Computer Science Education Welcoming submissions for an upcoming special issue

Advancing theory about the novice programmer

Computer Science Education

Computer science education is rapidly expanding, globally. Yet we currently have few theories and little scientific evidence to explain what factors affect the success rate of students. For many students, learning to program is especially difficult, regardless of previous academic success, and we struggle to explain why. What about learning to program is the barrier to success? Is learning programming different than learning content and skills in other STEM fields? What interventions can we use to help students succeed?

The purpose of this special edition is to collect evidence that will contribute to a theoretical understanding of the novice programmer. We seek original work that explicitly proposes, applies, and/or contributes to theories about learning to program based on rigorous empirical findings.

Submissions to this special issue should:

  • articulate the theoretical underpinnings of the work by applying theories from CS Education Research and allied fields such as Cognitive Science, Learning Sciences, or Educational Psychology,
  • pose theory-driven hypotheses,
  • collect and present evidence that supports or refutes the hypotheses, and
  • connect conclusions back to existing theories or pose new theories that advance computing education research.

Experimental and non-experimental research designs will be equally considered. All types of data collection and analysis methods (i.e., qualitative and/or quantitative) will be considered, but those that use multiple methods to thoroughly explore how students learn are strongly encouraged.

Topics of interest to this special issue include, but are not limited to:

  • The role of prior knowledge on learning programming
  • The role of cognitive load in learning programming
  • The role of metacognitive skills while learning programming
  • Defining and teaching declarative vs. procedural knowledge within programming
  • Scaffolding and supporting students as they develop programming skills
  • The role of motivation and affective dimensions in learning programming
  • Learning trajectories in programming
  • Programming Languages and tools that aid the cognitive processes of learning to program
  • Critical comparison of learning programming to learning in other disciplines, especially other STEM disciplines

Ready to submit?

All manuscripts should be submitted online at:


15 February 2018:    Open Call for Manuscripts
6 August 2018:        Deadline for Manuscripts
1 October 2018:       Reviews Back to Authors
19 November 2018:   Manuscript Deadline

Editorial information