Academics find that girls are better at boys than writing video games

Girls write more complex programs and learn more about coding than boys when it comes to making computer games, a study has found.
A group of 12 – 13-year old pupils spent eight weeks developing their own 3D role playing games as part of the University of Sussex study.
Dr Kate Howland and Dr Judith Good developed Flip, a programming language which uses a simple interface to help the pupils string together scripts, basic programs which trigger a change within the game, such as a message popping up once a treasure chest is opened.
The girls used seven triggers within the games, almost twice as many as the boys of the group, and were much more successful at creating complex scripts with two or more parts and conditional clauses.
Boys had a tendency to build their triggers around when a character said something, the most first and most simple trigger the class learned.
The games were created using software made available with fantasy game Neverwinter Nights 2, while Flip also translated the programs into English to help the students understand the scripts they’d created.
“Given that girls’ attainment in literacy is higher than boys across all stages of the primary and secondary school curriculum, it may be that explicitly tying programming to an activity that they tend to do well in leads to a commensurate gain in their programming skills,” said Dr Good.
“In other words, if girls’ stories are typically more complex and well developed, then when creating stories in games, their stories will also require more sophisticated programs in order for their games to work.”

The study is at:

but apparently one must pay to access these priceless pearls of wisdom.

Teaching basic computational concepts and skills to school children is currently a curricular focus in many countries. Running parallel to this trend are advances in programming environments and teaching methods which aim to make computer science more accessible, and more motivating. In this paper, we describe the design and evaluation of Flip, a programming language that aims to help 11-15 year olds develop computational skills through creating their own 3D role-playing games. Flip has two main components: 1) a visual language (based on an interlocking blocks design common to many current visual languages), and 2) a dynamically updating natural language version of the script under creation. This programming-language/natural-language pairing is a unique feature of Flip, designed to allow learners to draw upon their familiarity with natural language to “decode the code”. Flip aims to support young people in developing an understanding of computational concepts as well as the skills to use and communicate these concepts effectively. This paper investigates the extent to which Flip can be used by young people to create working scripts, and examines improvements in their expression of computational rules and concepts after using the tool. We provide an overview of the design and implementation of Flip before describing an evaluation study carried out with 12-13 year olds in a naturalistic setting. Over the course of 8 weeks, the majority of students were able to use Flip to write small programs to bring about interactive behaviours in the games they created. Furthermore, there was a significant improvement in their computational communication after using Flip (as measured by a pre/post-test). An additional finding was that girls wrote more, and more complex, scripts than did boys, and there was a trend for girls to show greater learning gains relative to the boys.

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2 Responses to Academics find that girls are better at boys than writing video games

  1. l17l17 says:

    Aren’t girls further along developmentally at age 12-13?

    • If you design a contrived experiment, with a customized programming language and bizarre metrics of success, you can prove anything.

      Girls do have a different verbal development curve, but that’s not what the experiment was measuring. The experiment design was completely rigged to squeeze a female-friendly result out of any possible data.

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