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

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.

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

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).

scholarly journals EXPLORING AND UNDERSTANDING THE SPREAD OF MOOCS IN AN EMERING ECONOMY : A TEXT MINING ANALYSIS

2021 ◽  
Vol 9 (12) ◽  
pp. 58-65
Author(s):  
El Moussaouiti Imane ◽  
Keyword(s):  
Higher Education ◽  
Distance Learning ◽  
Text Mining ◽  
Teaching Quality ◽  
New Method ◽  
Clear Picture ◽  
Online Course ◽  
Massive Open Online ◽  
Massive Open Online Course ◽  
The World

The Massive Open Online Course, or MOOC is a new method of distance learning especially in the universities, a number of them use this method to contain the different obstacle of leaning in higher education in order to improve the teaching quality among a large number of students. This paper will explore this new method of a distance learning in the word and its impact on an emergent economy as Morocco. The purpuse of this paper is to give a clear picture of the MOOC in the world and in moroccan universities as an emergent economy, by analysing a text mining of the use of MOOC and their classification.

scholarly journals Reviewer Experience vs. Expertise: Which Matters More for Good Course Reviews in Online Learning?

2021 ◽  
Vol 13 (21) ◽  
pp. 12230
Author(s):  
Zhao Du ◽  
Fang Wang ◽  
Shan Wang
Keyword(s):  
Online Learning ◽  
Analytical Approach ◽  
Online Courses ◽  
Online Reviews ◽  
Review Literature ◽  
Online Review ◽  
Online Course ◽  
Massive Open Online ◽  
Online Learners ◽  
Massive Open Online Course

With a surging number of online courses on MOOC (Massive Open Online Course) platforms, online learners face increasing difficulties in choosing which courses to take. Online course reviews posted by previous learners provide valuable information for prospective learners to make informed course selections. This research investigates the effects of reviewer experience and expertise on reviewer competence in contributing high-quality and helpful reviews for online courses. The empirical study of 39,114 online reviews from 3276 online courses on a leading MOOC platform in China reveals that both reviewer experience and expertise positively affect reviewer competence in contributing helpful reviews. In particular, the effect of reviewer expertise on reviewer competence in contributing helpful reviews is much more prominent than that of reviewer experience. Reviewer experience and expertise do not interact in enhancing reviewer competence. The analysis also reveals distinct groups of reviewers. Specifically, reviewers with low expertise and low experience contribute the majority of the reviews; reviewers with high expertise and high experience are rare, accounting for a small portion of the reviews; the rest of the reviews are from reviewers with high expertise, but low experience, or those with low expertise, but high experience. Our work offers a new analytical approach to online learning and online review literature by considering reviewer experience and expertise as reviewer competence dimensions. The results suggest the necessity of focusing on reviewer expertise, instead of reviewer experience, in choosing and recommending reviewers for online courses.

scholarly journals Data Collection Approaches to Enable Evaluation of a Massive Open Online Course About Data Science for Continuing Education in Health Care: Case Study

10.2196/10982 ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. e10982 ◽  
Author(s):  
Abrar Alturkistani ◽  
Azeem Majeed ◽  
Josip Car ◽  
David Brindley ◽  
Glenn Wells ◽  
...  
Keyword(s):  
Health Care ◽  
Data Collection ◽  
Continuing Education ◽  
Data Science ◽  
Online Course ◽  
Massive Open Online ◽  
Massive Open Online Course
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