Python for teaching introductory programming: A quantitative evaluation

This paper compares two different approaches of teaching introductory programming by quantitatively analysing the student assessments in a real classroom. The first approach is to emphasise the principles of object-oriented programming and design using Java from the very beginning. The second approach is to first teach the basic programming concepts (loops, branch, and use of libraries) using Python and then move on to oriented programming using Java. Each approach was adopted for one academic year (2008-09 and 2009-10) with first year undergraduate students. Quantitative analysis of the student assessments from the first semester of each year was then carried out. The results of this analysis are presented in this paper. These results suggest that the later approach leads to enhanced learning of introductory programming concepts by students

Content delivery and challenges in education hybrid students

Traditionally, taught postgraduate programmes placed students in well-defined categories such as 'distance learning' and 'on-campus' or 'part-time' and 'full-time'. The practical reality is that postgraduate students rarely fall into such simple, diametric roles and can be more suitably generalised under the concept of the 'hybrid student'. Hybrid students are dynamic, with changing requirements in relation to their education. They expect flexibility and the ability to make changes relating to module participation level, study mechanism and lecture attendance, in order to suit personal preference and circumstance. This paper briefly introduces the concept of the hybrid student and how the concept has been handled within the School of Electronic Engineering at DCU. Following this, some discussion is provided in relation to a number of the content delivery technologies used in programmes facilitating these students: HTML, PowerPoint, Moodle, DocBook and Wiki. Finally, some of the general challenges, which have been encountered in supporting such diverse students, are briefly discussed

A collaborative approach to learning programming: a hybrid learning model

The use of cooperative working as a means of developing collaborative skills has been recognised as vital in programming education. This paper presents results obtained from preliminary work to investigate the effectiveness of Pair Programming as a collaborative learning strategy and also its value towards improving programming skills within the laboratory. The potential of Problem Based Learning as a means of further developing cooperative working skills along with problem solving skills is also examined and a hybrid model encompassing both strategies outlined

Blackbox: A Large Scale Repository of Novice Programmers’ Activity

Automatically observing and recording the programming be- haviour of novices is an established computing education research technique. However, prior studies have been con- ducted at a single institution on a small or medium scale, without the possibility of data re-use. Now, the widespread availability of always-on Internet access allows for data col- lection at a much larger, global scale. In this paper we re- port on the Blackbox project, begun in June 2013. Black- box is a perpetual data collection project that collects data from worldwide users of the BlueJ IDE – a programming environment designed for novice programmers. Over one hundred thousand users have already opted-in to Blackbox. The collected data is anonymous and is available to other researchers for use in their own studies, thus benefitting the larger research community. In this paper, we describe the data available via Blackbox, show some examples of analyses that can be performed using the collected data, and discuss some of the analysis challenges that lie ahead

Investigating novice programming mistakes: educator beliefs vs. student data

Educators often form opinions on which programming mistakes novices make most often - for example, in Java: "they always confuse equality with assignment", or "they always call methods with the wrong types". These opinions are generally based solely on personal experience. We report a study to determine if programming educators form a consensus about which Java programming mistakes are the most common. We used the Blackbox data set to check whether the educators' opinions matched data from over 100,000 students - and checked whether this agreement was mediated by educators' experience. We found that educators formed only a weak consensus about which mistakes are most frequent, that their rankings bore only a moderate correspondence to the students in the Blackbox data, and that educators' experience had no effect on this level of agreement. These results raise questions about claims educators make regarding which errors students are most likely to commit

Using theory to inform capacity-building: Bootstrapping communities of practice in computer science education research

In this paper, we describe our efforts in the deliberate creation of a community of practice of researchers in computer science education (CSEd). We understand community of practice in the sense in which Wenger describes it, whereby the community is characterized by mutual engagement in a joint enterprise that gives rise to a shared repertoire of knowledge, artefacts, and practices. We first identify CSEd as a research field in which no shared paradigm exists, and then we describe the Bootstrapping project, its metaphor, structure, rationale, and delivery, as designed to create a community of practice of CSEd researchers. Features of other projects are also outlined that have similar aims of capacity building in disciplinary-specific pedagogic enquiry. A theoretically derived framework for evaluating the success of endeavours of this type is then presented, and we report the results from an empirical study. We conclude with four open questions for our project and others like it: Where is the locus of a community of practice? Who are the core members? Do capacity-building models transfer to other disciplines? Can our theoretically motivated measures of success apply to other projects of the same nature

Early Developmental Activities and Computing Proficiency

As countries adopt computing education for all pupils from primary school upwards, there are challenging indicators: significant proportions of students who choose to study computing at universities fail the introductory courses, and the evidence for links between formal education outcomes and success in CS is limited. Yet, as we know, some students succeed without prior computing experience. Why is this? <br/><br/> Some argue for an innate ability, some for motivation, some for the discrepancies between the expectations of instructors and students, and some – simply – for how programming is being taught. All agree that becoming proficient in computing is not easy. Our research takes a novel view on the problem and argues that some of that success is influenced by early childhood experiences outside formal education. <br/><br/> In this study, we analyzed over 1300 responses to a multi-institutional and multi-national survey that we developed. The survey captures enjoyment of early developmental activities such as childhood toys, games and pastimes between the ages 0 — 8 as well as later life experiences with computing. We identify unifying features of the computing experiences in later life, and attempt to link these computing experiences to the childhood activities. <br/><br/> The analysis indicates that computing proficiency should be seen from multiple viewpoints, including both skill-level and confidence. It shows that particular early childhood experiences are linked to parts of computing proficiency, namely those related to confidence with problem solving using computing technology. These are essential building blocks for more complex use. We recognize issues in the experimental design that may prevent our data showing a link between early activities and more complex computing skills, and suggest adjustments. Ultimately, it is hoped that this line of research will feed in to early years and primary education, and thereby improve computing education for all

Developing an Inclusive K-12 Outreach Model

This paper outlines the longitudinal development of a K-12 outreachmodel, to promote Computer Science in Ireland. Over a three-yearperiod, it has been piloted to just under 9700 K-12 students fromalmost every county in Ireland. The model consists of a two-hourcamp that introduces students to a range of Computer Sciencetopics: addressing computing perceptions, introduction to codingand exploration of computational thinking. The model incorporateson-site school delivery and is available at no cost to any interestedschool across Ireland. The pilot study so far collected over 3400surveys (pre- and post-outreach delivery).Schools from all over Ireland self-selected to participate, includ-ing male only, female only and mixed schools. The no-cost natureof the model meant schools deemed disadvantaged , to privatefee-paying schools participated. Initial findings are very positive,including the balance of male and female participants, where in the2017-18 academic year it was 56:44 and in 2019-20 (to date), it is35:65 respectively. Once the model is validated and tweaked (basedon survey data), the model will be published (open access) for otherinstitutions to implement the model locally. In addition, the authorsintend to link schools (that the team have worked with over thethree years) with local institutions, thus developing a sustainableecosystem for the program to continue. This paper describes themodel structure and outlines early finding