Books and Book Chapters

Permanent URI for this collectionhttps://repository.must.ac.tz/handle/123456789/82

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    Development of Learning Analytics Tool to Examine Students’ Activities in Moodle Learning Management System A Case Of Mbeya University Of Science And Technology
    (University Of Dar Es Salaam, 2016) Mwalumbwe, Imani
    The past decade has seen the rapid adoption and use of various Learning Management Systems (LMS) in Africa, and Tanzania in particular. Institutions have been spending thousands of dollars to implement these systems in a bid to improve the quality of education as well as increasing students’ enrolments through distance education. However, the impact of these systems on improving students’ learning has been a popular subject of research in recent years. Studies have been relying on data from users’ opinions and subjective interpretation through surveys to determine the effectiveness of LMS usage on students’ learning performance. The use of such data is normally subject to the possibility of distortion or low reliability. Therefore, this study designed and developed Learning Analytics tool and used it to determine the causation between LMS usage and students’ performance. Data from LMS log of three courses namely Applied Biology I, Services and Installation II and Advanced CAD I, delivered at Mbeya University of Science and Technology (MUST) were extracted using developed Learning Analytics tool and subjected into linear regression analysis with students’ final scores. The study found that discussion posts, peer interaction, and exercises were determined to be significant factors for students’ academic achievement in blended learning at MUST with forum posts being the leading with beta values of 77, 48.5 and 16.3 percent respectively. Nonetheless, time spend in the LMS, number of downloads, and login frequency were found to have no significant impact on students’ learning performance. The results of this study provide a new understanding on factors that contribute towards students’ performance in courses offered via the LMS.
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    Quantifying the Public Health Effects of Vaccine Hesitancy and Delays in Screening Clinically Infected Patients: Insights From a COVID-19 Transmission Model
    (IJMSO, 2025-05-14) Lolika, Paride O,; Mlyashimbi Helikumi,; Kenneth Sube,; Steady Mushayabasa
    Motivated by the recent COVID-19 outbreak, we develop a time delay infectious disease model that incorporates vaccination and screening of clinically infected patients and calibrate it using Chinese data to understand the quantitative implications of vaccine hesitancy and delay in the screening of clinically infected patients. Vaccine hesitancy refers to the denial or delay in acceptance of vaccines despite their availability. Understanding the implications of vaccine hesitancy is therefore essential for designing public health interventions. Analysis of the model revealed that whenever R0 ≤ 1, there exists a globally asymptotically disease-free equilibrium. However, whenever R0 > 1, there exists a unique endemic equilibrium which is globally asymptotically stable. In addition, results also show that vaccine hesitancy and delay in hospitalizing clinically infected patients have a stronger impact on the deaths toll and new infections generated [1,2]. Vaccine hesitancy and delayed screening of clinically infected patients lead to harmonic oscillations in deaths and new cases, which, however, die out over time. Our findings underscore the importance of including vaccine hesitancy and delay in hospitalizing clinically infected patients in the design of control strategies for infectious diseases