scholarly journals ALAS-KA: A learning analytics extension for better understanding the learning process in the Khan Academy platform

2015 ◽  
Vol 47 ◽  
pp. 139-148 ◽  
Author(s):  
José A. Ruipérez-Valiente ◽  
Pedro J. Muñoz-Merino ◽  
Derick Leony ◽  
Carlos Delgado Kloos
2021 ◽  
pp. 146144482110127
Author(s):  
Marcus Carter ◽  
Ben Egliston

Virtual reality (VR) is an emerging technology with the potential to extract significantly more data about learners and the learning process. In this article, we present an analysis of how VR education technology companies frame, use and analyse this data. We found both an expansion and acceleration of what data are being collected about learners and how these data are being mobilised in potentially discriminatory and problematic ways. Beyond providing evidence for how VR represents an intensification of the datafication of education, we discuss three interrelated critical issues that are specific to VR: the fantasy that VR data is ‘perfect’, the datafication of soft-skills training, and the commercialisation and commodification of VR data. In the context of the issues identified, we caution the unregulated and uncritical application of learning analytics to the data that are collected from VR training.


2018 ◽  
Vol 7 (3) ◽  
pp. 1124 ◽  
Author(s):  
Andino Maseleno ◽  
Noraisikin Sabani ◽  
Miftachul Huda ◽  
Roslee Ahmad ◽  
Kamarul Azmi Jasmi ◽  
...  

This paper presents learning analytics as a mean to improve students’ learning. Most learning analytics tools are developed by in-house individual educational institutions to meet the specific needs of their students. Learning analytics is defined as a way to measure, collect, analyse and report data about learners and their context, for the purpose of understanding and optimizing learning. The paper concludes by highlighting framework of learning analytics in order to improve personalised learning. In addition, it is an endeavour to define the characterising features that represents the relationship between learning analytics and personalised learning environment. The paper proposes that learning analytics is dependent on personalised approach for both educators and students. From a learning perspective, students can be supported with specific learning process and reflection visualisation that compares their respective performances to the overall performance of a course. Furthermore, the learners may be provided with personalised recommendations for suitable learning resources, learning paths, or peer students through recommending system. The paper’s contribution to knowledge is in considering personalised learning within the context framework of learning analytics. 


Author(s):  
Yaëlle Chaudy ◽  
Thomas M. Connolly

Assessment is a crucial aspect of any teaching and learning process. New tools such as educational games offer promising advantages: they can personalize feedback to students and save educators time by automating the assessment process. However, while many teachers agree that educational games increase motivation, learning, and retention, few are ready to fully trust them as an assessment tool. A likely reason behind this lack of trust is that educational games are distributed as black boxes, unmodifiable by educators and not providing enough insight about the gameplay. This chapter presents three systematic literature reviews looking into the integration of assessment, feedback, and learning analytics in educational games. It then proposes a framework and present a fully developed engine. The engine is used by both developers and educators. Designed to separate game and assessment, it allows teachers to modify the assessment after distribution and visualize gameplay data via a learning analytics dashboard.


2022 ◽  
pp. 1803-1846
Author(s):  
Yaëlle Chaudy ◽  
Thomas M. Connolly

Assessment is a crucial aspect of any teaching and learning process. New tools such as educational games offer promising advantages: they can personalize feedback to students and save educators time by automating the assessment process. However, while many teachers agree that educational games increase motivation, learning, and retention, few are ready to fully trust them as an assessment tool. A likely reason behind this lack of trust is that educational games are distributed as black boxes, unmodifiable by educators and not providing enough insight about the gameplay. This chapter presents three systematic literature reviews looking into the integration of assessment, feedback, and learning analytics in educational games. It then proposes a framework and present a fully developed engine. The engine is used by both developers and educators. Designed to separate game and assessment, it allows teachers to modify the assessment after distribution and visualize gameplay data via a learning analytics dashboard.


Author(s):  
Ahmed Tlili ◽  
Fathi Essalmi ◽  
Mohamed Jemni ◽  
Professor Kinshuk ◽  
Nian-Shing Chen

Advances in technology have given the learning analytics (LA) area further potential to enhance the learning process by using methods and techniques that harness educational data. However, the lack of guidelines on what should be taken into considerations during application of LA hinders its full adoption. Therefore, this article investigates the issues that should be considered during the design of LA experience from the data use perspective. The results obtained present a validated LA framework which is composed of eighteen validated key issues that should be considered by various stakeholders in their contexts to enhance designing LA experiences. This framework can also be used by researchers and practitioners to learn more about LA and its designing issues.


2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Mireille Hildebrandt

This article introduces the special issue from SoLAR’s 2016 Learning Analytics and Knowledge conference. The field of learning analytics (LA) draws heavily on theory and practice from a range of diverse academic disciplines. In so doing, LA research embodies a rich integration of methodologies and practices, assumptions and theory to bring new insights into the learning process. Reflecting this rich diversity, the theme of LAK 2016 highlights the multidisciplinary nature of the field and embraces the convergence of these disciplines to provide theoretical and practical insights to challenge current thinking in the field.  This overview introduces six articles, each of which expands on an invited talk or paper from the conference, with the added goal of offering a small taste of the rich experience that comes from  active participation in the conference. 


i-com ◽  
2012 ◽  
Vol 11 (1) ◽  
pp. 22-25 ◽  
Author(s):  
Mohamed Amine Chatti ◽  
Anna Lea Dyckhoff ◽  
Ulrik Schroeder ◽  
Hendrik Thüs

Summary Learning analytics has attracted a great deal of attention in technology enhanced learning (TEL) in recent years as educational institutions and researchers are increasingly seeing the potential that learning analytics has to support the learning process. Learning analytics has been identified as a possible key future trend in learning and teaching (Johnson et al., 2011). Analytics can be a powerful tool to support learning. There are, however, a number of issues that need to be addressed before starting analytics projects. In this paper, we identify various challenges and research opportunities in the emerging area of learning analytics.


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