The different types of contributions to knowledge (in CER): All needed, but not all recognised

The overall aim of this paper is to stimulate discussion about the activities within CER, and to develop a more thoughtful and explicit perspective on the different types of research activity within CER, and their relationships with each other. While theories may be the most valuable outputs of research to those wishing to apply them, for researchers themselves there are other kinds of contribution important to progress in the field. This is what relates it to the immediate subject of this special journal issue on theory in CER. We adopt as our criterion for value “contribution to knowledge”. This paper’s main contributions are: • A set of 12 categories of contribution which together indicate the extent of this terrain of contributions to research. • Leading into that is a collection of ideas and misconceptions which are drawn on in defining and motivating “ground rules”, which are hints and guidance on the need for various often neglected categories. These are also helpful in justifying some additional categories which make the set as a whole more useful in combination. These are followed by some suggested uses for the categories, and a discussion assessing how the success of the paper might be judged. These are followed by some suggested uses for the categories, and a discussion assessing how the success of the paper might be judged

Towards a Model of Conceptual Transfer for Students Learning New Programming Languages

As students learn computer science (CS), they will need to transfer skills and understanding from one programming language (PL) to another. Prior research has explored the transition between languages for (mainly experienced) programmers, identifying a number of challenges. I could not find research attempting to devise a model that describes how students' learning of programming concepts is affected during the shift between languages. I propose the first draft of a model to describe PL transfer for relative novices based on the literature and my observations of these students transitioning from procedural Python to Java. In the model, concepts in the new language may be Carryover, Changed or Novel; during the transition, learners automatically effect a transfer of semantics between languages based on matches made between the syntax of the two languages