Category Archives: Higher Education

The Technology Acceptance of Mobile Applications in Education

Dr Mark A. Camilleri from the University of Malta’s Department of Corporate Communication and Ms Adriana C. Camilleri, a PhD Candidate at the University of Bath (U.K.) have recently delivered a presentation of their latest empirical paper, entitled; The Technology Acceptance of Mobile Applications in Education during the 13th Mobile Learning Conference in Budapest, Hungary. More details on this highly indexed conference are available in this site: http://mlearning-conf.org/. An abstract of this paper is enclosed hereunder:

This paper explores the educators’ attitudes and behavioural intention toward mobile applications. Its research methodology has integrated previously tried and tested measures from ‘the pace of technological innovativeness’ and the ‘technology acceptance model’ to better understand the rationale for further investment in mobile learning technologies (m-learning). A quantitative study was carried out amongst two hundred forty-one educators to reveal their perceptions on their ‘use’ and ‘ease of use’ of mobile devices in their schools. A principal component analysis has indicated that these educators were committed to using mobile technologies. In addition, a stepwise regression analysis has shown that the younger teachers were increasingly engaging in m-learning resources. In conclusion, this contribution puts forward key implications for both academia and practitioners.

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Filed under Digital Learning Resources, digital media, Education, Higher Education, Marketing

Measuring the Academic Impact of Higher Education Institutions and Research Centres

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Although research impact metrics can be used to evaluate individual academics, there are other measures that could be used to rank and compare academic institutions. Several international ranking schemes for universities use citations to estimate the institutions’ impact. Nevertheless, there have been ongoing debates about whether bibliometric methods should be used for the ranking of academic institutions.

The most productive universities are increasingly enclosing the link to their papers online. Yet, many commentators argue that hyperlinks could be unreliable indicators of journal impact (Kenekayoro, Buckley & Thelwall, 2014; Vaughan & Hysen, 2002). Notwithstanding, the web helps to promote research funding initiatives and to advertise academic related jobs. The webometrics could also monitor the extent of mutual awareness in particular research areas (Thelwall, Klitkou, Verbeek, Stuart & Vincent, 2010).

Moreover, there are other uses of webometric indicators in policy-relevant contexts within the European Union (Thelwall et al., 2010; Hoekman, Frenken & Tijssen, 2010). The webometrics refer to the quantitative analysis of web activity, including profile views and downloads (Davidson, Newton, Ferguson, Daly, Elliott, Homer, Duffield & Jackson, 2014). Therefore, webometric ranking involves the measurement of volume, visibility and impact of web pages. These metrics seem to emphasise on scientific output including peer-reviewed papers, conference presentations, preprints, monographs, theses and reports. They also analyse other academic material including courseware, seminar documentation, digital libraries, databases, multimedia, personal pages and blogs among others (Thelwall, 2009; Kousha & Thelwall, 2015; Mas-Bleda, Thelwall, Kousha & Aguillo, 2014a; Mas-Bleda, Thelwall, Kousha & Aguillo, 2014b; Orduna-Malea & Ontalba-Ruipérez, 2013). Thelwall and Kousha (2013) have identified and explained the methodology of five well-known institutional ranking schemes:

  • “QS World University Rankings aims to rank universities based upon academic reputation (40%, from a global survey), employer reputation (10%, from a global survey), faculty-student ratio (20%), citations per faculty (20%, from Scopus), the proportion of international students (5%), and the proportion of international faculty (5%).
  • The World University Rankings: aims to judge world class universities across all of their core missions – teaching, research, knowledge transfer and international outlook by using the Web of Science, an international survey of senior academics and self-reported data. The results are based on field-normalised citations for five years of publications (30%), research reputation from a survey (18%), teaching reputation (15%), various indicators of the quality of the learning environment (15%), field-normalised publications per faculty (8%), field-normalised income per faculty (8%), income from industry per faculty (2.5%); and indicators for the proportion of international staff (2.5%), students (2.5%), and internationally co-authored publications (2.5%, field-normalised).
  • The Academic Ranking of World Universities (ARWU) aims to rank the “world top 500 universities” based upon the number of alumni and staff winning Nobel Prizes and Fields Medals, number of highly cited researchers selected by Thomson Scientific, number of articles published in journals of Nature and Science, number of articles indexed in Science Citation Index – Expanded and Social Sciences Citation Index, and per capita performance with respect to the size of an institution.
  • The CWTS Leiden Ranking aims to measure “the scientific performance” of universities using bibliometric indicators based upon Web of Science data through a series of separate size- and field-normalised indicators for different aspects of performance rather than a combined overall ranking. For example, one is “the proportion of the publications of a university that, compared with other publications in the same field and in the same year, belong to the top 10% most frequently cited” and another is “the average number of citations of the publications of a university, normalised for field differences and publication year.”
  • The Webometrics Ranking of World Universities Webometrics Ranking aims to show “the commitment of the institutions to [open access publishing] through carefully selected web indicators”: hyperlinks from the rest of the web (1/2), web site size according to Google (1/6), and the number of files in the website in “rich file formats” according to Google Scholar (1/6), but also the field-normalised number of articles in the most highly cited 10% of Scopus publications (1/6)” (Thelwall & Kousha, 2013).

Evidently, the university ranking systems use a variety of factors in their calculations, including their web presence, the number of publications, the citations to publications and peer judgements (Thelwall and Kousha, 2013; Aguillo, Bar-Ilan, Levene, & Ortega, 2010). These metrics typically reflect a combination of different factors, as shown above. Although they may have different objectives, they tend to give similar rankings. It may appear that the universities that produce good research also tend to have an extensive web presence, perform well on teaching-related indicators, and attract many citations (Matson et al., 2003).

On the other hand, the webometrics may not necessarily provide robust indicators of knowledge flows or research impact. In contrast to citation analysis, the quality of webometric indicators is not high unless irrelevant content is filtered out, manually. Moreover, it may prove hard to interpret certain webometric indicators as they could reflect a range of phenomena ranging from spam to post publication material. Webometric analyses can support science policy decisions on individual fields. However, for the time being, it is difficult to tackle the issue of web heterogeneity in lower field levels (Thelwall & Harries, 2004; Wilkinson, Harries, Thelwall & Price, 2003). Moreover, Thelwall et al., (2010) held that webometrics would not have the same relevance for every field of study. It is very likely that fast moving or new research fields could not be adequately covered by webometric indicators due to publication time lags. Thelwall et al. (2010) argued that it could take up to two years to start a research and to have it published. This would therefore increase the relative value of webometrics as research groups can publish general information online about their research.

This is an excerpt from: Camilleri, M.A. (2016) Utilising Content Marketing and Social Networks for Academic Visibility. In Cabrera, M. & Lloret, N. Digital Tools for Academic Branding and Self-Promotion. IGI Global (Forthcoming).

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