Module 5: How to ensure access to our content

Landing the concept
Take Action
Test Yourself

Landing the Concept

Data has become the oil of the 21th century. By 2013, the human being had created approximately 90% of the data since the existence of humanity [1], due to advances in storage capacity or computation of the big data ecosystem. Moreover, “in 2020, every person generated 1.7 megabytes per second” [2]. Data appears in the technological landscape in several forms: structured data as excel matrix or relational databases; non-structured as images, sounds, pdf documents, emails, etc; or in a semi-structure form based basically in languages such as XML (Extensible Markup Language). Data in their different forms have the potential to support decision-making in variate context; education is a sector which specially benefits from data analysis.

In education, data analysis, commonly named educational data mining, could prevent student dropout, suggest personalised learning paths to students, help teachers to improve learning materials and monitor the students advances in learning, identify patterns that can be used to support the design of collaborative learning, among others possibilities [3].

However, the use of data in education or in whatever domain imply to follow a process called Knowledge discovery [4]. This process begins from the identification of data sources needed to support the analysis, followed by the selection of the most promising source of data, clean or/and preprocessing the data to obtain an adequate dataset to be processed, and finally applying different kinds of analysis techniques as grouping or classification.

Knowledge discovery have evolved according to the growth of the technological ecosystem and the appearances of new needs from the economic and social sectors [5]. To build a comprehensive idea about what is and how to implement knowledge discovery in your institution, we invite you to visit the following links:

  • https://www.learninga-z.com/site/breakroom/data-in-education
    • In this link, the different types of data that come from the educational process are analysed. While reading, reflect about your institution and think where each kind of data could be storage.
    • On the other hand, the second part of that document provides best practices on educational data usage. Think about the application of these practices in your institution while you read them.
  • https://youtu.be/FkxaBRiXlVc
    • Learn how to get started creating reports and dashboards in Google Data Studio.
  • https://youtu.be/zHpxMIiJrTA
    • This video could give you some ideas about how to create attractive data visualisations using Google Data Studio.

Take Action!

Now, you have an idea about how the data are supposed to be used in an educational context, however it is important to practise the use of data for generating interesting dashboards that can help institutions to make decisions. With this purpose in mind, please:

  • Define one or two strategic questions important to be responded to by your educational institution. For instance:
    • What was the behaviour of dropouts during the last years?
    • What are the most difficult courses for the students?
  • Once questions have been defined, please identify data that could be used to answer them. Choose one dataset, easy for you to access them. They could be data about a particular class, or also regarding a particular academic process of your interest, depending on the question you have previously defined.
  • Considering the dataset, define indicators interesting for you to display in a dashboard that help to answer the defined questions. Indicators such as:
    • Number of students who dropped out by years.
    • Number of students who failed courses.
    • The average classroom or student grades in different academic periods.
    • Hours of study dedicated to a learning resource.
    • Formative grades of an activity or task
    • Number of accesses per student.
    • The most accessed resource of a topic or module.
  • Define the dashboard design, which represents how you plan to show the indicators in the dashboard. The design should help to answer the questions, what do you want to show, and how do you want to show it.
  • Create your dashboard using Google Data Studio (https://datastudio.google.com/)
  • Reflect regarding the results:
    • Could a dashboard be a good tool to support answering strategic questions in an educational institution?
    • Decisions driven by data analysis or visualisation could be better than those not driven by data?

Test Yourself

References

  • Bradshaw, L. (2013). Big Data and What it Means. Retrieved September 21, 2021, from U.S. Chamber of Commerce website: https://www.uschamberfoundation.org/bhq/big-data-and-what-it-means
  •  Petrov, C. (2021). 25+ Impressive Big Data Statistics for 2021. Retrieved September 21, 2021, from TechJury website: https://techjury.net/blog/big-data-statistics/#gref
  •  Ana Azevedo, Azevedo, J. M., Uhomoibhi, J. O., & Ossiannilsson, E. (2021). Advancing the Power of Learning Analytics and Big Data in Education. https://doi.org/10.4018/978-1-7998-7103-3
  •  Maimon, O., & Rokach, L. (2006). Introduction to Knowledge Discovery in Databases. In Data Mining and Knowledge Discovery Handbook (pp. 1–17). https://doi.org/10.1007/0-387-25465-x_1
  • Mariscal, G., Marbán, Ó., & Fernández, C. (2010). A survey of data mining and knowledge discovery process models and methodologies. Knowledge Engineering Review, 25(2), 137–166. https://doi.org/10.1017/S0269888910000032