fixing code with errors when solving Parsons problems with distractors than without. We also expect to find a correlation between self-efficacy and cognitive load ratings. The implications of this study are to improve programming learning tools for novice programmers.

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Eye tracking to determine cognitive load during programming practice

Novice programmers need scaffolded instruction to maximize their ability to learn how to program. Parsons problems are an increasingly popular solution. These problems require learners to place mixed-up code blocks in the correct order to solve a problem. We are conducting think-aloud sessions and a within-subjects experiment to understand the efficiency and cognitive load of solving adaptive Parsons problems versus writing the equivalent (isomorphic) code. We are also investigating the impact of prior programming experience on students’ experiences and changes in students’ self-efficacy. This study will report on cognitive load and self-efficacy ratings before and after the task for the two problem times. We expect students to exhibit greater learning gains on fixing code with errors when solving Parsons problems with distractors than without. We also expect to find a correlation between self-efficacy and cognitive load ratings. The implications of this study are to improve programming learning tools for novice programmers.

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Species Distribution Modeling of Pseudopipra pipra in the Neotropics

The Neotropics is one of the most species-rich regions in the world (Condon et al., 2008). Its diverse landscape and complex history has allowed for population isolation and subsequent diversification (e.g. Berv et al., 2021). While our knowledge of phylogenetic diversity in the Neotropics has dramatically increased in recent years (e.g. Berv et al., 2021; Tello et al., 2009), our understanding of how species’ have adapted across a myriad of climate regimes in the Neotropics is less well understood (Weir, 2006).

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A Literature Review on Combustion and Properties Studies of Alternative Fuels

A literature review has been undertaken in order to understand more about the ignition behavior of fatty alcohols and to eventually conduct my own experiments. Using Scopus, U of M’s online library, I searched for keywords, such as “fatty alcohols”, “diesel”, and/or “combustion”, in scholarly articles in order to find research that was relevant. After finding the article, I would read through it, occasionally skimming through parts I found non-pertinent, while taking notes on the important information. From there, I would compile all of the information into a three or four paragraph summary, giving a description of each scholarly article. So far, my main takeaway would be that fatty alcohols blended with biodiesel can serve as a substitute for fossil diesel, as they generally produce less emissions, and can make the engine more efficient. This research is necessary to provide insight into if these fuels can replace fossil diesel fuel, in order to transition to a more sustainable source such as biofuels.

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Testing a New Search Engine for Class Videos

The current research project investigates the relationship between a new search engine for instructional videos and the academic performance of university-level students and instructors. During the new-age of virtual learning, the hindrance of social interaction combined with the sudden increase in digital screen time has negatively impacted the mental health and in turn, the academic performance of many students because they are not being able to focus or concentrate on their work. A study proposed to determine if a new academic tool provides help for students academically utilized participants, who were recruited through email communication to various universities across America, to use the engine and record their grades on academic assignments and poll their opinions on the product. Currently, the research is still in progress and has no definite conclusion.

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Antarctic Atmospheric Rivers

Atmospheric Rivers (ARs) are long and narrow areas of concentrated moisture found within the first few kilometers of the atmosphere. When they make landfall, this moisture is released in the form of rain or snow, at times transporting moisture from the tropics or subtropics. Due to their impacts at landfall, there has been an explosion of interest in characterizing ARs. However, the AR definition is largely qualitative and relies on regionally specific case studies from the North Pacific, therefore, a number of AR detection algorithms exist. I will be focusing on the region of Antarctica because there is little studied from that region, and there are large differences between algorithms when applied to that region. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) aims to identify and quantify the uncertainty in AR science due to algorithm choice. The focus of this project is on a set of AR catalogues from ten algorithms run on MERRA-2 reanalysis (1 hour time intervals and 0.5 degree latitude and longitude intervals). This project seeks to understand and quantify the differences between regional and global algorithms when applied to the region of Antarctica by examining how the number of AR events changes with algorithm and comparing algorithms along transects in Antarctica. We can cross analyze the output of each of the detection algorithms to identify areas of inconsistency in atmospheric river detection and understand the nature and source of those inconsistencies, which is the goal of this UROP project.

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Testing a New Search Engine for Class Videos

The current research project investigates the relationship between a new search engine for instructional videos and the academic performance of university-level students and instructors. During the new-age of virtual learning, the hindrance of social interaction combined with the sudden increase in digital screen time has negatively impacted the mental health and in turn, the academic performance of many students because they are not being able to focus or concentrate on their work. A study proposed to determine if a new academic tool provides help for students academically utilized participants, who were recruited through email communication to various universities across America, to use the engine and record their grades on academic assignments and poll their opinions on the product. Currently, the research is still in progress and has no definite conclusion.

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Residue Depth Computation

Proteins, a class of macromolecules essential to biological processes, are characterized by their structure which directly correlates to functionality. Residues are considered the building blocks of proteins and studying their positions has been crucial in understanding the role a protein plays in a biological system. This research project investigates different measures of residue depth through calculations of RSA, DPX, Residue Depth, HalfSpace Depth, and L1 depth. The L1 depth function surpasses other residue structure predictors in that it can obtain positions of residues buried under the protein surface, or nested in pockets. In addition, the function uses O(N) time complexity, making it much more efficient than the HalfSpace predictor. Values of depth have strong correlations with properties such as physiochemical propensities, flexibility and polarity. Data was obtained from CULLPDB, Phospho3D, and PLB datasets. After reading in necessary information into an IDE, residue depth of each protein in the datasets and the correlation coefficients between the means of depth values of amino acids and hydrophobicity index of amino acids were calculated through an algorithm written in C++. These results showed that the means of depth values were strongly relative with hydrophobicity of amino acids. In addition, the secondary structures of the residues are also associated with L1 depth values, as residues in sheets are deeper under the surface in comparison to residues in coils and helices.

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Residue Depth Computation Project

Proteins, a class of macromolecules essential to biological processes, are characterized by their structure which directly correlates to functionality. Residues are considered the building blocks of proteins and studying their positions has been crucial in understanding the role a protein plays in a biological system. This research project investigates different measures of residue depth through calculations of RSA, DPX, Residue Depth, HalfSpace Depth, and L1 depth. The L1 depth function surpasses other residue structure predictors in that it can obtain positions of residues buried under the protein surface, or nested in pockets. In addition, the function uses O(N) time complexity, making it much more efficient than the HalfSpace predictor. Values of depth have strong correlations with properties such as physiochemical propensities, flexibility and polarity. Data was obtained from CULLPDB, Phospho3D, and PLB datasets. After reading in necessary information into an IDE, residue depth of each protein in the datasets and the correlation coefficients between the means of depth values of amino acids and hydrophobicity index of amino acids were calculated through an algorithm written in C++. These results showed that the means of depth values were strongly relative with hydrophobicity of amino acids. In addition, the secondary structures of the residues are also associated with L1 depth values, as residues in sheets are deeper under the surface in comparison to residues in coils and helices.

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The importance of the interface in predict protein-protein interactions

Protein-protein interactions (PPIs) are physical contacts between two or more protein molecules. The field of structural homology-based PPI prediction, has generally accepted that the interface region of the complex structure matters more than the global structure of proteins in predicting PPIs, although our preliminary data suggests otherwise. A study was undertaken to investigate the influence of the protein interface in predicting PPIs, using a tweaked version of TMalign. This edited version of the algorithm allows a weighting factor to be applied to specific residues, the interface residues, in these experiments. This study consists of experiments using different weighting values, each of which will be done on three sets of query data. The three data sets are: 1. pairs of proteins that are known to have positive interactions, 2. pairs of proteins that are said to not interact with one another, and 3. a randomized data set. The latter two will allow us to confirm the results of non-interactions. Once each query protein is aligned to the structural homologs in the database, the score can be calculated and then all scores will be sorted to determine the cutoff for classifying predicted positive interactions. The results allow us to determine how impactful the interface is in predicting whether two given proteins will interact or not. Additionally, it will either confirm or deny the long standing assumption that only the interface matters.

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