Introductory programming classes teach students to program using worked examples, code tracing, and code writing exercises. Parsons Problems are an educational innovation in which students unscramble provided lines of code, as a step towards bridging the gap between reading and writing code. Though Parsons Problems have been found effective, there is some evidence that students can use syntactic heuristics to help them solve these problems without fully understanding the solution. To address this limitation, we introduce Faded Parsons Problems, a variation of Parsons Problems where parts of the provided code are incomplete. We explore a specific instantiation of this idea, Blank-Variable Parsons Problems, in which all variable names are blanked out. Unlike another Parsons Problem variation-adding distractor code lines-Blank-Variable Parsons can be automatically created from a solution without additional effort from an instructor. A 75 minute pilot study with CS1 students indicates that solving standard Parsons Problems does not lead to short-term near-transfer in code writing, suggesting a need for problems with less scaffolding. Additionally, students self-report Blank-Variable Parsons as fitting in difficulty between Parsons Problems and code writing, suggesting Blank-Variable Parsons may be one opportunity to fill this gap. CCS CONCEPTS • Applied computing → Interactive learning environments; • Social and professional topics → CS1.
Context. Pair programming has been found to increase student interest in Computer Science, particularly so for women, and would therefore appear to be a way to help remedy the under-representation of women in the field. However, one reason for this underrepresentation is the unwelcoming climate created by gender stereotypes applied to engineers in general, and to software engineers in particular, assuming that men perform better than their women peers. If this same bias is present in pair programming, it could work against the goal of improving gender balance in computing.Objective. In a remote setting in which students cannot directly observe the gender of their peers, we aim to explore whether Software Engineering students behave differently when the perceived gender of their remote pair programming partners changes, searching for differences in (i) the perceived productivity compared to solo programming; (ii) the partner's perceived technical competency compared to their own; (iii) the partner's perceived skill level; (iv) the interaction behavior, such as the frequency of source code additions, deletions, validations, etc.; and (v) the type and relative frequencies of dialog messages used for collaborative behavior in a chat window. Although there are some studies on pair programming performance and gender pair combination, to the best of our knowledge there are no studies on the impact of gender stereotypes and bias within the pairs themselves. Method. We have developed an online platform (twincode) that randomly classifies students into gender-balanced groups, arranges them in pairs for remote pair programming (sharing an editor window and a chat window), and can selectively deceive one or both partners regarding the gender of the other via the use of a clearly gendered avatar. Several
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