Now showing 1 - 10 of 32
  • Publication
    Mindfulness and contemplative practices: The voice of the student
    There is a large spectrum of Mindfulness and Contemplative Practices (MCPs) which are gaining traction in the classroom. Many of these are aimed at reducing stress, reflecting on different points of view, expressing empathy, appreciating diversity and reducing absenteeism to name a few. Some of these practices hold promise to possibly improve attention, concentration and memory capabilities. However, there is no agreed consensus for what students want from MCPs (if anything), if they enjoy them, and if they want to engage in them. Further, it is likely that given the personal nature of MCPs, any findings are likely to be discipline and environment specific, if not specific to the cohort, or even the individual, warranting each educator to determine where their unique students stand. This paper draws motivation from previous empirical research, and the desire of the authors to capture the students? voice on what they want, and what they think works. The environment is a BSc in IT programme in Dublin, Ireland. Students were invited to participate in a mindfulness and contemplative practice workshop in which a number of MCPs were explored with faculty guidance. The MCPs were tailored using results of a preworkshop questionnaire completed by students, with inspiration drawn from the Tree of Contemplative Practices (The Center for Contemplative Mind in Society, 2015). During the workshop various practical sessions were led and results were captured through a postworkshop questionnaire. Results show a significant interest in MPCs, a range of motivations for engaging in them, and diverse practice interests. Overall, a high level of student engagement is a substantial outcome. This paper looks to inform educators seeking to introduce simple contemplative pedagogy practices in the classroom, hopefully making their first attempts more fruitful by allowing them to take into account their students? perceptions and desires. This can be determined by running their own workshop with their own students, or by using the results from ours, and making adjustments as required.
  • Publication
    Categorizing Compiler Error Messages with Principal Component Analysis
    Being a competent programmer is critical for students in all computing disciplines and software engineering in particular. Novice programming students face a number of challenges and these have been shown to contribute to worrying dropout rates for students majoring in computing, and the growing number of non-majors who are learning to program. Methods of identifying and helping at-risk programming students have been researched for decades. Much of this research focuses on categorizing the errors that novice programmers make, in order to help understand why these errors are made, with the goal of helping them overcome these errors quickly, or avoid them altogether. This paper presents the first known work on categorizing compiler errors using Principal Component Analysis. In this, we find a new way of discovering categories of related errors from data produced by the students in the course of their programming activity. This method may be used to identify where these students are struggling and provide direction in efforts to help them.
  • Publication
    High-Level Data Partitioning for Parallel Computing on Heterogeneous Hierarchical HPC Platforms
    (University College Dublin. School of Computer Science and Informatics, 2011)
    The current state and foreseeable future of high performance scientific computing (HPC) can be described in three words: heterogeneous, parallel and distributed. These three simple words have a great impact on the architecture and design of HPC platforms and the creation and execution of efficient algorithms and programs designed to run on them. As a result of the inherent heterogeneity, parallelism and distribution which promises to continue to pervade scientific computing in the coming years, the issue of data distribution and therefore data partitioning is unavoidable. This data distribution and partitioning is due to the inherent parallelism of almost all scientific computing platforms. Cluster computing has become all but ubiquitous with the development of clusters of clusters and grids becoming increasingly popular. Even at a lower level, high performance symmetric multiprocessor (SMP) machines, General Purpose Graphical Processing Unit (GPGPU) computing, and multiprocessor parallel machines play an important role. At a very low level, multicore technology is now widespread, increasing in heterogeneity, and promises to be omnipresent in the near future. The prospect of prevalent manycore architectures will inevitably bring yet more heterogeneity. Scientific computing is undergoing a paradigm shift like none before. Only a decade ago most high performance scientific architectures were homogeneous in design and heterogeneity was seen as a difficult and somewhat limiting feature of some architectures. However this past decade has seen the rapid development of architectures designed not only to exploit heterogeneity but architectures designed to be heterogeneous. Grid and massively distributed computing has led the way on this front. The current shift is moving from this to architectures that are not heterogeneous by definition, but heterogeneous by necessity. Cloud and exascale computing architectures and platforms are not designed to be heterogeneous as much as they are heterogeneous by definition. Indeed such architectures cannot be homogeneous on any large (and useful) scale. In fact more and more researchers see heterogeneity as the natural state of computing. Further to hardware advances, scientific problems have become so large that the use of more than one of any of the above platforms in parallel has become necessary, if not unavoidable. Problems such as climatology and projects including the Large Hadron Collider necessitate the use of extreme-scale parallel platforms, often encompassing more than one geographically central supercomputer or cluster. Even at the core level large amounts of information must be shared efficiently. One of the greatest difficulties in solving problems on such architectures is the distribution of data between the different components in a way that optimizes runtime. There have been numerous algorithms developed to do so over the years. Most seek to optimize runtime by reducing the total volume of communication between processing entities. Much research has been conducted to do so between distinct processors or nodes, less so between distributed clusters. This report presents new data partitioning algorithms for matrix and linear algebra operations. These algorithms would in fact work with little or no modification for any application with similar communication patterns. In practice these partitionings distribute data between a small number of computing entities, each of which can have great computational power themselves, and an even greater aggregate power. These partitionings may also be deployed in a hierarchical manner, which allows the flexibility to be employed in a great range of problem domains and computational platforms. These partitionings, in hybrid form, working together with more traditional partitionings, minimize the total volume of communication between entities in a manner proven to be optimal. This is done regardless of the power ratio that exists between the entities, thus minimizing execution time. There is also no restriction on the algorithms or methods employed on the clusters themselves locally, thus maximizing flexibility. Finally, most heterogeneous algorithms and partitionings are designed by modifying existing homogeneous ones. With this in mind the ultimate contribution of this report is to demonstrate that non-traditional and perhaps unintuitive algorithms and partitionings designed with heterogeneity in mind from the start can result in better, and in many cases optimal, algorithms and partitionings for heterogeneous platforms. The importance of this given the current outlook for, and trends in, the future of high performance scientific computing is obvious.
  • Publication
    Current Challenges and Future Research Areas for Digital Forensic Investigation
    Given the ever-increasing prevalence of technology in modern life, there is a corresponding increase in the likelihood of digital devices being pertinent to a criminal investigation or civil litigation. As a direct consequence, the number of investigations requiring digital forensic expertise is resulting in huge digital evidence backlogs being encountered by law enforcement agencies throughout the world. It can be anticipated that the number of cases requiring digital forensic analysis will greatly increase in the future. It is also likely that each case will require the analysis of an increasing number of devices including computers, smartphones, tablets, cloud-based services, Internet of Things devices, wearables, etc. The variety of new digital evidence sources poses new and challenging problems for the digital investigator from an identification, acquisition, storage and analysis perspective. This paper explores the current challenges contributing to the backlog in digital forensics from a technical standpoint and outlines a number of future research topics that could greatly contribute to a more efficient digital forensic process.
  • Publication
    Introducing Contemplative Pedagogy to the Classroom: Implementation, Experience and Effects on Concentration
    While there is no single theory or praxis of contemplative pedagogy (Coburn, 2011), there is a wide spectrum of Mindfulness Meditation Practices (MMPs) being used in the classroom at a growing number of institutions. Many of these are aimed outcomes such as reducing stress, reflection (including self-reflection), expressing empathy, appreciating diversity and reducing absenteeism. Some of these practices also hold promise to possibly improve cognition, concentration and memory capabilities. This paper explores the experience of implementing a one-pointedness MMP in the classroom at an Irish higher education institution. The focus is on simplicity of implementation, minimal disruption, student engagement with the practice and any positive effects this may bring to the concentration/attention abilities of students. Specifically, a one-pointedness meditation is practiced by students at the outset of each lecture in a specified module. At the end of the lecture period, students are given a form of Wilkins¿ counting test, a measure of sustained focused concentration. Results are then compared to the performance of the same cohort in another module with no one-pointedness exercise, serving as control. Results show a small and borderline statistically-significant increase in the concentration abilities of students in the module that includes the one-pointedness meditation. Students also participated in a questionnaire and a discussion group, reflecting on their experience with the practice, and their opinions on introducing MMPs into their learning. Overall the student experience was much more positive than the authors had envisioned, even hoped for. At a minimum the results of this paper can inform educators looking to introduce simple contemplative pedagogy practices in the classroom, hopefully making their first attempts more fruitful.  
  • Publication
    ProgSnap2: A Flexible Format for Programming Process Data
    In this paper, we introduce ProgSnap2, a standardized format for logging programming process data. The goal of this common format is to encourage collaboration among researchers by helping them to share data, analysis code, and data-driven tools to support students. We first highlight possible use cases for ProgSnap2 and give a high-level overview of the format. We then share two case studies of our experience using the format and outline goals for the future of ProgSnap2, including a call for collaboration with interested researchers.
  • Publication
    An Evaluation of Google Plus Communities as an Active Learning Journal Alternative to Improve Learning Efficacy
    (ICEP, 2015-12-04) ;
    Learning journals are a very beneficial learning tool for students across a range of disciplines. The requirement of frequent entries to a journal encourages students to start achieving the learning objectives from the first week of a module. The completed journal serves as a useful revision resource for students preparing for a final exam or even long after the module’s completion. The downside to learning journals is that they are passive and the class as a whole does not benefit from the variety of opinions, articles and personal experiences logged in their classmates' journals. If the journal is only handed in at the end a semester, there is no room for feedback for the students on their entries until after the module has completed. In this paper, guidelines for the deployment of an active learning journal alternative, using Google Plus Communities, are presented. A literature review is also included for alternative case studies in using learning journals, weblogs, and wikis for recording and encouraging student learning throughout a module.
  • Publication
    Variations in Sense of Belonging in Undergraduate Computing Students Through the COVID-19 Pandemic
    Student sense of belonging, or belongingness, is important and has been associated with motivation, persistence, and other outcomes. However, belongingness varies according to factors such as race/ethnicity and gender [2]. In previous work, there have been statistically significant differences in the belongingness of computing students identifying as women and as part of a minority [2]. During the COVID-19 pandemic there was a reduction in the belongingness of students identifying as men, and those not identifying as being part of a minority, and an increase in the belongingness of women identifying as a minority [3]. Our current work shows that the belongingness of men and women not identifying as being part of a minority has not returned to pre-pandemic levels, despite returning to campus, and a further statistically significant drop in the belongingness of men who identify as part of a minority. This work shows that further efforts need to be made to restore student belongingness to pre-pandemic levels and may yield insight into how events affect belongingness.
      26Scopus© Citations 4
  • Publication
    What Do CS1 Syllabi Reveal About Our Expectations of Introductory Programming Students?
    (ACM Press, 2019-03-02) ;
    A well-received ITiCSE 2016 paper challenged the orthodox view that programming is hard to learn. It contended that CS1 educators’ expectations are too high, which can result in poor teaching and learning, and could impact negatively on diversity and equity. The author posed a challenge to the community to collect research-based evidence of what novice programmers can achieve, and use evidence to derive realistic expectations for achievement. We argue that before rising to this challenge we must determine: What exactly do educators expect of introductory programming students? This paper presents our efforts toward answering this question. We manually curated hundreds of CS1 syllabi, providing a fresh perspective of expectation in CS1 courses. We analysed learning outcomes and their concepts, in addition to languages utilized and other useful CS1 design and delivery information. This work contributes to a current picture of what is expected of introductory programming students, and provides an interactive online tool linked to all collected syllabi and containing all learning outcomes and other associated information. We hope this will aid the community in deciding whether or not we have unrealistic expectations of our CS1 students and if so, our contributions provide a starting point for the community to adjust them.
      690Scopus© Citations 43
  • Publication
    Exploring Sense of Belonging in Computer Science Students
    Student sense of belonging has been shown to be associated with many attributes such as motivation and persistence. However, sense of belonging can show variations according to factors such as race and gender. In this study, we examine the relationship between undergraduate Computer Science students' participation in networking, outreach, and mentoring activities and their sense of belonging. Results reveal lower levels of sense of belonging in women and self-identified minorities. However, we observed a higher sense of belonging in female students who participated in networking, outreach, and mentoring activities.
      373Scopus© Citations 23