Andrew Brasher

Comparing universities and courses is of interest to a variety of stakeholders including potential students, policy makers, news and media organisations, ranking providers, and universities themselves. There are a range of existing university ranking schemes that provide comparisons (e.g. Academic Ranking of World Universities) but typically these are designed with face‐to‐face teaching and learning in mind. There is also a growing number of quality assurance tools and approaches aimed at ensuring the quality of online education This article reports on an analysis of a range of quality assurance systems for online higher education institutions and courses, together with variety of ranking systems targeting conventional universities—with the aim of establishing what they measure, and the metrics used to assess quality. The findings from this analytical study were compared with a meta‐analysis of the literature about how students choose their university in order to understand how these instruments influence current student opinion and can be used more proactively by universities themselves. The findings reveal: (1) current ranking systems are of limited value for most potential undergraduate students, particularly with reference to online education, (2) comparison systems that can be of value to students from a variety of different backgrounds are likely to be complex to set up and run, and (3) quality indicators that promote both formative and summative evaluation may be beneficial to both institutions and students.

Learning analytics involve the measurement, collection, analysis, and reporting of data about learners and their contexts, in order to understand and optimise learning and the environments in which it occurs. Since emerging as a distinct field in 2011, learning analytics has grown rapidly, and early adopters around the world are already developing and deploying these new tools. This paper reports on a study that investigated how the field is likely to develop by 2025, in order to make recommendations for action to those concerned with the implementation of learning analytics. The study used a Policy Delphi approach, presenting a range of future scenarios to international experts in the field and asking for responses related to the desirability and feasibility of these scenarios, as well as actions that would be required. Responses were received from 103 people from 21 countries. Responses were coded thematically, inter-rater reliability was checked using Cohen’s kappa coefficient, and data were recoded if kappa was below 0.6. The seven major themes that were identified within the data were power, pedagogy, validity, regulation, complexity, ethics, and affect. The paper considers in detail each of these themes and its implications for the implementation of learning analytics.

University ranking systems are being implemented with the aim of assessing and comparing higher education institutions at a global level. Despite their being increasingly used, rankings are often strongly criticized for their social and economic implications, as well as for limitations in their technical implementation. One of these limitations is that they do not consider the specific characteristics of online education. This study used a participatory approach to define a set of criteria and indicators suitable to reflect the specific nature of distance education. This endeavour will help evaluate and rank online higher education institutions more appropriately than in current practice, where indicators are devised for traditional universities. To this end, several stakeholders and informants were involved in a Delphi study in an attempt to reach the broader higher education institutions (HEI) community. According to the study participants, apart from students’ achievements and general quantitative measures of HEI performance, which are quite common in traditional ranking systems, teaching and student learning experience turned out to be the most important criteria. Student support, teacher support, technological infrastructure, research and organization were deemed middle ground criteria, while sustainability and reputation were regarded as the least important criteria.

The challenge of supporting immigrant language-learning and social integration has increased recently, leading to initiatives and projects that aim to provide assistance, including using smartphones in the course of daily activities. However, most of the Mobile Assisted Language Learning (MALL) literature focuses on classroom based learning thereby leaving a gap in understanding the learning in informal settings. This paper discusses a UK field trial of the European funded MASELTOV project, which developed a suite of smartphone tools and services (the ‘MApp’) to help immigrants’ language learning and social inclusion in four European cities. MApp tools and services include language lessons designed to assist informal learning in everyday life, focusing on situational language needs and a social forum for peer support, cultural information, comments and practice. The paper reports on interview data and social forum use. Our findings suggest that the MApp helps immigrants with their confidence; with relevant, practical language learning and practice of different language skills, and also supports social learning. Studying and practising language skills in the locations, and at times, of learner’s choice, along with access to a social forum for socio-emotional support and feedback, it is a powerful combination of informal mobile language learning.

This editorial introduces the JIME special collection looking at 'Migrants, education and technologies'.

Information about the paper titled "COMPARING ONLINE DISTANCE UNIVERSITIES" at IATED Digital Library

This paper describes how digital talking books (DTBs) with embedded functionality for learners can be generated from content structured according to the OU OpenLearn schema. It includes examples showing how a software transformation developed from open source components can be used to remix OpenLearn content, and discusses issues concerning the generation of synthesised speech for educational purposes. Factors which may affect the quality of a learner's experience with open educational audio resources are identified, and in conclusion plans for testing the effect of these factors are outlined. Editors: Doug Clow and Alexandra Okada (Open University, UK). Reviewers: Mike Sharples (University of Nottingham, UK) and Alexandra Okada (Open University, UK).