Thoughts on Learning Analytics and Institutions

Reading seminar

Review n. 4, ISKM57 Reading Seminar: Educational Technology and Learning Society

This week’s focus was on iconic book Learning Analytics: From Research to Practice (2014). It contains theoretical and research texts from various perspectives. I read the chapter Analytics Through an Institutional Lens: Definition, Theory, Design, and Impact which stretches out the possible use and impact of learning analytics in institutions.

Authors find learning analytics to be potentially very helpful framework for the university education. They wonder how to transform the data about students which universities already have or can collect easily with the help of ICTs, to meaningful actions resulting in students to retain in the university, have better results, and be overall more satisfied with their studies.

Theory first

First they lay out the theoretical basis: Tinto’s theory of student departure, Astin’s theory of student involvement, and Chickering and Gamson’s principles for good practice in undergraduate education.

Tinto and Austin both emphasize the need for the student’s involvement in the university life. Be it formal academic (discussion with professors in the class), informal academic (discussion with schoolmates after the class), formal social (school events, clubs or government), or informal social (spending free time with people from university). In short, the more student gets involved and invited in the university’s life, the more likely they are to be successful in their studies.

Chickering and Gamson articulate principles of good practice in higher education, which can help to build a healthy and motivating learning environment:

  1. Encourage contact between students and faculty
  2. Develop reciprocity and cooperation among students
  3. Encourage active learning
  4. Give prompt feedback
  5. Emphasize time on task
  6. Communicate high expectations
  7. Respect diverse talents and ways of learning

What about the data?

So how can data help to build this supportive and challenging learning environment? There are plenty of possibilities! Using data to improve learning is not a new idea and it usually follows this scheme – the course is taught and data is being collected, this data is then evaluated after the course, and helpful changes take place in the next semester. Authors propose different approach – to use data to help students in real time. How?

The course design and analytics must work synergically. For example, if teacher encourages active learning, provides fast feedback and increases communication with students, not only learning is improved but also more data is collected. That data can be used to spot red flags in student’s performance so they can be helped right away, in the moment of need. The help can come in form of an automatic notification in LMS, or personalized email from teacher.

To be able to recognize student’s behaviuor which leads to poor performance or drop out is crucial. The idea is to be able to take action when there is still time to reverse student’s path.

Individuality and emotions

In general, using learning analytics in the process of education is a very delicate topic. From collecting and storing personal data to communicating that the student is not performing well. I actually encounter this problem now as I am tutoring Kurz práce s informacemi.

I collect data about students’ fulfilment of obligations in an Excel table. I can easily see which ones struggle – they are late with their fulfilment, gain low rating on their homework etc. I need to inform them that they are close to fail the course, but in the same time, I do not want to discourage them from continuing and improving. How do I do it? So far I think the key is to pay attention to the right wording and to practice in writing this type of emails.

Although deriving from the data automatic solutions to typical problematic situations can be extremely helpful and effective, I think it is very important to pay attention to the last principle Chickering and Gamson propose. And that is “respect diverse talents and ways of learning”. It seems to me, that in the end, there needs to be an emphatic and experienced teacher/mentor who offers hand, when the student is in need, with respect to their individuality.

Larusson, J. A. & White, B. (2014). Learning Analytics: From Research to Practice. Springer.

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