Sentiment analysis on massive open online course evaluations: A text mining and deep learning approach

2020 ◽  
Author(s):  
Aytuğ ONAN
Keyword(s):  
Deep Learning ◽  
Text Mining ◽  
Sentiment Analysis ◽  
Course Evaluations ◽  
Online Course ◽  
Learning Approach ◽  
Massive Open Online ◽  
Massive Open Online Course

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 Analyzing the Sentiment of MOOC Discussion Posts

2019 ◽  
Vol 2 (2) ◽  
pp. 1-2
Author(s):  
Haniya Ahmed ◽  
Kenny Wong
Keyword(s):  
Natural Language ◽  
Sentiment Analysis ◽  
Online Course ◽  
Massive Open Online ◽  
Massive Open Online Course ◽  
Positive Sentiment ◽  
Negative Sentiment

The purpose of the project is to identify common difficulties that learners may face and to understand their emotions as they progress through MOOCs. MOOC is an abbreviation for the Massive Open Online Course and the research deals with the data from ten different courses from Coursera. The data is used to extract pieces of text that students have made. Then, those certain texts are required to be sent to Google Cloud Natural Language API. This app allows users to get a sentiment analysis of a text. The main goal is to assist instructors with monitoring MOOC to make it more efficient and easier for students to progress since it assists to improve the courses.  To achieve this, the first step is to gather all the data from each of the courses. Then use programming to dump all that data into one big database. The program that is used here is called Pycharm and user is required to use python and sql to aid him in dumping the data in the database. Once the database is created, coding is done to only select out the pieces of information that are needed. These texts should be where students make comments or ask questions. Next, the data is queried to send these texts to Google Cloud Natural Language API. Here, the program breaks down all the sentences to only be just words. Then the program is going to categorize each word according to whether its connotation is positive, negative or neutral. Next, all the words are sorted according to their connotations. The overall sentiment depends on the emotion that has the highest number. If positives and negatives are all balanced out then the sentiment is neutral. Sentiment scores range from -1 to 1, where -1 is the most negative, 1 is the most positive and anywhere near 0 is neutral.  Positive sentiment scores indicate instructors that students are doing well on their course and neutral sentiment scores indicate that the course is balanced out with difficulties and easy tasks. However, negative sentiment is the most important to instructors since it indicates them that students are struggling and they need to improve the course.

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.

Collaborative MOOC Content Design and Automatic Assessment Based on ODALA Approach

2017 ◽  
Vol 10 (2) ◽  
pp. 19-39 ◽  
Author(s):  
Nacera Hammid ◽  
Lynda Haddadi ◽  
Farida Bouarab-Dahmani
Keyword(s):  
Educational Institutions ◽  
Online Course ◽  
Pedagogical Issues ◽  
Learning Approach ◽  
Automatic Assessment ◽  
Massive Open Online ◽  
Massive Open Online Course ◽  
Automated Evaluation ◽  
E Learning ◽  
Content Design

Since the fall of 2011, the Massive Open Online Course (MOOC) phenomenon is still being qualified as the most attractive and discussed subject by educational communities and public. In the literature, there are many researches about this recent e-learning generation that vary as the goals vary from raising pedagogical issues to economics ones. Several case studies state that MOOCs are challenging the use of technologies to enhance learning; others think that MOOCs can induce to disruptive in education and educational institutions. In this paper, we propose an instructional design for a kind of MOOC platforms where mainly the use of disciplines specifications and automated evaluation of MOOC learners are possible to settle the source of these problems. Our proposition is based on ODALA (Ontology-Driven Auto-evaluation Learning Approach) principles and on the disciplines' knowledge capitalization using a meta-model represented as domain ontology for disciplines modeling inspired by this approach.

sentiment analysis on massive open online course evaluation

2021 ◽  
Author(s):  
Xiaowei Yan ◽  
Guangmin Li ◽  
Qian Li ◽  
Jiejie Chen ◽  
Wenjing Chen ◽  
...  
Keyword(s):  
Sentiment Analysis ◽  
Course Evaluation ◽  
Online Course ◽  
Massive Open Online ◽  
Massive Open Online Course

scholarly journals Empirical evidence from a connectivist Competitive Intelligence Massive Open Online Course (CI cMOOC) proof of concept

2020 ◽  
Vol 9 (3) ◽  
Author(s):  
Gianita Bleojua ◽  
Alexandru Capatinaa ◽  
Valter Vairinhosb ◽  
Rozalia Nistora ◽  
Nicolas Lescac
Keyword(s):  
Learning Community ◽  
Empirical Evidence ◽  
Theory Development ◽  
Competitive Intelligence ◽  
Online Course ◽  
Learning Approach ◽  
Proof Of Concept ◽  
Massive Open Online ◽  
Massive Open Online Course ◽  
Intelligence Approach

This study proposes a competitive intelligence connectivist Massive Open Online Course (CI cMOOC) proof of concept and highlights the interactions among content, context and community to explore relevance in CI cMOOC behavior. The CI cMOOC proof of concept was empirically tested with an online purposive sampling to target a qualified audience of similar and dissimilar information-rich cases, providing evidence about content-context-community competing influence on CI knowledge. The results revealed how the CI learning community perceive the capability of a cMOOC to train foreknowledge practices, given the best match between its content and context. The findings outline that tailored learning approach of the instructor influences the CI learning community’s satisfaction with the content. The study facilitates theory development in addressing the emerging paradigm of an open intelligence approach to cMOOC collective training. Within boundaries of empirical return on experience of qualified respondents, the research framework strengthens trust in supervised interpretive judgment of CI learners confronted with anticipating competitive challenges.

Valor dos massive open online course (MOOC) na educação para a cidadania

2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Hermano Carmo ◽  
Teresa Maia e Carmo
Keyword(s):  
Online Courses ◽  
Massive Open Online Courses ◽  
Online Course ◽  
Massive Open Online ◽  
Massive Open Online Course ◽  
Tecnología Educativa

A sociedade contemporânea é marcada por três macrotendências que a identificam como uma sociedade singular na história humana: processo de mudança acelerada, desigualdade crescente e fibrilhação dos sistemas de poder. Tais tendências têm tido como efeitos um quadro de ameaças e oportunidades que tanto têm constituído gigantesco desafio aos sistemas educativos quanto configuram a urgência de ressocialização de todas as gerações vivas no sentido da construção de uma cidadania global. Nesse contexto, propõe-se um modelo que configura uma estratégia de educação para a cidadania, com dois eixos, quatro vertentes e dez áreas-chave. Seguidamente, descreve-se e discute-se a emergência quase explosiva dos Massive Open Online Courses (MOOC) a partir de instituições de ensino superior internacionalmente reconhecidas, no quadro do novo paradigma digital, sua diversidade e seu potencial ainda em aberto. Confrontando a nova abordagem educativa com o modelo de educação para a cidadania proposto, conclui-se constituir um meio robusto para o potenciar.Palavras-chave:Conjuntura. Macrotendências. Educação para a cidadania. MOOC. Tecnologia educativa. Paradigma digital.Link: http://revista.ibict.br/inclusao/article/view/4171/3642

scholarly journals The Impact of Arabic Part of Speech Tagging on Sentiment Analysis: A New Corpus and Deep Learning Approach

2021 ◽  
Vol 184 ◽  
pp. 148-155
Author(s):  
Abdul Munem Nerabie ◽  
Manar AlKhatib ◽  
Sujith Samuel Mathew ◽  
May El Barachi ◽  
Farhad Oroumchian
Keyword(s):  
Deep Learning ◽  
Sentiment Analysis ◽  
Learning Approach ◽  
Part Of Speech Tagging ◽  
Part Of Speech ◽  
The Impact ◽  
Speech Tagging
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