scholarly journals The Potential of Learning Analytics in Understanding Students’ Engagement with Their Assessment Feedback

2017 ◽  
Author(s):  
Mireilla Bikanga Ada ◽  
Mark Stansfield
Keyword(s):  
Learning Analytics ◽  
Assessment Feedback

Integrating Assessment, Feedback, and Learning Analytics in Educational Games

2019 ◽  
pp. 127-169
Author(s):  
Yaëlle Chaudy ◽  
Thomas M. Connolly
Keyword(s):  
Learning Process ◽  
Learning Analytics ◽  
Teaching And Learning ◽  
Assessment Tool ◽  
Educational Games ◽  
Assessment Process ◽  
Crucial Aspect ◽  
Assessment Feedback ◽  
Black Boxes ◽  
Literature Reviews

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.

Integrating Assessment, Feedback, and Learning Analytics in Educational Games

2022 ◽  
pp. 1803-1846
Author(s):  
Yaëlle Chaudy ◽  
Thomas M. Connolly
Keyword(s):  
Learning Process ◽  
Learning Analytics ◽  
Teaching And Learning ◽  
Assessment Tool ◽  
Educational Games ◽  
Assessment Process ◽  
Crucial Aspect ◽  
Assessment Feedback ◽  
Black Boxes ◽  
Literature Reviews

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.

scholarly journals Serious Games for education and training

2014 ◽  
Vol 1 (1) ◽  
Author(s):  
Alessandro De Gloria ◽  
Francesco Bellotti ◽  
Riccardo Berta
Keyword(s):  
Learning Analytics ◽  
Serious Games ◽  
Formal Education ◽  
State Of The Art ◽  
Situated Cognition ◽  
Digital Games ◽  
Future Research ◽  
Assessment Feedback ◽  
And Training ◽  
Education Process

Serious Games (SGs) are gaining an ever increasing interest for education and traning. Exploiting the latest simulation and visualization technologies, SGs are able to contextualize the player’s experience in challenging, realistic environments, supporting situated cognition. However, we still miss methods and tools for effectively and deeply infusing pedagogy and instruction inside digital games. After presenting an overview of the state of the art of the SG taxonomies, the paper introduces the pedagogical theories and models most relevant to SGs and their implications on SG design.  We also present a schema for a proper integration of games in education, supporting different goals in different steps of a formal education process. By analyzing a set of well-established SGs and formats, the paper presents the main mechanics and models that are being used in SG designs, with a particular focus on assessment, feedback and learning analytics. An overview of tools and models for SG design is also presented. Finally, based on the performed analysis, indications for future research in the field are provided.

Learning Analytics Considered Harmful

2012 ◽  
Vol 16 (3) ◽  
Author(s):  
Laurie P Dringus
Keyword(s):  
Big Data ◽  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Research Community ◽  
Current Status ◽  
Online Course ◽  
Full Potential

This essay is written to present a prospective stance on how learning analytics, as a core evaluative approach, must help instructors uncover the important trends and evidence of quality learner data in the online course. A critique is presented of strategic and tactical issues of learning analytics. The approach to the critique is taken through the lens of questioning the current status of applying learning analytics to online courses. The goal of the discussion is twofold: (1) to inform online learning practitioners (e.g., instructors and administrators) of the potential of learning analytics in online courses and (2) to broaden discussion in the research community about the advancement of learning analytics in online learning. In recognizing the full potential of formalizing big data in online coures, the community must address this issue also in the context of the potentially "harmful" application of learning analytics.

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