scholarly journals A Cognitive Diagnostic Module Based on the Repair Theory for a Personalized User Experience in E-Learning Software

Computers ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 140
Author(s):  
Akrivi Krouska ◽  
Christos Troussas ◽  
Cleo Sgouropoulou

This paper presents a novel cognitive diagnostic module which is incorporated in e-learning software for the tutoring of the markup language HTML. The system is responsible for detecting the learners’ cognitive bugs and delivering personalized guidance. The novelty of this approach is that it is based on the Repair theory that incorporates additional features, such as student negligence and test completion times, in its diagnostic mechanism; also, it employs a recommender module that suggests students optimal learning paths based on their misconceptions using descriptive test feedback and adaptability of learning content. Considering the Repair theory, the diagnostic mechanism uses a library of error correction rules to explain the cause of errors observed by the student during the assessment. This library covers common errors, creating a hypothesis space in that way. Therefore, the test items are expanded, so that they belong to the hypothesis space. Both the system and the cognitive diagnostic tool were evaluated with promising results, showing that they offer a personalized experience to learners.

Author(s):  
David Wright

The network marketing industry with its need to train home-based workers is in a unique position to benefit from e-learning. The large numbers of people involved with this industry creates a significant demand from the viewpoint of creators of e-learning content and the providers of e-learning software and services. This article identifies the fit of e-learning within the network marketing industry and the consequent benefits to network marketers and to e-learning developers. It is an updated version of an earlier article, Hugli and Wright (2000).


Author(s):  
Tim de Jong ◽  
Alba Fuertes ◽  
Tally Schmeits ◽  
Marcus Specht

This chapter describes a multi-platform extension of learning networks. In addition to Web- and desktopbased access, the authors propose to provide mobile, contextualised learning content delivery, and creation. The extension to a multi-platform extension is portrayed as follows. First, the authors give a description of learning networks, the kind of learning focused at, and the mechanisms that are used for learner support. After that, they illustrate a possible extension to contextualised, more authentic forms of learning mediated by mobile devices. Moreover, they give some requirements for a multi-platform learning network system and describe a technical framework integrating contextualised media with learning networks. Two blended learning scenarios are given as examples of how the extended system could be used in practice. Last, the conclusions and outlook describe what is necessary to integrate multi-platform e-learning software in existing learning scenarios, and how a larger-scale adaptation can be achieved.


1992 ◽  
Vol 21 (2) ◽  
pp. 151-160 ◽  
Author(s):  
Michael G. Aamodt ◽  
Teige McShane

The current study reported the results of a meta-analytic investigation of the effects on test scores and test completion times of three aspects of writing test items: The number of answers in multiple-choice exams, the order of item difficulty, and the organization of items by content. The results of meta-analysis indicated that three-choice questions are slightly easier than four-choice questions (d = .90) and take significantly less time to complete (d = −.61). Exams beginning with easier items and then moving to more difficult items are slightly easier than exams with randomly ordered items (d = .11) or exams beginning with difficult items (d — .22). Exams in which the items are organized by content are slightly easier than exams containing randomly ordered items (d = .04). All of the above effect sizes are small.


2021 ◽  
Vol 16 (24) ◽  
pp. 205-219
Author(s):  
Emil Hadzhikolev ◽  
Stanka Hadzhikoleva ◽  
Hristo Hristov ◽  
Emil Yonchev ◽  
Vladimir Tsvetkov

Pedagogical patterns describe teaching ideas that can be applied in different ways in teaching in different disciplines, and for different types of students. They are a tool for sharing experience and good practices between teachers. The use of pedagogical patterns in online learning is a challenge that can be met by using an appropriate software system for learning management. The article proposes a model of educational objects, suitable for software imple-mentation, which we call pedagogical pattern instances, or for short - in-stances. One instance combines specific learning content with additional fea-tures. Learning content can have different “views” that present knowledge in different ways, for example, through text files of presentations, audio or video content, interactive content, etc. Logical categories of characteristics and activities form the “aspects” of the instance, such as methodology, adap-tivity, assessment, etc. The proposed pattern instance model is flexible. It can be expanded with new features and adapted to specific goals and designs. The paper also outlines a conceptual framework of an e-learning software system using the presented model of a pattern instance.


2010 ◽  
Vol 14 (3) ◽  
Author(s):  
Xin Bai ◽  
Michael B. Smith

Educational technology is developing rapidly, making education more accessible, affordable, adaptable, and equitable. Students now have the option to choose a campus that can provide excellent blended learning curriculum with minimal geographical restraints. We proactively explore ways to maximize the power of educational technologies to increase enrollment, reduce failure rates, improve teaching efficiency, and cut costs without sacrificing high quality or placing extra burden on faculty. This mission is accomplished through open source learning content design and development. We developed scalable, shareable, and sustainable e-learning modules as book chapters that can be distributed through both computers and mobile devices. The resulting e-learning building blocks can automate the assessment processes, provide just-in-time feedback, and adjust the teaching material dynamically based upon each student’s strengths and weaknesses. Once built, these self-contained learning modules can be easily maintained, shared, and re-purposed, thus cutting costs in the long run. This will encourage faculty from different disciplines to share their best teaching practices online. The end result of the project is a sustainable knowledge base that can grow over time, benefit all the discipline, and promote learning.


2018 ◽  
Vol 9 (1) ◽  
pp. 119-124 ◽  
Author(s):  
Todorka Terzieva ◽  
◽  
Asen Rahnev ◽  
Anatoli Karabov ◽  
◽  
...  

2021 ◽  
Author(s):  
Tibor Guzsvinecz ◽  
Éva Orbán-Mihálykó ◽  
Cecília Sik-Lányi ◽  
Erika Perge

AbstractThe interaction time of students who did spatial ability tests in a virtual reality environment is analyzed. The spatial ability test completion times of 240 and 61 students were measured. A desktop display as well as the Gear VR were used by the former group and by the latter one, respectively. Logistic regression analysis was used to investigate the relationship between the probability of correct answers and completion times, while linear regression was used to evaluate effects and interactions of following factors on test completion times: the users’ gender and primary hand, test type and device used. The findings were that while the completion times are not significantly affected by the users’ primary hand, other factors have significant effects on them: they are decreased by the male gender in itself, while they are increased by solving Mental Rotation Tests or by using the Gear VR. The largest significant increment in interaction time in virtual reality during spatial ability tests is when Mental Rotation Tests are accomplished by males with the Gear VR, while the largest significant decrease in interaction time is when Mental Cutting Tests are completed with a desktop display.


2021 ◽  
Author(s):  
S.C.M. de S Sirisuriya ◽  
L. Ranathunge ◽  
S.P. Karunanayake ◽  
N. A. Abdullah

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