eScholar

eScholar stores, preserves and disseminates digital copies of the research and scholarly output of eScholar faculty, researchers and students. These can include the following items:

  • Monographs
  • Pre- and post-prints of academic journal articles
  • Theses and dissertations
  • Major projects and papers
  • Reports/working papers and conference proceedings

Materials in eScholar are openly available to the world and discoverable through search engines such as Google Scholar. This high visibility, discoverability, and exposure can lead to increased citation. Contact Library Publishing for more information.

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Now showing 1 - 5 of 9

Recent Submissions

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    Exploring the double-edged nature of social media during student-athlete injury recovery and the need for digital wellness: a community-based project
    (2025-11-01) Pereira da Silva, Samantha; Laffier, Jennifer
    Adolescent student-athletes face unique challenges balancing sport, academics, and identity development during a critical stage of growth. These challenges often intensify after injury, disrupting physical activity, self-concept, and mental well-being. Social media, a central part of adolescent life, plays a complex role in recovery, offering both mental health benefits and risks. This multi-phase research project examined how social media use influences injured adolescent student-athletes and identified digital wellness needs. Phase one reviewed the literature on benefits, such as social support, transition assistance, and access to health information, as well as risks, such as negative commentary, identity loss, and social comparison. Findings highlight the need to integrate digital wellness education into athletic programs through healthy online support networks, transition support, mindfulness, and stigma reduction. Future research should explore interventions that help student-athletes manage recovery in the digital age. Phase two involved community workshops and webinars to share findings with athletes, parents, and coaches.
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    Developing future-ready learners: a scoping review on non-technical skills needed for employability in the digital economy
    (2025-12-01) Boateng, Paa Agyenim; van Oostveen, Roland
    The rapid advancement of technology across industries has led to digital transformation, reshaping labour market demands, making it crucial to understand how post-secondary learners can enhance their employability in technology-driven economies. Accordingly, educational institutions should align curricula and pedagogical approaches to cultivate the essential non-technical skills required in the digital age. While discussions on “critical skills” are common, limited research has systematically examined which specific non-technical skills most significantly influence employability outcomes. This study employs a scoping review methodology to analyze 40 peer-reviewed studies, identifying the non-technical skills that are most critical for post-secondary learners seeking employment in a technology-intensive world. The findings highlight the most emphasized skill areas and provide insights into the competencies educators should prioritize to bridge the gap between education and industry needs.
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    How is fairness measured in practice? A survey and critique of fairness analyses applied to predictive algorithms
    (2026-01-27) Putman, Andrew; Lewis, Peter; Rudoler, David
    The increasingly rapid pace of research and development of prediction algorithms over the past decade has spurred their adoption across seemingly every industry and aspect of life. This growth and the subsequent increase in public awareness have brought a range of concerns into focus regarding the potential bias and fairness impacts of these algorithms. This cross-disciplinary survey assesses peer-reviewed publications from the last 10 years which assessed fairness in a predictive algorithm using real world data. We begin with a descriptive overview of the fields of research, types of publication, and the types of outcomes being predicted. We then engage in a more detailed exploration of the fairness analyses that were applied, the metrics used, and the evidence provided to justify these selections. We also discuss the contexts in which these analyses were conducted. We conclude by highlighting the lack of inclusion of perspectives from people who are impacted by the algorithms being analyzed and discuss directions for future work in this area.
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    Design and development of a LIVE Digital Twin methodology for predictive maintenance of bearings in rotary machine systems
    (2025-12-01) Zonta, Tristan J.A.; Barari, Ahmad
    Digital Twin (DT) is a prominent focus for many predictive and prescriptive maintenance strategies. In maintenance, DT is used for connecting the physical and digital models of a maintenance monitoring system and proactively prescribing maintenance solutions to extend the products life. Many of the failures in modern DT can be attributed to the lack of defined structure, the unavailability of failure data to calibrate the systems, and poor connectivity between the physical and digital systems. LIVE provides a systematic approach to implement a DT system in 4 stages of Learn, Identify, Verify and Extend. This thesis uses LIVE DT for dynamic rotary systems connecting the physical asset to its DT to predict failure. In addition, this thesis covers the development of a device that will allow for emulating bearing defects in a controllable and repeatable way for calibrating virtual systems when historical or failure data is unavailable.