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IMPACT & CHALLENGES OF BIG DATA

Big Data brings a lot of benefits but also some challenges. According to  Adejo and Conolly (2017) LA aimed at providing significant benefits to both the learned and teachers in the learning institution. However, there are a lot of challenges that affect the implementation of LA in Higher Education.

In this section, we distinguish between legal challenges, ethical and social challenges, technological challenges, and human capacity challenges.

lEGAL (PRIVACY)

Privacy is a multi-faceted topic in higher education and the privacy implications for institutional activities can be nuanced (Educause, 2021). With regard to legal challenges, our society is facing much needed but complex data protection laws. For example, educational institutions in British Columbia are considered public bodies and is subjected to the Freedom of Information and Protection of Privacy Act (FOIPPA). Higher Educational institutions encounters privacy issues everyday. Due to the magnitude of data collected about student activities, there are huge gaps where educators, students and the institution can potentially engage in unethical practices. (Sclater, 2017, p.214)

This video answers our questions about the growing need for privacy management, the policies  in place to protect our privacy. Click Here

TECHNOLOGICAL (ACCESSIBILITY)

Accessibility and quality of data can be a concern. Analytics may affect the students who “may carry out much of their learning activities outside the monitored and recorded confines of the institution’s LMS (Sclater, 2017, p.82). It will be difficult to incorporate external data systems and capture the student’s activities to enhance analytics.tell people more about your business.
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ETHICAL & SOCIAL (SECURITY)

Slade and Prinsloo (2014) proposed six principles as a guiding framework for considering learning analytics as moral practice:
  • Principle 1: Learning Analytics as Moral Practice
  • Principle 2: Students as Agents
  • Principle : Student Identity and Performance Are Temporal Dynamic Constructs
  • Principle 4: Student Success Is a Complex and Multidimensional Phenomenon
  • Principle 5: Transparency
  • Principle 6: Higher Education Cannot Afford to Not Use Data. Transparency is the most important because institutions must be transparent about their methods and techniques used in collecting data.
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HUMAN CAPACITY

Technology opportunities seem to grow faster than human and organizational capacity and capabilities. There is not only a lack of expertise among teachers, but also a lack of experts who can assist them in the use of big data. Big data literacy is needed. Analytics may also affect faculty members, as some may be concerned about the additional expectations, teachers may struggle to find the right balance between too much support, encouraging students to become independent learners (Campbell & Oblinger, 2007, p. 9).

Choose one of the following questions to answer

(Write Benefits/Challenges at the top)

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1. What are some of the benefits of Learning Analytics within the education sector? 

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OR

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2. What are some challenges that educators face in an attempt to implement Learning Analytic tools?

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