Visual Analytics Design To Support Knowledge Generation: The Case Of Outcome Based Education Assessment in Malaysia

Lumius, L. D.; Hamzah, Muzaffar; Yee, Chin Pei; Pang, Vincent; Goh, Say Leng

doi:10.1109/iscaie47305.2020.9108793

Cited by 2 publications

(1 citation statement)

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“…Therefore, the factors of familiarity and preference need to be considered in generating appropriate visualization. The presented framework is a refined iteration of prior work [23], added with additional focus on design development. Driven by the identified requirements and factors, a visual analytics system was designed and developed for facilitating OBE predictive analysis.…”

Section: A Domain Characterization and Design Frameworkmentioning

confidence: 99%

OBEInsights: Visual Analytics Design for Predictive OBE Knowledge Generation

Lumius¹,

Asli²

2021

IJACSA

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Gaining traction in modern higher education, outcome-based education (OBE) focuses on strategizing pedagogical approaches to help the student achieve specified learning outcomes. In the context of Malaysia, OBE is oriented towards holistic development of graduates to ensure readiness towards the working sector. To empower OBE implementation, standardized measuring instrument iCGPA was introduced to higher education institutions nationwide. With lower dependency on provided curriculum, graduate abilities and values development are also attainable via extracurricular activities. However, analyzing the curriculum results in hand with extracurricular activities can be a daunting task, albeit the potential enriched performance assessment. In addition, the current iCGPA instrument employs radar map that restricts data exploration despite its capability in visualizing multivariate information. This study aims to enable predictive knowledge generation on understanding the relationship between learning activities and performance in OBE. Therefore, a predictive visual analytics system namely OBEInsights is proposed to facilitate education analysts in assessing OBE. The system development started with the identification of crucial design and analytic requirements via a domain expert case study. The system is then built with deliberate considerations of guiding factors of a design framework conceptualized from the case study. Subsequently, the system was then evaluated in usability testing with 10 domain experts that consist of usability rating and expert validation. The evaluation and expert validation results demonstrated the effectiveness and usability of OBEInsights in facilitating OBE predictive assessment. Several design insights on constructing visual analytics for OBE assessment were also discovered in terms of effective visualization, predictive modeling, and knowledge generation. Analytic designers and builders can leverage the reported design insights to enhance knowledge generation tools for OBE assessment.

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Section: A Domain Characterization and Design Frameworkmentioning

confidence: 99%