Urgency Analysis of Learners’ Comments: An Automated Intervention Priority Model for MOOC

Recently, the growing number of learners in Massive Open Online Course (MOOC) environments generate a vast amount of online comments via social interactions, general discussions, expressing feelings or asking for help. Concomitantly, learner dropout, at any time during MOOC courses, is very high, whilst the number of learners completing (completers) is low. Urgent intervention and attention may alleviate this problem. Analysing and mining learner comments is a fundamental step towards understanding their need for intervention from instructors. Here, we explore a dataset from a FutureLearn MOOC course. We find that (1) learners who write many comments that need urgent intervention tend to write many comments, in general. (2) The motivation to access more steps (i.e., learning resources) is higher in learners without many comments needing intervention, than that of learners needing intervention. (3) Learners who have many comments that need intervention are less likely to complete the course (13%). Therefore, we propose a new priority model for the urgency of intervention built on learner histories – past urgency, sentiment analysis and step access

Analytics of student behaviour in a learning management system as a predictor of learning success

Higher Education (HE) teachers are awarethat the evolution of technology changed the waystudents build their knowledge. New forms of access toinformation and new means of communication allowedcreating specialized learning tools. It is now importantto understand how the students' interaction withlearning technologies influences their learning success.For that purpose, data referring to the use of a learningmanagement system (LMS) supporting a specific coursewas collected and analyzed. Results indicate that aminor correlation exists between the effective use ofthose tools and student success

Evaluating topic-word review analysis for understanding student peer review performance

© 2013 International Educational Data Mining Society. All rights reserved. Topic modeling is widely used for content analysis of textual documents. While the mined topic terms are considered as a semantic abstraction of the original text, few people evaluate the accuracy of humans’ interpretation of them in the context of an application based on the topic terms. Previously, we proposed RevExplore, an interactive peer-review analytic tool that supports teachers in making sense of large volumes of student peer reviews. To better evaluate the functionality of RevExplore, in this paper we take a closer look at its Natural Language Processing component which automatically compares two groups of reviews at the topic-word level. We employ a user study to evaluate our topic extraction method, as well as the topic-word analysis approach in the context of educational peer-review analysis. Our results show that the proposed method is better than a baseline in terms of capturing student reviewing/writing performance. While users generally identify student writing/reviewing performance correctly, participants who have prior teaching or peer-review experience tend to have better performance on our review exploration tasks, as well as higher satisfaction towards the proposed review analysis approach

Discovering Design Principles for Persuasive Systems: A Grounded Theory and Text Mining Approach

Persuasive systems aim to change users\u27 behavior and lifestyle. These systems have been gaining popularity with the proliferation of wearable devices and recent advances in information technology. In that regard, recent research aims at identifying system design principles that are specific to persuasive systems. In this article we extend the existing literature by discovering design principles for persuasive systems from a systematic analysis of users feedback from the actual use of persuasive systems. Specifically, we use grounded theory and text mining (topic modeling) to extract design concepts from online user reviews of mobile diabetes applications. Overall, the results extend existing findings by highlighting the necessity of going beyond the techno-centric approach used in current practice and incorporating the social and structural features into persuasive system design

Using Data Mining for Predicting Relationships between Online Question Theme and Final Grade

As higher education diversifies its delivery modes, our ability to use the predictive and analytical power of educational data mining (EDM) to understand students\u27 learning experiences is a critical step forward. The adoption of EDM by higher education as an analytical and decision making tool is offering new opportunities to exploit the untapped data generated by various student information systems (SIS) and learning management systems (LMS). This paper describes a hybrid approach which uses EDM and regression analysis to analyse live video streaming (LVS) students\u27 online learning behaviours and their performance in their courses. Students\u27 participation and login frequency, as well as the number of chat messages and questions that they submit to their instructors, were analysed, along with students\u27 final grades. Results of the study show a considerable variability in students\u27 questions and chat messages. Unlike previous studies, this study suggests no correlation between students\u27 number of questions/chat messages/login times and students\u27 success. However, our case study reveals that combining EDM with traditional statistical analysis provides a strong and coherent analytical framework capable of enabling a deeper and richer understanding of students\u27 learning behaviours and experiences

Compatibility between Text Mining and Qualitative Research in the Perspectives of Grounded Theory, Content Analysis, and Reliability

The objective of this article is to illustrate that text mining and qualitative research are epistemologically compatible. First, like many qualitative research approaches, such as grounded theory, text mining encourages open-mindedness and discourages preconceptions. Contrary to the popular belief that text mining is a linear and fully automated procedure, the text miner might add, delete, and revise the initial categories in an iterative fashion. Second, text mining is similar to content analysis, which also aims to extract common themes and threads by counting words. Although both of them utilize computer algorithms, text mining is characterized by its capability of processing natural languages. Last, the criteria of sound text mining adhere to those in qualitative research in terms of consistency and replicability

Estudo de análise qualitativa em fórum de discussão

Este trabalho trata sobre uma proposta para a realização de uma análise das contribuições textuais registradas por alunos em um fórum de discussão. A abordagem desta proposta envolve mineração de textos utilizando grafos. O presente artigoapresenta alguns experimentos realizados em fóruns de discussão e os resultados que podem ser utilizados pelo professor para realizar uma análise qualitativa dascontribuições dos alunos

Discovering design principles for persuasive systems: A grounded theory and text mining approach

Persuasive systems aim to change users\u27 behavior and lifestyle. These systems have been gaining popularity with the proliferation of wearable devices and recent advances in information technology. In that regard, recent research aims at identifying system design principles that are specific to persuasive systems. In this article we extend the existing literature by discovering design principles for persuasive systems from a systematic analysis of users feedback from the actual use of persuasive systems. Specifically, we use grounded theory and text mining (topic modeling) to extract design concepts from online user reviews of mobile diabetes applications. Overall, the results extend existing findings by highlighting the necessity of going beyond the techno-centric approach used in current practice and incorporating the social and structural features into persuasive system design

Análise temática das mensagens de discussões online

Este artigo apresenta um estudo para investigar a relevância temática das contribuições textuais redigidas em fóruns de discussão. Foram realizadas experiências para analisar as mensagens postadas pelos alunos. O artigo apresenta os resultados provenientes do trabalho realizado