What does it mean for Computer Science to be harder to learn than other STEM subjects?

I made an argument in my Blog@CACM Post for this month that “Learning Computer Science is Different than Learning Other STEM Disciplines,” and on Twitter, I explicitly added “It’s harder.”

In my Blog@CACM post, I thought it was a no-brainer that CS is harder:

  1. Our infrastructure for teaching CS is younger, smaller, and weaker  (CS is so new, and we don’t have the decades of experience to figure out how to do it well yet.)

  2. We don’t realize how hard learning to program is (The fact that the Rainfall problem seems easy, but it’s clearly not easy, means that CS teachers don’t know how to estimate yet what’s hard for students, so our classes are probably harder than we mean them to be.)

  3. CS is so valuable that it changes the affective components of learning (Classes that are stuffed full of both CS majors and non-majors means that issues of self-efficacy, motivation, and belonging are much bigger in CS than in other STEM disciplines.)

The push back was really interesting.  People pointed out that they took CS classes and math classes, or CS and physics, and CS seemed easy in comparison.  They may be right, but that’s self-report on introspection by people who succeeded at both classes.  My point is that we are probably flunking out (or students are giving up, or opting out) of CS at much higher rates than any other STEM subject, because of the reasons I give.  We’re really using two different measures of “harder” — harder to succeed, or harder in retrospect once succeeded.

I only have a qualitative argument for “It’s harder.” I’m not sure how one would even evaluate the point empirically.  Any suggestions?  How could we measure when one subject is harder than another?

It’s not an important question to answer which is harder, CS vs math, or CS vs physics. A much more important and supportable claim is that CS “is harder” than it needs to be.  We have a lot of extraneous complexity and cognitive load in learning CS.

January 19, 2018 at 7:00 am 17 comments

ICER 2018 Call for Participation (I’m co-chairing Works in Progress)

Do submit to ICER 2018 in Finland.  I particularly encourage you to join the Works in Progress workshop, for which I’ll be the junior co-chair as I learn the ropes from Colleen Lewis. I was a participant in the Works in Progress workshop in Glasgow and found it fun and useful.

ICER’18 – Call For Participation

The fourteenth annual ACM International Computing Education Research (ICER) Conference aims to gather high-quality contributions to the computing education research discipline. We invite submissions across a variety of categories for research investigating how people of all ages come to understand computational processes and devices, and empirical evaluation of approaches to improve that understanding in formal and informal learning environments.


Research areas of particular interest include:
– discipline based education research (DBER) in computer science (CS), information sciences (IS), and related disciplines
– design-based research, learner-centered design, and evaluation of educational technology supporting computing knowledge or skills development
pedagogical environments fostering computational thinking
learning sciences work in the computing content domain
psychology of programming
learning analytics and educational data mining in CS/IS content areas
learnability/usability of programming languages
informal learning experiences related to programming and software development (all ages), ranging from after-school programs for children, to end-user development communities, to workplace training of computing professionals
measurement instrument development and validation (e.g., concept inventories, attitudes scales, etc) for use in computing disciplines
research on CS/computing teacher thinking and professional development models at all levels
rigorous replication of empirical work to compare with or extend previous empirical research results
systematic literature review on some topic related to computer science education


In addition to standard research paper contributions, we continue our longstanding commitment to fostering discussion and exploring new research areas by offering several ways to engage. These include a doctoral consortium for graduate students just prior to the conference, a work-in-progress workshop for researchers following the conference, and poster and lightning talks. This is in addition to the format of conference sessions, where all research paper presentations include time for discussion among the attendees followed by feedback to the paper presenters.

Submission Categories

ICER provides multiple options for participation, with various levels of discussion and interaction between the presenter and audience. These sessions also support work at various levels, ranging from formative work to polished, complete research results.


Research Papers
Papers are limited to 8 pages, excluding references, double-blind peer reviewed and published in the ACM digital library as part of the conference proceedings. Accepted papers are allotted time for presentation and discussion at the conference


Doctoral Consortium
2 page extended abstract submission required and published in ACM digital library as part of the conference proceedings. Students will present their work to distinguished faculty mentors during an all-day workshop and during the conference in a dedicated poster session.


Lightning Talks and Posters
Abstract (250 words) submission required and made available on conference website, but not published in proceedings. Accepted abstracts for lightning talks will be given a 3-minute time slot for rapid presentation at the conference followed by a discussion period for all attendees. Posters may either accompany a lightning talk or may be proposed separately using the same abstract submission process.


Work in Progress Workshop
This one-day workshop is a venue to get sustained engagement with and feedback about early work in computing education.    White paper submission required but not included in proceedings.


Co-located Workshops
Proposals for pre/post conference workshops of interest to the ICER community (i.e., those that aim to advance computer science education research) are welcomed and encouraged. ICER local arrangements personnel will be available to assist with workshop logistics where possible. If interested, contact the conference chairs for more details by April 10th, 2018: Lauri.Malmi@aalto.fi or Ari.Korhonen@aalto.fi.


For more information about preparation and submission, please visit the page corresponding to the submission type of interest.

Important Deadlines and Dates


Research Papers

30 March, 2018 – – Abstract submission (250 words, mandator)
6 April, 2018 – – Full paper submission 
1 June – – Notification of acceptance 
15 June – -Final camera ready deadline
Other Submission Types
1 May – – Doctoral consortium submissions
8 June – – Lightning talk and Poster proposals
8 June – – Work in progress workshop application

Conference Schedule

Doctoral Consortium, Sunday, August 12, 2018
ICER Conference, Monday, August 13 – Wednesday August 15, 2018
Work in Progress Workshop, Wednesday evening, August 15 – Thursday, August 16, 2018
For more details, see the conference website:
 http://www.icer-conference.org

Conference Co-Chairs
Lauri Malmi, Aalto University, Finland (Lauri.Malmi@aalto.fi)
Ari Korhonen, Aalto University, Finland (Ari.Korhonen@aalto.fi
Robert McCartney, University of Connecticut, USA (robert.mccartney@uconn.edu)
Andrew Petersen, University of Toronto Mississauga, Canada (andrew.petersen@utoronto.ca)


AUTHORS TAKE NOTE: The official publication date is the date the proceedings are made available in the ACM Digital Library. This date will be up to two weeks prior to the first day of the conference. The official publication date affects the deadline for any patent filings related to published work.

January 15, 2018 at 7:30 am Leave a comment

Georgia Tech Launches Constellations Center Aimed at Equity in Computing

 

The Constellations Center was launched at a big event on December 11.  I was there, to hear Executive Director Charles Isbell host the night, which included a great conversation with Senior Director Kamau Bobb (formerly of NSF).

 

Constellations is going to play a significant role in keeping a focus on broadening participation in computing in Georgia, and to serve as a national leader in making sure that everyone gets access to computing education.

Georgia Tech’s College of Computing has launched the Constellations Center for Equity in Computing with the goal of democratizing computer science education. The mission of the new center is to ensure that all students—especially students of color, women, and others underserved in K-12 and post-secondary institutions—have access to quality computer science education, a fundamental life skill in the 21st century.

Constellations is dedicated to challenging and improving the national computer science (CS) educational ecosystem through the provision of curricular content, educational policy assessment, and development of strategic institutional partnerships. According to Senior Director Kamau Bobb, democratizing computing requires a “real reckoning with the race and class divisions of contemporary American life.”

See more here.

January 12, 2018 at 7:00 am Leave a comment

Analysis of 2017 AP CS exam participation from Barbara Ericson

Like last year, I’m pleased that we can rely on others to write the blog post on Barbara Ericson’s annual AP CS exam data analyses.  The College of Computing at Georgia Tech just wrote a nice description of the findings here: Positive Signs, But Diversity Still Lagging in AP Computer Science Exam Participation, and quoted in part below. Barb’s detailed analyses can be found here, and her detailed gender and race analyses are here.

Barb has been doing more visualizations of her data.  The GVU Center at Georgia Tech produced this nice summary of 20 years of AP CS A data, by state. Of the images she’s produced, this is the one that I find most compelling — the number of exam-takers per 100,00 people in the state.  There are some big goose eggs and many single digit numbers out there.

Increasing female & minority access

According to Barbara Ericson, Georgia Tech research scientist and author of the analysis, the introduction this year of a new AP CS P course and exam contributed to the increases.

“This is exactly what we hoped for. The CS principles course is on par with a college-level intro course for non-CS majors, so it is more accessible to more people,” said Ericson.

Officials had estimated nearly 20,000 AP CS P exams would be taken this year. However, Ericson said the actual number topped 40,000.

“Although overall growth in female and minority participation in the AP CS A exam was relatively flat this year, we’re hopeful that the introduction of the P exam will help swell A exam participation rates in the next few years.”

AP Computer Science A

Despite marginal growth among underrepresented students, overall participation in the AP CS A exam grew by 11.2 percent year-over-year in 2017. A record 60,519 U.S. high school students took the exam with an overall pass rate of 61.8 percent, up more than a percentage point from the previous year.

“It’s great to see growth across the board, but there’s still a long way to go before AP computer science is as available in U.S. classrooms as, say, AP Physics or Calculus,” said Ericson.

More than 170,000 students took the AP Physics 1 exam this year, while more than 316,000 took the AP Calculus AB exam.

January 8, 2018 at 7:00 am 4 comments

What universities can do to prepare more Computer Science teachers? Evidence from UTeach

UTeach has published a nice blog post that explains (with graphs!) the ideas that I alluded to in my Blog@CACM post from last month.  While currently CS teacher production is abysmal, UTeach prepared CS teachers tend to stay in their classrooms for more years than I might have expected.  More, there is evidence that suggests that there is significant slice of the CS undergraduate population that would consider becoming teachers if the conditions were right.  There is hope to imagine that we can making produce more CS teachers, if we work from the University side of the equation.  Working from the in-service side is too expensive and not sustainable.

Michael Marder, Professor of Physics and Executive Director of UTeach, and Kim Hughes, Director of the UTeach Institute, write…

The number of computer science and computer science education teachers prepared per year is smaller than for any other STEM subject — even engineering and physics — and while estimates vary, it is safe to say it is on the order of 100 to 200 per year, compared to the thousands of biology or general science teachers prepared. 

The U.S. has around 24,000 public and 10,000 private high schools. Only 10% to 25% have been offering computer science, so to provide all of them with at least one teacher at the current rate simply looks impossible.

Source: What universities can do to prepare more Computer Science teachers

January 5, 2018 at 7:00 am Leave a comment

Do we really want computerized personalized tutoring systems? Answer: Yes

An excerpt from Mitchel Resnick’s new book Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play is published below in the Hechinger Report.  Mitchel argues against computerized personal tutoring systems, because they are only good for “highly structured and well-defined knowledge.”  Because we don’t know how to build these tutoring systems to teach important topics like creativity and ethics.

Agreed, but we are not currently reaching all students with the “highly structured and well-defined knowledge” that we want them to have. We prefer students to have well-educated teachers, and we want students to learn creativity and ethics, too. But if we can teach topics like mathematics well with personalized tutoring systems, why shouldn’t we use them?  Here in Atlanta, students are not learning mathematics well (see blog post referencing an article by Kamau Bobb). We have good results on teaching students algebra with cognitive tutors.

Here’s my concern: Wealthy schools can reject computerized personal tutoring systems because they can afford well-trained teachers, which means that there is less of a demand for computerized personal tutoring systems. Lower demand means higher costs, which means that less-wealthy schools can’t afford them. If we encourage more computerized personal tutoring systems where they are appropriate, more of them get created, they get better, and they get cheaper.

But I’m skeptical about personalized tutoring systems. One problem is that these systems tend to work only in subject areas with highly structured and well-defined knowledge. In these fields, computers can assess student understanding through multiple-choice questions and other straightforward assessments. But computers can’t assess the creativity of a design, the beauty of a poem, or the ethics of an argument. If schools rely more on personalized tutoring systems, will they end up focusing more on domains of knowledge that are easiest to assess in an automated way?

Source: OPINION: Do we really want computerized systems controlling the learning process? – The Hechinger Report

January 3, 2018 at 7:00 am 6 comments

Require CS at University in order to Get CS into K-12 (Revisited)

I wrote a blog post in Blog@CACM in 2011: If You Want High School CS, Require Undergraduate CS.  Everything we’ve seen since then makes me more convinced this is a viable path to providing high-quality CS education for every student.

There is a growing body of evidence that every student at University will need computing. The recent report from Burning Glass and Oracle Academy shows how much in demand CS skills are, far beyond just those who will be professional software developers. Teaching everyone about computing would help in addressing Cathy O’Neill’s calls for more people to be investigating the algorithms controlling our lives. The argument for why University involvement is necessary for K12 CS Ed is based on an observation made recently by Code.org: We are not producing enough CS teachers in University. If everyone took CS at University, that would also reach pre-service teachers. That would make it easier for those teachers to teach CS in the future.

Requiring CS at University may help with the bigger cultural and perception problem.  In England, we see that schools aren’t offering CS even if it’s part of the required curriculum, and students (especially females) aren’t taking it (see the Royal Society report from last month).  The problem is that we’re trying to shoehorn CS into a culture that isn’t asking for it, or rather, the students (and schools) don’t perceive a need for CS. This is a form of the same problem that came up when we were talking about getting more formal methods into software development practice. All professionals should understand the role of computing in our society and how to use computing as a literacy: To express ideas, to share ideas, and to use in developing ideas.

Schools follow society. Society is rarely (if ever) changed by schooling. If you want a computationally literate society, convince the adults. If most professionals use computing, the same professionals that students want to be like, then there is a social reason to learn computing. Social demand to prepare K-12 students in that literacy makes it more likely for that literacy to succeed in K-12 education.  Trying to teach all students something that society doesn’t value for everyone is counter to situated learning theory.  Students (even K-12 students) are engaged in legitimate peripheral participation — their “job” is to figure out what is expected of them in society. If they don’t see computational literacy broadly in society, students don’t get the message that it’s important for everyone to learn.

When I make this suggestion to University faculty, I often hear the argument, “Anything you require of students, they will hate.” Then they tell me an anecdote of some student who hated a requirement, or of some personal experience of a class they hated. I know of no empirical evidence that says that this is generally true. We do have empirical evidence that says it’s false. Mike Hewner’s work found that US students take required classes in order to discover what they like, and they make curricular choices based on what they like.

We are already seeing students from all over campus flooding into our classes (see the Generation CS report and the National Academies report). We are already learning how to manage the load. It’s already happening in some Universities that most or all students at University are taking CS. Why not require it so that we get the Education students who we may not be seeing yet in CS classes?

Instead of using Universities to make CS education work, we are pouring money into CS Ed via in-service professional development — a tenfold increase in England, and $1.5B in the next five years in the US.  In general, more money in education alone doesn’t change things. We have to think about systems, policies, and our educational ecosystem. Universities are part of that educational ecosystem.

Universities play a role in K-12 education in all other subjects. We have to involve them in order to create sustainable K-12 Computer Science education.

December 15, 2017 at 7:00 am Leave a comment

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