Pam Bedore, Chair

October 25, 2016

Opening Business

  1. Reminders about pending courses listed at registrar website
  2. News from the Grad School: all Masters degrees require a minimum of 30 credits, effective AY 2017-18

Approvals by the Chair

  1. 2016-118COMM 1993Foreign Study (S)
  2. 2016-119COMM 2993Foreign Study (S)
  3. 2016-120COMM 3993Foreign Study
  4. 2016-121PNB 3295Special Topic: Human Neuroanatomy
  5. 2016-124MCB 5896Investigation of Special Topics: The Footprints of Natural Selection in the Genome

New Business

  1. 2016-122EEB 4100Add Course
  2. 2016-123EEB 5110Add Course
  3. 2016-125HEJS/HRTS 2203 Add Course (G) (S)
  4. 2016-126Revise Engineering Physics Major

Topics for Discussion/Voting

  1. Minors Substitutions (Higgins). Given that substitutions are now allowed for minors (as per Senate by-laws), we will vote on adding the following language to the catalog: “Substitutions to minor requirements offered by departments or programs in the College of Liberal Arts and Sciences require approval by the dean or dean’s designee.”
  2. Alternate BS Requirements (Plan B BS Subcommittee). Discussion and vote on new documents created by the subcommittee in response to discussion for the 10.11.2016 meeting. See attached.
  3. Dual Degree Credit Requirement (Nanclares). Discussion of elimination of the 150-credit requirement for dual degrees.

Appendix of Materials

2016-122EEB 4100Add Course

Proposed Catalog Copy

EEB 4100. Data Science for Biologists

Four credits. Prerequisite: MCB 2400 or 2410 or EEB 2245.

Introduction to basic concepts and approaches associated with big datasets in the biological sciences. Online laboratories include examples from molecular biology, ecology, evolutionary biology, and systems biology. Topics include data creation, integration, curation, manipulation, and visualization.

2016-123EEB 5110Add Course

Proposed Catalog Copy

EEB 5110. Writing Research Proposals and Fellowship Applications

Two credits. Open to graduate students in EEB, others with permission.

The craft of writing persuasive fellowship applications and funding proposals in ecology, evolutionary biology, systematics, and conservation biology. Participants apply for financial support from agencies, foundations, and other sources. Participants also review each other’s work.

2016-125HEJS/HRTS 2203 Add Course (G) (S)

HEJS/HRTS 2203 Holocaust in Theater and Film

Three credits.

An examination of how authors and directors have represented the Holocaust including choices made in written structure, visual imagery, and the use of language. Readings/screenings will also include first-hand accounts and documentaries. Students will consider issues related to style and genre, point of view, tropes and textuality and the limits of representation. CA1 and CA4-INT.

2016-126Revise Engineering Physics Major

No catalog copy to review. This proposal is to add two new courses (ECE 3223 and 3225) to the electives as listed in the “Engineering Physics Guide to Course Selection” ( Additional Materials)

Additional Materials

2016-122EEB 4100Add Course

COURSE ACTION REQUEST
Request Proposer / Wegrzyn
Course Title / Data Science for Biologists
CAR Status / In Progress
Workflow History / Start > Ecology and Evolutionary Biology > Return > Ecology and Evolutionary Biology > College of Liberal Arts and Sciences
COURSE INFO
Type of Action / Add Course
Is this a UNIV or INTD course? / Neither
Number of Subject Codes / 1
Course Subject Code / EEB
School / College / College of Liberal Arts and Sciences
Department / Ecology and Evolutionary Biology
Course Title / Data Science for Biologists
Course Number / 4100
Will this use an existing course number? / No
CONTACT INFO
Initiator Name / Jill L Wegrzyn
Initiator Department / Ecology and Evolutionary Bio
Initiator NetId / jlw13012
Initiator Email /
Is this request for you or someone else? / Myself
Does the department/school/program currently have resources to offer the course as proposed? / Yes
COURSE FEATURES
Proposed Term / Spring
Proposed Year / 2017
Will this course be taught in a language other than English? / No
Is this a General Education Course? / No
Number of Sections / 1
Number of Students per Section / 35
Is this a Variable Credits Course? / No
Is this a Multi-Semester Course? / No
Credits / 4
Instructional Pattern / Tuesday/Thursday lectures; laboratories will be presented online and will require students to complete exercises and reports (3 hours per week).
COURSE RESTRICTIONS
Prerequisites / MCB 2400 or 2410 or EEB 2245
Corequisites / None
Recommended Preparation / None
Is Consent Required? / No Consent Required
Is enrollment in this course restricted? / No
GRADING
Is this course repeatable for credit? / No
What is the Grading Basis for this course? / Graded
Will the course or any sections of the course be taught as Honors? / No
SPECIAL INSTRUCTIONAL FEATURES
Do you anticipate the course will be offered at all campuses? / No
At which campuses do you anticipate this course will be offered? / Storrs
If not generally available at all campuses, please explain why
Will this course be taught off campus? / No
Will this course be offered online? / No
DETAILED COURSE INFO
Provide proposed title and complete course catalog copy / EEB 4100. Data Science for Biologists Four credits. Prerequisite: MCB 2400 or 2410 or EEB 2245. Introduction to basic concepts and approaches associated with big datasets in the biological sciences. Online laboratories include examples from molecular biology, ecology, evolutionary biology, and systems biology. Topics include data creation, integration, curation, manipulation, and visualization.
Reason for the course action / This course is applicable to all students in the biological sciences with an interest in research. Today, researchers acquire large datasets from the laboratory and/or field and translate them into meaningful inferences. The course will enable students to distill these complex datasets into information that can lead to reasoned conclusions. The course will introduce a suite of computational tools that are useful for data integration, visualization, and analysis.
Specify effect on other departments and overlap with existing courses / No overlapping courses exist (consulted with MCB and STATS, 20 April 2016).
Please provide a brief description of course goals and learning objectives / This course will provide training in informatics as it pertains to the biological sciences. Students will interact with examples from several fields and the unique challenges they present. Computational laboratory exercises conducted online will teach students how to apply appropriate tools and understand basic statistical concepts. They will apply their knowledge through these laboratories as well as a final independent group research project. Each group will design and analyze ‘big data’ in biology. They will practice concepts related to scientific oral presentation and visualization in web and print format. Additional learning will include readings and interactive blog responses. Course Competencies: 1. Efficiently create and curate meaningful datasets for biological research. 2. Develop basic code in at least two programming languages for data manipulation. 3. Integrate data from disparate sources to understand complex biological phenomena. 4. Apply appropriate computational tools to visualize a variety of data types.
Describe course assessments / Students will have three forms of graded work. First, students are expected to submit lab exercises each week. Second, students are expected to create blog entries summarizing the reading each week. Full participation includes written questions in your blog as well as commenting on the written work of at least two other students. Finally, students will form groups and participate in a data science project that involves the creation, curation, manipulation, visualization, and analysis of a complex biological dataset of their choosing. Students will prepare a 20-minute presentation on this project that will be given during the last week of class/finals week. Students are expected to report their contribution to group assignments honestly. Final grades are submitted as a whole or partial letter grade.
Syllabus and other attachments / Attachment Link / File Name / File Type
Wegrzyn_DataScienceBiologists_4100_v2.docx / Wegrzyn_DataScienceBiologists_4100_v2.docx / Syllabus
COMMENTS / APPROVALS
Committee Sign-Off Date
Post College Routing / Workflow
Comments & Approvals Log / Stage / Name / Time Stamp / Status / F_CommitteeSignOff / Comments
Start / Jill L Wegrzyn / 10/10/2016 - 16:31 / Submit / Submission for EEB 4100 (Spring 2017)
Ecology and Evolutionary Biology / Paul O Lewis / 10/11/2016 - 20:37 / Return / Need to uncheck INTD
Return / Jill L Wegrzyn / 10/11/2016 - 21:20 / Resubmit / Current submission has been amended to reflect 'Neither'
Ecology and Evolutionary Biology / Paul O Lewis / 10/12/2016 - 13:24 / Approve / 5/11/2016 / Approved by EEB faculty 11-May-2016 (delay due to the need to create this CAR)

EEB 4100 Data Science for Biologists: Syllabus for Spring 2017

Instructor:

Dr. Jill Wegrzyn

Office Location: TLS 75

Course Information:

Credits: 4, Lecture and Lab

Time: Tuesday/Thursday Lecture, Lab Online (3hr/week)

Course Description: This course will introduce students in the biological sciences to the concepts and approaches associated with big datasets. Students will interact with real data from molecular biology, ecology, evolutionary biology, and systems biology. We will emphasize data creation, integration, curation, manipulation, and visualization.

Course Application:This course is applicable to all students in the biological sciences with an interest in research.Today, researchers acquire large datasets from the laboratory and/or field and translate them into meaningful inferences The course will enable students to distill these complex datasets into information that can lead to reasoned conclusions. The course will introduce a suite of computational tools that are useful for data integration, visualization, and analysis.

Prerequisites:

MCB2400 or 2410 orEEB 2245

Course Competencies:

1. Efficiently create and curate meaningful datasets for biological research.

2. Develop basic code in at least two programming languages for data manipulation.

3. Integrate data from disparate sources to understand complex biological phenomena.

4. Apply appropriate computational tools to visualize a variety of data types.

Course Format: The course is a mixture of lectures, code demonstrations, and discussions. Labs allow for greater exploration of the lecture material with exercises designed to build core skills. Labs are conducted online.

Grading:

Students will have three forms of graded work. First, students are expected to submit lab exercises each week. Second, students are expected to create blog entries summarizing the reading each week. Full participation includes written questions in your blog as well as commenting on the written work of at least two other students. Finally, students will form groups and participate in a data science project that involves the creation, curation, manipulation, visualization, and analysis of a complex biological dataset of their choosing. Students will prepare a 20-minute presentation on this project that will be given during the last week of class/finals week. Students are expected to report their contribution to group assignments honestly. Final grades are submitted as a whole or partial letter grade.

  1. Lab assignments (55%)
  2. Weekly blog entries from readings (25%)
  3. Final group project/presentation (20%)

Grading scale: A = 93%-100%, A- = 90%-92.9%, B+ =87%-89.9%, B = 83%-86.9%, B- = 80%-82.9%, C+ = 77%-79.9%, C = 73%-76.9%, C- =70%-72.9%, D = 60%-69.9%, F = 59.9%-0%.

Required Text: No required text. Readings will be provided.

Technical Requirements: Access to a computer with the R programming language, Rstudio, ArcGIS Desktop (available via SkyBox), and an SSH client.

Course Schedule:

Date / Topic / Objectives / Lab
Week 1 / Data and Metadata / Understanding data from different disciplines / What spreadsheets cannot do for you
Week 2 / Data Creation / Data recording, data collection, and quality control / Data collection and quality control
Week 3 / Concepts in Visualization (I) / Best practices for data presentation
(scientific presentations and web-based) / Introduction to R (basic functions)
Week 4 / Data Reduction (I) / Considerations for merging and formatting data / Introduction to R (tidyr)
Week 5 / Data Reduction (II) / Descriptive statistics and probability / Introduction to R (descriptive statistics)
Week 6 / Concepts in Visualization (II) / Best practices for data presentation
(lessons from Tufte) / Introduction to R (ggplot2 and shiny)
Week 7 / Relational Databases / Storing and retrieving data / Querying databases with SQL
Week 8 / Online Resources (I) / Data resources for bioinformatics and genomics / Comparative genomics and BioMart
Week 9 / Online Resources (II) / Understanding and applying biological ontologies / Enrichment in Evo-Devo data
Week 10 / Online Resources (III) / Data resources for ecoinformatics and GIS / Python and spatial data
Week 11 / Data Integration / Integration and curation of data from disparate sources / Genome-wide association studies
Week 12 / Network Analysis / Data resources for systems biology / Visualizing gene networks withCytoscape
Week 13 / Student Presentations
FINALS / Student Presentations / Final project due (written report)

2016-123EEB 5110Add Course

COURSE ACTION REQUEST
Request Proposer / Schultz
Course Title / Writing Research Proposals and Fellowship Applications
CAR Status / In Progress
Workflow History / Start > Ecology and Evolutionary Biology > Return > Ecology and Evolutionary Biology > Return > Ecology and Evolutionary Biology > College of Liberal Arts and Sciences
COURSE INFO
Type of Action / Add Course
Is this a UNIV or INTD course? / Neither
Number of Subject Codes / 1
Course Subject Code / EEB
School / College / College of Liberal Arts and Sciences
Department / Ecology and Evolutionary Biology
Course Title / Writing Research Proposals and Fellowship Applications
Course Number / 5110
Will this use an existing course number? / No
CONTACT INFO
Initiator Name / Eric T Schultz
Initiator Department / ECOLOGY & EVOL BIOLOGY
Initiator NetId / ets02002
Initiator Email /
Is this request for you or someone else? / Myself
Does the department/school/program currently have resources to offer the course as proposed? / Yes
COURSE FEATURES
Proposed Term / Fall
Proposed Year / 2016
Will this course be taught in a language other than English? / No
Is this a General Education Course? / No
Number of Sections / 1
Number of Students per Section / 15
Is this a Variable Credits Course? / No
Is this a Multi-Semester Course? / No
Credits / 2
Instructional Pattern / Weekly sessions of 1.5 to 2 hours. Some sessions are presentations by faculty or staff on subjects relevant to proposal writing (e.g. the funding environment; searching for funding opportunities; proposal quality from NSF's perspective), and other sessions are devoted to group discussions (constructive critiques) of participant proposals.
COURSE RESTRICTIONS
Prerequisites / none
Corequisites / none
Recommended Preparation / none
Is Consent Required? / Instructor Consent Required
Is enrollment in this course restricted? / Yes
Is it restricted by class? / No
Is there a specific course prohibition? / No
Will this course NOT count towards any specific major or related subject area? / No
Are there concurrent course conditions? / No
Are there other enrollment restrictions? / Yes
Other restrictions / Open to students in EEB, others by permission of instructor.
GRADING
Is this course repeatable for credit? / Yes
Number of Total Credits Allowed / 6
Is it repeatable only with a change in topic? / No
Does it allow multiple enrollments in the same term? / No
What is the Grading Basis for this course? / S/U
Rationale for S/U Grading / There are no exams or similar assessments; participation consists of writing a proposal, the quality of which is not graded by the instructor (but is by the funding agency!), and peer review of other's proposals.
Will the course or any sections of the course be taught as Honors? / No
SPECIAL INSTRUCTIONAL FEATURES
Do you anticipate the course will be offered at all campuses? / No
At which campuses do you anticipate this course will be offered? / Storrs
If not generally available at all campuses, please explain why / Graduate students in EEB, who are almost exclusively at Storrs, are the primary audience for this course.
Will this course be taught off campus? / No
Will this course be offered online? / No
DETAILED COURSE INFO
Provide proposed title and complete course catalog copy / EEB 5110. Writing Research Proposals and Fellowship Applications 2 credits. Open to graduate students in EEB, others with permission. The craft of writing persuasive fellowship applications and funding proposals in ecology, evolutionary biology, systematics, and conservation biology. Participants apply for financial support from agencies, foundations, and other sources. Participants also review each other’s work
Reason for the course action / This course has been offered on an 'experimental' basis for three years and has had a positive effect on proposal writing skills and (anecdotally) on funding rates.
Specify effect on other departments and overlap with existing courses / I am not aware of existing courses that overlap with this course. The course is directed primarily at EEB students. Upperclass biology students who are preparing proposals, such as to NSF's Graduate Research Fellowship Program, will also be encouraged to enroll if their research topic overlaps those of EEB students.
Please provide a brief description of course goals and learning objectives / Students in the course will become familiar with the process of applying for funding. Learning objectives include becoming knowledgeable about different sources of funding, searching for funding opportunities, recognizing the components required for compliance with the grantor's requirements, and developing an approach to effective description of project rationale, methods and expected outcomes.
Describe course assessments / Each participant writes and submits one or more proposals, and conducts peer review of the proposals of other participants. Peer review is both written and in classwide discussions.
Syllabus and other attachments / Attachment Link / File Name / File Type
EEB 5894 Seminar writing proposals fall 2015.docx / EEB 5894 Seminar writing proposals fall 2015.docx / Syllabus
COMMENTS / APPROVALS
Committee Sign-Off Date
Post College Routing / Workflow
Comments & Approvals Log / Stage / Name / Time Stamp / Status / F_CommitteeSignOff / Comments
Start / Eric T Schultz / 03/01/2016 - 20:03 / Submit / This is the inaugural proposal of the new online form and workflow system!
Ecology and Evolutionary Biology / Cheryl D Galli / 09/27/2016 - 07:12 / Return / Eric, there is a new department level approver for EEB. Please resubmit form. No changes needed. The resubmission should update the workflow and route to the correct person - thank you, Cheryl
Return / Eric T Schultz / 09/28/2016 - 15:13 / Resubmit / I'm running this through again! EEB Curriculum Committee will make some changes to catalog description.
Ecology and Evolutionary Biology / Eldridge S Adams / 10/04/2016 - 17:28 / Return / I entered suggested edits for the catalog description of the course. We suggest that a brief justification for the number of credits be added and that the instructional pattern is included.
Return / Eric T Schultz / 10/04/2016 - 17:41 / Resubmit / I have added justification for the number of credits in the instructional pattern box (course features page) and I have made a minor further modification to the course description.
Ecology and Evolutionary Biology / Paul O Lewis / 10/12/2016 - 13:21 / Approve / 10/12/2016 / Approved by EEB faculty 12-Oct-2016

EEB 5894 Seminar,Fall 2015
Writing Compelling Proposals