CompSci 692V/Psych 891V Making Sense of Visual Data: Human Perception, Attention, and Information Visualization
In this course, we will focus on basic aspects of human perception and attention, and how they are relevant to areas of computer science, such as data visualization, human-computer interaction, and computer vision. We will also explore how applied research in these areas contributes to understanding the basic perceptual and cognitive mechanisms. Topics may include saliency models, memory, mental imagery, motion perception, eye-tracking, ensembling coding, and visual comparisons.
Time: TuTh 1:00PM – 2:15PM
Location: Tobin Hall room 307
Instructor: Cindy Xiong and Kyle Cave
Office Hours:
Cindy Xiong: Thursdays 2:30pm – 3:30pm or by appt.
LGRC A217E or via ZOOM (link provided upon request)
Kyle Cave: Wed 2:00pm – 3:00pm or by appt.
Tobin 432 or via ZOOM (link provided upon request)
Course Objectives and Learning Outcome After completing this course, you should be able to…
- Understand theories in visual perception/data visualization and the underlying brain mechanisms
- Utilize concepts from visual perception to design and evaluate data visualizations
- Explore and conduct interdisciplinary research
- Effectively communicate data insights and research findings with audiences from diverse backgrounds
| Monday | Tuesday | Wednesday | Thursday | Friday | |
|---|---|---|---|---|---|
| Week 1: Intro | Sept 6: Lecture: Introduction (Round 1 Topic Selection Sign-Up Opens) |
Sept 7 | Sept 8: Lecture: Introduction to Data Visualization |
Sept 9 (Round 1 Topic Selection Sign-Up Ends) (Round 2 Topic Selection Sign-Up Opens) |
|
| Week 2: Background | Sept 12 |
Sept 13: Lecture: |
Sept 14 (Round 2 Topic Selection Sign-Up Ends) |
Sept 15: Lecture: Student Presentation (Research Interests) |
Sept 16 |
| Week 3: Research | Sept 19 | Sept 20 Lecture: Attention I (Behavioral) |
Sept 21 | Sept 22 Lecture: Attention II (Neuroscience) |
Sept 23 |
| Week 4: Attention | Sept 26 |
Sept 27 Lecture: |
Sept 28 |
Sept 29 Lecture: |
Sept 30 |
| Week 5: Shape | Oct 3 |
Oct 4 Lecture: |
Oct 5 |
Oct 6 Lecture: |
Oct 7 |
| Week 6: Eye-Tracking | Oct 10 (Holiday) |
Oct 11 |
Oct 12 |
Oct 13 Lecture: |
Oct 14 |
| Week 7: VIS Week |
Oct 17 (IEEE VIS) |
Oct 18 (IEEE VIS) |
Oct 19 (IEEE VIS) |
Oct 20 (IEEE VIS) |
Oct 21 (IEEE VIS) |
| Week 8: Reflection and Presentation | Oct 24 | Oct 25 Midterm Presentations Day 1 |
Oct 26 | Oct 27 Midterm Presentations Day 2 + VIS Reflection |
Oct 28 |
| Week 9: Ensemble Coding | Oct 31 |
Nov 1 Lecture: |
Nov 2 |
Nov 3 Lecture: |
Nov 4 |
| Week 10: Animation | Nov 7 |
Nov 8 Lecture: |
Nov 9 |
Nov 10 Lecture: |
Nov 11 (Holiday) |
| Week 11: Memory | Nov 14 | Nov 15: Lecture: Writing Research Papers |
Nov 16 |
Nov 17 (Psychonomics) |
Nov 18 (Psychonomics) |
| Week 12: Break | Nov 21 | Nov 22 No Class (Friday Schedule) |
Nov 23 (Holiday) | Nov 24 (Holiday) | Nov 25 (Holiday) |
| Week 13: Mental Imagery | Nov 28 |
Nov 29 Lecture: |
Nov 30 |
Dec 1 Lecture: |
Dec 2 |
| Week 14: Final Presentations | Dec 5 | Dec 6 Student Presentation Day 1 |
Dec 7 | Dec 8 Student Presentation Day 2 |
Dec 9 |
| Week 15 | Dec 12 (Last Day of Class) | Dec 13 (Reading Day) | Dec 14 | Dec 15 | Dec 16 Final Paper Due! |
Course Activities
Preparedness (5%)
Starting from Week 3, students will be required to post questions about assigned readings on a discussion board prior to class. (Due at 12pm the day before the corresponding topics). You are required to post 2-3 questions, and across those questions, refer to 2-3 of the assigned papers. Try to ask questions that refer to multiple papers. Please read the paper fairly thoroughly before writing the questions.
Presentation on Research Interest (5%)
You will prepare a 1 minute elevator pitch on your research program and/or research interests and present during class. Pay close attention to other people’s presentations. In addition to presenting on your own research interest, you will also be required to brainstorm how you might integrate your research interest with that of another student and write about it in a paragraph (3-5 sentences) on a discussion board.
Reading Presentation (15% + 15%)
Throughout the semester, there are 16 topics we will discuss. The instructor will provide a short introduction to these topics at the beginning of each class. For the remainder of the class, students will be presenting on corresponding readings. You need to find peers from a different backgrounds to form groups of 2-3 (depending on the class size, but each group should have at least one CS student and one psych student) and select two topics to present on by the end of Week 2. Every group will present twice.
Your group will prepare a 15-min presentation on the readings, which will include summaries of the paper’s takeaways. Everyone in your group should talk for approximately equal length during the presentation. You don’t have to cover every section of every paper. You are encouraged to emphasize the most important takeaways from the paper, and perhaps also from other related papers, and offer your own interpretation. For example, if you find particular references from your readings that might provide relevant background information, feel free to include that information in your presentation.
You also need to connect the paper to materials we discussed in previous class and/or your own research and research interests. You should also consider what real-world problem the readings may be related to or be used to resolve. If the reading is a psychology paper, you should discuss a related application or a research direction in computer science. If the reading is a data visualization paper, you should discuss a related basic research question or potential next steps from a psychology perspective.
Prior to your presentation day, you will read and think through the questions your peers posted on the discussion board and be prepared to discuss them somewhere within your presentation. Expect to lead a 15-min discussion session immediately following your presentation (the instructors will help with moderating the discussion).
Detailed information on how we will grade your presentations can be found here.
Attendance and Participation (5%)
You are expected to attend class and engage in the discussions even when you are not presenting. You will get to evaluate your classmates’ presentations via a set of questions. Please watch your classmates’ presentations carefully and provide constructive feedback and thoughtful evaluations. You are permitted 3 freebie absences. No questions asked.
Final Paper (25%)
At the end of the semester, you will integrate everything you have learned to propose either 1) an interdisciplinary experiment that examines a visualization problem with implications for human perception, 2) an interdisciplinary experiment that examines a human perception question with applications to data visualization, or 3) an idea of a visualization system or tool that draws on principles of human perception to address a currently unmet need in the real world. This will be an individual assignment, but you are encouraged to brainstorm with your peers and provide each other with feedback. You are encouraged to consult with the instructors as you design your topic.
More detailed information can be found here.
Final Presentation (20%)
You will prepare a 5-min presentation on your final paper. The presentation must contain a description of your experiment or visualization tool, and a clear motivation for your ideas, with explanations of relevant theoretical background and related work based on the papers we read in class and/or other studies you have found. During the final week of this class, you will present your idea to the class. The presentation will be graded both by the instructors and your peers on its clarity, creativity, and relevance to class materials.
More detailed information can be found here.
Midterm presentation (10%)
You will have an opportunity to share your idea on your final paper half way through the course. Prepare a 2-min lighting talk or elevator pitch on your idea. We will allocate time in class for the instructors and your peers to provide feedback on your idea. You are welcome to use this opportunity to seek advice on your approach to the final paper/presentation. The presentation will be graded by the instructors on its clarity, creativity, and relevance to class materials.
More detailed information can be found here.
Grading
A ≥ 93
A- 90 – 92
B+ 87 – 89
B 83 – 86
B- 80 – 82
C+ 77 – 79
C 73 – 76
C- 70 – 72
D+ 60 – 69
D 50 – 59
F < 50
Attendance and Class Policies
You should only enroll in this class if you intend to attend the classes and participate in the discussion. You are responsible for all material presented in the class. If you have to miss a class, you should expand your contributions to the discussion board accordingly.
Assignments Policies
Students may collaborate and consult outside sources when doing assignments. However, all assignments that you turn in must be written entirely by you, with a note describing the nature of any collaboration. You are required to attend class for presentation-based assignments. For non-presentation based assignments, they will be accepted up to 48 hours after the due time, with a 10% penalty if turned in within the first 24 hours and an additional 10% penalty if turned in within the second 24 hours. Late assignments will not be accepted.
Exams
There are no exams for this course.
Communication Policy
The instructor and the Teaching Assistant will only respond to course-related comments and inquiries via Slack, and will not respond to them via email (unless it pertains to troubles with Slack). The instructor and the Teaching Assistant will check Slack channels daily Monday through Friday to answer questions and address concerns.
Accommodation Statement
The University of Massachusetts Amherst is committed to providing an equal educational opportunity for all students. If you have a documented physical, psychological, or learning disability on file with Disability Services (DS), you may be eligible for reasonable academic accommodations to help you succeed in this course. If you have a documented disability that requires an accommodation, please notify me within the first two weeks of the semester so that we may make appropriate arrangements.
Academic Honesty
Since the integrity of the academic enterprise of any institution of higher education requires honesty in scholarship and research, academic honesty is required of all students at the University of Massachusetts. Academic dishonesty is prohibited in all programs of the University. Academic dishonesty includes but is not limited to: cheating, fabrication, plagiarism, and facilitating dishonesty. Appropriate sanctions may be imposed on any student who has committed an act of academic dishonesty. Any person who has reason to believe that a student has committed academic dishonesty should bring such information to the attention of the appropriate course instructor as soon as possible. Instances of academic dishonesty not related to a specific course should be brought to the attention of the appropriate department Head or Chair. Since students are expected to be familiar with this policy and the commonly accepted standards of academic integrity, ignorance of such standards is not normally sufficient evidence of lack of intent. Further details can be found here: https://www.umass.edu/honesty/sites/default/files/academic_honesty_policy_rev_sen_doc_no16-038a.pdf
Inclusivity Statement
In this course, each voice in the classroom has something of value to contribute. Please take care to respect the different experiences, beliefs and values expressed by students and staff involved in this course. We support UMass Amherst’s commitment to diversity, and welcome individuals of all ages, backgrounds, citizenships, disability, sex, education, ethnicities, family statuses, genders, gender identities, geographical locations, languages, military experience, political views, races, religions, sexual orientations, socioeconomic statuses, and work experiences.
Title IX Statement
UMass is committed to fostering a safe learning environment by responding promptly and effectively to complaints of all kinds of sexual misconduct. If you have been the victim of sexual violence, gender discrimination, or sexual harassment, the university can provide you with a variety of support resources and accommodations If you experience or witness sexual misconduct and wish to report the incident, please contact the UMass Amherst Equal Opportunity (EO) Office ([email protected] | phone: 413-545-3464) to request an intake meeting with EO staff. Members of the CICS community can also contact Erika Lynn Dawson Head, director of diversity and inclusive community development ([email protected] | 860-770-4770).
Learning Support
There are also a range of resources on campus, including:
UMass Libraries: https://www.library.umass.edu/
Writing Center – http://www.umass.edu/writingcenter
Learning Resource Center – http://www.umass.edu/lrc
Assistive Technology Center – https://www.umass.edu/it/assistive
Disability Services – https://www.umass.edu/disability/
Student Success – https://www.umass.edu/studentsuccess/
Center for Counseling and Psychological Health (CCPH) http://www.umass.edu/counseling
English as a Second Language (ESL) Program – http://www.umass.edu/esl
CMASS Success Coach Program – https://www.umass.edu/cmass/get-involved/success/academic-support
Single Stop Resources – https://www.umass.edu/studentlife/single-stop