This research is a mixed method research using an explanatory design. The purpose of this study is to use Elista to assess a lecturer's response to thesis guidance based on the lecturer's gender. This study was condi-cted in Jambi University, involving 330 female and 359 male lecturers respectively. The sampling method used was purposive sampling technique, with the sample criterion being academics who became thesis su-pervisors. Interviews and surveys on Elista were conducted and the responses were gathered. The goal of this study is to establish a technology-based final project guidance system in which it is explored if the thesis supervisor's speedy response to guidance at Elista is affected by the gender of the thesis supervisor. The findings of the study demonstrate that female supervisors respond faster than male supervisors when em-ploying technology such as Elista to carry out the guidance procedure. Elista improves the effectiveness and efficiency of the guidance process between supervisors and students in terms of implementation.

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Current m-learning media are available in both native application and web-based application forms which create different user experience. Also, as the learners generally have diverse preferences and needs, a single style of m-learning may not meet such requirements. In order to formulate better and more attractive interaction between the learner and m-learning system, this study introduces augmented reality (AR) to both native and web applications as a means to improve captivation and create new user experience. A single group of learners is selected to try both types of application. The researcher groups the learner by learning style, using Felder-Silverman Learning Style Model, and then determines effectiveness of both forms of m-learning through an experiment. Experiment showed that all 4 learner groups were more satisfied with AR-enhanced native application based on user experience design due to its attractiveness and entertainment.

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