Real-Time, Real World Learning—Capitalising on Mobile Technology

This chapter explores the adoption of Web 2.0 technologies to promote active learning by students and to both mediate and enhance classroom instruction. Web 2.0 refers to open source, web-enabled applications (apps) that are driven by user-manipulated and user-generated content (Kassens-Noor, 2012). These apps are often rich in user participation, have dynamic content, and harness the collective intelligence of users (Chen, Hwang, & Wang, 2012). As such, these processes create “active, context based, personalised learning experiences” (Kaldoudi, Konstantinidis, & Bamidis, 2010, p. 130) that prioritise learning ahead of teaching. By putting the learner at the centre of the education process educators can provide environments that enhance employability prospects and spark a passion for learning that, hopefully, lasts a lifetime. As such, we critique an active learning approach that makes use of technology such as mobile applications (apps), Twitter, and augmented reality to enhance students’ real world learning. Dunlap and Lowenthal (2009) argue that social media can facilitate active learning as they recreate informal, free-flowing communications that allow students and academics to connect on a more emotional level. Furthermore, their use upskills students in the technical complexities of the digital world and also the specialised discourses that are associated with online participation, suitable for real world learning and working (Fig. 16.1). Three case studies explore the benefits of Web 2.0 processes. The first details the use of Twitter chats to connect students, academics, and industry professionals via online synchronous discussions that offer a number of benefits such as encouraging concise writing from students and maintaining on-going relationships between staff, students, and industry contacts. The second details a location-based mobile app that delivers content to students when they enter a defined geographical boundary linked to an area of a sports precinct. Finally, we explore the use of augmented reality apps to enhance teaching in Human Geography and Urban Studies

Facebook and Informal Learning

This chapter examines the social media tool Facebook through the lens of teaching theory. We reflect in detail on the challenges such social media present to those working in Higher Education, for example the ethical aspects of working with Facebook and the threat such social media might present to deep learning. The chapter begins with a review of the literature surrounding social theory of learning, particularly on the debates around informal learning. There is then a discussion of social media in Higher Education in general and the use of Facebook in particular. Data from the Faculty Facebook page is used to illustrate how this technology stimulates and encourages informal learning. We go on to examine these developments within a critical perspective, in particular exploring the ethical and practical challenges of using commercially controlled software within an HE environment. The concluding section then presents a summary and points to useful areas of future research

Social media for tertiary education

Technology has facilitated the rediscovery of traditional teaching methods by incorporating pedagogically useful features in a multidimensional environment. A by-product of the advancement in technology is social media – a dominant social interaction technology that has a plethora of uses. This chapter first considers the benefits of social media for tertiary education. It then outlines some uses of social media for tertiary education. This is followed by the challenges of social media for tertiary education. Guidelines for social media usage in tertiary education are then outlined. Tertiary education institutions should not lag behind and must progressively consider incorporating social media into teaching and learning activities

Most healthcare interventions tested in Cochrane Reviews are not effective according to high quality evidence: a systematic review and meta-analysis

Objective To estimate the proportion of healthcare interventions tested within Cochrane Reviews that are effective according to high-quality evidence. Study design and setting We selected a random sample of 2428 (35%) of all Cochrane Reviews published between 1 January 2008 and 5 March 2021. We extracted data about interventions within these reviews that were compared with placebo, or no treatment, and whose outcome quality was rated using Grading of Recommendations Assessment, Development and Evaluation (GRADE). We calculated the proportion of interventions whose effectiveness was based on high-quality evidence according to GRADE, had statistically significant positive effects, and were judged as beneficial by the review authors. We also calculated the proportion of interventions that suggested harm. Results Of 1567 eligible interventions, 87 (5.6%) had high quality evidence on first-listed primary outcomes, positive, statistically significant results and were rated by review authors as beneficial. Harms were measured for 577 (36.8%) interventions, 127 of which (8.1%) had statistically significant evidence of harm. Our dependence on the reliability of Cochrane author assessments (including their GRADE assessments) was a potential limitation of our study. Conclusion Most healthcare interventions studied within recent Cochrane Reviews are not supported by high quality evidence, and harms are under-reported.</p

Influence maximization for dynamic allocation in voter dynamics

In this paper, we study the competition between external controllers with fixed campaign budgets in which one of the controllers attempts to maximize the share of a desired opinion in a group of agents who exchange opinions on a social network subject to voting dynamics. In contrast to allocating all the budgets at the beginning of the campaign, we consider a version of a temporal influence maximization problem, where the controller has the flexibility to determine when to start control. We then explore the dependence of optimal starting times to achieve maximum vote shares at a finite time horizon on network heterogeneity. We find that, for short time horizons, maximum influence is achieved by starting relatively later on more heterogeneous networks than in less homogeneous networks, while the opposite holds for long time horizons