Learner Intrinsic Motivation in Online Social Learning Platforms: A Case Study of Massive Open Online Course (MOOC) in Thailand

New forms of cartographic education are becoming possible with the synthesis of easy to use web GIS tools and learning platforms that support online education at a massive scale. The internet classroom can now support tens of thousands of learners at a time, and while some common types of assessments scale very easily, others face significant hurdles. A particular concern for the cartographic educator is the extent to which original map designs can be evaluated in a massive open online course (MOOC). Based on our experiences in teaching one of the first MOOCs on cartography, we explore the ways in which very large collections of original map designs can be assessed. Our methods include analysis of peer grades and qualitative feedback, visual techniques to explore design methods, and quantitative comparison between expert ratings and peer grades. The results of our work suggest key challenges for teaching cartography at scale where instructors cannot provide individual feedback for every student.

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Oral production skills and pronunciation improvement in MOOCs for migrants and refugees: an unavoidable challenge

Lengua y migración ◽

10.37536/lym.13.2.2021.1025 ◽

2021 ◽

Vol 13 (2) ◽

Author(s):

Victoria Marrero-Aguiar

Keyword(s):

Online Course ◽

Massive Open Online ◽

Oral Production ◽

Massive Open Online Course ◽

Oral Skills

This article is focused on the challenges posed by the development of oral production skills (speaking, pronunciation) in a Massive Open Online Course (MOOC), a resource that is totally conditioned by the technologies and has very limited posibilities for individual adaptation. First of all, the difficulties that this goal poses are reviewed and confronted with some successful precedents that show how to deal with those challenges. Next, we present a case study in which some strategies and resources have been used to develop oral skills and improve pronunciation in technologically mediated environments, an Spanish L-MOOC for migrants and refugees, absolute beginners, developed at UNED (Spain).

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Utilizing Text Mining and Feature-Sentiment-Pairs to Support Data-Driven Design Automation Massive Open Online Course

International Journal of Emerging Technologies in Learning (iJET) ◽

10.3991/ijet.v16i01.17095 ◽

2021 ◽

Vol 16 (01) ◽

pp. 134

Author(s):

Nasa Zata Dina ◽

Riky Tri Yunardi ◽

Aji Akbar Firdaus

Keyword(s):

Text Mining ◽

Design Automation ◽

Online Reviews ◽

User Preferences ◽

User Preference ◽

Online Course ◽

Massive Open Online ◽

Massive Open Online Course ◽

Related Design

This study aimed to develop a case-based design framework to analyze online us-er reviews and understanding the user preferences in a Massive Open Online Course (MOOC) content-related design. Another purpose was to identify the fu-ture trends of MOOC content-related design. Thus, it was an effort to achieve da-ta-driven design automation. This research extracts pairs of keywords which are later called Feature-Sentiment-Pairs (FSPs) using text mining to identify user preferences. Then the user preferences were used as features of an MOOC content-related design. An MOOC case study is used to implement the proposed framework. The online reviews are collected from www.coursera.org as the MOOC case study. The framework aims to use these large scale online review data as qualitative data and converts them into quantitative meaningful infor-mation, especially on content-related design so that the MOOC designer can de-cide better content based on the data. The framework combines the online re-views, text mining, and data analytics to reveal new information about users’ preference of MOOC content-related design. This study has applied text mining and specifically utilizes FSPs to identify user preferences in the MOOC content-related design. This framework can avoid the unwanted features on the MOOC content-related design and also speed up the identification of user preference.

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