1.0 Introduction

 

OUTCOMES

  • Describe what "learning analytics" is
  • Identify different types of learning analytics data
  • Differentiate “learning analytics” projects from other projects using data

 

What is "learning analytics"?

LEARNING ANALYTICS is the measurement, collection, analysis, and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs. According to the Society for Learning Analytics Research (SoLAR),

Learning analytics is both an academic field and commercial marketplace which have taken rapid shape over the last decade. As a research and teaching field, Learning Analytics sits at the convergence of Learning (e.g. educational research, learning and assessment sciences, educational technology), Analytics (e.g. statistics, visualization, computer/data sciences, artificial intelligence), and Human-Centered Design (e.g. usability, participatory design, sociotechnical systems thinking).

(Society for Learning Analytics Research (SoLAR), 2021)

While there is significant overlap with Educational Data Mining, “learning analytics” tends to focus more on the processes of learning of individuals, where Educational Data Mining tends to focus more on knowledge discovery from other data sources. (Lemay et al., 2021) Importantly, learning analytics has a greater focus on applications to teaching practice.

“Learning analytics” is a broad, encompassing, and quickly growing field that often includes varied definitions and equally varied applications. This chapter will describe common types of data and analytics in education, types of learning analytics data specifically, how they may be used (including examples of specific projects), and some considerations to keep in mind before using learning analytics data.

 

Watch Learning analytics in a nutshell

Learn more about learning analytics from the Society for Learning Analytics and Research:

 

Access the video transcript on YouTube. Links to an external site.

 

What are data and analytics in the context of higher education?

Educators have used data to make innovative and iterative changes to the world of education for years. Grade point averages, information in transcripts, and even grades are all data reporting students’ progress through a course or program. These data have historically informed teaching practices, and when examined by computer software in order to find useful patterns, the results can be described as analytics. (Cambridge Dictionary, 2022)

As education has increased its use of digital technology to deliver learning experiences, for example, by adopting the use of learning management systems (LMSes) like Canvas, the ability to capture and visualize new aspects of student interactions and learning data has similarly grown.  Instructors often have questions related to their course or practice, and now more than ever before, learning data may inform the answers to those questions.

 

Types of learning analytics uses

There are multiple types of learning analytics data uses, each of which is defined by the type of outcome generated by the data. These outcomes are most often descriptive, diagnostic, predictive, or prescriptive in nature. (Society for Learning Analytics Research (SoLAR), 2021)

Learning analytics provide instructors a tool to reflect upon their activities, their teaching, and their course or program to identify areas that may be improved or better understood. The use of learning analytics data may yield distinct knowledge that, when combined with the larger course context, can be made actionable by a faculty member. For example, learning analytics data may inform changes that could be made during a semester to an upcoming activity or order of activities based on indicators of students’ understanding of course content. Similarly, learning analytics data may yield information that can inform future course design, programming decisions, or a combination of all three. Generally, questions that can be answered by learning analytics are grouped into larger categories associated with different types of learning analytics data: 

 

Types of Learning Analytics Data

Question being asked

Data type

What occurred?

Descriptive learning data

Why did it occur?

Diagnostic Learning Data

What might occur?

Predictive Learning Data

What should occur?

Prescriptive Learning data

 

Regardless of the question or goal, using learning analytics requires an understanding that the uniqueness of courses will lead to unique sets of data and that these data require careful interpretation to be used successfully.

In this curriculum, we'll focus on descriptive and diagnostic data.