e-Learning Recommender System for Teachers using Opinion Mining

“…Other authors have reported successful experience using similar ideas. See for example (Ghauth and Abdullah, 2011;Lee et al, 2012;Dwivedi and Bharadwaj, 2013;Tewari et al, 2015).…”

Section: Recommender Systems and Learning Environmentsmentioning

confidence: 99%

Recommending Exercises in Scratch: An Integrated Approach for Enhancing the Learning of Computer Programming

Cobo

Novoa-Hernández

Puris

et al. 2017

Engineering Education for a Smart Society

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In this chapter we focused on how to improve the learning of computer programming in college students. From the reported success, we relied on Scratch, a visual programming language for enhancing the informal learning. Despite the progress achieved in the past, we have observe some issues regarding the use of Scratch by college students. First, there is a gap between the employed learning approaches since professors are constrained to classroom activities. Second, certain students feel unmotivated because they are confronted with programming exercises that do not fulfill their individual expectations. So, in order to solve this issue we propose an integrated approach consisting of a simple Web Application that includes Scratch as a project editor along with an Recommender System for exercises. The preliminary results demonstrate the positive impact of our proposal.

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“…Mixture of datasets [34,42,43,47,49,53,67,68,85,97,98] In this category, we grouped all those studies which used several datasets to conduct their experiments RQ6. What are the solutions with respect to the packages, tools, frameworks and libraries utilized for sentiment analysis?…”

Section: Rq5 What Are the Most Common Sources Used To Collect Students' Feedback?mentioning

confidence: 99%

Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study

et al. 2021

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In the last decade, sentiment analysis has been widely applied in many domains, including business, social networks and education. Particularly in the education domain, where dealing with and processing students’ opinions is a complicated task due to the nature of the language used by students and the large volume of information, the application of sentiment analysis is growing yet remains challenging. Several literature reviews reveal the state of the application of sentiment analysis in this domain from different perspectives and contexts. However, the body of literature is lacking a review that systematically classifies the research and results of the application of natural language processing (NLP), deep learning (DL), and machine learning (ML) solutions for sentiment analysis in the education domain. In this article, we present the results of a systematic mapping study to structure the published information available. We used a stepwise PRISMA framework to guide the search process and searched for studies conducted between 2015 and 2020 in the electronic research databases of the scientific literature. We identified 92 relevant studies out of 612 that were initially found on the sentiment analysis of students’ feedback in learning platform environments. The mapping results showed that, despite the identified challenges, the field is rapidly growing, especially regarding the application of DL, which is the most recent trend. We identified various aspects that need to be considered in order to contribute to the maturity of research and development in the field. Among these aspects, we highlighted the need of having structured datasets, standardized solutions and increased focus on emotional expression and detection.

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e-Learning Recommender System for Teachers using Opinion Mining

Cited by 9 publications

References 4 publications

Recommender Systems and Scratch: An Integrated Approach for Enhancing Computer Programming Learning

Recommender Systems and Scratch: An Integrated Approach for Enhancing Computer Programming Learning

Recommending Exercises in Scratch: An Integrated Approach for Enhancing the Learning of Computer Programming

Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study

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