Unveiling the Potential of Big Data Analytics for Transforming Higher Education in Bangladesh; Needs, Prospects, and Challenges

• URL: http://arxiv.org/abs/2311.10727v2
• Date: Fri, 24 Nov 2023 21:37:40 GMT
• Title: Unveiling the Potential of Big Data Analytics for Transforming Higher Education in Bangladesh; Needs, Prospects, and Challenges
• Authors: Sabbir Ahmed Chowdhury (1), Md Aminul Islam (2), Mostafa Azad Kamal (3), ((1) School of Education and Social Sciences, University of the West of Scotland, IER, University of Dhaka (2) School of Engineering, Computing and Mathematics, Oxford Brookes University, School of Computing and Technologies, University of Gloucestershire, UK (3) School of Business, Bangladesh Open University, Gazipur)
• Abstract summary: Big Data Analytics (BDA) can be a piece of the answer to accomplishing Bangladesh Higher Education (BHE) objectives. This paper reviews the capacity of BDA, considers possible applications in BHE, gives an insight into how to improve the quality of education or uncover additional values from the data generated by educational institutions.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Big Data Analytics has gained tremendous momentum in many sectors worldwide. Big Data has substantial influence in the field of Learning Analytics that may allow academic institutions to better understand the learners needs and proactively address them. Hence, it is essential to understand Big Data and its application. With the capability of Big Data to find a broad understanding of the scientific decision making process, Big Data Analytics (BDA) can be a piece of the answer to accomplishing Bangladesh Higher Education (BHE) objectives. This paper reviews the capacity of BDA, considers possible applications in BHE, gives an insight into how to improve the quality of education or uncover additional values from the data generated by educational institutions, and lastly, identifies needs and difficulties, opportunities, and some frameworks to probable implications about the BDA in BHE sector. Keywords; Big Data Analytics, Learning Analytics, Quality of Education, Challenges, Higher Education, Bangladesh

Related papers

• DSBench: How Far Are Data Science Agents to Becoming Data Science Experts? [58.330879414174476]
  We introduce DSBench, a benchmark designed to evaluate data science agents with realistic tasks. This benchmark includes 466 data analysis tasks and 74 data modeling tasks, sourced from Eloquence and Kaggle competitions. Our evaluation of state-of-the-art LLMs, LVLMs, and agents shows that they struggle with most tasks, with the best agent solving only 34.12% of data analysis tasks and achieving a 34.74% Relative Performance Gap (RPG)
  arXiv  Detail & Related papers  (2024-09-12T02:08:00Z)
• Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI [189.05642691423347]
  This paper revisits the strengths of Bayesian deep learning (BDL) and acknowledges existing challenges. It highlights some exciting research avenues aimed at addressing these obstacles. Looking ahead, the discussion focuses on possible ways to combine large-scale foundation models with BDL to unlock their full potential.
  arXiv  Detail & Related papers  (2024-02-01T17:45:26Z)
• Data-centric Artificial Intelligence: A Survey [47.24049907785989]
  Recently, the role of data in AI has been significantly magnified, giving rise to the emerging concept of data-centric AI. In this survey, we discuss the necessity of data-centric AI, followed by a holistic view of three general data-centric goals. We believe this is the first comprehensive survey that provides a global view of a spectrum of tasks across various stages of the data lifecycle.
  arXiv  Detail & Related papers  (2023-03-17T17:44:56Z)
• Data-centric AI: Perspectives and Challenges [51.70828802140165]
  Data-centric AI (DCAI) advocates a fundamental shift from model advancements to ensuring data quality and reliability. We bring together three general missions: training data development, inference data development, and data maintenance.
  arXiv  Detail & Related papers  (2023-01-12T05:28:59Z)
• Big Data and Analytics Implementation in Tertiary Institutions to Predict Students Performance in Nigeria [0.0]
  The term Big Data has been coined to refer to the gargantuan bulk of data that cannot be dealt with by traditional data-handling techniques. This paper explores the attributes of big data that are relevant to educational institutions. It investigates the factors influencing the adoption of big data and analytics in learning institutions.
  arXiv  Detail & Related papers  (2022-07-29T13:52:24Z)
• A Survey of Learning on Small Data: Generalization, Optimization, and Challenge [101.27154181792567]
  Learning on small data that approximates the generalization ability of big data is one of the ultimate purposes of AI. This survey follows the active sampling theory under a PAC framework to analyze the generalization error and label complexity of learning on small data. Multiple data applications that may benefit from efficient small data representation are surveyed.
  arXiv  Detail & Related papers  (2022-07-29T02:34:19Z)
• "If we didn't solve small data in the past, how can we solve Big Data today?" [0.0]
  We aim to research terms such as'small' and 'big' data, understand their attributes, and look at ways in which they can add value. Based on the research, it can be inferred that, regardless of how small data might have been used, organizations can still leverage big data with the right technology and business vision.
  arXiv  Detail & Related papers  (2021-11-08T16:31:01Z)
• Federated Learning for Big Data: A Survey on Opportunities, Applications, and Future Directions [5.124701758921822]
  We present a survey on the use of federated learning for big data services and applications. We review the use of FL for key big data services, including big data acquisition, big data storage, big data analytics, and big data privacy preservation.
  arXiv  Detail & Related papers  (2021-10-08T14:36:43Z)
• Personalized Education in the AI Era: What to Expect Next? [76.37000521334585]
  The objective of personalized learning is to design an effective knowledge acquisition track that matches the learner's strengths and bypasses her weaknesses to meet her desired goal. In recent years, the boost of artificial intelligence (AI) and machine learning (ML) has unfolded novel perspectives to enhance personalized education.
  arXiv  Detail & Related papers  (2021-01-19T12:23:32Z)
• From Data to Knowledge to Action: A Global Enabler for the 21st Century [26.32590947516587]
  A confluence of advances in the computer and mathematical sciences has unleashed unprecedented capabilities for enabling true evidence-based decision making. These capabilities are making possible the large-scale capture of data and the transformation of that data into insights and recommendations. The shift of commerce, science, education, art, and entertainment to the web makes available unprecedented quantities of structured and unstructured databases about human activities.
  arXiv  Detail & Related papers  (2020-07-31T19:19:42Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.