Increasing Quality & Participation: Learning Management System Report

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Analytics is at the heart of any competent LMS as it helps instructors and administrators in improving eLearning delivery. Through the use of detailed reports, thorough performance analysis can be conducted, allowing to examine user engagement and identify both student and instructor needs through elements requiring improvement. This paper will analyze findings of an LMS report and attempt to determine areas of improvement which require a further change to increase quality and participation.

Summary of Findings

An examination of the reports presents several important data points that can be used to conclude. The overview of course activity demonstrates a large disparity in time spent on the course throughout the week, with the majority of the time being on weekends, greatly exceeding most weekdays. Tuesday was the only weekday with 32.25 hours that showed the greatest use. These tendencies demonstrate that the course structure and activity planning rely on a traditional “turn in at the end of the week” model which does not perpetuate continuous user engagement and often leaves the learning process to be crammed into short time frames.

The course overview also demonstrates an extreme disparity among individual students participating in the course. While some spend upward of 14 to 18 hours, others spend below 5 hours, and a few below 2 hours. The average time is relatively low with a few students raising it for the most part. Individual reports for students x, y, and z indicate similar patterns despite radically varying times spent on the course.

It shows that weekly assignments and some e-activities tend to use up the majority of the student’s time on the course. Meanwhile, weekly discussions are commonly overlooked and not given much time, even by more engaged students. Furthermore, additional activities, class introductions, and supporting resources are extremely underutilized. This is an indicator that students choose to focus primarily on grade activities but have little incentive or interest to engage with the online course as a whole.

Areas of Improvement

The first area of improvement necessary based on the reports is consistent student engagement. The phenomena observed in this LMS are consistent with the challenges that others face regarding user visitation and time spent on the platform. Tendencies demonstrate a decrease in activity throughout the week and usage spikes before exams or assignment submission dates as well as a disparity among students with many showing little activity while a few spending extensive time on the platform (Hershkovitz & Nachmias, 2010). As a result, the patterns of online activity are inconsistent.

The goal is to achieve higher persistence of use and retain user rates at a level that shows more consistency and motivation. This includes equalizing time spent on the platform by facilitating more participation in blended learning.

The second area of improvement is student motivation for participation in a wider range of course activities, including those beyond the graded assignments, and utilization of supporting learning resources. Predicting low engagement allows instructors to understand student behavior. Research demonstrates that comprehensive student participation in LMS activities, including course content, discussion forums, and supporting resources results in positive engagement and scores in the course (Hussain, Zhu, Zhang, & Abidi, 2018).

To maintain engagement and attention span of students in a digitized highly competitive world, the platform needs to be versatile with a holistic approach to learning. Strategies for improving these aspects range from layout and activity types to learning visual stimulation and social experiences which would facilitate a more equally distributed time spent on assignments and utilization of the majority of resources.

A recommended change to improving participation in the course and increase eLearning competency is to introduce teamwork as part of the activities and performance objectives for the students. The cooperative model of learning states that better outcomes are produced when small groups of students exchange information and engage in debate. It allows students to build mental models that help in learning as well as developing teamwork competency. The LMS helps to facilitate user interaction and provide an enhanced method of teamwork through various activities that demonstrate group evidence in an online format (Fidalgo-Blanco, Sein-Echaluce, García-Peñalvo, & Conde, 2015).

For example, a more social approach to discussion forums may be viable along with large projects such as producing a wiki on the studied concepts. Another aspect to help better time management concerning assignments is to implement periodic deadlines throughout the week for various parts of the week’s assignments. This ensures that the majority of LMS utilization is not spent on the weekends attempting to cram it in, but rather introduce a spread-out model of learning with assignment submissions throughout the week…

Increasing engagement can be challenging, particularly if a course is on concepts that are not easily interpreted. Suggested improvement for engagement of activities is to introduce socialization and gamification of the learning environment to increase effectiveness. Gamification has been proven to create necessary conditions for student motivations by transforming education into a game of some sort (Kirillov, Vinichenko, Melnichuk, Melnichuk, & Vinogradova, 2016).

The adoption of learning material is better when participating in a game environment since students see a decreased level of stress due to the lack of worrying about grades and evaluations. Instead, there is an evident behavior change that promotes the formation of habits and knowledge patterns with a burst of positive emotions as well as a better understanding of concepts that they can apply in-game scenarios (Kirillov et al., 2016). In combination with the socialization and teamwork aspect described above, students will most likely demonstrate a better engagement with the LMS, not only in the gamified material but the rest of the course concepts as well.

Targeted Report

A learning progress and performance report is an important targeted report that would benefit from analysis and help further improve the LMS. It would enable tracking of completion rates as well as average scores for students on the online course. This would help identify several aspects such as the progress that students are making on specific parts of the course, thus showing whether they are falling behind or getting ahead as well as topics of difficulty where students may require more time than usual. Meanwhile, a performance report would demonstrate the results of graded assignments, creating a matrix of average scores.

An instructor can use this to gauge the difficulty of assignments based on their type and topic. It can enhance the learning process since additional material can be added to supplement the activities or more time spent in the online course or real-life instructional time to understanding a specific concept. Therefore, progress and performance reports can serve as a vital tool to not only improve the LMS but enhance the instructional capabilities that will be reflected in the content.

Conclusion

LMS analytical reports are critical tools in identifying patterns of use, student engagement, and other data which are important to instructors and administrators of the system. In this paper, it was identified that students often demonstrated inconsistent patterns of use, lack of engagement with some of the material, and significant disparity in participation. Solutions were offered regarding making the content more game-like, social, and implementing deadlines that would spread out the workload. Overall, it is vital to continue examining LMS reports with targeted analytics such as progress and performance that can greatly benefit instructors in improving the course.

References

Fidalgo-Blanco, Á, Sein-Echaluce, M. L., García-Peñalvo, F. J., & Conde, M. Á. (2015). Using learning analytics to improve teamwork assessment. Computers in Human Behavior, 47, 149-156. Web.

Hershkovitz, A., & Nachmias, R. (2010). Is students’ activity in LMS persistent? Web.

Hussain, M., Zhu, W., Zhang, W., & Abidi, S. M. (2018). Student engagement predictions in an e-learning system and their impact on student course assessment scores. Computational Intelligence and Neuroscience, 1-21. Web.

Kirillov, A. V., Vinichenko, M. V., Melnichuk, A. V., Melnichuk, Y. A., & Vinogradova, M. V. (2016). . International Electronic Journal of Mathematics Education, 11(7), 2071-2085. Web.

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