Making Programming Easier for Beginners

Introduction

In the days when home computers had BASIC it was common for bright children to write little programs - egg-timers, etc. They gained experience of programming as a concept, but just as importantly they got practise at making mistakes and fixing them.

In the Windows/Mac era this option was no longer available. Some of the older lecturers here say they have noticed a consequent reduction in programming skills amongst our new students.

It's been suggested that the Raspberry Pi might be used as a way to encourage entry-level home programming in the future. And perhaps schools might deliver more programmers to universities. But for now we have to cope with a significant minority of students arriving without programming skills. This leads to student anxiety when they're at their most vulnerable, poor end-of-year results, and perhaps an under-use of computing in their career.

In this document I consider the factors involved with these difficulties. The problem goes beyond being purely cognitive. Some students seem to acquire something like a phobia about the subject (not helped by the public perception of Computing being a male, nerdy, obsessive topic).

Attempted solutions aim to

• Develop programming skills (or aid the transfer of other skills)
• Reduce the anxiety levels associated with the topic thus aiding the learning process.
• Identify the students who'd most gain from extra help once term starts.

What is hard about computing

Computing languages are unlike anything else that students are likely to have done. They're not even like maths. Compilers are unforgiving - always criticising and never praising. Students' programming skills span a wider range than that of any other examined skill, so non-programmers will feel stupid right from the start. Comments similar to the following are common - "It's too hard"; "It's too easy"; "Other people find it easy. Why do I find it so hard?"; "If it mattered we'd have been taught it already"; "arbitrary rules, it's all about jumping through hoops".

It may be that we're trying to teach topics that are known to be difficult but that only a few students will ever need. We teach a compiled language (C++) though few student will use one. Speed of execution is rarely a critical factor in student programs, but a significant factor in our choice of language.

People know which topics students find difficult. It's less clear how to exploit this knowledge. In "When do students learn? Investigating factors in introductory courses" ("JCSC", 2012) it said "we found that instructional time spent on a topic often has a far weaker connection to student learning levels than does instructor emphasis. ... Just spending more classroom teaching time on a concept will not improve student learning as much as an instructor placing greater emphasis on that concept ... For CS1, there were few topics for which there were statistically significant correlations between instructional time and student learning. ... Interestingly, three topics, control structures, subroutines/functions, and types, had weakly negative correlations."

Easing the Learning Curves

One can broadly categorize the problem areas as follows - Algorithms (What to do), Implementation (How to do it) and Psychology (Finding a congenial context within which to learn). Each category has a learning curve that can be made more shallow. Each has been targeted by educationalists

Algorithms

The idea of planning for eventualities that might occur during the planners' absence is not a scenario that students have much experience in. Also programming involves much more failure (error messages) than success, which distresses beginners. Solutions to these difficulties include getting students to

• begin solely with algorithms - flowcharts, paper exercises involving recipes, etc
• begin with easier algorithms - "Add 2 numbers"; "Write a times table". These tasks are boring but at least they let students focus on the implementation.

Implementation

• Re-order the topics (e.g. delay the introduction of functions, Object-Orientation etc.)
• Expand the documentation at the start of the course - offer cribsheets, etc.
• Change the language
• Write tools targeted to help the student with specific, known problem areas (we've written animations and teaching aids - e.g. 'for' loop help
• Use a new language just for the start of the course - Interpreted languages help accelerate the edit-run cycle, reducing the psychological consequences of errors.
  Some sites use Scratch to narrow the gap between algorithms and implementation - the programs are flowcharts. One paper reported that "not only did Scratch excite students at a critical time (i.e., their first foray into computer science), it also familiarized the inexperienced among the with fundamentals of programming without the distraction of syntax".
  Jonathan D. Blake wrote that "Research has shown that assignments that provide early feedback and early success (and that are compelling and visual) are important in improving not just retention, but also gender equity" ((JCSC 26, 6, p.126). Languages like Turtle Graphics make feedback more visual (especially if they use robots - students can then see the physical consequences of their work).

Psychology

• Computer-based Teaching - a supportive development environment can be developed (one that attempts to diagnose errors, for example). But this is likely to be language-specific and expensive to produce
• More Interesting algorithms - If the task is interesting enough, students will be more stubborn when dealing with implementation issues. Students' supposed interest in computer games has been used to incite interest. Lisa Torrey "concluded that the most important interest factors were graphics, usefulness and entertainment value".
• Working in Teams - This might help some to learning without exposing their ignorance to staff. Some students like to be taught via the language of their peers. However, the results are patchy and over-praised by students. Also, girls get a lot more help than boys.
• Offer a choice of slow and fast courses, or easy and hard questions, or extra help. Lisa Torrey found that given a choice, "students disproportionately chose to write less challenging programs than their interest patterns had suggested". She felt that "many students would choose easy programs that happen to contain other interesting factors" ("Student interest and choice in programming assignments", JCSC 26, 6)
  Extra help can be made available
  • Making help available by phone or e-mail, or having a drop-in surgery
  • Offering 1-to-1 tuition
  • Online self-help (or supervised) groups (could offer marks for the quality of involvement; could use Skype).

See Also

• The camel has two humps (working title) Saeed Dehnadi and Richard Bornat, School of Computing, Middlesex University, UK, 2006