Posts tagged ‘university CS’

MIT creates a College of Computing to integrate across all disciplines

Last month, MIT announced the creation of the MIT Schwarzman College of Computing, with a $1 Billion commitment (see article here).  Below is my favorite part of the press release.  I’ll paraphrase the elements that have me excited about what MIT is going do with this new College:

  • It’s not just about taking CS to the other disciplines. It’s about “allowing the future of computing and AI to be shaped by insights from all other disciplines.”  This is key to Peter Denning’s notion of Computing and not just Computer Science.  Computing is about the rest of the world influencing, pushing, and advancing what we know about computer science.
  • The 50 new positions are going to be in the College and joint with other departments.  That’s a key step to get integration.
  • When they talk about what they’re going to do with this new College, “education” is the first word, and “research and innovation” are second and third.  Does that ordering imply a priority? Will it really keep those priorities? Who knows, but they’re good words.
  • There goal is that every student knows to “responsibly use and develop” computing technologies and AI.  Is MIT going to institute a campus-wide computing course requirement?  Even better would be to make sure that there is significant computing in the disciplinary courses.  The NYTimes article (see here) quotes MIT President Reif as aiming to “educate the bilinguals of the future.”

    He defines bilinguals as people in fields like biology, chemistry, politics, history and linguistics who are also skilled in the techniques of modern computing that can be applied to them.

Yes! That’s an exciting vision.

Headquartered in a signature new building on MIT’s campus, the new MIT Schwarzman College of Computing will be an interdisciplinary hub for work in computer science, AI, data science, and related fields. The College will:

  • reorient MIT to bring the power of computing and AI to all fields of study at MIT, allowing the future of computing and AI to be shaped by insights from all other disciplines;

  • create 50 new faculty positions that will be located both within the College and jointly with other departments across MIT — nearly doubling MIT’s academic capability in computing and AI;

  • give MIT’s five schools a shared structure for collaborative education, research, and innovation in computing and AI;

  • educate students in every discipline to responsibly use and develop AI and computing technologies to help make a better world; and

  • transform education and research in public policy and ethical considerations relevant to computing and AI.

 

November 19, 2018 at 8:00 am 5 comments

Workshops for New Computing Faculty in Summer 2018: Both Research and Teaching Tracks

This is our fourth year, and our last NSF-funded year, for the New Computing Faculty Workshops which will be held August 5-10, 2018 in San Diego. The goal of the workshops is to help new computing faculty to be better and more efficient teachers. By learning a little about teaching, we will help new faculty (a) make their teaching more efficient and effective and (b) make their teaching more enjoyable. We want students to learn more and teachers to have fun teaching them. The workshops were described in Communications of the ACM in the May 2017 issue (see article here) which I talked about in this blog post. The workshop will be run by Beth Simon (UCSD), Cynthia Bailey Lee (Stanford), Leo Porter (UCSD), and Mark Guzdial (Georgia Tech).

This year, for the first time, we will offer two separate workshop tracks:

  • August 5-7 will be offered to tenure-track faculty starting at research-intensive institutions.
  • August 8-10 will be offered to faculty starting a teaching-track job at any school, or a tenure-track faculty line at a primarily undergraduate serving institution where evaluation is heavily based in teaching.

This year we added new organizers, Ben Shapiro (Boulder) for the research-intensive track, and Helen Hu (Westminster) and Colleen Lewis (Harvey Mudd) for the teaching-intensive track.

The new teaching-oriented faculty track is being added this year due to enthusiasm and feedback we heard from past participants and would-be participants. When I announced the workshops last year (see post here), we heard complaints (a little on email, and a lot on Twitter) asking why we were only including research-oriented faculty and institutions. We did have teaching-track faculty come to our last three years of new faculty workshops that were research-faculty focused, and unfortunately those participants were not satisfied. They didn’t get what they wanted or needed as new faculty. Yes, the sessions on peer instruction and how to build a syllabus were useful for everyone. But the teaching-track faculty also wanted to know how to set up their teaching portfolio, how to do research with undergraduate students, and how to get good student evaluations, and didn’t really care about how to minimize time spent preparing for teaching and how to build up a research program with graduate students while still enjoying teaching undergraduate students.

So, this year we made a special extension request to NSF, and we are very pleased to announce that the request was granted and we are able to offer two different workshops. The content will have substantial overlap, but with a different focus and framing in each.

To apply for registration, To apply for registration, please apply to the appropriate workshop based on the type of your position: research-focused position http://bit.ly/ncsfw2018-research or teaching-focused position http://bit.ly/ncsfw2018-teaching. Admission will be based on capacity, grant limitations, fit to the workshop goals, and application order, with a maximum of 40 participants. Apply on or before June 21 to ensure eligibility for workshop hotel accommodation. (We will notify respondents by June 30.)


Many thanks to Cynthia Lee who helped a lot with this post

June 12, 2018 at 6:00 am 1 comment

What Universities Must Do to Prepare Computer Science Teachers: UTeach leads a multi-university group to grow computing education

Kimberly Hughes, Director of the UTeach Institute at The University of Texas at Austin has written a blog post about a multi-university effort to grow CS education. They have an interesting set of recommendations. I look forward to seeing the white paper that the blog post promises!

In-service teacher professional development has been key to the explosive growth of K–12 CS education offerings, but the role of universities in the preparation of computer science teachers is absolutely critical if we are going to address the current shortage of CS teachers at scale and with any kind of lasting impact. Yet there are precious few exemplars on which to model new programs. Partly this has been a chicken and egg problem. For example, the UTeach program at UT Austin has had an undergraduate pathway to CS certification for more than ten years. But with so little demand for CS teachers at secondary schools throughout the state, very few students were recruited and prepared. Now that the demand for CS teachers is increasing, UTeach Austin and other UTeach partner universities are ramping up and expanding their efforts.

Source: What Universities Must Do to Prepare Computer Science Teachers: Networked Improvement in Action

February 23, 2018 at 7:00 am 5 comments

How to be a great (CS) teacher from Andy Ko

Andy Ko from U-W is giving a talk to new faculty about how to be a great CS teacher.  I only quote three of his points below — I encourage you to read the whole list.  Andy’s talk could usefully add some of the points from Cynthia Lee’s list on how to create a more inclusive environment in CS.  CS is far less diverse than any other STEM discipline.  Being a great CS teacher means that you’re aware of that and take steps to improve diversity in CS.

My argument is as follows:

  • Despite widespread belief among CS faculty in a “geek gene”, everyone can learn computer science.
  • If students are failing a CS class, it’s because of one or more of the following: 1) they didn’t have the prior knowledge you expected them to have, 2) they aren’t sufficiently motivated by you or themselves, 3) your class lacks sufficient practice to help them learn what you’re teaching. Corollary: just because they’re passing you’re class doesn’t mean you’re doing a great job teaching: they may already know everything you’re teaching, they may be incredibly motivated, they may be finding other ways to practice you aren’t aware of, or they may be cheating.
  • To prevent failure, one must design deliberate practice, which consists of: 1) sustained motivation, 2) tasks that build on individual’s prior knowledge, 3) immediate personalized feedback on those tasks, and 4) repetition.

Source: How to be a great (CS) teacher – Bits and Behavior – Medium

May 29, 2017 at 7:00 am Leave a comment

Every University Student should Learn to Program: Guzdial Arguing for CS for All in Higher Education

A colleague recently approached me and said, “It would be useful if Universities got involved in this CS for All effort.  All Universities should offer courses aimed at everyone on campus. There should be a systematic effort to get everyone to take those classes.”

I agree, and have been making this argument for several years now.  I spent a few minutes gathering the papers, blog posts, and book where I’ve made that argument over the last decade and a bit.

In 2002, Elliot Soloway and I argued in CACM that we needed a new way to engage students in intro programming: Teaching the Nintendo Generation to Program.

In 2003, I published the first paper on Media Computation: A media computation course for non-majors.

In 2004, Andrea Forte led the team studying the Media Computation class at GT:Computers for communication, not calculation: Media as a motivation and context for learning and  A CS1 course designed to address interests of women.

In 2005, Andrea Forte and I presented empirical evidence about the courses we’d designed for specific audiences: Motivation and nonmajors in computer science: identifying discrete audiences for introductory courses. I published a paper in CACM about how the courses came to be at Georgia Tech: Teaching computing to everyone.

In 2008, I offered the historical argument for teaching everyone to program: Paving the Way for Computational Thinking.

We’ve published several papers about our design process: Imagineering inauthentic legitimate peripheral participation: an instructional design approach for motivating computing education and Design process for a non-majors computing course.

My 2013 ICER paper was a review of a decade’s worth of research on Media Computation: Exploring hypotheses about media computation

My keynote at VL/HCC 2015 was on how computing for all is a requirement for modern society: Requirements for a computing-literate society

My 2015 book is, to a great extent: an exploration of how to achieve CS for All: Learner-Centered Design of Computing Education: Research on Computing for Everyone.

In blog posts, it’s been a frequent topic of conversation:

I don’t know how to convince University CS departments to do just about anything, but here are my contributions to the dialogs that I hope are happening at Colleges and Universities worldwide about how to prepare students to engage in computational literacy.

September 19, 2016 at 7:15 am 17 comments

College-level CS Principles Courses

My Blog@CACM post for July is about why I gave up on creating a CSP equivalent course at Georgia Tech — see post here.  The conclusions are (a) I’m not convinced that AP is the best lever available for getting CS into Georgia schools that don’t have CS and (b) Georgia Tech already has a set of intro courses that cover CSP-like content, are contextualized for different majors, and are successful.  I wish more universities had CSP-like courses.

Towards that end, I’m listing there the college-level CSP courses that I found when starting to build one for Georgia Tech.  Offered here as a resource to others.

August 5, 2016 at 7:01 am 2 comments

The Connected Learner: The Teaching Research Taboo

The Connected Learner is an interesting project led by Mary Lou Maher at the University of North Carolina Charlotte. Her blog post quoted below points to one of the difficulties in talking about teaching among CS faculty.

It seems relatively uncommon for research-track CS faculty to discuss their teaching at conferences and research meetings (no, I’m not saying it never happens, but it is rarely the focus, except at CS education conferences like SIGCSE and ICER). So, while we are likely aware of our colleagues’ research projects, we may not realize that our colleagues are experimenting with innovative teaching methods, trying out new learning technologies or adapting some best practices related to active learning. Because we don’t talk about it, we may think it’s not happening and this can lead to us not wanting to talk about our own innovations. We think our colleagues only value core research, so that is what we focus our own discussions on.

Source: The Connected Learner: The Teaching Research Taboo

July 1, 2016 at 8:03 am Leave a comment

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