Bridging the gap between school and out-of-school science: A Making pedagogical approach

Making provides a beneficial learning environment that requires skills and knowledge from the areas of science, technology, engineering, and mathematics to design and construct a product or an artefact. In this paper the maker approach reflects on the pedagogical potential of learning through the design and deployment of an automated system that monitors and records environmental parameters in lakes and rivers. IoT technologies are used to connect schools with natural ecosystems, providing the opportunity to students to be actively involved in designing and developing technology artefacts to experiment with, and further, in the formulation of research questions, and in the processing and interpretation of research results and measurements. The study contributes to the research literature on bridging the gap between the school and out-of-school science

An Exploratory Study of K-12 Music Educators’ Use of the Online Crowdfunding Platform DonorsChoose

Music educators contending with resource insufficiency have developed novel ways of acquiring assets. The advent of internet-based crowdfunding, where individual teachers directly solicit contributions from personal and professional associates, now stands as the most frequentlyemployed means of finding external sources of funding for teaching projects. The purpose of this study was to explore K-12 music educators’ use of one such crowdfunding web site, DonorsChoose.org, to obtain resources to support their teaching endeavors. Participants comprised a sample of teachers (n = 102) running campaigns on DonorsChoose.org in January and February of 2019. The majority of participants were females teaching elementary or middle school in underserved communities who turned to crowdfunding out of necessity when traditional resource channels failed. They set out to raise an average of $1,274.81 and strongly endorsed the effectiveness of the DonorsChoose platform. Their self-reported levels of work motivation and entrepreneurial self-efficacy were moderately strong and compared favorably to the same measures reported by members of a control group. Findings of this exploratory study help create a baseline portrait of music educators who turn to crowdfunding to obtain resources for their teaching initiatives

Empirical Assessment of Mobile Device Users’ Information Security Behavior towards Data Breach: Leveraging Protection Motivation Theory

User information security behavior has been an area of growing demand in information systems (IS) research. Unfortunately, most of the previous research done in user information security behavior have been in broad contexts, therefore creating a gap in the literature of similar research that focuses on specific emerging technologies and trends. With the growing reliance on mobile devices to increase the flexibility, speed and efficiency in how we work, communicate, shop, seek information and entertain ourselves, it is obvious that these devices have become data warehouses and platform for data in transit. This study was an empirical and quantitative study that gathered data leveraging a web-survey. Prior to conducting the survey for the main data collection, a Delphi study and pilot study were conducted. Convenience sampling was the category of nonprobability sampling design used to gather data. The 7-Point Likert Scale was used on all survey items. Pre-analysis data screening was conducted prior to data analysis. The Partial Least Square Structural Equation Modeling (PLS-SEM) was used to analyze the data gathered from a total of 390 responses received. The results of this study showed that perceived threat severity has a negative effect on protection motivation, while perceived threat susceptibility has a positive effect on protection motivation. Contrarily, the results from this study did not show that perceived response cost influences protection motivation. Response efficacy and mobile self-efficacy had a significant positive influence on protection motivation. Mobile device security usage showed to be significantly influenced positively by protection motivation. This study brings additional insight and theoretical implications to the existing literature. The findings reveal the PMT’s capacity to predict user behavior based on threat and coping appraisals within the context of mobile device security usage. Additionally, the extension of the PMT for the research model of this study implies that mobile devices users also can take recommended responses to protect their devices from security threats

Discovering Rare Hematopoietic Clones Harboring Leukemia-Associated Mutations Using Error-Corrected Sequencing

Cancer is a heterogeneous group of diseases that currently takes over half a million lives per year in the United States alone. Our understanding of cancer has improved dramatically over the last forty years, beginning with the discovery that cancer is a disease of the genome. Currently, the set of somatic mutations found in malignancy are largely known. The specific somatic mutations driving an individual’s disease can be readily assessed at clinical presentation. Additionally, the functional consequences for many of these mutations are known as well as their role in tumorigenesis. Despite this understanding, a cure for cancer remains elusive. Acute myeloid leukemia (AML) is a particularly deadly example, which currently kills about 10,000 people per year and has a 5-year survival rate of only 25%. While the current outlook for these patients is grim, much is known about the disease, which will fuel future improvements in detection and therapy. Existing research has identified the spectrum of somatic mutations driving most cases of AML and has elucidated the oligoclonal nature of the disease. Following treatment, relapse often arises from a minor clone that was inconspicuous at presentation, but resistant to treatment. The current gold standard for assessing response to treatment is multiparameter flow cytometry (MPFC), which identifies persistent leukemic cells marked by a patient-specific leukemia-associated immunophenotype. Unfortunately, MPFC is only useful in a subset of patients and not sensitive to the clonal diversity present in many tumors. Conversely, virtually every case of AML is marked by leukemia-specific somatic mutations that theoretically distinguish every leukemic cell from its normal counterparts. These limitations of MPFC and the general need for improved residual disease detection were early motivations for this thesis work: to develop a sequencing-based modality for rare leukemic-clone detection. Previous efforts to develop a sequencing-based platform for residual disease detection had largely failed because of the intrinsic error rate of next-generation sequencing (NGS) technology, which precludes the detection of leukemic clones less common than 1:20 cells (0.025 variant allele fraction for heterozygous mutations). For comparison, MPFC is sensitive and prognostic to a detection limit of 1:10,000 cells. To address this limitation, we developed methods for targeted error-corrected sequencing that mitigated the effect of sequencing errors. After an extensive development and validation process, we applied this technology to study two fundamental questions in AML and hematopoiesis in general. First, we applied our error-corrected sequencing methods to study leukemogenesis in therapy-related AML (t-AML). This aggressive form of leukemia arises months to years following treatment with chemotherapy or radiation for a primary malignancy. The prevailing notion was that antecedent therapy introduced somatic mutations in hematopoietic stem and progenitor cells (HSPCs) that directly caused the development of t-AML. We used error-corrected sequencing to demonstrate that leukemogenic TP53 mutations were present at low frequency months to years before the diagnosis of t-AML and in some cases preceded the initial chemotherapy exposure. These findings redefined the etiology of t-AML. Instead of being introduced by chemotherapy, these TP53 mutations likely arose stochastically in HSPCs throughout the patient’s lifetime and were selected for by cytotoxic therapy, eventually spawning malignancy. Second, we applied error-corrected sequencing to further our understanding of benign clonal hematopoiesis in healthy individuals over time. Recent work had identified benign hematopoietic clones harboring leukemia-specific somatic mutations in the blood of healthy individuals. The prevalence of this phenomenon increased as a function of age; while rare below 50, clones were detected in up to 10% of individuals by 70 years-old. These findings were made with conventional NGS and, likewise, did not detect rare clonal mutations in fewer than 1:20 cells. We sought to characterize the prevalence, stability and mutation spectrum of benign hematopoietic clones below this threshold. Using our error-corrected sequencing approach, we demonstrated that approximately 95% of disease-free individuals have hematopoietic clones harboring leukemia-associated mutations by 50-60 years of age. We also demonstrated that these clonal mutations were stable over time and originated in long-lived HSPCs. These findings demonstrate the utility of our error-corrected sequencing platform to identify and characterize previously undetectable leukemia-associated somatic mutations. We applied these techniques to unveiled new insights into clonal HSPC biology and the development of t-AML. Future work will apply this technology as a sequencing-based modality for residual disease detection in pediatric AML. We believe this technology will improve the detection of residual leukemia, identify the step-by-step molecular perturbations driving relapse, inform therapeutic selection, and improve clinical outcomes and survival

Measuring primate gene expression evolution using high throughput transcriptomics and massively parallel reporter assays

A key question in biology is how one genome sequence can lead to the great cellular diversity present in multicellular organisms. Enabled by he sequencing revolution, RNA sequencing (RNA-seq) has emerged as a central tool to measure transcriptome-wide gene expression levels. More recently, single cell RNA-seq was introduced and is becoming a feasible alternative to the more established bulk sequencing. While many different methods have been proposed, a thorough optimisation of established protocols can lead to improvements in robustness, sensitivity, scalability and cost effectiveness. Towards this goal, I have contributed to optimizing the single cell RNA-seq method "Single Cell RNA Barcoding and sequencing" (SCRB-seq) and publishing an improved version that uses optimized reaction conditions and molecular crowding (mcSCRB-seq). mcSCRB-seq achieves higher sensitivity at lower cost per cell and shows the highest RNA capture rate when compared with other published methods. We next sought the direct comparison to other scRNA-seq protocols within the Human Cell Atlas (HCA) benchmarking effort. Here we used mcSCRB-seq to profile a common reference sample that included heterogeneous cell populations from different sources. Transfer of the acquired knowledge on single cell RNA sequencing methods to bulk RNA-seq, led to the development of the prime-seq protocol. A sensitive, robust and cost-efficient bulk RNA-seq protocol that can be performed in any molecular biology laboratory. We compared the data generated, using the prime-seq protocol to the gold standard method TruSeq, using power simulations and found that the statistical power to detect differentially expressed genes is comparable, at 40-fold lower cost. While gene expression is an informative phenotype, the regulation that leads to the different phenotypes is still poorly understood. A state-of-the-art method to measure the activity of cis-regulatory elements (CRE) in a high throughput fashion are Massively Parallel Reporter Assays (MPRA). These assays can be used to measure the activity of thousands of cis-Regulatory Elements (CRE) in parallel. A good way to decode the genotype to phenotype conundrum is using evolutionary information. Cross-species comparisons of closely related species can help understand how particular diverging phenotypes emerged and how conserved gene regulatory programs are encoded in the genome. A very useful tool to perform comparative studies are cell lines, particularly induced Pluripotent Stem Cells (iPSCs). iPSCs can be reprogrammed from different primary somatic cells and are per definition pluripotent, meaning they can be differentiated into cells of all three germlayers. A main challenge for primate research is to obtain primary cells. To this end I contributed to establishing a protocol to generate iPSCs from a non-invasive source of primary cells, namely urine. By using prime-seq we characterized the primary Urine Derived Stem Cells (UDSCs) and the reprogrammed iPSCs. Finally, I used an MPRA to measure activity of putative regulatory elements of the gene TRNP1 across the mammalian phylogeny. We found co-evolution of one particular CRE with brain folding in old world monkeys. To validate the finding we looked for transcription factor binding sites within the identified CRE and intersected the list with transcription factors confirmed to be expressed in the cellular system using prime-seq. In addition we found that changes in the protein coding sequence of TRNP1 and neural stem cell proliferation induced by TRNP1 orthologs correlate with brain size. In summary, within my doctorate I developed methods that enable measuring gene expression and gene regulation in a comparative genomics setting. I further applied these methods in a cross mammalian study of the regulatory sequences of the gene TRNP1 and its association with brain phenotypes

Improving & applying single-cell RNA sequencing

The cell is the fundamental building block of life. With the advent of single-cell RNA sequencing (scRNA-seq), we can for the first time assess the transcriptome of many individual cells. This has profound implications for biological and medical questions and is especially important to characterize heterogeneous cell populations and rare cells. However, the technology is technically and computationally challenging as complementary DNA (cDNA) needs to be generated and amplified from minute amounts of mRNA and sequenceable libraries need to be efficiently generated from many cells. This requires to establish different protocols, identify important caveats, benchmark various methods and improve them if possible. To this end, we analysed amplification bias and its effect on detecting differentially expressed genes in several bulk and a single-cell RNA sequencing methods. We found that correcting for amplification bias is not possible computationally but improves the power of scRNA-seq considerably, though neglectable for bulk-RNA-seq. In the second study we compared six prominent scRNA-seq protocols as more and more single-cell RNA-sequencing are becoming available, but an independent benchmark of methods is lacking. By using the same mouse embryonic stem cells (mESCs) and exogenous mRNA spike-ins as common reference, we compared six important scRNA-seq protocols in their sensitivity, accuracy and precision to quantify mRNA levels. In agreement with our previous study, we find that the precision, i.e. the technical variance, of scRNA-seq methods is driven by amplification bias and drastically reduced when using unique molecular identifiers to remove amplification duplicates. To assess the combined effects of sensitivity and precision and to compare the cost-efficiency of methods we compared the power to detect differentially expressed genes among the tested scRNA-seq protocols using a novel simulation framework. We find that some methods are prohibitively inefficient and others show trade-offs depending on the number of cells per sample that need to be analysed. Our study also provides a framework for benchmarking further improvements of scRNA-seq protocol and we published an improved version of our simulation framework powsimR. It uniquely recapitulates the specific characteristics of scRNA-seq data to enable streamlined simulations for benchmarking both wet lab protocols and analysis algorithms. Furthermore, we compile our experience in processing different types of scRNA-seq data, in particular with barcoded libraries and UMIs, and developed zUMIs, a fast and flexible scRNA-seq data processing software overcoming shortcomings of existing pipelines. In addition, we used the in-depth characterization of scRNA-seq technology to optimize an already powerful scRNA-seq protocol even further. According to data generated from exogenous mRNA spike-ins, this new mcSCRB-seq protocol is currently the most sensitive scRNA-seq protocol available. Single-cell resolution makes scRNA-seq uniquely suited for the understanding of complex diseases, such as leukemia. In acute lymphoblastic leukemia (ALL), rare chemotherapy-resistant cells persist as minimal residual disease (MRD) and may cause relapse. However, biological mechanisms of these relapse-inducing cells remain largely unclear because characterisation of this rare population was lacking so far. In order to contribute to the understanding of MRD, we leveraged scRNA-seq to study minimal residual disease cells from ALL. We obtained and characterised rare, chemotherapy-resistant cell populations from primary patients and patient cells grown in xenograft mouse models. We found that MRD cells are dormant and feature high expression of adhesion molecules in order to persist in the hematopoietic niche. Furthermore, we could show that there is plasticity between resting, resistant MRD cells and cycling, therapy-sensitive cells, indicating that patients could benefit from strategies that release MRD cells from the niche. Importantly, we show that our data derived from xenograft models closely resemble rare primary patient samples. In conclusion, my work of the last years contributes towards the development of experimental and computational single-cell RNA sequencing methods enabling their widespread application to biomedical problems such as leukemia

“NOW LET US SHIFT”: A CASE STUDY OF DEVELOPMENTAL EDUCATION REFORM IN A HISPANIC SERVING COMMUNITY COLLEGE

Background: Latina/o/x students who persist to college are likely to enter through community college (Contreras & Contreras, 2018) and until the enactment of California Assembly Bill 705, would have been susceptible to placement in developmental education courses (Rodriguez, Cuellar Mejia, & Johnson, 2018). The implementation of AB 705 shifted the requirements for new student placement in all 115 California Community Colleges. With compliance mandated by Fall 2019, the law required colleges to maximize the probability that entering students enroll and complete transfer-level English or mathematics within a one-year timeframe and within a three-year timeframe for students enrolled in English as a Second Language courses (A. B. 705, 2017, para. 2). Purpose: This study examined organizational changes related to developmental education reform, AB 705, at a Hispanic Serving Community College. Methodology: This instrumental case study, at a Hispanic Serving Community College, employed various data collection methods including semi-structured interviews, document collection and analysis, physical artifact collection, and observations. Primarily, the enquiry focused on learning from eleven participants (faculty, staff, and administration) who were strategically involved in reform efforts. Conclusions: The findings identified structural and procedural changes to the placement process as well as existing supplemental supports and curriculum at the research site. Barriers and supports for faculty, staff, and administration influenced the change process and the perceived implications for equitable student outcomes of students. As all community colleges throughout the state are required to comply with AB 705, this study may be of interest to those invested in similar change processes

The Impact of 1:1 Technology Initiatives on New Literacy in the Secondary ELAR Classroom: A Metasynthesis

Guided by socio-cultural learning theories of Vygotsky’s (1979) social-constructivism and cultural-historical activity theory (Engeström, 2014), the researcher of this study formed three research questions regarding the emergent research trends on 1:1 technology initiatives in the secondary ELAR classroom and new literacy. In response, a meta-synthesis of relevant studies was conducted. To provide an initial framework for the synthesis, the researcher provided conceptual definitions and backgrounds of 1:1 technology initiatives, socio-cultural learning theories, and new literacy, supported by the history of literacy movements that led to this new model of literacy. Utilizing narrowed inclusion and exclusion criteria, the research yielded six journal articles and dissertations that served as participants for this study. In a second phase of data analysis, the researcher established the emergent themes across all studies included topics on the impact of 1:1 on new literacy acquisition, the changing role of the teacher in 1:1 settings, the deictic nature of literacy, and common challenges that impede technology integration. In a third and final phase of this meta-synthesis, the researcher utilized the original theoretical framework and research question as a lens to provide additional interpretations. The findings from this process related to a lack of unified terminology regarding the emergent form of literacy, as well as conditions for student engagement and acquisition of new literacy skills

Unraveling Population Heterogeneity using Single-Cell Analysis

The human body contains approximately 100 trillion cells, encompassing distinct cell types that serve diverse functions. Understanding cell population heterogeneity is vital for uncovering different biological functions and mechanisms. In addition, cells at transition during continual processes, such as development, reprogramming, and disease, are essential for painting the entire blueprint and highlighting critical stages of the progression trajectory. For instance, cell fate engineering holds much promise for generating clinically valuable cell types from mature somatic cells. Nonetheless, current reprogramming protocols are inefficient, and charting the changes in cell identity during such processes can help design strategies to mitigate the off-target and increase efficiency. RNA-sequencing allows us to study transcript abundance and dissect different genetic features. Prior to single-cell level sequencing, bulk-level transcriptomics have demonstrated power at a lower resolution to distinguish populations and identify differential gene markers. The advent of single-cell RNA-sequencing technologies has brought us a new era of exploring the small world inside individual cells via their transcriptome profiles. Single-cell RNA-sequencing takes a snapshot of individual cells, enabling the dissection of population composition and capture of cells at different states in complex biological systems. Cell type annotation has been a long-standing interest in understanding cell identities from gene profiles. Yet, manual annotations require prior knowledge of cell-type-specific gene signatures and are labor-intensive and time-consuming. Automated annotation approaches are in demand for exponentially growing single-cell datasets.In response to such demand, many computational approaches have been developed. However, they classify cells in a discrete, categorical manner, limiting their application in continuous biological systems. Focusing on continual processes, we designed a computational tool, \u27Capybara,\u27 to measure cell identity as a continuum at a single-cell resolution. This approach enables the classification of discrete cell identities and recognizes cells harboring hybrid identities, supporting a quantitative cell-fate transition metric. After benchmarking against other classifiers and validation with ground-truth lineage data, we apply Capybara to a diverse range of cellular programming and reprogramming protocols: The application to direct cardiac reprogramming uncovers a patterning bias and a hybrid state between atrial and ventricular cardiomyocytes; Capybara reveals previously uncharacterized patterning deficiencies in motor neuron programming, instructing a new approach to alleviate the lack of proper patterning; Further, we apply Capybara to our in-house system, direct reprogramming of fibroblast to induced endoderm progenitors, and find a putative in vivo correlate for this engineered cell type that has, to date, remained poorly defined. These findings highlight the utility of Capybara to dissect cell identity and fate transitions in development, reprogramming, and disease. Finally, we further explore the direct cardiac reprogramming system using the comprehensive set of tools developed in the lab. We resolve lineage relationships in this system using CellTagging, find key regulatory transcription factors using CellOracle, and evaluate small molecules\u27 effect on the patterning bias using Capybara. In summary, I have developed a tool to highlight cell fate transitions and reveal insight into cellular heterogeneity in different continuous biological processes. Further investigation in the transition states by integration with other data modalities and experimental approaches may help pinpoint key checkpoints for successful reprogramming, allowing future interventions to improve the efficiency and fidelity of cell fate engineering

A Phenomenological Study on Liberal Arts Graduate Employability: The Relationship Between Baccalaureate Internships and Graduate Underemployment

The purpose of this study was to examine liberal arts graduate employability specifically as it relates to baccalaureate internships and underemployment. This qualitative phenomenological study examined experiences from 19 recent liberal arts college graduates from an urban college setting 1 to 3 years postgraduation. A focus group and in-depth interviews were used to ascertain the graduates’ perceptions of the effect that internships, interactions with faculty advisors, and the Office of Career Services had on postgraduate employment. The results of this study produced four major findings that provide new information about how the use of internships can affect liberal arts graduates’ perception of postgraduate underemployment. The findings from this study amplify the perspective of liberal arts graduates on the efficacy of the liberal arts degree, in general, and internships, specifically. The study adds to the body of knowledge on experiential learning, career advisement, liberal arts graduate employability, and the perceived effect of a liberal arts bachelor’s degree. Recommendations include implementing university-wide changes within academic affairs, advisement, and student support services that value the unique perspectives of nontraditional students