Desperately seeking the impact of learning analytics in education at scale: Marrying data analysis with teaching and learning

• URL: http://arxiv.org/abs/2105.06680v1
• Date: Fri, 14 May 2021 07:33:17 GMT
• Title: Desperately seeking the impact of learning analytics in education at scale: Marrying data analysis with teaching and learning
• Authors: Olga Viberg, Ake Gronlund
• Abstract summary: 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.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Learning analytics (LA) is argued to be able to improve learning outcomes, learner support and teaching. However, despite an increasingly expanding amount of student (digital) data accessible from various online education and learning platforms and the growing interest in LA worldwide as well as considerable research efforts already made, there is still little empirical evidence of impact on practice that shows the effectiveness of LA in education settings. Based on a selection of theoretical and empirical research, this chapter provides a critical discussion about the possibilities of collecting and using student data as well as barriers and challenges to overcome in providing data-informed support to educators' everyday teaching practices. We argue that in order to increase the impact of data-driven decision-making aimed at students' improved learning in education at scale, we need to better understand educators' needs, their teaching practices and the context in which these practices occur, and how to support them in developing relevant knowledge, strategies and skills to facilitate the data-informed process of digitalization of education.

Related papers

• Revolutionising Role-Playing Games with ChatGPT [0.0]
  The aim of the study was to analyse the impact of AI-based simulations on students' learning experience. Based on Vygotsky's sociocultural theory, ChatGPT was used to give students a deeper understanding of strategic decision-making processes.
  arXiv  Detail & Related papers  (2024-07-02T08:21:40Z)
• Large Language Models for Education: A Survey and Outlook [69.02214694865229]
  We systematically review the technological advancements in each perspective, organize related datasets and benchmarks, and identify the risks and challenges associated with deploying LLMs in education. Our survey aims to provide a comprehensive technological picture for educators, researchers, and policymakers to harness the power of LLMs to revolutionize educational practices and foster a more effective personalized learning environment.
  arXiv  Detail & Related papers  (2024-03-26T21:04:29Z)
• Bringing Generative AI to Adaptive Learning in Education [58.690250000579496]
  We shed light on the intersectional studies of generative AI and adaptive learning. We argue that this union will contribute significantly to the development of the next-stage learning format in education.
  arXiv  Detail & Related papers  (2024-02-02T23:54:51Z)
• Revealing Networks: Understanding Effective Teacher Practices in AI-Supported Classrooms using Transmodal Ordered Network Analysis [0.9187505256430948]
  The present study uses transmodal ordered network analysis to understand effective teacher practices in relationship to traditional metrics of in-system learning in a mathematics classroom working with AI tutors. Comparing teacher practices by student learning rates, we find that students with low learning rates exhibited more hint use after monitoring. Students with low learning rates showed learning behavior similar to their high learning rate peers, achieving repeated correct attempts in the tutor.
  arXiv  Detail & Related papers  (2023-12-17T21:50:02Z)
• Integrating AI and Learning Analytics for Data-Driven Pedagogical Decisions and Personalized Interventions in Education [0.30723404270319693]
  This research study delves into the conceptualization, development, and deployment of an innovative learning analytics tool. This tool is designed to quantify student engagement, map learning progression, and evaluate the efficacy of diverse instructional strategies.
  arXiv  Detail & Related papers  (2023-12-15T06:00:26Z)
• Comparative Study of Learning Outcomes for Online Learning Platforms [47.5164159412965]
  Personalization and active learning are key aspects to successful learning. We run a comparative head-to-head study of learning outcomes for two popular online learning platforms.
  arXiv  Detail & Related papers  (2021-04-15T20:40:24Z)
• 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)
• Transfer Learning in Deep Reinforcement Learning: A Survey [64.36174156782333]
  Reinforcement learning is a learning paradigm for solving sequential decision-making problems. Recent years have witnessed remarkable progress in reinforcement learning upon the fast development of deep neural networks. transfer learning has arisen to tackle various challenges faced by reinforcement learning.
  arXiv  Detail & Related papers  (2020-09-16T18:38:54Z)
• Key principles for workforce upskilling via online learning: a learning analytics study of a professional course in additive manufacturing [2.014343808433054]
  This study combines learning objective analysis and visual learning analytics to examine the relationships among learning trajectories, engagement, and performance. The study also emphasizes broader strategies for course designers and instructors to align course assignments, learning objectives, and assessment measures with learner needs and interests.
  arXiv  Detail & Related papers  (2020-08-15T00:30:56Z)
• SARS-CoV-2 Impact on Online Teaching Methodologies and the Ed-Tech Sector: Smile and Learn Platform Case Study [50.591267188664666]
  The study analyzes the importance of online methodologies and usage tendency of an educational resource example: The Smile and Learn platform. Thereby, the study presents the different models implemented to support education and its impact in the use of the platform.
  arXiv  Detail & Related papers  (2020-07-15T10:06:51Z)

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.