A significant aspect (and a big challenge as well) of instructional design and online learning development is to be familiar with the behavior of your students. By doing this, you can set up an eLearning experience that provides the most benefit for the students and makes sure that every component of the online learning course is assisting them when it comes to achieving their aims and objectives. By far the most effective ways to amass this very useful data is through passive analytics.

Passive Analytics is, basically, the collection of data that is collected while students are taking part in the eLearning experience. Passive analytics also includes the analysis and tracking of this information. Specifically concerning online learning, important pieces of data are revealed throughout the interval of the eLearning course which includes how many times have they have logged in, In addition, passive Analytics also provide online facilitators and tutors an in-depth look at how a learner is doing, if he/she will need extra help with a particular course or program, and even if the student is likely to pass or not an online lesson or course. Such data will be better positioned to make educational predictions and analysis that help to figure out which learning materials are useful, appropriate or irrelevant for the students. The following passive analytics emphasizes how you can leverage passive analytics to get an idea as to how the class is going:

1. Monitor your students’ development and give more, better and targeted response

This integrates data from any eLearning tool (Learning Management System, class attendance, classroom response system, discussion board, etc.) and lets you, the instructor, clearly define progress indicators. You can examine a dashboard of student progress metrics, a particular person and aggregate. Even more powerfully, you can easily send a custom e-mail or text feedback to subsets of learners who aren’t reaching performance indicators, giving them an exclusive reminder of the things they should do to catch up.

2. Monitor learner activity in your course’s online discussion boards

It’s challenging to track class discussion boards and give out fair grades for engagement. The analytics gives tutors manipulable visualizations of what’s going on in the discussion boards, and reliable metrics revealing the level of engagement. Weekly, it is possible to discover who is involved and who is not, whose opinions are going unanswered, and whether you're achieving your student engagement objectives for your course or lesson.

3. Know your learners before the first class

Precisely what might you modify about your teaching or course content if you knew which courses your learners had already completed, and thus with what success? Also to know the number of learners that will likely opt for a major in your discipline. Getting to know your audience is the bedrock of starting off a course at the perfect level with the perfect tone. Research suggests a good potential to assist course instructors to tailor teaching, curriculum, and preferences based on improved understanding of their possible class discipline, past course history or records, likely study path, demographics, etc.

4. Monitor learner and class activities in real time

Teachers in large online or combined courses need resources that can help them track student online activity and behavior, for instructors to provide support and attention as needed. It let course instructors monitor student activity and behavior in courses with several sections and large enrollment with the aid of an interactive, multilevel heat map. This will help reveals an aggregated view with students' behavior towards the course in accordance with participation in discussions , quiz and poll attempts, page views, whether they stay around for the entire length of the class, whether they keep the teaching window in focus, page views, etc and submission scores for all course segments .

5. Make good use of student performance data to advise curriculum redesign

Passive Analytics can provide departments insight into their courses, and guide and educate curricular (re) design. The analytics makes use of statistical and visual strategies to historic student performance data to give insights into program difficulty, individual program influence on the overall academic performance of students, dropout paths, curriculum coherence, and the impact of course load on learner performance.