Encouraging the Online Creation of Knowledge

There have been a number of models of digital literacy over the last couple of decades.

Groupings by Usage

In 2001, Prensky suggested that younger people thought and processed information in fundamentally different ways compared to older generations.  He suggested that younger people (pre 1980s) were ‘digital natives’ and ‘speakers’ of the new technologies, while older people were ‘digital immigrants’ who were able to learn and use the new technologies, but not in the same intuitive way.  But this dividing of generations has not been borne out by research (Helsper and Eynon, 2009), and more recent studies have been more nuanced. For example a recent study found that information search competencies have a high-level correlation with information literacy and a low-level correction with digital nativity (Çoklar, Yaman, and Yurdakul, (2017).

As a replacement for Prensky’s model, White and LeCornu (2011) suggested that the creation of Web 2.0 resulted in users behaving in either a resident-like fashion (using sites as social spaces for sharing and discussion), or visitors using the Web in a more instrumental way.  It would be expected (according to the Pareto Principle) that visitors would predominate over a small number of ‘noisy’ residents. Wright, White, Hirst, and Cann, (2013) found that there was evidence that the visitor and resident model could be used to map student attitudes to academic use of social networks.

creative commons image taken from https://www.flickr.com/photos/wfryer/39501087882

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Homophily Among Students and Academics

Homophily and Academic Isolation

In addition to the sense of isolation felt by all researchers who will spend much of their time working alone, some people may also be subject to additional feelings of isolation.

Research suggests that international and part-time doctoral researchers, and those from underrepresented minority groups, are more likely to feel isolated.  

Studies have also shown that unless a programme is specifically designed to support interdisciplinary researchers, they will often feel excluded from the wider traditional research culture of the university. ‘The increased diversity of the doctoral researcher population can lead to challenges and mismatches in expectations between student and supervisor ’. Duke and Denicolo (2017).   Continue reading “Homophily Among Students and Academics”

Power Differentials Between Students and Supervisors

Any social network potentially brings together groups with different perspectives and circumstances. ‘MeetingofMinds’ must take into account possible power dynamics between students and academics.

Models of PhD Supervision

There have been a number of attempts to model PhD supervision. More recently these have focused on supportive approaches allowing students to move from a state of relative dependency to complete independence (through a shift in the balance of control).

However there are also a number of potential power inequalities built into the relationship between supervisor and student. This includes:

  1. The supervisor is in a position of legitimate authority.
  2. They have perceived abilities to mediate rewards (e.g supporting publications) or punishments (e.g being unavailable for important meetings).
  3. A student may be influenced by the perceived expertise of the supervisor.
  4. Some students may be in awe of their supervisor, seeing them an example that they wish to live up to.

Photograph from  Contributor(s): Queensland figaro – Copied and digitised from an image appearing in Queensland figaro, 28 July 1888, p. 140., Public Domain, https://commons.wikimedia.org/w/index.php?curid=12662338

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Privacy and Age Online

The Need for Nuanced Research

Many existing studies (often focused on adolescent or student samples) try to make general assumptions about how humans regard privacy and what actions they take, or fail to take, to protect their own privacy.

But Blank, Bolsover, and Dubois (2014) found that only three peer-reviewed papers that addressed questions of privacy using a sample that could be generalized to a population. Continue reading “Privacy and Age Online”