Structure and content of messages in an online environment: An approach from participation

Chávez, Jorge; Montaño, Rosa; Barrera, Rosa

doi:10.1016/j.chb.2015.08.046

Cited by 13 publications

(14 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We find that relatively lengthy messages deliver more cognitive value and are far more important to the larger audience of the community -be it a hacker forum or an CQA such as StackOverflow [10] [52] [53]. Word counts and message lengths increase significantly across all types of information levels with rising depth of the messages in an online learning platform [39]. Studies also confirm that users in traditional OSNs such as Facebook experience more views and replies for longer messages [40].…”

Section: Expertise Based On Text-mining Featuresmentioning

confidence: 56%

"Leadership in Action: How Top Hackers Behave" A Big-Data Approach with Text-Mining and Sentiment Analysis

Biswas

Mukhopadhyay

Gupta

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

View full text Add to dashboard Cite

show abstract

Section: Expertise Based On Text-mining Featuresmentioning

confidence: 56%

"Leadership in Action: How Top Hackers Behave" A Big-Data Approach with Text-Mining and Sentiment Analysis

Biswas

Mukhopadhyay

Gupta

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

View full text Add to dashboard Cite

show abstract

“…According to several analysis schemes provided by De Wever et al [29], there is a wide variety of work related to content analysis of forum posts. The majority explore the effectiveness of online forums as platforms for innovating the educational practices of teachers [30], facilitating the teaching process [31], and providing indicators of student learning which can assist in student assessment [32]- [34]. This information provides teachers and forum administrators with an indication as to the development of critical thinking skills and whether learning has taken place.…”

Section: A Related Work On Discussion Forum Analysismentioning

confidence: 99%

A Review of the Analytics Techniques for an Efficient Management of Online Forums: An Architecture Proposal

et al. 2019

View full text Add to dashboard Cite

E-learning is a response to the new educational needs of society and an important development in information and communication technologies because it represents the future of the teaching and learning processes. However, this trend presents many challenges, such as the processing of online forums which generate a huge number of messages with an unordered structure and a great variety of topics. These forums provide an excellent platform for learning and connecting students of a subject but the difficulty of following and searching the vast volume of information that they generate may be counterproductive. The main goal of this paper is to review the approaches and techniques related to online courses in order to present a set of learning analytics techniques and a general architecture that solve the main challenges found in the state of the art by managing them in a more efficient way: 1) efficient tracking and monitoring of forums generated; 2) design of effective search mechanisms for questions and answers in the forums; and 3) extraction of relevant key performance indicators with the objective of carrying out an efficient management of online forums. In our proposal, natural language processing, clustering, information retrieval, question answering, and data mining techniques will be used. INDEX TERMSOnline forums, natural language processing, analytics techniques, KPIs, data mining.

show abstract

“…Given the positive role of OLIC, some studies have analysed OLIC. To present potential influences, Chávez et al (2016) categorized OLIC into four dimensionslearning task messages, social messages, regulatory messages and other messagesto investigate the relationship between information level and message depth. To determine the role of knowledge construction, OLIC is also categorized into different dimensions to measure the cognitive quality of participants and determine the relationship between an individual's hierarchical positions and communication type (Naranjo et al, 2012;Rehm et al, 2016).…”

Section: Online Learning Interaction Contentmentioning

confidence: 99%

Automatic evaluation of online learning interaction content using domain concepts

Palmer

et al. 2020

View full text Add to dashboard Cite

Purpose Interaction content is created during online learning interaction for the exchanged information to convey experience and share knowledge. Prior studies have mainly focused on the quantity of online learning interaction content (OLIC) from the perspective of types or frequency, resulting in a limited analysis of the quality of OLIC. Domain concepts as the highest form of interaction are shown as entities or things that are particularly relevant to the educational domain of an online course. The purpose of this paper is to explore a new method to evaluate the quality of OLIC using domain concepts. Design/methodology/approach This paper proposes a novel approach to automatically evaluate the quality of OLIC regarding relevance, completeness and usefulness. A sample of OLIC corpus is classified and evaluated based on domain concepts and textual features. Findings Experimental results show that random forest classifiers not only outperform logistic regression and support vector machines but also their performance is improved by considering the quality dimensions of relevance and completeness. In addition, domain concepts contribute to improving the performance of evaluating OLIC. Research limitations/implications This paper adopts a limited sample to train the classification models. It has great benefits in monitoring students’ knowledge performance, supporting teachers’ decision-making and even enhancing the efficiency of school management. Originality/value This study extends the research of domain concepts in quality evaluation, especially in the online learning domain. It also has great potential for other domains.

show abstract

Structure and content of messages in an online environment: An approach from participation

Cited by 13 publications

References 39 publications

"Leadership in Action: How Top Hackers Behave" A Big-Data Approach with Text-Mining and Sentiment Analysis

"Leadership in Action: How Top Hackers Behave" A Big-Data Approach with Text-Mining and Sentiment Analysis

A Review of the Analytics Techniques for an Efficient Management of Online Forums: An Architecture Proposal

Automatic evaluation of online learning interaction content using domain concepts

Contact Info

Product

Resources

About