Mobile Learning Application Development for Improvement of English Listening Comprehension
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 8
Abstract
Trend towards English language learning has been increased because it is considered as Lingua franca i.e. language of communication for all. However students of Pakistan are behind in this pace, especially rural elementary students. In rural areas there is crucial need to get assistance in their own curriculum after school because mostly they do not find anyone to help at home. M-Learning (Mobile Learning) assists learning anywhere and anytime. This ubiquitous power of M-Learning helps in after school programs and education in rural areas. The aim of this study is to develop M-Learning application for improvement of English listening comprehension in rural primary school students. This study developed English learning application based on Listening Comprehension, which embeds English curriculum of Sindh Textbook board for grade 1, 2 and 3. This study took the form of an after-school program in a village in Pakistan. There were 45 students of grade 3 from rural primary school of Pakistan selected as participants. Since developed application is based on recognition and memorization of information, so that knowledge and comprehension level of cognitive domain from Bloom’s taxonomy were selected for choosing the type of evaluation questions. On the basis of those question types, EGRA (Early Grade Reading Assessment) test is used for evaluation. This test was conducted on two experimental groups and one control group and the results of the groups were compared to one another. The results confirm that English M-learning applications can become helpful tool for students who live in rural areas where they face problems in learning of their English curriculum, since their relatives are not capable to teach them as accordingly.
Authors and Affiliations
Zahida Parveen Laghari, Hameedullah Kazi, Muhammad Ali Nizamani
Training an Agent for FPS Doom Game using Visual Reinforcement Learning and VizDoom
Because of the recent success and advancements in deep mind technologies, it is now used to train agents using deep learning for first-person shooter games that are often outperforming human players by means of only scre...
Analysis of the SNR Estimator for Speech Enhancement Using a Cascaded Linear Model
Elimination of tainted noise and improving the overall quality of a speech signal is speech enhancement. To gain the advantage of individual algorithms we propose a new linear model and that is in the form of cascade ada...
Performance Evaluation of Mesh-Based Multicast Routing Protocols in MaNETs
Multicasting is a challenging task that facilitates group communication among the nodes using the most efficient strategy to deliver the messages over each link of the network. In spite of significant research achievemen...
Developing Communication Strategy for Multi-Agent Systems with Incremental Fuzzy Model
Communication can guarantee the coordinated behavior in the multi-agent systems. However, in many real-world problems, communication may not be available at every time because of limited bandwidth, noisy environment or c...
A Fuzzy Rough Rule Based System Enhanced By Fuzzy Cellular Automata
Handling uncertain knowledge is a very tricky problem in the current world as the data, we deal with, is uncertain, incomplete and even inconsistent. Finding an efficient intelligent framework for this kind of knowledge...