Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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    Data Quality Challenges in Educational Process Mining: Building Process-Oriented Event Logs from Process-Unaware Online Learning Systems
    (Inderscience, 2022-05-04) Umer R; Susnjak T; Mathrani A; Suriadi S
    Educational process mining utilizes process-oriented event logs to enable discovery of learning practices that can be used for the learner’s advantage. However, learning platforms are often process-unaware, therefore do not accurately reflect ongoing learner interactions. We demonstrate how contextually relevant process models can be constructed from process-unaware systems. Using a popular learning management system (Moodle), we have extracted stand-alone activities from the underlying database and formatted it to link the learners’ data explicitly to process instances (cases). With a running example that describes quiz-taking activities undertaken by students, we describe how learner interactions can be captured to build process-oriented event logs. This article contributes to the fields of learning analytics and education process mining by providing lessons learned on the extraction and conversion of process-unaware data to event logs for the purpose of analysing online education data.
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    Digital divide framework: online learning in developing countries during the COVID-19 lockdown
    (Taylor and Francis Group, 2022) Mathrani A; Sarvesh T; Umer R
    This article showcases digital inequalities that came to the forefront for online learning during the COVID-19 lockdown across five developing countries, India, Pakistan, Bangladesh, Nepal and Afghanistan. Large sections of population in developing economies have limited access to basic digital services; this, in turn, restricts how digital media are being used in everyday lives. A digital divide framework encompassing three analytical perspectives, structure, cultural practices and agency, has been developed. Each perspective is influenced by five constructs, communities, time, location, social context and sites of practice. Community relates to gendered expectations, time refers to the lockdown period while locations are interleaved online classrooms and home spaces. Societal contexts influence aspects of online learning and how students engage within practice sites. We find structural issues are due to lack of digital media access and supporting services; further that female students are more often placed lower in the digital divide access scale. Cultural practices indicate gendered discriminatory rules, with female students reporting more stress due to added household responsibilities. This impacts learner agency and poses challenges for students in meaningfully maximising their learning outcomes. Our framework can inform policy-makers to plan initiatives for bridging digital divide and set up equitable gendered learning policies.
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    All-Dielectric Transreflective Angle-Insensitive Near-Infrared (NIR) Filter
    (MDPI (Basel, Switzerland), 2022-08) Shaukat A; Umer R; Noble F; Arif K
    This paper presents an all-dielectric, cascaded, multilayered, thin-film filter, allowing near-infrared filtration for spectral imaging applications. The proposed design is comprised of only eight layers of amorphous silicon (A-Si) and silicon nitride (Si₃N₄), successively deposited on a glass substrate. The finite difference time domain (FDTD) simulation results demonstrate a distinct peak in the near-infrared (NIR) region with transmission efficiency up to 70% and a full-width-at-half-maximum (FWHM) of 77 nm. The theoretical results are angle-insensitive up to 60⁰ and show polarization insensitivity in the transverse magnetic (TM) and transverse electric (TE) modes. The theoretical response, obtained with the help of spectroscopic ellipsometry (SE), is in good agreement with the experimental result. Likewise, the experimental results for polarization insensitivity and angle invariance of the thin films are in unison with the theoretical results, having an angle invariance up to 50⁰.