Farhana Sarker

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The ability to predict students’ mark could be useful in a great number of different ways associated with university-level learning. In this study, student’s mark prediction models have been developed using institutional internal databases and external open data sources. The results of empirical study for undergraduate students’ first year mark prediction(More)
Higher education institutions are large, complex, adaptive social systems like all other human organizations. Over the last decade, Higher Education around the world is facing a number of challenges and potential threats to effective learning and teaching support. In recent years considerable interest has focused on identifying those challenges, identifying(More)
Research in student retention and progression to completion is traditionally survey-based, where researchers collect data through questionnaires and interviewing students. The major issues with survey-based study are the potentially low response rates and cost. Nevertheless, a large number of datasets that could inform the questions that students are(More)
Research in student retention is traditionally survey-based, where researchers use questionnaires to collect student data to analyse and to develop student predictive model. The major issues with survey-based study are the potentially low response rates, time consuming and costly. Nevertheless, a large number of datasets that could inform the questions that(More)
This paper presents a new segment and semi circle based model (S-SCBM) to write Bangla vowel characters. All vowel characters are formulated by using arc(s), line(s) and segment(s). Here an efficient method for segment and semi circle based character recognition has been implemented. For character recognition, required features are number of line(s), arc(s)(More)
In this paper a pronunciation error detection system was modeled and also tested for large vocabulary, speaker independent and continuous speech recognizer for Bengali language. The recognizer was developed using Hidden Markov Model (HMM); and the Hidden Markov Modeling Toolkit was used to implement it. In the process, a corpus database comprised of 3000(More)
Smart-NDA is a cloud based, automated framework for screening neurodevelopmental disorder for the children of age 0 to 60 months. It is not possible to cure neurodevelopmental disorder fully but sometimes, early detection leaves an opportunity to improve the condition through proper initiatives. In Bangladesh, due to lack of awareness, resources, and(More)
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