CSE 5916
Transcript Abbreviation:
Cpstn: CS Research
Course Description:
Capstone design project; convergent and scalable research formulation and development, computational solutions to open-ended research problems, teamwork, written and oral communication skills.
Course Levels:
Undergraduate (1000-5000 level)
Graduate (5000-8000 level)
Designation:
Elective
General Education Course:
(N/A)
Cross-Listings:
(N/A)
Credit Hours (Minimum if “Range”selected):
4.00
Max Credit Hours:
(N/A)
Select if Repeatable:
Off
Maximum Repeatable Credits:
(N/A)
Total Completions Allowed:
(N/A)
Allow Multiple Enrollments in Term:
No
Course Length:
14 weeks (autumn or spring)
Off Campus:
Never
Campus Location:
Columbus
Instruction Modes:
In Person (75-100% campus; 0-24% online)
Prerequisites and Co-requisites:
Prereq: 2501 or Philos 1338, and CSE 3901 or 3902 or 3903, and second writing course; or Grad standing.
Electronically Enforced:
No
Exclusions:
(N/A)
Course Goals / Objectives:
Master synthesizing and applying prior knowledge to identify research directions for addressing open-ended research questions while considering multiple realistic constraints
Master deadline-driven research in a team setting for addressing an open-ended problem
Be competent in evaluating alternative research approaches
Be competent with issues of teamwork, project scheduling, individual and group time management
Be competent with presenting work to an audience of peers
Be competent with techniques for effective oral and written communication for a range of purposes, including professional and formal presentations and communications to a varied set of stakeholders.
Master principles of agile research methods, consisting of both qualitative and quantitative components
Check if concurrence sought:
No
Contact Hours:
| Topic | LEC | REC out-of-class | REC in-class | Weekly LAB out-of-class | Weekly LAB in-class |
|---|---|---|---|---|---|
| Course overview and project guidelines | 1.0 | 0.0 | 0 | 0.0 | 0 |
| Project selection and team formation | 1.0 | 0.0 | 0 | 0.0 | 0 |
| The scientific method; theory-guided data science; the data science life-cycle; literature reviews; hypothesis formulation and testing; data analysis. | 8.0 | 0.0 | 0 | 3.0 | 0 |
| In class research design and research work | 15.0 | 0.0 | 0 | 8.0 | 0 |
| Midterm presentation | 5.0 | 0.0 | 0 | 0.0 | 0 |
| Final presentation | 8.0 | 0.0 | 0 | 0.0 | 0 |
| Technical research report and poster | 4.0 | 0.0 | 0 | 3.0 | 0 |
| Total | 42 | 0 | 0 | 14 | 0 |
Grading Plan:
Letter Grade
Course Components:
Lecture
Lab
Grade Roster Component:
Lecture
Credit by Exam (EM):
No
Grades Breakdown:
| Aspect | Percent |
|---|---|
| Team presentations | 20% |
| Research project, split into 5 milestones | 50% |
| Literature survey | 10% |
| Technical research report | 20% |
Representative Textbooks and Other Course Materials:
| Title | Author | Year |
|---|---|---|
| "The data science life cycle: a disciplined approach to advancing data science as a science", Communications of the ACM June 2020 https://doi.org/10.1145/3360646 | Victoria Stodden | |
| "Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data", IEEE Transactions on Knowledge and Data Engineering, Vol. 29, No. 10, October 2017 | Anuj Karpatne, Gowtham Atluri, et. al., | |
| Towards methods for systematic research on big data”, 2015 IEEE International Conference on Big Data (BIGDATA), Oct. 29-Nov. 1, 2015. | Manirupa Das, Renhao Cui, David R. Campbell, Gagan Agrawal, Rajiv Ramnath | |
| Agile data analysis: https://datadrivenscrum.com/ | N/A |
ABET-CAC Criterion 3 Outcomes:
| Significant contribution (7+ hours) | 1 | Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions. |
| Some contribution (1-2 hours) | 2 | Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline. |
| Significant contribution (7+ hours) | 3 | Communicate effectively in a variety of professional contexts. |
| Some contribution (1-2 hours) | 4 | Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles |
| Significant contribution (7+ hours) | 5 | Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline |
| Significant contribution (7+ hours) | 6 | Apply computer science theory and software development fundamentals to produce computing-based solutions. |
ABET-ETAC Criterion 3 Outcomes:
(N/A)
ABET-EAC Criterion 3 Outcomes:
| Significant contribution (7+ hours) | 1 | an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics |
| Some contribution (1-2 hours) | 2 | an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors |
| Significant contribution (7+ hours) | 3 | an ability to communicate effectively with a range of audiences - pre-2019 EAC SLO (g) |
| Some contribution (1-2 hours) | 4 | an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts |
| Significant contribution (7+ hours) | 5 | an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives |
| Significant contribution (7+ hours) | 6 | an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions |
| Significant contribution (7+ hours) | 7 | an ability to acquire and apply new knowledge as needed, using appropriate learning strategies |
Embedded Literacies Info: