LMS Performance Analysis: 3 Web Analytics Methods To Enhance eLearning

Education Technology Insights | Friday, December 04, 2020

Life-Cycle Analysis (LCA) can establish how the learning resources or evaluations are obtained and utilized by these groups through the course. It is a vital element of the analysis.

FREMONT, CA: LMS is the center of each online course and links all of the educational and business processes together. Therefore, to tailor it best to the users’ requirements, training providers need to recognize business and IT processes and content elements with scope for further enhancement.

Below are three standard web analytics methods that are employed in LMS performance analysis projects, namely:

1. Learner Web Log Analysis (WLA)

Learner WLA will help determine the existing state of learning activities. WLA involves learning when, how, and by whom several sections of the system are visited. It is also possible to produce activity reports basis the data gathered and, depending on those reports, monitor the nature of the events and changes to the demand.

Data collected and analyzed through the WLA can differ based on the Key Performance Indicators (KPIs) investigated. Some of the standard WLA indicators to be examined are:

• Page, site, section visit times, durations, and the number of visits.

• Most and least viewed pages.

• User authentication and access times per individual user.

When applied to an LMS, such analysis can offer many valuable data sets that reflect upon several system performance indicators, like recognizing sections that are hardly accessed by learners or vice-versa—identify areas that are opened more often than others.

2. Learner Life-Cycle Analysis (LCA)

The LCA focuses on the visitor-centered strategy and investigates KPIs connected to individual learners or separate learner groups, including classes or study majors. A few parameters that can be applied are:

• Comparative adoption of the resources encompassing different subjects or study areas.

• Technology implementation level for the groups (for example, how many of the study-enhancing applications are being employed).

• Comparative participation (learning activities, discussions, etc.)

LCA can also establish how the learning resources or evaluations are obtained and utilized by these groups through the course. It is a vital element of the analysis. The crucial challenge behind developing a competent LMS is not associated with technical requirements (like balancing traffic load, download times) but with business and learning processes.

3. Learning Progression Analysis (LPA)

LPA is founded on an effective combination of data available through web metrics-driven analysis of LMSs and data (including qualitative data) accessible on the online training programs’ learning outcomes.

LPA is impartially complex when compared to old web metrics analysis methods, as it cannot be accomplished without looking past system usage and understanding not only the nature and context of the events that the learners accept while logged in but also the relative efficiency of these activities from a data building perspective.

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