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Research Paper | Information Technology | Kenya | Volume 8 Issue 1, January 2019
Social Software Learnability Index
Abstract: Social software, they bring people into creative interaction with one another, making the web an online meeting place where anyone can connect and collaborate with others it also enhances communication the user is able to post team updates and brainstorm on content ideas in an open, collaborative and searchable environment is well worth for different users. The paper evaluates the utilization of mobile social software and the need for social softwares to provide customization in order to enhance software learnability. A sample of 340 respondents was selected. The data was collected through the use of interview and questionnaires targeting mobile social users in Kericho County Kenya. The researched randomly sampled WhatsApp, Facebook, and Twitter as softwares used in this study. Descriptive statistics were used to analyze the data The finding indicated that It was also observed that a majority of Facebook users used the software to meet new friends commanding 38.8 %. This was followed by WhatsApp and Twitter at 22.6 % and 2.8 % respectively.34.8 % of the respondents affirmed that they frequently use the Facebook software in uploading and downloading items on social media followed by WhatsApp and Twitter with 16.2 % and 6.7 % respectively. Regarding customization 58.0 % avowed that customization does not create errors in WhatsApp as compared to Facebook and Twitter mobile social softwares. However, 36.5 % contested that customization does not downgrade the performance of the software Learnability can be optimized by creating simple user interface designs that are predictable in layout and navigation.
Keywords: Learnability, utilization, customization
Edition: Volume 8 Issue 1, January 2019,
Pages: 1137 - 1142
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Research Paper, Information Technology, Kenya, Volume 8 Issue 8, August 2019
Pages: 1825 - 1829The Social Software Learnability Prediction (SSLP) Tool
Masese. B. Nelson
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Research Paper, Information Technology, Kenya, Volume 6 Issue 10, October 2017
Pages: 1527 - 1533Interface Features, Program Complexity and Memorability as Indicators of Learnability of Mobile Social Software
Nelson Bogomba Masese [3] | Geoffrey Muchiri Muketha [2] | Samuel Mungai Mbuguah