This study analyzed student responses to an examination, after the students had completed one semester of instruction in programming. The performance of students on code tracing tasks correlated with their performance on code writing tasks. A correlation was also found between performance on "explain in plain English" tasks and code writing. A stepwise regression, with performance on code writing as the dependent variable, was used to construct a path diagram. The diagram suggests the possibility of a hierarchy of programming related tasks. Knowledge of programming constructs forms the bottom of the hierarchy, with "explain in English", Parson's puzzles, and the tracing of iterative code forming one or more intermediate levels in the hierarchy.

The increasing availability of genetic sequence data associated with explicit geographic and ecological information is offering new opportunities to study the processes that shape biodiversity. The generation and testing of hypotheses using these data sets requires effective tools for mathematical and visual analysis that can integrate digital maps, ecological data, and large genetic, genomic, or metagenomic data sets. GenGIS is a free and open-source software package that supports the integration of digital map data with genetic sequences and environmental information from multiple sample sites. Essential bioinformatic and statistical tools are integrated into the software, allowing the user a wide range of analysis options for their sequence data. Data visualizations are combined with the cartographic display to yield a clear view of the relationship between geography and genomic diversity, with a particular focus on the hierarchical clustering of sites based on their similarity or phylogenetic proximity. Here we outline the features of GenGIS and demonstrate its application to georeferenced microbial metagenomic, HIV-1, and human mitochondrial DNA data sets.

Current CS1 learning outcomes are relatively general, specifying tasks such as designing, implementing, testing and debugging programs that use some fundamental programming constructs. These outcomes impact what we teach, our expectations, and our assessments. Although prior work has demonstrated the utility of single concept assessments, most assessments used in formal examinations combine numerous heterogeneous concepts, resulting in complex and difficult tasks. As a consequence, teachers may not be able to diagnose the actual difficulties faced by students and students are not provided with accurate feedback about their achievements. Such limitations on the nature and quality of feedback to teachers and students alike may contribute to the perceived difficulty and high dropout rates commonly observed in introductory programming courses.In this paper we review the concepts that CS education researchers have identified as important for novice programming. We survey learning outcomes for introductory programming courses that characterize the expectations of CS1 courses, and analyse assessments designed for CS1 to determine the individual components of syntax and semantics required to complete them. Having recognized the implicit and explicit expectations of novice programming courses, we look at the relationships between components and progression between concepts. Finally, we demonstrate how some complex assessments can be decomposed into atomic elements that can be assessed independently.Pre-print of the paper (accepted manuscript) for the institutional repository and not for redistribution. See terms of the ACM Copyright Transfer Agreement.

This paper explores the programming knowledge of novices using Biggs' SOLO taxonomy. It builds on previous work of Lister et al. (2006) and addresses some of the criticisms of that work. The research was conducted by studying the exam scripts for 120 introductory programming students, in which three specific questions were analyzed using the SOLO taxonomy. The study reports the following four findings: when the instruction to students used by Lister et al.-"In plain English, explain what the following segment of Java code does"-is replaced with a less ambiguous instruction, many students still provide multistructural responses; students are relatively consistent in the SOLO level of their answers; student responses on SOLO reading tasks correlate positively with performance on writing tasks; postgraduates students manifest a higher level of thinking than undergraduates.

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