1,720,982 research outputs found
Exploring Navigation Styles in a FutureLearn MOOC
Get PDFThis paper presents for the first time a detailed analysis of fine-grained navigation style identification in MOOCs backed by a large number of active learners. The result shows 1) whilst the sequential style is clearly in evidence, the global style is less prominent; 2) the majority of the learners do not belong to either category; 3) navigation styles are not as stable as believed in the literature; and 4) learners can, and do, swap between navigation styles with detrimental effects. The approach is promising, as it provides insight into online learners’ temporal engagement, as well as a tool to identify vulnerable learners, which potentially benefit personalised interventions (from teachers or automatic help) in Intelligent Tutoring Systems (ITS)
A Multidimensional Deep Learner Model of Urgent Instructor Intervention Need in MOOC Forum Posts
Get PDFIn recent years, massive open online courses (MOOCs) have become one of the most exciting innovations in e-learning environments. Thousands of learners around the world enroll on these online platforms to satisfy their learning needs (mostly) free of charge. However, despite the advantages MOOCs offer learners, dropout rates are high. Struggling learners often describe their feelings of confusion and need for help via forum posts. However, the often-huge numbers of posts on forums make it unlikely that instructors can respond to all learners and many of these urgent posts are overlooked or discarded. To overcome this, mining raw data for learners’ posts may provide a helpful way of classifying posts where learners require urgent intervention from instructors, to help learners and reduce the current high dropout rates. In this paper we propose, a method based on correlations of different dimensions of learners’ posts to determine the need for urgent intervention. Our initial statistical analysis found some interesting significant correlations between posts expressing sentiment, confusion, opinion, questions, and answers and the need for urgent intervention. Thus, we have developed a multidimensional deep learner model combining these features with natural language processing (NLP). To illustrate our method, we used a benchmark dataset of 29598 posts, from three different academic subject areas. The findings highlight that the combined, multi-dimensional features model is more effective than the text-only (NLP) analysis, showing that future models need to be optimised based on all these dimensions, when classifying urgent posts
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Educators' Validation on a Reflective Writing Framework (RWF) for Assessing Reflective Writing in Computer Science Education
Get PDFThe need for effective Intelligent Tutoring Systems (ITSs) and automated assessment is increasing. One area of ITSs has become urgent is that of the automated assessment of reflective writing. The reflective writing has been promoted, in higher education, in order to encourage students to think critically about their learning. However, many frameworks have been developed for assessing student's reflective writing. Up to our knowledge, there is no empirical studies to validate reflective writing frameworks that used in Computer Science (CS) education. This paper presents the validation of reflective Writing Framework (RWF) by CS educators. The expert panelists validated the RWF. Subsequently, we proposed an ITS model for automating reflective writing analysis. The RWF was accepted that it received a level of consensus from the experts who reported obtaining from good to appropriate results using it
Machine Learning for Everyone
No full textThis course introduces Machine Learning to everyone. Machine learning is a subset of Artificial Intelligence (AI) that enables computer systems to learn and improve from experience without being explicitly programmed. It is done by developing computer programs that can access data and use it to learn for themselves. With the appropriate machine learning models, organisations can use these systems to continually observe changes in their business to predict what may be coming next. In this micro course, you will learn about machine learning, its techniques, and why it is important for all of us. This micro course presents machine learning concepts and techniques and the relation of machine learning to our everyday life in a way that anyone can understand. This course skips confusing academic jargon and offers clear explanations that require only basic mathematics. The online interactive version of the course is at https://colcommons.org
Validating the Reflective Writing Framework (RWF) for Assessing Reflective Writing in Computer Science Education Through Manual Annotation
Get PDFThe accuracy of a framework for annotating reflective writing can be increased through the evaluation and revision of the annotation scheme to ensure the reliability and validity of the framework. To our knowledge, there is a lack of literature related to the accuracy of any reflective writing framework in Computer Science (CS) education. This paper describes a manual annotation scheme, applied during four pilot studies, to validate the authors’ novel Reflective Writing Framework (RWF) for CS education. The results show, through the pilot studies, that the accuracy of Inter-Rater Reliability (IRR) increases from 0.5 to 0.8, which was substantial and close to an almost perfect agreement. This paper contributes to CS education through the reliability and validity of the RWF that can be potentially used for generating an Intelligent Tutoring Systems (ITS) using machine learning algorithms
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Data-Driven Analysis of Engagement in Gamified Learning Environments: A Methodology for Real-Time Measurement of MOOCs
Get PDFWelfare and economic development is directly dependent on the availability of highly skilled and educated individuals in society. In the UK, higher education is accessed by a large percentage of high school graduates (50% in 2017). Still, in Brazil, a limited number of pupils leaving high schools continue their education (up to 20%). Initial pioneering efforts of universities and companies to support pupils from underprivileged backgrounds, to be able to succeed in being accepted by universities include personalised learning solutions. However, initial findings show that typical distance learning problems occur with the pupil population: isolation, demotivation, and lack of engagement. Thus, researchers and companies proposed gamification. However, gamification design is traditionally exclusively based on theory-driven approaches and usually ignore the data itself. This paper takes a different approach, presenting a large-scale study that analysed, statistically and via machine learning (deep and shallow), the first batch of students trained with a Brazilian gamified intelligent learning software (called CamaleOn), to establish, via a grassroots method based on learning analytics, how gamification elements impact on student engagement. The exercise results in a novel proposal for real-time measurement on Massive Open Online Courses (MOOCs), potentially leading to iterative improvements of student support. It also specifically analyses the engagement patterns of an underserved community
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