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Browsing Research Articles by Author "Andogah, Geoffrey"
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Item Mobile devices for learning in universities: challenges and effects of usage.(International Journal of Scientific Engineering and Science, 2018) Businge, Phelix Mbabazi; Guma, Ali; Andogah, Geoffrey; Nkamwesiga, LawrenceMobile devices are no longer playing the role of voice or short message communication but also in learning. These devices allow students to interact with educational content and learning can occur regardless of their location. It is therefore important to establish the factors hindering the use of Mobile devices for learning in Universities: A Case of Muni University. The study answered research questions such as; (a) what are the negative effects of using Mobile devices during lectures for other activities not related to the Lecture? (b) what are the reactions of lecturers towards the use of Mobile devices during lecture time? which factors are hindering the use of Mobile devices for learning? Quantitative design was employed using questionnaires containing a Five (5) Point Likert scale items ranging from strongly agree, agree, neutral, disagree, and strongly disagree and open-ended items were utilized in this study to obtain quantitative information to answer the research questions: A total population of 331 was considered and sample size of 181 was obtained using Krejcie and Morgan table. Stratified sampling was used to collect data from each stratum and data was analyzed using SPSS Version 20. The reliability of the data collected was tested using the Cronbach's reliability test coefficient were the overall value of all the options was on average 0.67 which was beyond recommended Cronbach’s Alpha coefficient values 0.6 for an instrument to be declared reliable. In terms of ascertaining the negative effects of using Mobile devices during lectures for other activities to the related Lecture, students agreed that it distract students' attention, disturb other students, disturbs the instructors and the course of the lesson and reflects disrespect for the instructor. The findings also agreed that the following were ranked among top five (5) factors hindering the use of Mobile devices for learning: Lack of mobile devices, Slow Speed of the mobile devices, Power problems, Network Connections Issues and Battery problem but disagreed that the course is not suited for mobile devices, lack of interest and complicated to use. This study recommended that mobile devices should be encouraged, allow students to use Mobile devices according to lesson’s topics since students disagreed that lack of interest is not hindering the use of mobile devices, discourage students from using Mobile devices in class for other activities not related to the topic and formulate the usability policy of mobile devices.Item Reviewing the pertinence of Sentinel-1 SAR for urban land use land cover classification(International Journal of Scientific & Engineering Research, 2020-05) Abudu, Dan; Parvin, Nigar Sultana; Andogah, GeoffreyConventional approaches for urban land use land cover classification and quantification of land use changes have often relied on the ground surveys and urban censuses of urban surface properties. Advent of Remote Sensing technology supporting metric to centimetric spatial resolutions with simultaneous wide coverage, significantly reduced huge operational costs previously encountered using ground surveys. Weather, sensor’s spatial resolution and the complex compositions of urban areas comprising concrete, metallic, water, bare- and vegetation-covers, limits Remote Sensing ability to accurately discriminate urban features. The launch of Sentinel-1 Synthetic Aperture Radar, which operates at metric resolution and microwave frequencies evades the weather limitations and has been reported to accurately quantify urban compositions. This paper assessed the feasibility of Sentinel-1 SAR data for urban land use land cover classification by reviewing research papers that utilised these data. The review found that since 2014, 11 studies have specifically utilised the datasets. The reviewed studies demonstrated that, features representing urban topography such as morphology and texture can easily and accurately be extracted from Sentinel-1 SAR and subjected to state-of-the-art classification algorithms such as Support Vector Machine and ensemble Decision Trees for accurate urban land use land cover classification. Development of robust algorithms to deal with the complexities of SAR imagery is still an active research area. Furthermore, augmentation of SAR with optical imagery is required especially for classification accuracy assessments.Item Spatial assessment of urban sprawl in Arua Municipality, Uganda(The Egyptian Journal of Remote Sensing and Space Science, 2019-12) Abudu, Dan; Echima, Robert Azo; Andogah, GeoffreyArua Municipality is one of the regional municipalities that has been earmarked for transformation to city status. Its population has been growing at rate of 3% per annum 1% higher than the capital, Kampala. Urbanisation provides economic opportunities. However, it also lead to emergence of unplanned urban settlements and urban sprawl. This paper applied remote sensing and geographical information system techniques to map land cover changes from 2001 to 2016, quantify urban sprawl within the period and estimate the urban growth pattern up to 2031. TerrSet’s Land Change Modeller has been used to model the urbanisation and Markov Chain matrices used to predict future changes in the urban composition. Land cover classification accuracy of 85% in 2001, 84% in 2010 and 89.2% in 2016 were obtained. From 2001 to 2016, the four land cover types considered, contributed a total of 11.5% to the composition of built-up area with agricultural land cover type contributing the most at 7.4%. Results of urbanisation analyses indicated that in 2001, 18.2% of the total area were built-up. This increased to 28.8% in 2010 and 40.9% in 2016. Urbanisation is predicted to increase to 57.4% by the year 2031. This prediction indicates that agricultural land cover will be most negatively affected at _10% loss rate while built-up areas will increase by 6%. While urbanisation continues to increase at this rate, the municipal authority must implement sustainable measures to protect agricultural lands and ecosystems against the land consuming urbanisation.Item Use of mobile devices by students to support learning in universities: a case of Muni university(International Journal of Research in Engineering & Technology, 2017-06) Guma, Ali; Businge, Phelix Mbabazi; Nkamwesiga, Lawrence; Andogah, GeoffreyIt’s a requirement in admission for every student to come with a mobile device for any programme admitted. The main objective of this study was to establish how the students use mobile devices in lecture rooms /classroom this was achieved by answering the following research questions: which mobile devices are owned by students? what are benefits of using mobile devices by students?and how mobile devices are used for learning?Quantitative design was employed using questionnaires containing a five (5) Likert scale items ranging from strongly agree, agree, neutral, disagree-strongly disagree and open-ended items was utilized in this study to obtain quantitative information to answer the research questions: A total population of 331 was considered and sample size of 181 was obtained using Krejcie and Morgan table, stratified sampling was used to collect data from each stratum and data was analyzed using SPSS Version 16. The reliability of the data collected was tested using the Cronbach's reliability test coefficient where the overall value of all the options was on average 0.65 which was beyond recommended 0.6 for an instrument to be declared reliable. The findings showed that, 56.2% (91) respondents use smart phones, 40.7 %( 66) use Laptops in class and only 1.2 %( 2) use kindle in class room while no student indicated that he/she uses Ipad or PDA in classroom or lecture room. In terms of the benefits of using mobile devices, students the following among the top four (4) benefits; easy to access information, storage of information, mobility of the device and use of social media but cost effective and security of information were ranked last. The findings also showed students use mobile devices to access course materials, doing class work, send and receive e-mails and taking and sharing of notes but virtual classroom, discussion forums and using pre-recorded lecturers with PowerPoint were ranked among the last three (3). This study recommends that Smartphone’s and mobile devices should be allowed to use by students, lecturer to start virtual classroom, discussion forums and using pre-recorded lecturers with PowerPoint so that the students can also benefit from these functionalities since they were ranked among the last three(3) services not used.