Shirley Williams

What do people study when they study Twitter? Classifying Twitter related academic papers

Purpose – Since its introduction in 2006, messages posted to the microblogging system Twitter have provided a rich dataset for researchers, leading to the publication of over a thousand academic papers. This paper aims to identify this published work and to classify it in order to understand Twitter based research.Design/methodology/approach – Firstly the papers on Twitter were identified. Secondly, following a review of the literature, a classification of the dimensions of microblogging research was established. Thirdly, papers were qualitatively classified using open coded content analysis, based on the papers title and abstract, in order to analyze method, subject, and approach.Findings – The majority of published work relating to Twitter concentrates on aspects of the messages sent and details of the users. A variety of methodological approaches is used across a range of identified domains.Research limitations/implications – This work reviewed the abstracts of all papers available via database search...

Massive Open Online Courses on Health and Medicine: Review

Background Massive open online courses (MOOCs) have become immensely popular in a short span of time. However, there is very little research exploring MOOCs in the discipline of health and medicine. Objective We aim to provide a review of MOOCs related to health and medicine offered by various MOOC platforms in 2013, by analyzing and comparing the various offerings, their target audience, typical length of course, and credentials offered. We also discuss opportunities and challenges presented by MOOCs in health and medicine. Methods Health and medicine–related MOOCs were gathered using several methods to ensure the richness and completeness of data. Identified MOOC platform websites were used to gather the lists of offerings. In parallel, these MOOC platforms were contacted to access official data on their offerings. Two MOOC aggregator sites (Class Central and MOOC List) were also consulted to gather data on MOOC offerings. Eligibility criteria were defined to concentrate on the courses that were offered in 2013 and primarily on the subject of health and medicine. All language translations in this paper were done using Google Translate. Results The search identified 225 courses, of which 98 were eligible for the review. Over half (58%, 57/98) of the MOOCs considered were offered on the Coursera platform, and 94% (92/98) of all the MOOCs were offered in English. Universities offered 90 MOOCs, and the John Hopkins University offered the largest number of MOOCs (12/90). Only three MOOCs were offered by developing countries (China, West Indies, and Saudi Arabia). The duration of MOOCs varied from 3-20 weeks with an average length of 6.7 weeks. On average, MOOCs expected a participant to work on the material for 4.2 hours a week. Verified certificates were offered by 14 MOOCs, while three others offered other professional recognition. Conclusions The review presents evidence to suggest that MOOCs can be used as a way to provide continuous medical education. It also shows the potential of MOOCs as a means of increasing health literacy among the public.

Elderly Learners and Massive Open Online Courses: A Review

Background Massive open online courses (MOOCs) have become commonplace in the e-learning landscape. Thousands of elderly learners are participating in courses offered by various institutions on a multitude of platforms in many different languages. However, there is very little research into understanding elderly learners in MOOCs. Objective We aim to show that a considerable proportion of elderly learners are participating in MOOCs and that there is a lack of research in this area. We hope this assertion of the wide gap in research on elderly learners in MOOCs will pave the way for more research in this area. Methods Pre-course survey data for 10 University of Reading courses on the FutureLearn platform were analyzed to show the level of participation of elderly learners in MOOCs. Two MOOC aggregator sites (Class Central and MOOC List) were consulted to gather data on MOOC offerings that include topics relating to aging. In parallel, a selected set of MOOC platform catalogues, along with a recently published review on health and medicine-related MOOCs, were searched to find courses relating to aging. A systematic literature search was then employed to identify research articles on elderly learners in MOOCs. Results The 10 courses reviewed had a considerable proportion of elderly learners participating in them. For the over-66 age group, this varied from 0.5% (on the course “Managing people”) to 16.3% (on the course “Our changing climate”), while for the over-56 age group it ranged from 3.0% (on “A beginners guide to writing in English”) to 39.5% (on “Heart health”). Only six MOOCs were found to include topics related to aging: three were on the Coursera platform, two on the FutureLearn platform, and one on the Open2Study platform. Just three scholarly articles relating to MOOCs and elderly learners were retrieved from the literature search. Conclusions This review presents evidence to suggest that elderly learners are already participating in MOOCs. Despite this, there has been very little research into their engagement with MOOCs. Similarly, there has been little research into exploiting the scope of MOOCs for delivering topics that would be of interest to elderly learners. We believe there is potential to use MOOCs as a way of tackling the issue of loneliness among older adults by engaging them as either resource personnel or learners.

Knowledge Construction in E-Learning: Designing an E-Learning Environment

In the traditional classroom, students learned to depend on tutors for their motivation, direction, goal setting, progress monitoring, self-assessment, and achievement. A fundamental limitation is that students have little opportunity to conduct and manage their learning activities which are important for knowledge construction. e-Learning approaches and applications which are supported by pervasive technologies, have brought in great benefits to the whole society, meanwhile it also has raised many challenging questions. One of the issues that researchers and educators are fully aware is that technologies cannot drive a courseware design for e-Learning. An effective and quality learning requires an employment of appropriate learning theory and paradigms, organisation of contents, as well as methods and techniques of delivery. This paper will introduce our research work in design an e-Learning environment with emphases on instructional design of courseware for e-learning.

How Twitter Is Studied in the Medical Professions: A Classification of Twitter Papers Indexed in PubMed

Background Since their inception, Twitter and related microblogging systems have provided a rich source of information for researchers and have attracted interest in their affordances and use. Since 2009 PubMed has included 123 journal articles on medicine and Twitter, but no overview exists as to how the field uses Twitter in research. Objective This paper aims to identify published work relating to Twitter within the fields indexed by PubMed, and then to classify it. This classification will provide a framework in which future researchers will be able to position their work, and to provide an understanding of the current reach of research using Twitter in medical disciplines. Methods Papers on Twitter and related topics were identified and reviewed. The papers were then qualitatively classified based on the paper’s title and abstract to determine their focus. The work that was Twitter focused was studied in detail to determine what data, if any, it was based on, and from this a categorization of the data set size used in the studies was developed. Using open coded content analysis additional important categories were also identified, relating to the primary methodology, domain, and aspect. Results As of 2012, PubMed comprises more than 21 million citations from biomedical literature, and from these a corpus of 134 potentially Twitter related papers were identified, eleven of which were subsequently found not to be relevant. There were no papers prior to 2009 relating to microblogging, a term first used in 2006. Of the remaining 123 papers which mentioned Twitter, thirty were focused on Twitter (the others referring to it tangentially). The early Twitter focused papers introduced the topic and highlighted the potential, not carrying out any form of data analysis. The majority of published papers used analytic techniques to sort through thousands, if not millions, of individual tweets, often depending on automated tools to do so. Our analysis demonstrates that researchers are starting to use knowledge discovery methods and data mining techniques to understand vast quantities of tweets: the study of Twitter is becoming quantitative research. Conclusions This work is to the best of our knowledge the first overview study of medical related research based on Twitter and related microblogging. We have used 5 dimensions to categorize published medical related research on Twitter. This classification provides a framework within which researchers studying development and use of Twitter within medical related research, and those undertaking comparative studies of research, relating to Twitter in the area of medicine and beyond, can position and ground their work.

Articulation of Learners Requirements for Personalised Instructional Design in e-Learning Services

As e-Learning environments evolve, learners have become increasingly demanding on personalised learning which allows them to build their own knowledge pathway. This significant change in learning requirements imposes a new learning paradigm which ensures one-to-one learning with flexible mode of content configuration, and adaptive delivery and assessment. Although in the past years, Learning Management Systems (LMS) providers have upgraded system functionality to support instructional design for e-learning package, incorporating individual learners’ personal learning requirements in content design still remains challenging. To involve learners in the content design requires identification of their personal learning requirements. This paper presents a method for articulating individual learners’ learning requirements (e.g., learning styles, and prior knowledge), and representing them in a set of computable parameters in Learner’s Profile. These parameters will then be mapped onto instructional design strategies which determine a selection of suitable learning content and sequencing of content with adequate instruction in a learning package.

IMPROVED PROGRAM PERFORMANCE USING A CLUSTER OF WORKSTATIONS

Computers linked via a network can be used together to provide a powerful computing resource. Spreading the work of computationally intensive calculations across a cluster of computers considerably reduces the elapsed execution time compared to that achieved on a single workstation. Overall performance is limited by the slowest machine in the cluster. Here we investigate mechanisms by which the effects of slow machines can be ameliorated.

Design for a Learner-Oriented Tracking

Learning Management Systems (LMS) in e-learning have functionality for monitoring learning activities. The statistics generated from learning performances can be processed for tutors and a group of learners to improve their quality of teaching and learning. However the current LMS are not designed to facilitate personalised learning support for an individual learner, e.g. adaptive delivery, constructive feedback on assessment and real-time learning activities monitoring. This paper presents a learner-oriented tracking approach for one-to-one support. Technical components of this approach can be embedded in the LMS to effectively facilitate learning experience of the individual learner and quality of learning content design. A learner-oriented tracking model relies on the information from a Learner’s Profile and educational requirements. This determines initially suitable learning content (learning objects) and delivery methods and also provides monitoring information about learners’ experiences.

Ontology supported competency system

Traditionally, representation of competencies has been very difficult using computer-based techniques. This paper introduces competencies, how they are represented, and the related concept of competency frameworks and the difficulties in using traditional ontology techniques to formalise them. A ‘vaguely’ formalised framework has been developed within the EU project TRACE and is presented. The framework can be used to represent different competencies and competency frameworks. Through a case study using an example from the IT sector, it is shown how these can be used by individuals and organisations to specify their individual competency needs. Furthermore, it is described how these representations are used for comparisons between different specifications applying ontologies and ontology toolsets. The end result is a comparison that is not binary, but tertiary, providing ‘definite matches’, possible/partial matches, and ‘no matches’ using a ‘traffic light’ analogy.

A design for generating personalised feedback in knowledge construction

As the learning paradigm shifts to a more personalised learning process, users need dynamic feedback from their knowledge path. Learning Management Systems (LMS) offer customised feedback dependent on questions and the answers given. However these LMSs are not designed to generate personalised feedback for an individual learner, tutor and instructional designer. This paper presents an approach for generating constructive feedback for all stakeholders during a personalised learning process. The dynamic personalised feedback model generates feedback based on the learning objectives for the Learning Object. Feedback can be generated at Learning Object level and the Information Object level for both the individual learner and the group. The group feedback is meant for the tutors and instructional designer to improve the learning process.