Tagged: W23A15

Week 23 – Activity 15: Citation networks

Timing: 4 hours

This activity focuses on an article that you are likely to find difficult to understand unless you have previous experience of network analytics. It was written for one of the Learning Analytics and Knowledge (LAK) conferences by some of the leaders in the field.

  • Now turn to the practical implications of the paper (Section 4.3). Read this, and expand your notes in the form of a bullet-point list. Note which findings are linked to a practical implication. At this stage, you will have gained a sense of what the paper is about, although you have only read a couple of sections.
    • the development of curriculum in the growing number of academic programs that include learning analytics as a topic; (practical – expansion of the application of LA)
    • promotion of under-represented groups and research methods to the learning community; (practical – expanding the research types and sister fields)
    • fostering the development of empirical work and decreased reliance on founding, overview and conceptual papers; and
    • improved connection to sister organisation such as the International Educational Data Mining Society. (practical – combining experience)
  • Note what the authors aimed to do in the paper, and what their main findings were.
    • An evaluation of the current state the field of learning analytics through analysis of articles and citations occurring in the LAK conferences.
    • A citation analysis and structured mapping aimed to identify the emergence of trends and disciplinary hierarchies that are influencing the development of the field to date.
    • An evaluation of the current state of learning analytics. 
  • Begin by looking at the abstract of this paper:
  • Note whether you think this is an example of learning analytics, according to the definition you produced in Week 21 of this module, or whether it is simply about learning analytics.
    • My definition: Learning analytics concerns the process of measuring and collecting learning data from a variety of student activity, with the aim of using said data to improve and/or alter the student learning process.
    • Noting the bolded section, this would fit more as being about learning analytics, as it is research based and no student based. 
  • Look at the figures and tables in the paper. Some require specialist knowledge, but others are clearer to non-experts. Figure 4 shows the disciplinary background of learning analytics researchers. Table 1 identifies the ten most-cited papers in the field.
  • In the forum, suggest why it is that these most-cited papers have similar numbers of citations in the learning analytics literature, but very different citation rates in a wider context (the Google Scholar citation counts shown on the right of Table 1).
    • Possibly due to the papers cross applicability. For example, if a paper has implications for other research areas, or provides a useful summary of an issue, it will be picked up by those in other fields in referencing and discussion. Whilst, within the LAK community, the paper might only provide a few cases of important information for their work. 
  • Now read carefully through Sections 1 and 2 of the paper, and use all you have read to produce a two-page summary of the article.

    the strategic application of analytics [16] to inform practice has not been extensive within the education sector.

    The outcome of limited systemic analytics activity is a predominance of research that is founded on the extraction of readily available data such as those drawn from learning management systems (LMS), student information systems (SIS), and basic demographics and student grades.

    However, these commonly bivariate analyses are t h e “low hanging fruit” in terms of the overall potential for analytics to redefine and shape education praxis.

    For example, while it is helpful to note that students who regularly log into a LMS may perform better than their less active peers, this information is not suitable for developing a focused response to poor performing students.

    LMS or SIS data can be a useful proxy for seeing a part of a problem, but it is insufficient to serve as a model for intervention that is based on the current state of learning sciences.

    Learning analytics to date has served to identify a condition, but has not advanced to deal with t h e learning challenges in a more nuanced and integrated manner.

    For instance, the field draws on assorted theory and methodologies from disciplines as diverse as education, psychology, philosophy, sociology, linguistics, learning sciences, statistics, machine learning/artificial intelligence and computer science.

    An evaluation of the current state of learning analytics provides numerous benefits for the development of the field, including:

    •  a foundation for future research through the acknowledgement of past research activities;
    •  assistance for grant-making agencies by identifying promising research areas that align with regional and national education goals;
    •  identify disciplines that are under-represented and require more strategic and targeted support and funding opportunities;
    •  identify gaps in research for researchers and students; and
    •  improve the integration between theory and practice by identifying connections between researchers and papers.
    • To address these questions this paper explores through the lens of structured mapping and citation networks the research domains and relationships that have extensively contributed to the field to date.

     

    To address these questions this paper explores through the lens of structured mapping and citation networks the research domains and relationships that have extensively contributed to the field to date.

    In undertaking a mapping and review of the collaborations that have evolved in the field, researchers and practitioners can identify the cliques and sub-culture that define the broader learning analytics community.

    Citation profiles and analyses are central measures adopted in these practices in order to determine research impact.

    As Waltman et al., [20] argued, highly cited papers are not always indicative of impactful research. However, as the authors further noted, on average this premise does tend to hold true. As such, it is reasonable to assume that high citation rates do reflect a certain level of quality [23].

    Current citation databases such as Elsevier’s Scopus, Google Scholar, web of science and others have made the extraction of co-citations and identification of co-author networks more accessible.

    The aim for this paper is to provide a mapping of the learning analytics research community to identify the:

    •  prominent papers referred to in the research;
    •  dominant disciplines and methodologies adopted in learning analytics; and
    • diversity of research paper genres that comprise learning analytics (e.g., opinion papers, reviews, conceptual, empirical research, etc.).

  • Write an entry in your learning journal or blog about your experience of reading a paper in this way. What do you think you gained or lost by missing out some sections?

I found that the general context was lost. I was picking up the surface, but not really able to think critically about what was being said.

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