What does physiological synchrony reveal about metacognitive experiences and group performance?

There is a growing body of research on physiological synchrony (PS) in Collaborative Problem Solving (CPS). However, the current literature presents inconclusive findings about the way in which PS is reflected in cognitive and affective group processes and performance. In light of this, this study investigates the relationship between PS and metacognitive experiences (ie, judgement of confidence, task interest, task difficulty, mental effort and emotional valence) that are manifested during CPS. In addition, the study explores the association between PS and group performance. The participants were 77 university students who worked together on a computer-based CPS simulation in groups of three. Participants’ electrodermal activity (EDA) was recorded as they worked on the simulation and metacognitive experiences were measured with situated self-reports. A Multidimensional Recurrence Quantification Analysis was used to calculate the PS among the collaborators. The results show a positive relationship between continuous PS episodes and groups’ collective mental effort. No relationship was found between PS and judgement of confidence, task interest, task difficulty or emotional valence. The relationship between PS and group performance was also non-significant. The current work addresses several challenges in utilising multimodal data analytics in CPS research and discusses future research directions.     

Does competency-based education with blockchain signal a new mission for universities?

New technologies and the knowledge economy are destabilising graduate professions, with artificial intelligence and the analysis of ‘big data’ making significant impacts on formerly secure jobs. Blockchain technology, offering automated secure credentialling of undergraduate students’ activities and achievements, may significantly erode existing systems of assessment. The challenge for universities will be not only to maintain the relevance of their curricula but also to manage erosion of their current near-monopoly in awarding degrees. This paper envisions a landscape in which universities must outsource parts of their course delivery and assessment in order to remain competitive. It examines a potentially sustainable mission strategy: to move away from narrow academic disciplines towards an authentic learning curriculum focusing on the development of students as whole persons with rounded educations. This paper examines implications for the academy of the convergence of artificial intelligence, data analytics and blockchain technology.     

Digital analytics in professional work and learning

In a wide range of fields, professional practice is being transformed by the increasing influence of digital analytics: the massive volumes of big data, and software algorithms that are collecting, comparing and calculating that data to make predictions and even decisions. Researchers in a number of social sciences have been calling attention to the far-reaching and accelerating consequences of these forces, claiming that many professionals, researchers, policy-makers and the public are just beginning to realise the enormous potentials and challenges these analytics are producing. Yet, outside of particular areas of research and practice, such as learning analytics, there has been little discussion of this to date in the broader education literature. This article aims to set out some key issues particularly relevant to the understandings of professional practice, knowledge and learning posed by the linkages of big data and software code. It begins by outlining definitions, forms and examples of these analytics, their potentialities and some of the hidden impact, and then presents issues for researchers and educators. It seeks to contribute to and extend debates taking place in certain quarters to a broader professional education and work audience.     

Learning dashboards at scale: early warning and overall first year experience

Abstract

In this study, we present a case study involving two self-service dashboards providing feedback on learning and study skills and on academic achievement. These dashboards were offered to first-year university students in several study programmes in Flanders, Belgium. Data for this study were collected using usage tracking (N?=?2875) and a survey taken at the beginning of the second year before (N?=?484) and after (N?=?538) the introduction of the dashboards. We found that early dashboard usage is related to academic achievement later in the academic year and that students’ review of the feedback received in the first year improved. Although these results are modest in comparison to how high the bar is sometimes set for learning analytics applications, we argue that low-cost deployments of self-service dashboards are an interesting approach to start building experience with similar tools and to start paving the way for future developments.     

Implementing randomised control trials in open and distance learning: a feasibility study

Randomised control trials (RCTs) are an evidence-based research approach which has not yet been adopted and widely used in open and distance education to inform educational policy and practice. Despite the challenges entailed in their application, RCTs hold the power to robustly evaluate the effects of educational interventions in distance learning and conclude on whether (or not) these interventions should be adopted and used extensively. The aim of this paper is to spark discussions around the use of RCTs in distance learning by illustrating their benefits and drawbacks including challenges in adopting RCTs in education. To achieve this aim, a RCT was implemented to examine whether a small-scale intervention in four language modules could improve attendance at an end-of-module speaking assessment, and in consequence, performance, completion and pass rates. Results raise the need for further research in order to identify what type of interventions should be designed and put into practice to elicit a positive impact on learners. The paper concludes with a discussion on why RCTs should be brought to the forefront as a viable method for the effective evaluation of the impact of open learning analytic interventions.     

Exploring the relationship between clout and cognitive processing in MOOC discussion forums

The purpose of this study was to explore the relationship between clout and cognitive processing in massive open online course (MOOC) discussion forum posts. Cognitive processing, a category variable generated by the automated text analysis tool, Linguistic Inquiry Word Count (LIWC), is made up of six sub-scores (insight, causation, discrepancy, tentativeness, certainty and differentiation). Clout is a nontransparent summary variable in LIWC that can be used to understand the level of confidence conveyed in the text. Because clout is nontransparent, we do not know the algorithm used to calculate its value. To better understand this variable, this study examined cognitive processing alongside clout. In this study, a series of linear mixed models were fitted to evaluate, after controlling for gender, degree and type of post, if the focal relationship between each sub-score of cognitive processing as the predictor variables and clout as the dependent variable changed across courses with different pacing (self-paced or instructor-paced). Next, the focal relationship between each predictor and clout was examined with or without regard to pacing. Findings showed words classified as showing discrepancy, certainty or differentiation were negatively associated with clout scores.     

Big data analytics in health sector: Theoretical framework,techniques and prospects

Clinicians, healthcare providers-suppliers, policy makers and patients are experiencing exciting opportunities in light of new information deriving from the analysis of big data sets, a capability that has emerged in the last decades. Due to the rapid increase of publications in the healthcare industry, we have conducted a structured review regarding healthcare big data analytics. With reference to the resource-based view theory we focus on how big data resources are utilised to create organization values/capabilities, and through content analysis of the selected publications we discuss: the classification of big data types related to healthcare, the associate analysis techniques, the created value for stakeholders, the platforms and tools for handling big health data and future aspects in the field. We present a number of pragmatic examples to show how the advances in healthcare were made possible. We believe that the findings of this review are stimulating and provide valuable information to practitioners, policy makers and researchers while presenting them with certain paths for future research.     

Theory building with big data-driven research – Moving away from the “What” towards the “Why”

Data availability and access to various platforms, is changing the nature of Information Systems (IS) studies. Such studies often use large datasets, which may incorporate structured and unstructured data, from various platforms. The questions that such papers address, in turn, may attempt to use methods from computational science like sentiment mining, text mining, network science and image analytics to derive insights. However, there is often a weak theoretical contribution in many of these studies. We point out the need for such studies to contribute back to the IS discipline, whereby findings can explain more about the phenomenon surrounding the interaction of people with technology artefacts and the ecosystem within which these contextual usage is situated. Our opinion paper attempts to address this gap and provide insights on the methodological adaptations required in “big data studies” to be converted into “IS research” and contribute to theory building in information systems.     

Beyond Description: Converting Web Site Usage Statistics into Concrete Site Improvement Ideas

Web site usage statistics are a widely used tool for Web site development, but libraries are still learning how to use them successfully. This case study summarizes how Morris Library at Southern Illinois University Carbondale implemented Google Analytics on its Web site and used the reports to inform a site redesign. As the main campus library at a research university with about 20,000 undergraduate and graduate students, the library included resources from multiple library departments on a single site. In planning the redesign, Morris Library's Virtual Library Group combined usage reports with information from other sources, such as usability tests and user comments. The Virtual Library Group faced barriers to interpreting and applying the usage statistics in the site redesign, including some that were specific to the library's implementation of the Google Analytics tool and some limitations inherent with Web usage statistics in general. Some key barriers in applying the usage statistics to a redesign included sifting through data that did not have implications for the site redesign, interpreting the implications of usage numbers for the site redesign, and balancing competing interests within the library. Nevertheless, the usage statistics enabled the Virtual Library Group to make better decisions by providing a source of factual information about the site's use rather than relying on staff members’ opinions and conjectures.     

Using Piwik Instead of Google Analytics at the Cornell University Library

Like many other libraries, Cornell University Library uses Google Analytics (GA) to track website usage. GA, designed to support Google’s primary revenue stream, advertising, has many strengths, including cost (free). Given our tradition in libraries to protect reader privacy, a compelling argument can be made that Google Analytics is inappropriate for libraries. After a review of alternatives to GA following Edward Snowden's revelations, we selected Piwik (piwik.org) as a replacement for GA. Piwik is a free, open source, and most importantly, supports local data collection. We summarize what some of the library literature says about web analytics tools, explain why we selected Piwik, and describe what is involved when migrating from GA to Piwik.