Matt Suntay’s jump into the PINC computing program

Matt Suntay is one of the students in the PINC program and also a research student in my lab in the E. coli / drug resistance / machine learning team. A few days ago he gave a speech at our PINC/GOLD/gSTAR graduation event. I thought it was a great speech and Matt was kind enough to let me share it here both as a video and the text for those of you who prefer reading.

“To those of you who may know me, you all know I’m pretty adventurous. For those of you who may not know me, first off, my name is Matthew Suntay, and I have jumped off planes, cliffs, and bridges – and each time was just as exhilarating as the last. But, let me tell you about my most favorite jump: the leap of faith I took for the PINC program.

I call it a leap of faith because when I first heard about the PINC program, and specifically CSC 306, I thought, “Ain’t no way this could be for me. I may be stupid because I can barely understand the English in o-chem and now I gotta understand the English in Python? Maaaan, English isn’t even my first language… But they said I don’t need any prior computer science knowledge, so why not? It’s Spring ‘21, new year, new me, right?”

And let me tell you, it definitely made me a new me. I went from printing “Hello World!” to finding genes in Salmonella to constructing machine-learning models to study Alzheimer’s Disease and antibiotic resistance in E. coli. These are some pretty big jumps–my favorite, right?–and they weren’t easy to make. However, I was never scared to make any one of those jumps because of the PINC program.

When I think PINC, I don’t only see lines of code across my screen or cameras turned off on Zoom. I see friends, colleagues, mentors, and teachers. I see a community.

I see a community willing to support me in my efforts to develop myself as a scientist. I see a community providing me the platform and opportunities to grow as a researcher. And most importantly, I see a community that shared hardships, tears, laughter, and success with me.

I can confidently say that the PINC program was, and still is, monumental to my journey through science. Thanks to the PINC program, many doors have been opened to me and one of those doors I’m always happy to walk through each time is the one in Hensill Hall, Room 406 – or the CoDE lab. It was here in this lab that I met some of the most amazing people who want to do nothing but help me reach new heights. I’m so grateful and lucky to have them. So thank you, Dr. Pennings, for believing in me and continuing to believe in me. Thank you to everyone in the CoDE lab for supporting me and laughing at my terrible jokes – and real talk, please keep doing so, I don’t know how to handle the embarrassment that comes after a bad joke.

If I haven’t said it enough already, thank you so much to the PINC program. If you were to ask the me from a year ago what his plans were for the future, he would tell you, “Slow down, dude, I don’t even know I’m trying to eat for breakfast tomorrow.” But now if you were to ask me what my plans for the future are, I’d still tell you I don’t know what I’m trying to eat for breakfast tomorrow because I’m too busy writing code to solve my most current research question, whatever it may be.

For many students, including myself, one of the biggest causes of an existential crisis is, “What am I gonna do after I graduate?” To be honest, I’m still thinking that same thought, but without the dread of an existential crisis. One of the coolest parts of the PINC program is the exposure to research and the biotechnology industry, and learning that research == me and not just != the stereotype of a scientist.

Dr. Yoon, thank you for taking the time and effort to push me and my teammates forward, because even though our projects were difficult, we learned a lot about machine-learning and ourselves, like who knew we had it in us this whole time? You definitely did and you helped us see that. Professor Kulkarni, you also helped us realize that we should give ourselves more credit. 601 and 602 showed us we can be competitive and that we’re worth so much more than we make ourselves out to be. Also, I would like to give a quick shoutout to Chris Davies and Chun-Wan Yan for the wonderful seminars because those talks gave me hope and inspiration for the future. Knowing that there’s something out there for me makes going into the future a lot less scary and a lot more exciting because who knows what awesome opportunity is waiting for me?

And one last honorable mention I would like to make is to Professor Milo Johnson. He was my CSC 306 professor, and I don’t know if he is here today, but he was an amazing teacher in more ways than one. He helped me turn my ideas into possibilities and I have him to thank for helping kick start my journey through PINC. When I thought “I couldn’t do it, this isn’t for me,” he said “Don’t worry, you got this.”

So, once again, to wrap things up, thank you to everyone who’s helped me out this far and continues to help me out. Thank you to all my friends, mentors, and teachers that I’ve met along the way. And thank you to the PINC program, the best jump I’ve ever made.

Matthew Suntay – PINC graduate 2022

How we run an inclusive & online coding program for biology and chem undergrads in 2020

By: Nicole Adelstein, Pleuni Pennings, Rori Rohlfs

In 2018 this team (led by Chinomnso Okorie) met in the “yellow room” for 8 hours a week to learn R.  

We have been running combined coding/research summer programs for several years, with a  focus on undergraduate students, women, and students from historically underrepresented racial and ethnic groups. This summer, we will run our 9-week program as an online program. We think that others may be interested in doing this too, so we’ll share here how we plan to  do it. 

Some of the information below will also be published as a “ten rules paper” in Plos Computational Biology*, but we wanted to share this sooner and focus on doing things online vs in person. 

TL; DR version

1. Have students work in teams of 4 or 5, for 2 hours per day, 4 days a week. Learning to code should be done part-time, even if your program is full time. 
2. Use near-peer mentors to facilitate the team meetings (not to teach, but to facilitate). 
3. Use existing online courses – we’ll share a few that we like. Don’t try to make your own curriculum last minute. There are good online courses available. 
4. Give the students a simple (repeat: simple!) research project to work on together. 

1. Have students work in teams for two hours a day – with pre-set times. 

Learning to code is stressful and tiring. Even though many students may not have jobs this summer – it doesn’t mean that they can code for 8 hours a day. First, because they have other stuff to do (like taking care of family members) and second because there’s a limit to how long you can be an effective learner. 

Our program is 10 hours per week (8 hours of coding, 2 hours of “all-hands” meeting). We make it clear that no work is expected outside of these hours. For example, a team may meet from 10am to 12pm four days a week for coding. 

Check-ins, quiet working, shared problem solving. 

During the coding hours, the near-peer mentor is always present (on Zoom, of course!) and facilitates the meeting. The very first day should be all about introductions and expectations. After that, we suggest that every day, there is time for check-ins (everybody shares how they are doing, what they’re excited about or struggling with, or what music they’re listening to), quiet working (mute all microphones, set a timer, everybody works on the online class by themselves) and shared problem solving (for example, let’s talk about the assignment X from the online class). One of the mentors last year was successful with starting every meeting with a guided meditation. 

Each team has a faculty mentor in our program (this could be a postdoc or faculty member). Once a week, the faculty mentor joins the meeting for about 1 hour. This hour could consist of introductions / check-ins, a short presentation or story by the faculty mentor, and the opportunity for the team to ask questions. It’s great if the near-peer mentor and the team prepare questions beforehand. 

1B. Add a non-coding meeting (if you can/want)

In addition to the 8 coding hours per week, our students also meet for 2 hours per week in an “all hands meeting”. Such an all-hands meeting is not absolutely necessary, but if you have the bandwidth, it may be nice to meet once a week to do something other than coding. Maybe to read a paper together or meet with someone online (an alum who is now somewhere else? A faculty member or grad student?). 

If your program is full time (like an REU program), we suggest to still only do about 8-15 hours of coding per week. Fill up the rest with more standard things such as lectures, reading etc (and don’t make anyone do Zoom 40 hours a week!). If students are enjoying themselves with coding and getting more confident, they may do more coding by themselves, but in our program it is not the expectation. 

2. Mentors and teams are key 

When working alone, we’ve often seen students get stuck on technical problems, leaving many feeling lost and inadequate and wanting to discontinue learning this new skill. Working in a mentored team, however, students have access to immediate support from their peers and mentor. This helps them learn technical skills more efficiently, develop relationships with each other, and cultivate a shared sense of belonging in computational research (Kephart et al. 2008). We recommend that each participant in a coding summer program be assigned to a team of 4 to 5 students with similar technical skill levels led by a near-peer mentor. 

Mentors in our program are typically a year or two ahead of participants but belong to similar demographic groups and come from similar academic backgrounds. The mentor facilitates the meetings and leads the team in learning skills and applying them to a research question (without doing the work themselves). 

Each team also has a faculty advisor, who comes up with a research project that is likely to be completed in the available time and that is of interest to the students (Harackiewicz et al. 2008). The faculty advisor meets with the whole team at least once per week to guide learning and research. Of note, acting as a mentor improves students’ retention and success in STEM (Trujillo et al. 2015) therefore, this setup benefits mentors as well as mentees. 

2B. Who can be mentors? 

Over the years, we have found that near-peer mentors are incredibly useful for a number of reasons including 1) student participants are more likely to ask for help from a near-peer mentor than from a faculty advisor, 2) near-peer mentors serve as role models, giving participants an idea of what they can aim for in the next year or two, and 3) the use of mentors allows the program to serve many more participants than it could if it relied on a few time-pressed faculty advisors. Our selection criteria for mentors include essential knowledge (for example, the mentor for a team doing an advanced chemistry research project should have taken physical chemistry), mentoring experience or potential, logistical availability, and having a similar demographic background as the participants. Mentors don’t need experience with the specific coding language or research topic they will work on with their team. Rather than being the expert in the room, they are expected to help team members work together to find solutions or formulate questions for the faculty advisor. 

Mentors are crucial for the success of the program and need to be paid well for their work. Each week of the program, we pay our mentors a competitive wage for 8 contact hours with their team, a 2-hour all hands lunch meeting, a 2-hour mentor meeting, and 3-4 additional hours to account for preparation. However, we realize that this summer, things may be different for many! You may find that PhD students or Master’s students who can not work in the lab (but are still paid / on a fellowship) could be excellent near-peer mentors. Just make sure that the mentors know that this is a real commitment that will eat up a significant chunk of time each week. 

3. Identify an appropriate online course for each team

We have found that when learning basic coding skills, interactive online classes to learn computer programming (for example, from Datacamp, Udacity or Coursera) motivate and engage students better than books or online texts. Yet, when working individually, most students – especially beginners and historically underrepresented students – don’t finish online classes (Ihsen et al. 2013; Jordan 2015). As a solution, we have found that in teams, where students can work together and support each other, they learn a great deal from an online class. 

Each team’s faculty advisor picks a free, clearly structured online class with videos and assignments to teach participants coding skills. We have had good experiences with Udacity’s Exploratory Data Analysis course because this class is suitable for beginners. It does a good job motivating students to think about data and learn R. In early team meetings, participants spend time quietly working on the online class with their headphones on, followed by a team discussion or collaborative problem-solving session. If students encounter difficulty with any of the material, mentors may develop mini-lectures or create their own exercises to facilitate learning. Note, the students’ goal is not necessarily to finish the online course, but to learn enough to perform their research project. 

3B. Suggested classes:

Udacity Exploratory Data Analysis with R https://www.udacity.com/course/data-analysis-with-r–ud651

CodeHS https://codehs.com/ (the faculty mentor or the near-peer-mentor needs to create a section on Code HS, we use the introduction to python (rainforest).  

Coursera https://www.coursera.org/learn/r-programming (this one is a tip from our UCSF colleague Dr Kala Mehta)

4. Assign each team a simple and engaging research project 

Learning to code without a specific application in mind can feel boring and irrelevant, sometimes leading students to abandon the effort. In our summer program, teams carry out a research project to motivate them to learn coding skills, improve their sense of belonging in science (Jones, Barlow, and Villarejo 2010) and cultivate their team work and time/project management skills. Faculty advisors assign each team a research project early in the program. These projects should answer real questions so that participants feel their work is valuable (Woodin, Carter, and Fletcher 2017). The projects should also be relatively simple. Small and self contained projects that can be completed within a three week time frame are ideal to ensure completion and make participants feel that their efforts have been successful. For example, past research projects in our program, which reflect the interests of faculty advisors and the students, include writing computer simulations to model the evolution of gene expression, analyzing bee observations from a large citizen science project, examining trends in google search term data with respect to teen birth outcomes, and building an app for finding parking spots on or near campus. 

For 2020, we’d like to encourage you to pick a project that appears extremely simple if you normally use R or Python to make your plots / do stats, but that would be quite challenging if you’re new to coding. We also suggest that – unless the students are already quite advanced – you don’t give them a project that you want to publish on quickly. Nobody needs more pressure this summer.  

Here are some suggestions for simple research projects

1. Let students plot the number of COVID19 cases in their county over time using R. Let them plot the number of cases in 5 different counties on the same figure. Add an arrow for when a stay-at-home order was implemented or terminated. Easy to download data are here: https://github.com/nytimes/covid-19-data 
2. Let students keep track of how many steps they take each day for 10 days using their phone or watch. Let them plot the number of steps per day using R. Let them add a line for the mean. Collect data from 6 people and create a pdf with 6 plots in different colors. 
3. If you have any data from your lab, let the students plot those data. Try making 4 different plots with the same data (scatter, box, histogram, etc). 
4. Let students recreate an existing plot from a publication when the data are available. 
5. Let students analyze (anonymized) data from your class. How strong is the correlation between midterm grades and final exam grades? Do students who hand in homework regularly do better on the test? 

* reference: Pleuni Pennings, Mayra M. Banuelos, Francisca L. Catalan, Victoria R. Caudill, Bozhidar Chakalov, Selena Hernandez, Jeanice Jones, Chinomnso Okorie, Sepideh Modrek, Rori Rohlfs, Nicole Adelstein Ten simple rules for an inclusive summer coding program for non-CS undergraduates, accepted for publication in Plos Computational Biology.

The ridiculous order of the streets in the Excelsior (SF)

I live in the Excelsior neighborhood in San Francisco. My street is Athens Street. If I walk westwards from my home, I come to Vienna Street and then Naples, Edinburgh and Madrid. If you have any knowledge of map of Europe, you realize that the order makes no sense!

(Also, why is there Naples, but not Rome, and why Munich, but not Berlin? And why oh why, is there no Amsterdam Street? So many questions!)

Last week, I asked the students in the CoDE lab to create a map to show the ridiculous order of the streets in the Excelsior. They had fun figuring out how to make a map in R, so I thought I share their work here. Several students were involved, but my graduate student Olivia Pham did most of the work.

The code is here: http://rpubs.com/pleunipennings/212840

The surprising order of street names in the Excelsior neighborhood in San Francisco. We connected the cities in the order of the streets. London Street is the first city-name street if you enter the neighborhood from Mission Street, just east of London Street is Paris Street, then Lisbon Street etc. The last city-name street is Dublin Street which is closest to McLaren Park.

A map of part of the Excelsior neighborhood showing the order of the city-name streets.

The acknowledgement section of our NSF proposal

A few weeks ago two colleagues and I submitted an NSF proposal. We submitted on a Friday afternoon even though the deadline wasn’t until Tuesday! I am proud that we managed this almost without any deadline stress!

I had fun and we wrote a great proposal

I know that we may not end up getting funded by NSF, but until we get that message, I plan to be very optimistic. We wrote a really neat proposal for a great project. I can’t wait to get started! The ambitious goal of the project is to determine the fitness cost of every possible point mutation in the HIV genome in vivo.

I think nobody likes to write proposals when the success rate is only 5%, but I actually enjoyed working on this proposal and I learned a lot while writing it: both about the biology of our project and about the art of proposal writing. It’s important for me to commit that to paper (OK, screen) so that if NSF decides not to fund us, I will remember that writing the proposal was actually a good experience.

Writing with a newborn

In addition the many scientists and administrators who contributed to the proposal, I also want to mention how I could write a proposal with a newborn. We started working on the proposal two weeks before I gave birth and we submitted the proposal when our baby was just shy of seven weeks old. The hours that I spent on the proposal were made possible by my mom who flew in to help and by the fact that Facebook gives new parents four months paid paternity leave so that my husband was also at home during my maternity leave. It was fun to be home together with my husband and we took shifts working and taking care of Maya. Most days I worked on the proposal just two or three hours, so a large part of the work was done by others.

Me in my home office with baby, changing table, a laptop and a grant writing handbook.

It was a huge team effort

Many people were involved in writing the proposal. Many more than I ever expected to be. I want to list them here so that I remember who helped out and also to show that being a researcher doesn’t have to be a lonely affair.

Note that these people are only the people I am aware off. Others certainly helped my co-PI Adi Stern.

The main team that wrote the proposal consisted of four people:

• co-PI Adi Stern (Tel Aviv)
• postdoc Marion Hartl (SFSU)
• professional grant writer Kristin Harper
• myself

At SFSU, people from the Office for Research and Sponsored Programs helped:

• Rowena Manalo
• Raman Paul
• Michael Scott
• Jessica Mankus
• Uschi Simonis (vice-dean for Research)

At Stanford there were

• co-PI Bob Shafer
• collaborator David Katzenstein
• Elizabeth White (Katzenstein lab)
• Holly Osborne (Office for Sponsored Research)

In Tel Aviv

• Office for Sponsored Research
• Adi Stern’s lab members brainstormed ideas
• Maoz Gelbart help with ideas and figures

Colleagues who read earlier versions of the proposal

• Sarah Cobey (U Chicago)
• Sarah Cohen (SFSU)
• Alison Feder (Stanford)
• Nandita Garud (UCSF)
• Arbel Harpak (Stanford)
• Joachim Hermisson (U Vienna)
• Claus Wilke (U Texas Austin)

A huge thank you to all these amazing people! I am lucky to be part of such a supportive community.

Jobs in physiology and CS at SFSU

There are two job searches that interest me this year on our campus. One in our department (Biology) for an animal physiologist (the committee already started looking at applications, so if you are interested, you need to be fast!). The link to the ad is here .

The second search is in the Computer Science Department, and the ad is here. They are looking for someone with a “background in the database area, but also in areas related to social networking and collaboration, mobile computing, cloud computing and/or human/computer interaction.”

Both jobs are open to candidates at the assistant or associate professor level.

SFSU is a great place to work. Here are all the reasons why I am happy to be at SFSU.

If you are interested in doing research, training an extremely diverse student body and living in San Francisco, you should apply! Shoot me an email if you have any questions (pennings at sfsu dot edu).

 

 

 

A reading seminar where every student reads, writes and contributes to the discussion in class

I remember reading seminars as follows: one student spends the entire week preparing for a powerpoint presentation, which often turns out to be stressful for the student and somewhat boring and uninformative for the audience. The other students only glanced over the paper and so any discussion quickly falls flat. I therefore decided to have multiple short presentations without powerpoint (less preparation, more fun to listen to, plus repetition is good for learning a skill). I also decided to use short writing assignments as homework to make sure that all students were prepared to contribute to the discussion in class. At the same time, I wanted to keep things manageable for everyone.

1. Learning to present: every student does multiple short presentations without powerpoint.

No powerpoint: I didn’t want students to spend too much time preparing a presentation. I believe that often, when students spend a lot of time preparing presentations, they focus too much on making powerpoint slides and not enough on informing the audience and telling a story.

Short presentations: Doing an engaging 45 minute presentation is extremely difficult, and a skill that most postdoc don’t have, so why do we use 45 minute presentations in our graduate seminars? I decided in stead to let each student do three 10 minute presentations.

Feedback: After each presentation the presenters got feedback (from the other students and myself), so that they could improve their presentation skills during the semester.

Easy listening: An added benefit of 10 minute presentations is that it is much easier for the audience. Each week started with three student presentations, one on the background and main question of the paper, one on the data and the results of the paper, and one on the conclusion and implications of the paper.

2. Practice writing: every student does a different writing assignment every week.

Graded homework each week: A paper discussion can only work if people have read the paper. If students don’t read, they may spend most of their energy to try to hide that they didn’t read (I know I was in that situation!). So even though I understand that life and research get in the way of reading, I really wanted to make sure that the students were prepared for the seminar. To do that, I made every student do a written assignment every week that would count towards their grade (unless they were presenting that week).

A different assignment for each student: I had a long list of assignments so that each week, many different assignments were done AND so that over the course of the semester each student did many different assignments. This guaranteed that the students read the paper, but each with a different question in mind.

There were several types of written assignments. Descriptive: 1. Describe the background and main question of the paper, 2. describe the data and the results, 3. describe the conclusions, 4. describe which virus the paper is about. Critical: 5. What is your opinion of the paper? 6. What do you think the authors should have done differently? 7. Play the devil’s advocate: why should the paper not have been published? Summaries: 8. Summarize the paper in your own words, as if writing to a friend, 9. summarize the paper using only the most common 1000 words of the English language, 10. summarize the paper in a graphical abstract, 11. summarize the paper in a tweet. Meta: 12. Who are the authors of the paper? 13. How often is the paper cited, do you think it is influential?

Short! Each written assignment could not be more than 150 words, to keep the workload manageable for me and for the students.

Surprisingly hard: Some of the assignments were harder than the others. Summarizing the paper using only the 1000 most common words from the English language turned out to be very hard, but some of the students did a great job (see here and here). The graphical abstract was also hard for some students, but others liked it just because it was so different from their usual work (see here and here). The ”devil’s advocate” writing assignment was always very interesting to read.

Easy: Grading the written assignments was quite easy. I simply gave a plus or minus for 5 categories (answered the question, scientific accuracy, clarity, grammar and word count).

Revisions allowed: After a request from a student, I decided that the students could redo any assignment where they had gotten less than 100% because I believe that feedback is most useful when it can be applied to a revision.

3. Promoting equity: thanks to the written assignments, every student could contribute to every class.

Everyone contributes: One of the nice things about the homework schedule with different assignments for everyone is that in class, I could ask each student about their homework. This way, each student contributed to the class, promoting equity, and the brief discussions of the homework assignments always let to questions from other students. Even if I didn’t ask, some students would volunteer to share information they found while they researched for their homework. For example, I remember someone remarking at the end of a presentation: “In your presentation, you said this result may be very important, but I found that the paper hardly has any citations even though it was published ten years ago, so I think it may not have been picked up by anyone.”

Sharing homework: I also encouraged the students to share their written assignments on the online forum we had for the class, so that the other students (and not just me) could read them. Sometimes they led to interesting forum threads. I also published some of the written assignments on my blog, after asking the students for permission. This way even more people could enjoy them.

Heb B study graphical abstract using paper and pens

One of the most fun things about teaching a grad seminar last semester was reading the homework assignments. Seriously!

Before I move on to the next semester (teaching genetics for undergrads), I wanted to share one more homework assignment. This one by Emily Chang, a graduate student in Scott Roy’s lab. The paper about viral quasispecies in Hep B was one of the harder ones for the students, but this graphical abstract very neatly sums up the main results. I also love that Emily used old fashioned paper and pens to make the abstract, knowing that using fancy drawing software isn’t needed to communicate science.

Graphical abstract by Emily Chang

How I survived my first semester as assistant prof (with a new baby)

First of all, the job as assistant professor is all mine, but the baby is very much shared with my husband.

Earlier this year I gave birth to a baby boy and two months later I started my new position as an assistant professor in biology at San Francisco State University. Several people have asked me how I managed to combine the baby and the new job and not go insane (*).

The first semester is over, our baby is 6 months old, and I didn’t go insane. I taught a class, submitted a paper, wrote a grant proposal, went to a conference (baby & husband came along!) and served on a search committee. In fact, I enjoyed the semester (but now it is time for a break!)

Here are some of the things that made it possible.

1. My husband, because he never thinks that taking care of a baby is something that only women should do.

2. Facebook, the company where my husband works, because they give men and women four months of parental leave to be taken any time during the first year. Knowing that my husband could take time off during my first semester as a professor made a big difference, because we didn’t know how things would work out with work, teaching, nanny, and baby. Without the generous parental leave from Facebook, I would not have started my job this semester, instead, I would have started the new job 6 months later. Also thanks to his parental leave, he and baby could travel with me to the conference I went to on the East Coast.

3. My colleagues at SFSU because they did not put any pressure on me this semester. They understood when I missed department meetings or when I didn’t show my face on campus for days in a row. Maybe it helped that many of the professors in my department are women with kids.

4, Professional help. We live far away from our families, so we depend on professional help with childcare. We had a night nanny early on, which really helped us get some sleep. Then when the baby was two months old we hired a full-time nanny. We could not have combined work and parenting if we wouldn’t have hired these amazing professionals.

5. Saying no. I only taught one class. I did no reviews. I started no new projects. I accepted only one student in my lab and this only in the second half of the semester. I didn’t buy furniture for my office space yet. I didn’t go to our departmental seminars. I only had lunch with colleagues a few times. These things will have to change next semester!

—-

*I think that often, behind such a question (“how do you do it?”) is the tacit assumption that I, as the woman, do most of the caring for the baby. This is not the case. My husband does just as much, if not more.

My husband and I were both at home for the first two months after our baby was born, but I usually hear: “Wow, you went back to work after only two months?”, whereas he hears: “Wow, how cool that you were home for two full months!”

So if you are wondering how it was for me to go back to work after two months of being at home with our newborn, you should really be asking my husband the same thing. Maybe he’s interested in writing a blog too.

 

No powerpoint allowed

One of the students in my class (Arturo Altamirano) as he is giving a talk about Influenza virus. The drawings on the whiteboard were a very helpful for understanding his presentation.

One of the things I did in my seminar this semester was to prohibit the use of Powerpoint or any other presentation software. For their talks, the students had to use the whiteboard or handouts or anything that didn’t require a projector. Most of them used the whiteboard. Initially some of them didn’t like it much. But every student had to give three short presentations during the semester and so they had a chance to improve their whiteboard skills during the semester.

Focus on the story

I asked them not to use Powerpoint because I wanted to make sure that they did not spend a lot of time preparing beautiful slides. Instead, I wanted them to you to focus on the story of their presentation and the connection with their audience. I’m happy that I made this decision because the presentations that students did were really nice and I think they wouldn’t have been as good if I had allowed Powerpoint. All of the students improved their presentation skills during the semester and as the semester progressed, it got more more fun to listen to their talks.

Whiteboard exercises

One thing I will do differently next time is that I will start the semester with some exercises to become familiar with using the whiteboard. I am thinking about asking each student in the first class to introduce themselves using the whiteboard. For example, they could draw (very roughly) the geographic location of the cities or neighborhoods in which they have lived. The exercise would be to combine drawing on the whiteboard and talking to an audience. And hopefully, such an exercise would take away some of the fear they may have about talking without slides.

The picture I attach to this blog is of one of the students in the class (Arturo Altamirano) as he is giving a talk about Influenza virus. The drawings on the whiteboard were a very helpful for understanding his presentation.

World AIDS Day at SF State

Yesterday it was the 1st of December, and I almost forgot that it was world AIDS day! However walking around on the campus of SF State University (where I work) reminded me of the day it as. On the central lawn of the campus red and blue flags were planted in the shape of an aids ribbon. Surrounding the lawn along the path, there were white labels with names of people who died of AIDS. Some of these people were students or staff of SF State University. Others were well known people, such as Nelson Mandela’s son, Makgatho Mandela. In addition, in the student union the SF State AIDS memorial quilt is on display, with names of people from SF State who died of AIDS. The sign next to the quilt explains that Cleve Jones, who started the AIDS quilt was also an SF State student.

Finally, the university health services offered HIV testing yesterday. Testing is extremely important, because many people in the US do not know they are infected with HIV and these people may unknowingly infect others. If you’re looking for a place to get tested in San Francisco, check out the website of the San Francisco AIDS Foundation.

I attach some pictures to this blog.