Education and Learning Analytics Market Trends

The learning analytics market is expected to grow at a CAGR of 29.91% during 2019-2024 (Technavio, 2020). Online learning emerged as a safe and viable option for education continuity as the COVID-19 pandemic turned personal and professional worlds upside down. Even before the pandemic, the global elearning market was already seeing a massive annual global growth. It is expected to reach $336.98 billion by 2026, at a compound annual growth rate (CAGR) of 9.1% from 2018 to 2026 (Syngene Research, 2019).

Emerging Trends in Learning Analytics

Due to the pandemic, there has been a shift in trends and Learning Analytics returned as a hot topic, "the ultimate goal is to drive “data innovation” in which the users of data can interpret it and take evidence-based positive action, leading to more institutional agility, optimization, and data-informed practices" (Horizon Report, 2021 p, 20). By real-time data analysis, it is possible to predict which students are at risk and direct interventions can be applied. This enables teachers to adapt their teaching to the needs of the students. Campbell et. al (2007) outlined some examples of different cases predicting and improving student retention. More recently, The Center for the Analytics of Learning and Teaching (C-ALT) at Colorado State University has dedicated specific resources to the interpretation and use of learning analytics data in order to “move theory into practice” by helping instructors and students interpret learning analytics for direct applications (Horizon Reportm 2021, p,20). Two recent projects are outlined below;

U Behaviour

U-Behavior is a method of teaching and learning that reimagines and redesigns
the Canvas quiz as Retrieval Practice Activities.
The U-Behavior method includes educational tools designed to inform students how to use Robotic Process Automation (RPAs) to improve their learning
behaviors, promoting practice strategies that have been shown to boost long-term learning.
U-Behavior provides online instruction, showing students why they would
want to practice (study) in these ways. The method reinforces these practice
strategies by generating personalized high-resolution visualizations (visual-form learning analytics), presenting students with their individualized RPA
Canvas use data (C-ALT, 2020).

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Epistemic Network Analysis

Discussion-based Epistemic Network Analysis is a learning and teaching method that uses ENA to uncover connections within students’ discussion posts.
C-ALT researchers are exploring how DB-ENA can assist faculty and students in understanding where students may be missing contextual connections based on their discussion board data.
In addition, researchers are interested in how DB-ENA can help faculty evaluate student text-based responses, and provide formative feedback based on both the visual-form learning analytics and the quantitative evidence underlying the network (C-ALT, 2020).

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ACTIVITY 3

Let us have a discussion on the emerging trends, let me know your thoughts on U behavior or EMA. Feel free to add other emerging trends in Learning Analytics.

Pretend that you are an advisor for the Technology Committee of a higher education institution. You are given the choice to implement U behavior or EMA at your institution. Which one would you vote for and why?

Optional Activity:

Explore the interactive visualization data

Some of the Key players in the Learning Analytics Market

BLACKBOARD

D2L

TABLEAU

Factors Driving the growth of Learning Analytics

The amplified awareness about the potential of learning analytics is transforming the learning system in response to improving student performance. Learning analytics helps the education sector improve the quality of teaching & learning through innovative and adaptive lessons that suit the cognitive abilities of a variability of learners. This encourages the increased adoption of these techniques in the education sector. In addition, the shift in technological trends due to the pandemic pushes this growth and creates opportunities in the area of Mental Health.

Mental Health

In a survey conducted earlier in the COVID-19 pandemic, a full 80% of college students reported that the pandemic had negatively impacted their mental health, and a fifth reported that their mental health had significantly worsened (Active minds, 2020).
There are clear opportunities for Jisc’s current and proven expertise in learning analytics to be expanded and applied in the broader area of student wellbeing, and specifically to the current crisis in student mental health (Hall, 2018).

The Quality of Online Learning

The shift in the quality off online learning prompted everyone to be creative in content creation, learning activities, and content delivery. A remarkable example of this is the Conestoga College in Ontario who "created a series of virtualized culinary lessons and learning experiences called Bloom that replicate a real culinary school. With guidance from the Virtual and Augmented Reality Lab specialists, a 13-module digital learning simulation (EDUCAUSE Horizon Report, 2021, p.29)

Key feature of QOL:

Virtual Exhibit Hall
Self service resources

Microcredentialing

The State University of New York defines Micro-credentialing as "programs of study that verify, validate, and attest that specific skills and/or competencies have been achieved. They differ from traditional degrees and certificates in that they are generally offered in shorter or more flexible time spans and tend to be more narrowly focused". The credential engine reported thousands of unique credentials in the United States that stretched across four different education providers: High school, non-academic provider, MOOCs and Post-secondary education institutions.

Some key features of Micro- Credentialing are:

Peer mentors and tutors
Game-based course

The fact that Micro-credentials can be offered online, in the classroom, or via a hybrid of both contributes to its growing trend because it is easily accessible.