Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC

Asli, Mohammad Fadhli; Hamzah, Muzaffar; Ibrahim, Ag Asri Ag; Ayub, Enna

doi:10.1016/j.heliyon.2020.e05733

Cited by 12 publications

(7 citation statements)

References 22 publications

(26 reference statements)

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“…The result can be supported by the findings of Julia et al [68] wherein they stated that MOOCs such as Coursera lack the guidance and instructions for different activities needed to complete the course. Moreover, Asli et al [69] highlighted that interaction should also take place for students to be engaged. With that, Kim et al [70] stated that for MOOCs such as Coursera to be effective, students' commitment would be, at best, interested.…”

Section: Discussionmentioning

confidence: 99%

Students’ Preference Analysis on Online Learning Attributes in Industrial Engineering Education during the COVID-19 Pandemic: A Conjoint Analysis Approach for Sustainable Industrial Engineers

et al. 2021

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The decline of enrollees for industrial engineering during the COVID-19 pandemic and the increasing demand for professional industrial engineers should be explored. The purpose of this study was to determine the preference of industrial engineering students of different educational levels on online learning during the COVID-19 pandemic. Specifically, this study utilized conjoint analysis with orthogonal design considering seven attributes: delivery type, layout, term style, final requirements, Coursera requirements, seatwork and practice sets, and platforms. Among the attributes, 20 stimuli were created through SPSS and were answered voluntarily by 126 respondents utilizing a 7-point Likert Scale. The respondents were comprised of 79 undergraduate, 30 fully online master’s degree, and 17 master’s and doctorate degree students collected through purposive sampling. One university from the two available universities that offer all educational levels of IE in the Philippines was considered. The results showed that undergraduate students considered the final requirements with multiple-choice as the highest preference, followed by non-modular term style, and no seatwork and practice sets. In addition, fully online master’s degree students considered delivery type with the mix as the highest preference, followed by layout, and no seatwork and practice sets. Finally, master’s and doctorate degree students considered final requirements with publication as the highest preference, followed by no seatwork and practice sets, and mix delivery type. The students are technologically inclined, want to learn at their own pace, know where and how to get additional online learning materials, but still need the guidance of teachers/professors. The results would help contribute to the theoretical foundation for further students’ preference segmentation, specifically on online learning during the COVID-19 pandemic worldwide. Moreover, the design created could be utilized for other courses in measuring students’ preference for online learning even after the COVID-19 pandemic.

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Section: Discussionmentioning

confidence: 99%

Students’ Preference Analysis on Online Learning Attributes in Industrial Engineering Education during the COVID-19 Pandemic: A Conjoint Analysis Approach for Sustainable Industrial Engineers

et al. 2021

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“…Traditional English classes are limited by time and space, making it challenging to ensure that students can learn English at any time and in any environment. However, the mobile information technology-based English MOOC has broken through the time and space limitations of traditional English classroom teaching and has changed students' English learning methods dramatically [16]. Students no longer need to be constrained by external conditions such as place, time, and environment to learn English.…”

Section: The Merits Of Moocmentioning

confidence: 99%

Building an Open Sharing Platform for ELT Courses: The Example of MOOC Network

Li¹,

Zhang²

2022

Advances in Multimedia

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English language teaching (ELT) has become an essential and indispensable part of primary education in today’s increasingly frequent international exchanges, and MOOC, as a massive online teaching model integrating content and learning support services, is leading a pedagogical transformation, providing a historic opportunity to build an open sharing platform for ELT. However, developing an open sharing platform around MOOC networks is still challenging, especially for English courses, where various course designs significantly increase the difficulty of tracking students’ learning status. Therefore, we introduce RNN-based sequence-to-sequence knowledge tracing models as the software foundation of the shared platform. The transformer model is further chosen to simulate students’ historical learning trajectories to solve the problem of long-term dependency in traditional models. The research results have important theoretical and practical implications for building an open sharing platform for ELT courses.

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“…The domain characterization helps specify the analysis interests and practices from OBE analyst and practitioners to identify crucial design requirements. The factors of visualization familiarity and preferences plays a role in enhancing the learnability of the system [27]. The evaluation result in Table V and Table VI indicates that the featured interaction and visualization encodings applied into OBEInsights are effective in facilitating OBE predictive analysis.…”

Section: B Discussionmentioning

confidence: 97%

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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Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC

Cited by 12 publications

References 22 publications

Students’ Preference Analysis on Online Learning Attributes in Industrial Engineering Education during the COVID-19 Pandemic: A Conjoint Analysis Approach for Sustainable Industrial Engineers

Students’ Preference Analysis on Online Learning Attributes in Industrial Engineering Education during the COVID-19 Pandemic: A Conjoint Analysis Approach for Sustainable Industrial Engineers

Building an Open Sharing Platform for ELT Courses: The Example of MOOC Network

OBEInsights: Visual Analytics Design for Predictive OBE Knowledge Generation

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