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I’m sharing in this blog post my comments on the K12 CS Ed framework, to serve two purposes.
First, to remind you to do the review which you can start here: http://k12cs.org/review/. The review period ends Wed Feb 17 at 11:59pm PT. Please participate. If you disagree with what I write below, be sure to do the review yourself and counter what I say!
Second, I’m writing from Schloss Dagstuhl where I will be attending the first (to my knowledge) Dagstuhl Seminar on CS Education, on Assessing Learning in Introductory Computer Science (click here for more info). As the seminar leaders say in their introduction, “What is needed are shared objectives and assessment methods that enable more useful computing education research while providing guidance to those outside the area.” The K12 CS Framework is an attempt to define shared objectives, which are a necessary predecessor to effective measurement of learning.
Now, the seminar leaders also raise the research question, “What outcomes would we like to see in non-major courses that are not merely preparing students to write scripts needed on the job?” Providing students with the CS knowledge so that they can “merely prepare to write scripts needed on the job” is an important goal — which will be the focus of my poster presentation later this week.
Criteria for Concepts and Practices
Concepts and practices should…
- have broad importance across the field of computer science
I agree. Breadth is good. It’s not important to cover the field of computer science. There is more in mathematics and science than can (or should) be covered in K-12 education.
- be important and relevant to all students’ current and future lives
This is the most important criterion, in opposition to “be important to computer scientists.”
- have potential for connections with other disciplines’ practices, such as Math and Science
- be a useful tool for developing and illuminating more ideas in computer science.
The former is very important. The latter is much less so. CS is very new. I’m not sure that we have the right ideas to teach everyone. Given a choice, it’s much more important to teach everyone CS that helps them learn math and science and is useful to understand computing in their lives. I’d rather not (for example) teach hex and octal just because we use hex and octal in CS.
Computing Devices and Systems
Overview: Computing systems include a broad range of devices that incorporate hardware and software to process information using a variety of inputs and outputs. The term is not limited to computers themselves, but rather includes many everyday objects that contain computational components that sense and act on the world. Complex systems are built from simple components that interact under the control of an operating system in an ever-changing world of technology.
This is quite nice. I have a couple of suggestions. Great research by people like John Pane at CMU has shown that novices think of programs as responding to events, being reactive (e.g., think apps, games, GUI interfaces). Thinking of computing as input-processing-output is an older model, difficult to understand, and less common today.
Are operating systems so important that they belong in the overview? Yes, students should know about operating systems, but they’re not key to CS. I’m thinking of Dan Ingalls’ famous 1981 quote in Byte magazine:
Operating System: An operating system is a collection of things that don’t fit into a language. There shouldn’t be one.
Computing devices require continual diagnosis, maintenance, and upgrades. Effectively maintaining and troubleshooting complex devices is not only a critical skill, but is also essential for sustainability and cost-saving efforts. Researching and applying solutions found in existing knowledge-base resources and recognizing patterns play an important role in troubleshooting.
I strongly disagree with that first statement. I run software that’s been unchanged for over 15 years. It’s a goal of software not to require continual diagnosis, maintenance, and upgrades. It’s worth discussing why software needs continual diagnosis, maintenance, and upgrades, but it is not a key concept and assumption of CS that it does.
A computing system is comprised of an integrated collection of computer components that work together in a hierarchy to process information. At its most basic layer, a computing system operates through binary calculations conducted by transistors; at more advanced layers, a computing system is capable of performing high-level tasks, including the ability to interact with other computing systems.
Transistors? Really? Everyone has to know about transistors? Computing can be mapped to a wide variety of underlying mechanisms (see the Tinkertoy Tic-Tac-Toe computer).
An operating system allows computer components to work together. Without an operating system, computing devices have minimal, if any, utility. The complexity, capability, and compatibility of an operating system impacts the functionality of a computer system.
This is obviously a false statement. The Internet has no operating system, yet leads to many components working together to great utility.
This would be a great place to introduce systems thinking. What are ways to organize components? An operating system is one. Having a powerful set of guidelines that define interactions (like in the Internet) is another. Which works better?
Networks and Communication
Overview: With the very first computing devices, knowledge and information became a very powerful thing. Sharing of that early knowledge gained from computing was a challenge. Networking and communication systems were designed to facilitate the interconnecting of devices and sharing of information. The practices of networking and computing now encompass reliability, authentication, confidentiality, security, acceptable use, filtering, cryptography, and mitigating security concerns and system breeches. A computer or computing system can no longer exist in isolation with the age of the Internet, and with demand for immediate connectivity of large numbers of new devices, this is an area that will continue to see lots of growth and innovation. Without networks and communication, the rest of the computing world would be isolated and the speed of innovation would be much slower.
This is really quite nice — I don’t have any concerns.
Protocols are designed, refined, and selected based on the desired result of communication among devices. Protocols are developed or updated as additional devices need to be connected and the security concerns, regulation, and standardization of devices change.
I’d rather see this section be a statement about communication. Protocols are a set of agreements, made by human beings. They can be structured in a range of ways. This is a great place to connect to other systems that communicate.
Transmitted data may be passed between many devices before reaching its final destination. Computing devices choose paths to transmit data based on a number of factors including routing algorithms, distance, security, redundancy, speed, error handling, and amount of information supported.
The first sentence is absolutely an important idea for understanding the Internet. The rest goes way too deep to be useful for all high school students.
Sure, talk about how the Internet routes data. I think it’s even useful to talk about UDP, in the sense that data can get out of order and there has to be an effort to serialize it and guarantee its delivery. I love the idea of talking about routing so that we can explain by policy ideas like censorship or even “turning off the Internet” are both so hard to actually implement. It’s important to talk about the Internet as a collection of networks held together by guidelines making it complicated to change. It’s super important to point out that there is no master operating system of the Internet — which is a great place to tie into system ideas of decentralized thinking in science.
I’d like for every student to know about the Domain Name Server system. It’s a great example of mapping (how names are mapped to addresses). It’s an amazing example of a decentralized system. It’s useful to know that it’s a separate system, e.g., your “Internet” connection may be working, but you might not be able to get to Google if your DNS server is failing.
As the size and complexity of networks grow, so does the need for systems to prioritize, distribute, load balance, be redundant, perform Quality of Service, provide gateways, be resilient and adaptable; through the use of Access and Distribution Layer Switching.
I don’t see any part of this which is useful for all students to know. I can’t find any definition of what “Distribution Layer Switching” is.
Data and Information
Once collected, data can be stored using computers in a variety of ways. The choices we make about how that data is represented, organized, and physically recorded has impacts on cost, speed, and reliability, as well as accessibility and security.
You’re missing an important point here: that in the end, everything in the computer is represented in binary, usually bytes. Everything, and the computer does now know which byte is a character in a text, the red channel of a particular pixel, or part of an instruction to the virus or to the operating system. The notion that everything in the computer is a representation is a powerful idea. It’s useful because it allows us to understand how we could possibly get a virus from a picture or Word file.
Yes, there are cost, speed, and reliability implications, but those are much higher levels of abstraction and not useful to everyone. Not everyone makes cost estimates of data representations. Everyone gets viruses.
Data often needs to be transformed from its raw state to be easily understood. Data can be transformed through mathematical expressions, aggregation (sum/average of rows/columns), rearrangement, and visualization. The type of transformation can influence the people who view the data.
These are narrow notions of transformation. How about just talking about noise and error? People make mistakes with data. That’s a powerful idea that crosses disciplines.
Data about prior events can be used to predict future events based upon computational models of varying complexity. The accuracy of the prediction depends on the choice of factors and the amount and diversity of data used to produce the model.
This is counter to how science thinks about the world today. This is the billiard ball, Newtonian model of the universe. Let’s not tell students this.
Programs and Algorithms
Types allow programmers to think of problems in terms of data and variables. Programmers use abstraction to define new data types, combine data with operations, and hide implementation details. Collections of data or data structures provide simple interfaces coupled with specific efficiency properties. (introduced at earlier grade bands: data representation, primitive data types, and operations associated with types)
I’m worried about this assumption that predecessor concepts will be introduced in elementary school and then expanded upon in high school. We have very little CS in schools today. States will choose where to emphasize: Build up high school CS first? Elementary school CS first? For at least a decade yet, few students will have K-12 CS Ed.
What happens to high school students who don’t get the predecessor concepts? Just give up on them and wait for the elementary school students?
Control constructs determine when sequences of instructions are executed. Recursion is a control technique in which a procedure calls itself. This is appropriate when problems can be expressed in terms of smaller versions of themselves. Selecting from different control structures that can be used to solve the same problem introduces a tradeoff between runtime efficiency and code readability. (introduced at earlier grade bands: sequence, iteration, branching, events, nesting, and competing control structures)
Not everyone needs to know recursion.
I wish that we taught students a simple notional machine and described everything in terms of that. Here’s what I teach my CS students: A computer can only do six things:
- They can store data with a name(s).
- They can name parts of programs (instructions), and follow those instruction when commanded.
- They can take data apart.
- They can transform data into other forms.
- They can follow a set of instructions repeatedly.
- They can test data (is this true or not?), then take actions depending on what the result is.
Everything that I teach in Python, I relate to one or more of those six points. I make sure that I relate everything to a small, easily learnable notional machine.
I do not see why K-8 students should learn about nesting and competing data structures. This is an example of teaching things that are in CS, but are not useful in math and science.
There are several steps in the development process, including problem clarification, design, implementation, and testing. Teams creating computational artifacts must make important design decisions and iteratively refine them. Different programming environments have distinct resources and features. Selecting from different programming languages and libraries introduces tradeoffs between functionality, efficiency, design and implementation time, security, and personal experience or preference.
No, not everyone needs to know this level of a software development process.
Impacts of Computing
In early grades, students differentiate between responsible and irresponsible computing behaviors. Students learn that responsible behaviors can help individuals while irresponsible behaviors can hurt individuals. They examine legal and ethical considerations for obtaining and sharing information and apply those behaviors to protect original ideas. As students progress academically, they engage in legal and ethical behaviors to guard against intrusive applications and promote a safe and secure computing experience.
Laws impact many areas of computing in an effort to protect privacy, data, property, information, and identity. The legal oversight of computing involves tradeoffs; such laws can expedite or delay advancements and infringe upon or protect human rights. Ethical concerns also shape computing practices and professions. International variations in legal and ethical considerations should be examined.
This is a great point to larger systems issues of politics and history. Describe democracy as a similar set of tradeoffs and design considerations.
The seven practices of computer science are the behaviors and ways of thinking that computationally literate citizens use to fully participate in the modern data-rich and interconnected digital world. Students in grades K-12 should engage in all seven practices over each grade band with increasing sophistication over time.
1. Recognizing and Representing Computational Problems
2. Developing Abstractions
3. Creating Computational Artifacts
4. Testing and Iteratively Refining
5. Fostering an Inclusive Computing Culture
6. Communicating About Computing
7. Collaborating With Computing
I’d rather see 2 as Using Abstractions. Not everyone is going to Develop Abstractions. Developing Abstractions isn’t necessary for everyone. It’s a difficult and challenging thing for students to learn, but you can be effective at using computing without it.
Communicating About Computing
Computationally literate citizens use a variety of mechanisms to share information and insights about computer science. This includes communicating about their design processes, the elements and functionality of computational artifacts, and both the technical and societal implications of computational solutions. For example, they write clear comments on their code, document their work through technical writing, and create demonstrations that include visualizing multiple representations and account for the diversity of audiences members. They attend to precision by using language in contextually appropriate ways (for example, the term function has meanings in both mathematics and computer programming).
These are really programmer-centric ways of talking about computing. Can we open this up, or not list any at all? I like the idea of videos or even dance about computing, not just comments in code.
It’s a starting point. I hope that it gets revised a lot before going out to states for standards.
Mostly, I want the framework writers to emphasize what everyone needs to know and teaching computing as a generative set of ideas. We can use computing as a powerful lever for learning in a wide variety of areas. Don’t teach everyone things about computing that are not generative, that only teach about CS itself.
Marvin Minsky died last month. I never met Marvin. I met his daughter, and worked with people who knew him well. He must have been a remarkable person.
The NYTimes piece has several quotes from Alan Kay about Marvin. Below is my favorite. I’ve heard it before, and I think about it often when designing classes and lessons.
I want students to understand what I do in class, but not memorize it. I want them to understand it in more than one way. It’s why I emphasize revision and multiple iterations so often in a class. I want them to understand well enough to transfer the knowledge, at least in near contexts.
For Dr. Kay, Professor Minsky’s legacy was his insatiable curiosity. “He used to say, ‘You don’t really understand something if you only understand it one way,’” Dr. Kay said. “He never thought he had anything completely done.”
Steve Cooper organized a series of workshops (see blog posts here and here) exploring how we might grow computing education research within computing departments. How do we make sure that computing education research (CER) faculty succeed (e.g., get tenured and promoted)? How can we have CER PhD students within computing departments? Interesting to note that in Craig Wills’ recent analysis of CS department job ads, CS Education Research is in the “other” category. (Thanks to Yasmin Kafai for pointing this out.) Too few departments were interested in CS Ed to appear on his graphs.
The report with recommendations from those workshops is now out and available here. Quoting from the report:
This growth is an unparalleled opportunity to expand the reach of computing education. However, this growth is also a unique research challenge, as we know very little about how best to teach our current students, let alone the students soon to arrive. The burgeoning field of Computing Education Research (CER) is positioned to address this challenge by answering research questions such as:
- How should we teach computer science, from programming to advanced principles, to a broader and more diverse audience?
- How can we ensure that we retain this more diverse audience through inclusive pedagogy and generally more effective teaching?
- How can teaching approaches and their assessment (regarding student learning) scale effectively?
- What training should K-12 teachers receive? What methods have been shown to be effective?
- How can computer science teaching adapt to how different people learn and build on age related learning progressions?
- How should computing be taught and integrated into other disciplines?
We argue that computer science departments should lead the way in establishing CER as a foundational research area of computer science, discovering the best ways to teach CS, and inventing the best technologies with which to teach it. This is not only in the best long-term interest of our field, but also the long-term interests of society. This white paper provides a snapshot of the current state of CER and makes actionable recommendations for academic leaders to grow CER as a successful research area in their departments.
A recent article in The Chronicle talked about just how white higher education faculty are — see article here. Most of the student protests about equity and diversity on college campuses this last year demanded more minority faculty.
In this graph, I found a different and fascinating story in just the first two bars in each set:
Professors are overwhelmingly male. Associate professors are only slightly more male. Assistant professors are slightly more female. Instructors are much more female.
It’s not surprising, but it’s interesting to see it. The women in academia have the lion’s share of the lower status jobs, and the men have the lion’s share of the higher status jobs. When you take into account the landed-gentry/tenant-farmer relationship between the tenure track faculty and the teaching track faculty (see previous blog post), the relationship between gender and academic power becomes much more stark.
There are many, many teaching jobs available in computer science right now. Scarcely a day goes by that there isn’t another ad posted in the SIGCSE Members list — sometimes for many positions at the same department. A great many of these are at Universities, with a clear statement that this is a Teaching track position, not a Tenure track position.
Many of these ads, when posted to SIGCSE Members, contain a paragraph like this (edited and hopefully anonymized):
(Highly-ranked University)’s full-time (without tenure) teaching faculty positions are called (pick one of:) Lecturers with Security of Employment, Professors of the Practice, or Teaching Professors, or Lecturers, or Instructors. These positions typically involve a teaching load of two courses each semester, advising responsibilities, and service (committee work) as well. (Highly-ranked University)’s computer science teaching faculty are NOT treated as second class citizens. We vote at faculty meetings, represent the department on university committees, and are generally well respected inside and outside the department. We currently are seeking more (see ad below).
From time to time, I write the person (almost always a teaching track faculty member) who posted the ad, to follow-up on the “NOT second class citizens” part.
- Do teaching faculty get to serve on the hiring committee for teaching faculty? Usually yes.
- Do teaching faculty get to serve on the hiring committee for tenure-track faculty? Usually not. This question often results in a snort of laughter. Why should teaching professionals be involved in hiring tenure-track faculty? That seemed obvious to me — teaching faculty are hired to be experts in teaching, and tenure-track faculty do teach.
- Do teaching faculty serve on tenure-track promotion and tenure committees? Almost never, despite the fact that tenure track faculty are expected to teach and are supposed to be evaluated (at least in part) on that teaching. Shouldn’t professionals with expertise in teaching have a voice in evaluating teaching of tenure-track faculty?
- Do teaching faculty have a voice/position at the Dean/Chair’s Cabinet/Executive Committee? I know of only one in the US.
Maybe I have been watching too much “Downton Abbey.” The treatment of teaching track faculty by tenure track faculty sounds like the relationship between the landed gentry and the tenant farmers. The University teaches as one of its primary roles, just as the estate survived through farming (and the sales and rent that were generated). The tenure track faculty (landed gentry) leave most of that to the teaching track faculty (tenant farmers). It’s a delegated responsibility, like custodial and lawn management services. The teaching track faculty don’t own the department or programs (land). The tenure track faculty make the decisions about hiring and promoting the teaching track faculty. The teaching track faculty don’t make any of the decisions about tenure track faculty. Of course, the greatest match with the analogy is that tenured faculty can’t be fired — like the landed gentry, they own their positions. Teaching track faculty are rarely tenured. One of the teaching faculty with whom I work has only a six month contract and can be fired with a month’s notice.
It is in our best interests for teaching track to be a profession. Teaching track faculty should be experts in teaching. Members should be expected to join professional organizations like SIGCSE (see previous post about the lack of membership in SIGCSE), to attend and present at organizational meetings, and to improve their practice. They should have a promotion path and evaluation as rigorous as the tenure-track promotion and tenure process. I’m pleased to see these ads, because they suggest national searches for good teaching track faculty — as opposed to hiring (for example) graduate students and post-docs who don’t want to leave their home institution.
A first step towards professionalization of teaching track faculty is to treat them with the same respect as tenure-track faculty. Tenure track faculty are treated as experts in research. Teaching track faculty should be treated as experts in teaching. If both teaching and research are important, then treat the teaching track faculty like the research faculty. There should be a comparable sense of responsibility, power, and ownership.
I’ve mentioned the K12 CS Framework Process a couple of times before (see this blog post). It’s now available for public comment.
Individuals and institutions are invited to be reviewers of the K-12 CS framework. Institutions, such as state/district departments of education and organizations (industry, companies, non-profits), are responsible for selecting an individual or a group to represent the institution. Reviewers can choose to participate in one or both of the two review periods:
- Feb 3 to Feb 17: Review of the 9-12 grade band concepts and practices
- March 14 to April 1: Review of the entire K-12 concepts and practices
There will be a public webinar (save this link) to launch the first review period on Feb 3 at 8pm ET / 5pm PT. Learn about the development of the framework and how to provide an effective review.
Find different instructions for individuals and facilitators of group reviews, including an informational session kit for review group facilitators at http://k12cs.org/review. Visit this page after 9 am on Feb 3rd and you’ll be able to access the framework draft and an online feedback form for the first public review
Lian Halbert, K-12 CS Framework development staff
P.S. Are you attending SIGCSE 2016 in Memphis this March 2-5? We will hold a Birds of a Feather session on Thursday March 3 for all SIGCSE attendees – feel free to invite folks so they can learn about the K-12 CS framework.
Summarizing the Research on Designing Programming Languages to be Easier to Learn: NSF CS Ed Community Meeting
I’m at the NSF STEM+Computing and Broadening Participation in Computing Community Meeting. At our ECEP meeting on Saturday, we heard from White House Champion of Change Jane Margolis. She did a great job of getting our states to think about how to change their state plans to emphasize diversity and equity — more on that in a future blog post.
I moderated a panel yesterday on how to integrate computing education into schools of education. Here’s the description of the session — again, more later on this.
Integrating Computing Education into Preservice Teacher Development Programs
(Mark Guzdial (moderator), Leigh Ann DeLyser, Joanna Goode, Yasmin Kafai, Aman Yadav)For computing education to become ubiquitous and sustainable in US K-12 schools, we need schools of Education to teach computing.
- What should we be teaching to preservice teachers?
- Where should we teach CS methods in preservice teacherdevelopment?
- How do we help schools of Ed to hire and sustain faculty who focus on computing education?Panelists will talk about how CS Ed is being integrated into their preservice teacher development programs, and about alternative models for addressing these questions.
Yesterday, our other computing education research Champion of Change, Andreas Stefik presented a summary of the empirical evidence on how to design programming languages to make them easier to learn. Follow the link below to get to the two-page PDF pamphlet he produced for his presentation — it’s dense with information and fascinating.
This pamphlet is designed to provide an overview of recent evidence on human factors evidence in programming language design. In some cases, our intent is to dispel myths. In others, it is to provide the result of research lines.