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Keeping the Machinery in Computing Education: Back to the Future in the Definition of CS

ComputingEd - 7 hours 3 min ago

I’ve been excited to see this paper finally come out in CACM. Richard Connor, Quintin Cutts, and Judy Robertson are leaders in the Scotland CAS effort. Their new curriculum re-emphasizes the “computer” in computer science and computational thinking. I have bold-faced my favorite sentence in the quote below. I like how this emphasis reflects the original definition of computer science: “Computer science is the study of computers and all the phenomena surrounding them.”

We do not think there can be “computer science” without a computer. Some efforts at deep thinking about computing education seem to sidestep the fact that there is technology at the core of this subject, and an important technology at that. Computer science practitioners are concerned with making and using these powerful, general-purpose engines. To achieve this, computational thinking is essential, however, so is a deep understanding of machines and languages, and how these are used to create artifacts. In our opinion, efforts to make computer science entirely about “computational thinking” in the absence of “computers” are mistaken.

As academics, we were invited to help develop a new curriculum for computer science in Scottish schools covering ages 3–15. We proposed a single coherent discipline of computer science running from this early start through to tertiary education and beyond, similar to disciplines such as mathematics. Pupils take time to develop deep principles in those disciplines, and with appropriate support the majority of pupils make good progress. From our background in CS education research, we saw an opportunity for all children to learn valuable foundations in computing as well, no matter how far they progressed ultimately.

Source: Keeping the Machinery in Computing Education | November 2017 | Communications of the ACM


Tagged: CAS, computing education, curriculum, K12

NSF-funded scientists to present on long-term ecological research findings at AGU fall meeting

News From NSF - 8 hours 3 min ago

Find related stories on NSF's Long-Term Ecological Research Program at this link.

Hurricanes Harvey, Irma and Maria this fall. Wildfires that raged across California and British Columbia this summer. Unseasonable cold snaps in South Florida in past winters. How do such events shape and re-shape ecosystems?

And how do events from past decades affect the ways in which ...
More at https://www.nsf.gov/news/news_summ.jsp?cntn_id=243731&WT.mc_id=USNSF_51&WT.mc_ev=click


This is an NSF News item.

Predicting Seasonal Weather

News From NSF - Fri, 11/17/2017 - 15:46

Large-scale weather patterns play a large role in controlling seasonal weather. Knowing the conditions of these atmospheric oscillations in advance would greatly improve long-range weather predictions.
More at https://www.nsf.gov/news/special_reports/autumnwinter/index.jsp?WT.mc_id=USNSF_51


This is an NSF News item.

Parsons Problems have same Learning Gains as Writing or Fixing code, in less time: Koli Calling 2017 Preview

ComputingEd - Fri, 11/17/2017 - 07:00

On Saturday, Barbara Ericson will be presenting at Koli Calling her paper (with Lauren Margulieux and Jeff Rick), “Solving Parsons Problems Versus Fixing and Writing Code.”

The basic design of her experiment is pretty simple.  Everybody gets a pretest where they answer multiple-choiced questions, write some code, fix some code, and solve some Parsons problems.  (I’ve written about Parsons Problems here before.)

Then there are three instructional treatments with three different kinds of problem-solving practice:

  • One group gets Parsons Problems with distractors in them — blocks that should not be dragged into the solution.
  • One group gets the same code to fix — same code as in the Parsons Problems but all the distractors are there.  They have to fix the broken code in the distractor to get to the same code as the correct block in the Parsons.
  • One group gets to write the code to solve the same problem.

Then they take an isomorphic (same basic problems with context and constants changed) post-test, go away, and come back one week later for a retention test (which is isomorphic to both the pretest and the first posttest: multiple choice questions, Parsons, fix code, write code).  So we have students who study with Parsons Problems getting tested by writing and fixing code.

Here’s the bottom line from their abstract: “We found that solving two-dimensional Parsons problems with distractors took significantly less time than fixing code with errors or than writing the equivalent code. Additionally, there was no statistically significant difference in the learning performance, or in student retention of the knowledge one week later.”

That’s it. It’s simple but profound.  Below is the timing table from the paper. The Parsons Problems took effort, but always less time — sometimes they took only half the time of fixing or writing code, and other times it was only a few percentage less. But it was always less.

One takeaway idea is: If Parsons leads to the same learning in less time, why wouldn’t every teacher use more Parsons problems?  A second one that we’ve been thinking alot about is: Can we provide more Parsons problems so that in the same amount of time that students were writing code, they actually learn more? Efficiency matters, as Elizabeth Patitsas’s work suggests — more efficient learning may mean less belief in Geek Gene by CS teachers.


Tagged: computing education research, efficiency, Parsons Problems

Arecibo: Statement on NSF Record of Decision

News From NSF - Thu, 11/16/2017 - 15:48

On Nov. 15, 2017, the National Science Foundation (NSF) signed its Record of Decision for the Arecibo Observatory in Puerto Rico. This important step concludes the agency's decision-making process with respect to the general path forward for facility operations in a budget-constrained environment and provides the basis for a future decision regarding a new collaborator.

NSF issued its Record of ...
More at https://www.nsf.gov/news/news_summ.jsp?cntn_id=243729&WT.mc_id=USNSF_51&WT.mc_ev=click


This is an NSF News item.

NSF-supported scientists present research results on Earth's critical zone at 2017 AGU fall meeting

News From NSF - Thu, 11/16/2017 - 06:00

Find related stories on NSF's Critical Zone Observatories at this link.

The thin veneer of Earth's surface that stretches from the top of the forest canopy to the base of bedrock is known as the "critical zone." It's where fresh water flows, rock turns to soil and life flourishes.

To provide a deeper understanding of the critical zone, the National Science Foundation (NSF) supports nine ...
More at https://www.nsf.gov/news/news_summ.jsp?cntn_id=243660&WT.mc_id=USNSF_51&WT.mc_ev=click


This is an NSF News item.

NSF makes new awards to advance Science of Learning

News From NSF - Wed, 11/15/2017 - 17:02

The National Science Foundation (NSF) has awarded $8.2 million through its Science of Learning program to fund 24 new projects that will advance theoretical insights and fundamental knowledge of learning principles, processes, environments and constraints.

"NSF has shown long-standing leadership in the Science of Learning through past investments in the Science of Learning Centers and Science of Learning Collaborative Networks," said Fay Lomax Cook, assistant director for NSF's ...
More at https://www.nsf.gov/news/news_summ.jsp?cntn_id=243658&WT.mc_id=USNSF_51&WT.mc_ev=click


This is an NSF News item.

Shape of Lake Ontario generates white-out blizzards, study shows

News From NSF - Tue, 11/14/2017 - 13:00

A 6-foot-wide snow blower mounted on a tractor makes a lot of sense when you live on the Tug Hill Plateau. Tug Hill, in upstate New York, is one of the snowiest places in the Eastern U.S. and experiences some of the most intense snowstorms in the world. This largely rural region, just east of Lake Ontario, gets an average of 20 feet of snow a year.

Hence the tractor-mounted snow blower.

The region's massive snow totals are due to lake-effect snowstorms and, it turns out, to ...
More at https://www.nsf.gov/news/news_summ.jsp?cntn_id=243636&WT.mc_id=USNSF_51&WT.mc_ev=click


This is an NSF News item.

Royal Society Report on CS in English Schools: The Challenge of Reaching Everyone

ComputingEd - Mon, 11/13/2017 - 07:00

The new report from the UK’s Royal Society is fascinating and depressing. More than half of school don’t offer CS. Because the largest schools do offer CS, 70% of English students are at a school that offer CS — but they’re still not getting into CS classes. Only 1 in 5 CS students are female. The Royal Society recommends a tenfold increase in funding.

We have heard about some of these demographics before (see the Roehampton report and BBC coverage). Here in the US, we’re also talking about dramatically increasing funding (see blog post here about the $1.3B funding from White House and Tech industry).  Are the US and England on the same paths in CS? Is there any reason to expect things to be different, or better, in the US?

report by the UK’s national academy of sciences finds that more than half of English schools do not offer GCSE Computer Science, leaving too many young people without the chance to learn critically important programming and algorithm skills at a crucial stage of their education.

Unless the government urgently invests £60m in computing education over the next five years – a tenfold increase from current levels that puts it on par with support for maths and physics – an entire generation may never unlock the full potential of new technologies such as robotics, artificial intelligence and machine learning.

Key findings from the report include:

  • 54% of English schools do not offer Computer Science GCSE

  • 30% of English GCSE pupils attend a school that does not offer Computer Science GCSE – the equivalent of 175,000 pupils each year

  • Bournemouth leads England with the highest uptake of Computer Science GCSE (23% of all pupils), with Kensington & Chelsea (5%), Blackburn (5%) and City of London coming last (4%)

  • England meets only 68% of its recruitment target for entries into computing teacher training courses, lower than Physics and Classics

  • Only 1 in 5 Computer Science GCSE pupils are female

Source: Invest tenfold in computing in schools to prepare students for digital world, says Royal Society


Tagged: CAS, computing education, public policy

Why do so few schools try LiveCode? We let industry dictate our tools

ComputingEd - Fri, 11/10/2017 - 07:00

I’m an old HyperCard programmer, so I like LiveCode.  LiveCode does very well on the five principles I suggest for picking an educational programming language. The language is highly readable, and was actually designed drawing on research on how novices best understand programming. It’s easy to put together something that looks authentic and that runs on virtually any platform — much easier than Python, Java, Scratch, Blockly, or any of the other top five most popular teaching languages. Authenticity is often engaging for students.

The LiveCode folks have just put together a web page (linked below) describing some of the reasons why teachers should consider LiveCode.  But in general, we don’t.  Why not?  I have two guesses:

  1. There is no community of practice. There isn’t a visible community of teachers using LiveCode. There isn’t an obvious industry call for more LiveCode programmers.
  2. We in computing education are mostly driven by surface-level interpretations of industry needs.  It isn’t obvious that it must be so, or even that it should be so.  But the same forces that killed Pascal and promoted Python, Java, and C++ as our intro languages prevent LiveCode from getting adopted.

I think LiveCode, Smalltalk, and Lisp are all excellent pedagogical programming languages, but our teaching decisions in secondary and post-secondary CS education are rarely based on what will engage students, be easier to learn, or lead to transferable knowledge.  Instead, we tend to make decisions on what obviously looks like what current professionals do.  It binds us to normative practices. We’re stuck in apprenticeship as our teaching perspective, and can’t consider social reform or developmental perspectives.

Better Exam Results, Better Real Life Outcomes, More Fun!

Over a third of Scottish schools are now teaching using LiveCode. They are doing this because they have proven results showing that using LiveCode results in more students remaining engaged, reaching good grades, and continuing in the direction of a coding career.

Source: Education | LiveCode


Tagged: computing education, HyperCard, Java, Lisp, Livecode, pascal, Smalltalk

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