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Preparation for first-time tas 

GRS 097: Fundamentals for Teaching Assistants                   Fall 2018

Meeting time to be determined. CNS has partnered with the Graduate School and the Faculty Innovation Center (FIC) to develop this course to support Teaching Assistants who will be leading a lab or discussion section for the first time. In this research-based seminar on pedagogy, graduate students will learn strategies for effectively leading lab/discussion sections, and will receive personalized support and feedback designed to improve their confidence and skills as instructors. Matthew Landry, a PhD student in Nutritional Sciences who has completed GRS 097, NSC 088L, and NSC 088T, will lead this class; Dr. Molly Hatcher of the FIC will serve as its instructor of record.

Prerequisites: None. 

Any CNS graduate student in their first year of leading a lab/discussion session in Fall 2017 can apply for this course by completing the survey here. Applications are due by August 25.

 

Concentration in Teaching and Mentoring 

NSC 088L: Intro to Evidence Based Teaching                                Fall 2017

T 5:00-6:30pm. This seminar is designed for graduate students (and postdocs) interested in learning how to teach science effectively in their own courses rather than as teaching assistants. Topics include defining learning objectives, designing learning tasks, observing classrooms to identify effective teaching strategies, and practice teaching. Participants will also develop familiarity with research on science teaching and learning, including how and why to lead class discussions, structure group work, engage students with different levels of preparation and motivation, and promote equity in the classroom.

Prerequisites: None

  

NSC 088T: Mentored Teaching Experience                                 Spring 2018

No meeting time assigned. In this seminar, graduate students and postdocs who have completed Introduction to Evidence-based Teaching or the equivalent will design, teach, and conduct assessment of an instructional unit (~3 hours of class time) in an undergraduate CNS course. The process will be accomplished in collaboration with a faculty member currently teaching the course, with guidance and mentorship from Dr. Kristin Patterson, an education specialist in TIDES. Total time commitment is ~15 hours, which is scheduled on an ad hoc basis over a semester. This time commitment includes designing and planning instruction, practice teaching, formal classroom instruction, informal student interaction, and student assessment.

Prerequisites: NSC 088L – Introduction to Evidence-based Teaching

 

NSC 088M: Mentoring Undergraduate Researchers               Summer 2018

Meeting times to be arranged. This seminar aims to develop graduate students’ and postdocs' skills in mentoring undergraduates and other junior researchers in doing STEM research. The course will involve discussions about how to define appropriate projects, establish relationships, set expectations, encourage communication, balance guidance and independence, and consider ethical issues and diversity in mentoring.

Prerequisites: None

Concentration in Communicating Science

CMS 081: Science Communication Seminar                            Spring 2018

(Temporarily Titled: Intro to Graduate Studies in Human Communication)                            

Meeting time to be determined. This seminar course is a professional development elective within the CNS Concentration in Communicating Science.  Students may take this course alone or in conjunction with the Practicum described below. Taught by Anthony Dudo from the Stan Richards School of Advertising and Public Relations in the Moody College of Communication, this seminar course will introduce students to topics chosen from the following: 

  • Models of “public engagement with science” (deficit model, contextual model, public participation model)
  • Public understanding of science, science literacy, and trust in science
  • Sources of information about science (journalism, entertainment media, social media)
  • Motivations and barriers to scientist communicators
  • Communicating science strategically (choosing communication goals and styles, working with media/public information officers)
  • Science communication case studies (climate change, genetic engineering) 
  • Prerequisites: None

    CMS 081: Science Communication Practicum                            Spring 2018

    Meeting time to be determined. This is a lab that may be taken concurrently with the Science Communication Seminar described above.  The practicum will provide interested students with opportunities to focus on skill development while receiving constructive assessment and evaluation. Students will focus on topics chosen from the following: 

  • Functions of communication (inform, persuade, express, etc.)
  • Persuasion strategies (pilot testing with audiences, creating, implementing and monitoring communication campaigns, assessing outcomes)
  • Source variables (factors that affect credibility; evaluating legitimacy)
  • Format (public speaking, interviewing, digital presentations)
  • Presentation skills (written, oral, communicating to large/small groups)
  • Ethics (media and communication ethics, legal issues) 
  • Prerequisites: current or prior enrollment in the Science Communication Seminar.

     

    Concentration in Leadership and Project Management

    MAN 390: Leading People and Organizations                             Spring 2018

    Meets Tuesday evenings, 5:00-8:00, in GSB 5.142A. This course is a professional development elective within the CNS Concentration in Leadership and Project Management. Taught by Caroline Bartel from the Department of Management in the McCombs College of Business, this is a special section of a McCombs MBA course tailored for graduate students in STEM disciplines. This course will develop the knowledge and skills necessary for scientists to manage and lead effectively within organizations. Students may take this class on either a C/NC (low workload) or a full credit (higher workload) basis.

    Prerequisites: None 

     

    NSC 088S: Strategic Management                                                    Fall 2018

    This course is concerned with the job of the general manager, who has responsibility for the performance of an entire organization or a multi-functional unit of an organization. The primary task faced by such managers is that of developing and managing an overall strategy; hence, the name "strategic management." Accordingly, the objectives of the course are to (1) take the first steps in developing a "general management" orientation in all students, (2) develop the new skills and knowledge needed in such positions, and (3) synthesize the skills and knowledge students have obtained through prior work experience and course work. Among the topics covered in the course are the role of the general manager, formulating business and corporate-level strategy, managing strategic change, strategy implementation, and developing general managers. The objectives of the course will be accomplished primarily through a combination of readings and case discussions. Students will be evaluated based on the quality of their participation in in-class discussions and course papers. The participative nature of the course requires daily preparation and participation of the highest quality.Further topics in this concentration will be piloted in the 2018-19 academic year.

    Prerequisites:  None

    Data Analysis - all workshops take place in gdc 1.406

    Introduction to Unix                             August 22nd, 2018

    Learn the basics of using UNIX from the command line. Introductory topics include the filesystem, the shell, permissions, and text files. The course will touch on manipulating text files using standard UNIX utilities, how to string utilities together, and how to output the results to files. The goal of the course is to develop some basic comfort at the command line, get a sense of what's possible, and learn how to find help.

    Introduction to TACC                             August 22nd, 2018

    Students in the course will learn what a cluster is and how to use the world-class clusters available at the Texas Advanced Computing Center (TACC). The course will discuss the basic architecture of the Lonestar and Stampede computing clusters, how they compare to a regular computer, job launchers and job scheduling, and how to submit your own jobs to TACC. Custom tools by the Bioinformatics Consulting Group for job submission will be emphasized. Familiarity with a unix command line is a prerequisite. Students must also establish a TACC account and can do so by visiting this link.

     

    Introduction to Python I                             August 23rd, 2018

     

    Python is a simple and popular programming language that can be used across platforms, and is useful for a wide variety of tasks.

    This Short Course is a basic introduction to scripting using python. Skills taught will include data structures, input and output, loops, and if time permits, function definitions. These tools will be useful for researchers in many fields for data management, automating tedious computational tasks, and handling 'big data'. This course is taught at an introductory level and is appropriate for students with no experience, but will contain material and techniques helpful to moderately experienced python programmers.Topics to be covered:

    • Introduction 
    • Control Flow 
    • Lists 
    • Input and Output 
    • Strings 
    • Functions 

     

     

    Introduction to R, Part I                             August 24th, 2018

    This course introduces R, a free and open-source software package used for statistical computing and graphics. We will cover navigating the free graphical user interface RStudio, importing and exporting data, combining (merging) data, creating and manipulating variables, basic data descriptives, and visualization. The course will introduce installation of R packages to leverage two popular workflows: the tidyverse and ggplot2.After completing this course, a new user should be able to:

    • Navigate RStudio.
    • Install and use R packages.
    • Import/export data from/to external files.
    • Create and manipulate new variables.
    • Generate simple descriptive statistics to summarize data.
    • Graphically display various types of data.
    • Edit features of graphs (titles/labels, colors, shading, etc.).
    • Make graphs using ggplot2.

     

    ABOUT THE INSTRUCTOR: Michael J. Mahometa is the Director of Consulting Services and Professional Education at the Department of Statistics & Data Sciences (SDS) at The University of Texas at Austin. He received his Ph.D. in Psychology from The University of Texas at Austin in 2006. His major course work was completed in Behavioral Neuroscience, with a minor in Statistics. His background in animal models of learning makes him familiar with full factorial designs—which he quickly expanded into a love of all things regression. Dr. Mahometa has been a statistical consultant for the SDS department since its inception in 2006 and enjoys helping members of the UT community reach their “light bulb moment in statistics” through both his courses and his consulting practice. 

     

     

    Introduction to Data Vizualization & SQL                  August 27th, 2018

    Data Visualization

    This course introduces both principles and practice of scientific data visualization, especially as applied to large multivariate data sets. Will cover common methods of visually summarizing data and illustrating relationships between variables of various common types (continuous, categorical, etc.) as well as design concepts for increasing the clarity of quantitative graphical communication. Will introduce modern "grammar of graphics" ideas as foundation for thinking about, relating, and ultimately building new types of informative plots. Implementations of covered methods in both R and python will be presented.

    Students should bring their own laptops to the course. Installation of either R (with ggplot2) or Python (with matplotlib, seaborn, and plotnine) prior to class is required.

    ABOUT THE INSTRUCTOR: Dennis Wylie joined the CCBB Bioinformatics group in 2015. He has experience in NGS data analysis including variant calling and RNA-Seq-based biomarker discovery and predictive modeling (classification, regression, etc.). Prior to UT, he earned a PhD in Biophysics from UC Berkeley applying stochastic simulation methods to problems in immunology, did postdoctoral work modeling the transmission of infectious disease, and spent six years as a bioinformatician in industry.

     

    Working with SQL Databases

    This is an introductory course on the basics of database technology using MySQL, including the structured query language (SQL) along with modes of database interaction specific for bioinformatics workflows. We begin with a hands-on introduction to databases and the MySQLWorkbench user interface, creating and populating a schema, followed by simple and more complex queries to manipulate different subsets of data. Finally, we discuss bulk loading of database tables and programmatic database access, for example from Python.

    ABOUT THE INSTRUCTOR: Anna Battenhouse is a research scientist in the labs of Drs. Edward Marcotte and Vishy Iyer as well as leading the Biomedical Research Support Facility in its mission to support the IT and computational needs of the UT Austin biomedical research community. She has extensive experience working with NGS data, and teaches the Introduction to NGS Tools course in the Big Data in Biology Summer School as well as several CCBB short courses.

     

     

     

    Introduction to R, Part II                           August 28th, 2018

    This short course covers data analysis in R in greater depth than the introductory course.  For various statistical methods (see list below), participants will learn how to prepare a dataset, test relevant assumptions, and carry out the analyses. In addition, students will be introduced to the premise of reproducible research, and create RMarkdown objects. This hands-on course will teach participants how to use R to run different types of analysis, interpret the output, and reproducible documents.After completing this course, participants should be able to carry out:

    • Correlation and simple linear regression analysis.
    • Chi-squared tests.
    • T-tests and one-way ANOVA.
    • Multiple regression and multivariate ANOVA models.
    • Logistic regression.
    • Reproducible report creation in RStudio.

    ABOUT THE INSTRUCTOR: Michael J. Mahometa is the Director of Consulting Services and Professional Education at the Department of Statistics & Data Sciences (SDS) at The University of Texas at Austin. He received his Ph.D. in Psychology from The University of Texas at Austin in 2006. His major course work was completed in Behavioral Neuroscience, with a minor in Statistics. His background in animal models of learning makes him familiar with full factorial designs—which he quickly expanded into a love of all things regression. Dr. Mahometa has been a statistical consultant for the SDS department since its inception in 2006 and enjoys helping members of the UT community reach their “light bulb moment in statistics” through both his courses and his consulting practice.