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ISSN:
2377-2891(Print); 2377-2905(Online)
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Bimonthly
Editor-in-Chief:
Prof. Eric C. K. Cheng
Associate Executive Editor:
Ms. Jenny Jiang
DOI:
10.18178/ijlt
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Editor-in-Chief
Prof. Eric C. K. Cheng
Professor & Vice President (Academic)
Yew Chung College of Early Childhood Education, Hong Kong, China
As the Editor-in-Chief of IJLT, I invite you to contribute your scholarly work to our esteemed publication. IJLT serves as a beacon for original and impactful academic contributions in the realm of education, fostering multidisciplinary research and development to enhance teaching-learning processes globally. We welcome submissions spanning a wide spectrum of topics, from innovative program development to the integration of digital tools in education. Our scope encompasses areas such as student leadership, diversity in education, and collaborative initiatives, reflecting our commitment to a sustainable and inclusive society. [
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2020
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Volume 6, No. 1, March 2020
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Assessment Innovation in Higher Education by Integrating Learning Analytics
Samaa Haniya
1
, Anastasia Olga Tzirides
1
, Keratso Georgiadou
2
, Matthew Montebello
3
, Mary Kalantzis
1
, and Bill Cope
1
1. University of Illinois Urbana-Champaign, USA
2. DUTH Greece
3. Department of Artificial Intelligence, University of Malta, Malta
Abstract
—With the rise of social networking sites and the arrival of an open education era characterized by Massive Open Online Courses MOOCs, learning is undergoing a paradigm shift which requires new assessment strategies. The boundaries between what we know, how we know it and the ways we assess and evaluate knowledge in formal and informal settings are now blurred [1], [2]. In these environments, students often interact with one another to produce and reproduce knowledge and transfer it into a new context to reach a mastery level of learning [3]. The massive amount of data being generated by learners makes it easier to assess performance than ever before [4], [5]. Every learner action is logged and factored in as a source of evidence to contribute to the overall learner assessment both from a summative perspective, and also in a formative way where immediate feedback is actionable. The integration of learning analytics tools and machine learning techniques can facilitate the process of assessment. In this paper we present a case study to show how the integration of learning analytics benefited learners and improved their performance in an online educational course at the University of Illinois Urbana-Champaign, while also holding them accountable for their own learning. The study utilized a survey method for data collection and quantitative and qualitative data analysis to interpret learners’ experiences after taking the course.
Index Terms
—assessment, learning analytics, big data, e-learning
Cite: Samaa Haniya, Anastasia Olga Tzirides, Keratso Georgiadou, Matthew Montebello, Mary Kalantzis, and Bill Cope, "Assessment Innovation in Higher Education by Integrating Learning Analytics," International Journal of Learning and Teaching, Vol. 6, No. 1, pp. 53-57, March 2020. doi: 10.18178/ijlt.6.1.53-57
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License (
CC BY-NC-ND 4.0
), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
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