What are Learning Analytics?

Learning analytics refers to the interpretation of a wide range of data produced by and gathered on behalf of students to assess academic progress, predict future performance, and spot potential issues. Data are collected from explicit student actions, such as completing assignments and taking exams, and from tacit actions, including online social interactions, extracurricular activities, posts on discussion forums, and other activities that are not typically viewed as part of a student’s work. The goal of learning analytics is to enable teachers and [[#|schools]] to tailor educational opportunities to each student’s level of need and ability. Learning analytics promises to harness the power of advances in data mining, interpretation, and modeling to improve understanding of teaching and learning, and to tailor education to individual students more effectively. Still in its very early stages, and not yet at the stage where it is practical to talk about implementation in schools, learning analytics is an emerging scientific practice that hopes to redefine what we know about learning by mining the vast amount of data produced by students in academic activities.

INSTRUCTIONS: Enter your responses to the questions below. This is most easily done by moving your cursor to the end of the last item and pressing RETURN to create a new bullet point. Please include URLs whenever you can (full URLs will automatically be turned into hyperlinks; please type them out rather than using the linking tools in the [[#|toolbar]]).

Please "sign" your contributions by marking with the code of 4 tildes (~) in a row so that we can follow up with you if we need additional information or leads to examples- this produces a signature when the page is updated, like this: - Larry Larry Jan 25, 2011

(1) How might this technology be relevant to the educational sector you know best?

  • [[#|Distance learning]] institutions, as well as massive open on-line courses (MOOC), have the power of tracking most of the interactions in the educational process because they are done in their own e-learning platforms. However, most of these interactions are not appropriately analyzed. The study of these massive data will considerably improve the way we teach and the way we learn.- Sergio Sergio Jul 22, 2012
  • assessment and feedback i simportant to provide feedback to [[#|students]], teachers and institutions; it might help to uncover problems in the learning approach, missunderstanding of concepts, etc. - Christian.Guetl Christian.Guetl Aug 9, 2012
  • Any system/process that promotes a HE culture of accountability for the support, retention and success of students has to be a plus. - shirley.reushle shirley.reushle Aug 13, 2012
  • Providing feedback that enables the learner to proactively explore information that might enhance their learning while they are in the midst of it is "good"! - Phillip.Long Phillip.Long Aug 18, 2012

(2) What themes are missing from the above description that you think are important?

  • Whereas the present research, development and practical uses in learning analytics have been focusing more on formal learning settings, I foresee that the field will gradually venture into the informal spaces where younger learners' out-of-school or out-of-learning-portal online activities pertaining to, say, social media and social networking, may be analyzed. The aim is to inform the educators on how to tap on the learners' online behaviors to support formal education, or to inform parents on their children's online activity patterns. Of course, the privacy issue may arise. - Lung-Hsiang.Wong Lung-Hsiang.Wong Aug 18, 2012
  • The emphasis in LA is intended to be on the learner with the data visualisations and information presented back to her in a form that provides near real-time actionable choices. Data mining and academic analytics emphasize the methodology of big data analysis (the former) and course/program/curriculum level analysis (the latter). LA is all about data that a learner can act on to facilitate their learning. - Phillip.Long Phillip.Long Aug 18, 2012
  • add your response here

(3) What do you see as the potential impact of this technology on STEM+ education?

  • Improvement of course contents because we will know which parts are more easy and difficult to be understood.- Sergio Sergio Jul 22, 2012
  • Personalized learning depending on the learning style of each [[#|student]].- Sergio Sergio Jul 22, 2012
  • get support for the individual learner and the teacher, improve learning strategies - Christian.Guetl Christian.Guetl Aug 9, 2012
  • While I don't buy the whole 'learning styles' argument at all, I do think the potential to provide insight to the learner through both contextualising their learning relative to others (e.g., those in their class, team or group, or those in prior courses) as well as through modeling identify patterns the learner might be in and possible alternatives that they might pursue has great potential. - Phillip.Long Phillip.Long Aug 18, 2012
  • add your response here

(4) Do you have or know of a project working in this area?

Please share information about related projects via our NMC Horizon Report project submission form.