This paper describes the results of an ITiCSE working group convened in 2013 to review and revisit the influential ITiCSE 2001 McCracken working group that reported [18] on novice programmers' ability to solve a specified programming problem. Like that study, the one described here asked students to implement a simple program. Unlike the original study, students' in this study were given significant scaffolding for their efforts, including a test harness. Their knowledge of programming concepts was also assessed via a standard language-neutral survey. One of the significant findings of the original working group was that students were less successful at the programming task than their teachers expected, so in this study teachers' expectations were explicitly gathered and matched with students' performance. This study found a significant correlation between students' performance in the practical task and the survey, and a significant effect on performance in the practical task attributable to the use of the test harness. The study also found a much better correlation between teachers' expectations of their students' performance than in the 2001 working group.

This paper presents a case study of the use of a repeated single-criterion card sort with an unusually large, diverse participant group. The study, whose goal was to elicit novice programmers' knowledge of programming concepts, involved over

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Peer Instruction (PI) is a student-centric pedagogy in which students move from the role of passive listeners to active participants in the classroom. Over the past five years, there have been a number of research articles regarding the value of PI in computer science. The present work adds to this body of knowledge by examining outcomes from seven introductory programming instructors: three novices to PI and four with a range of PI experience. Through common measurements of student perceptions, we provide evidence that introductory computing instructors can successfully implement PI in their classrooms. We find encouraging minimum (74%) and average (92%) levels of success as measured through student valuation of PI for their learning. This work also documents and hypothesizes reasons for comparatively poor survey results in one course, highlighting the importance of the choice of grading policy (participation vs. correctness) for new PI adopters.

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Section 6 of the "Repository policy for OpenAIR @ RGU" (available from http://www.rgu.ac.uk/staff-and-currentstudents/library/library-policies/repository-policies) provides guidance on the criteria under which RGU will consider withdrawing material from OpenAIR. If you believe that this item is subject to any of these criteria, or for any other reason should not be held on OpenAIR, then please contact openair-help@rgu.ac.uk with the details of the item and the nature of your complaint. saw@ecs.soton.ac.uk ABSTRACTAcademics expend a large amount of time and effort to sustain and enhance the motivation of undergraduate students. Typically based on a desire to ensure that all students achieve their full potential, approaches are based on an understanding that students who are highly motivated will learn more. Furthermore, institutional rewards accrue from effective use of academics' time, along with financial benefits associated with high levels of retention and progression. This working group report, based on practice in Europe, Australasia and North America, builds on previous work. It provides an updated and revised literature review, analyses a larger collection of survey data and has sought to triangulate earlier findings with qualitative data from practitioner interviews. The report covers established approaches in teaching, support and extra-curricular activities. It tracks emerging practice such as streamed and differentiated teaching, and research based and authentic learning. It also considers contemporary innovations in student activities. Finally it reports on a repository of tips and techniques which has been established to support faculty wishing to change or review current methods. Categories and Subject Descriptors

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