The Commodification of Open Educational Resources for Teaching and Learning by Academics in an Open Distance e-Learning Institution

• URL: http://arxiv.org/abs/2108.09938v1
• Date: Mon, 23 Aug 2021 05:17:47 GMT
• Title: The Commodification of Open Educational Resources for Teaching and Learning by Academics in an Open Distance e-Learning Institution
• Authors: Lancelord Siphamandla Mncube, Maureen Tanner and Wallace Chigona
• Abstract summary: The use of open educational resources (OER) is gaining momentum in higher education institutions. This study sought to establish academics' perceptions and knowledge of OER for teaching and learning in an open distance e-learning university. The study found that academics with prior experience and knowledge of OER are more successful in the use of these resources for teaching, learning, and research.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: The use of open educational resources (OER) is gaining momentum in higher education institutions. This study sought to establish academics' perceptions and knowledge of OER for teaching and learning in an open distance e-learning (ODeL) university. The study also sought to establish how perceptions are formed. The inductive approach followed the lens of commodification to answer the research questions. The commodification phase allowed for a better understanding of the academics' prior knowledge, informers, academics behaviour about OER, and how they perceived OER to be useful for teaching and learning. The study employed a qualitative method, with semi-structured interviews to collect data. The study found that academics with prior experience and knowledge of OER are more successful in the use of these resources for teaching, learning, and research. OER is also perceived as a useful tool to promote African knowledge, showcase the contributions of African academics, improve academic research capabilities, improve student's success rate, particularly for financially vulnerable students. Based on the acquired perceptions, the study able to propose a new guideline to formulate user perceptions. However, this can only be achieved through a solid OER policy with the support of government and tertiary institution top management. The findings may inform higher education institutions when they consider the development of OER strategies and policies, especially in response to the Covid-19 emergency online learning transition.

Related papers

• Explainable Few-shot Knowledge Tracing [48.877979333221326]
  We propose a cognition-guided framework that can track the student knowledge from a few student records while providing natural language explanations. Experimental results from three widely used datasets show that LLMs can perform comparable or superior to competitive deep knowledge tracing methods.
  arXiv  Detail & Related papers  (2024-05-23T10:07:21Z)
• The Perceived Learning Behaviors and Assessment Techniques of First-Year Students in Computer Science: An Empirical Study [0.0]
  Students believe that in-person instruction is the most effective way to learn. For evaluation methods, there is a preference for practical and written examinations.
  arXiv  Detail & Related papers  (2024-05-10T08:45:32Z)
• Knowledge Tracing Challenge: Optimal Activity Sequencing for Students [0.9814642627359286]
  Knowledge tracing is a method used in education to assess and track the acquisition of knowledge by individual learners. We will present the results of the implementation of two Knowledge Tracing algorithms on a newly released dataset as part of the AAAI2023 Global Knowledge Tracing Challenge.
  arXiv  Detail & Related papers  (2023-11-13T16:28:34Z)
• Exploring the Cognitive Knowledge Structure of Large Language Models: An Educational Diagnostic Assessment Approach [50.125704610228254]
  Large Language Models (LLMs) have not only exhibited exceptional performance across various tasks, but also demonstrated sparks of intelligence. Recent studies have focused on assessing their capabilities on human exams and revealed their impressive competence in different domains. We conduct an evaluation using MoocRadar, a meticulously annotated human test dataset based on Bloom taxonomy.
  arXiv  Detail & Related papers  (2023-10-12T09:55:45Z)
• Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators [78.63553017938911]
  Large language models (LLMs) outperform information retrieval techniques for downstream knowledge-intensive tasks. However, community concerns abound regarding the factuality and potential implications of using this uncensored knowledge. We introduce CONNER, designed to evaluate generated knowledge from six important perspectives.
  arXiv  Detail & Related papers  (2023-10-11T08:22:37Z)
• A Machine Learning system to monitor student progress in educational institutes [0.0]
  We propose a data driven approach that makes use of Machine Learning techniques to generate a classifier called credit score. The proposal to use credit score as progress indicator is well suited to be used in a Learning Management System.
  arXiv  Detail & Related papers  (2022-11-02T08:24:08Z)
• Desperately seeking the impact of learning analytics in education at scale: Marrying data analysis with teaching and learning [0.0]
  Learning analytics (LA) is argued to be able to improve learning outcomes, learner support and teaching. There is still little empirical evidence of impact on practice that shows the effectiveness of LA in education settings. We argue that in order to increase the impact of data-driven decision-making aimed at students' improved learning at scale, we need to better understand educators' needs.
  arXiv  Detail & Related papers  (2021-05-14T07:33:17Z)
• Challenges of Applying E-Learning in the Libyan Higher Education System [5.607676459156789]
  This paper endeavors to find the obstacles that may face the adoption of E-learning in Libya. It highlights the potentials for the adoption of E-learning in the higher education system in Libya using both qualitative and quantitative approaches.
  arXiv  Detail & Related papers  (2021-02-17T03:20:46Z)
• KnowledgeCheckR: Intelligent Techniques for Counteracting Forgetting [52.623349754076024]
  We provide an overview of the recommendation approaches integrated in KnowledgeCheckR. Examples thereof are utility-based recommendation that helps to identify learning contents to be repeated in the future, collaborative filtering approaches that help to implement session-based recommendation, and content-based recommendation that supports intelligent question answering.
  arXiv  Detail & Related papers  (2021-02-15T20:06:28Z)
• 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)
• Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills [155.11646755470582]
  'Explore, Discover and Learn' (EDL) is an alternative approach to information-theoretic skill discovery. We show that EDL offers significant advantages, such as overcoming the coverage problem, reducing the dependence of learned skills on the initial state, and allowing the user to define a prior over which behaviors should be learned.
  arXiv  Detail & Related papers  (2020-02-10T10:49:53Z)

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.