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

Krouska, Akrivi; Troussas, Christos; Sgouropoulou, Cleo

doi:10.3390/computers10110140

Cited by 13 publications

(7 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using the GBL approach to raise awareness of climate adaptation aims to increase motivation and increase people's engagement in a particular activity (Deen et al, 2015;Diab et al, 2020). The aim is to create an environment where mistakes do not have serious consequences and learning is encouraged (Krouska et al, 2021). However, this requires clear communication and follow-up, as Lewandowsky (2021) and Madani et al (2017) emphasize.…”

Section: Resistance To Changementioning

confidence: 99%

Adapting to climate change through play? Didactically effective elements of a business simulation game

Fischer,

Göhlich,

Schmitt

2024

Front. Educ.

View full text Add to dashboard Cite

IntroductionThe negative consequences of climate change are widespread and have a global impact. An industrialized region of Germany must adapt to the effects of climate change and comply with political regulations. Previous studies indicate that economic actors who are not directly affected by climate change approach climate change mitigation and adaptation primarily based on legal requirements and often feel discouraged by the absence of data-based reports. Addressing this challenge, game-based learning emerges as a promising pathway.MethodsTo examine game-based learning’s applicability and potential for climate adaptation, we developed a business simulation game, simultaneously identifying didactically effective elements for managers who would participate in it. Using expert interviews and focus groups, we conducted a qualitative study with three HR developers from larger companies and nine managers and founders of startups to develop a business simulation game on climate adaptation. Based on the Grounded Theory methodology, theoretical coding was used to analyze the qualitative data.ResultsThe derived core categories indicate that personnel development in companies is evolving in response to economic changes. Individual resources such as motivation (especially for managers), personnel and time play a crucial role in establishing a business game as an educational offering. The identified game elements can also be used theoretically and practically in the development of other educational games.DiscussionWe discussed common human resource development measures in companies and compared them with more innovative approaches such as a simulation game. The study underscores the importance of innovative approaches, such as game-based learning, in fostering climate adaptation efforts among economic actors. By integrating theoretical insights with practical applications, our findings provide valuable guidance for the development of educational games aimed at addressing complex challenges like climate change. Further research and implementation of such approaches are essential for promoting proactive climate adaptation strategies within industrialized regions and beyond.

show abstract

Section: Resistance To Changementioning

confidence: 99%

Adapting to climate change through play? Didactically effective elements of a business simulation game

Fischer,

Göhlich,

Schmitt

2024

Front. Educ.

View full text Add to dashboard Cite

show abstract

“…The genetic algorithm (GA) is an effective domain-independent search technique that was motivated by Darwin's idea. 54 Because the GA is populationbased, a different answer is produced in each iteration. 55 The main concept of this natural selection algorithm is that stronger people survive and pass on their strong characteristics to their children.…”

Section: Least Squares Supportmentioning

confidence: 99%

Determination of the Rate of Penetration by Robust Machine Learning Algorithms Based on Drilling Parameters

Alavi Nezhad Khalil Abad,

Hazbeh,

Rajabi

et al. 2023

ACS Omega

View full text Add to dashboard Cite

Underground resources, particularly hydrocarbons, are critical assets that promote economic development on a global scale. Drilling activities are necessary for the extraction and recovery of subsurface energy resources, and the rate of penetration (ROP) is one of the most important drilling parameters. This study forecasts the ROP using drilling data from three Iranian wells and hybrid LSSVM-GA/PSO algorithms. These algorithms were chosen due to their ability to reduce noise and increase accuracy despite the high level of noise present in the data. The study results revealed that the LSSVM-PSO method has an accuracy of roughly 97% and is more precise than the LSSVM-GA technique. The LSSVM-PSO algorithm also demonstrated improved accuracy in test data, with RMSE = 1.92 and R 2 = 0.9516. Furthermore, it was observed that the accuracy of the LSSVM-PSO model improves and degrades after the 50th iteration, whereas the accuracy of the LSSVM-GA algorithm remains constant after the 10th iteration. Notably, these algorithms are advantageous in decreasing data noise for drilling data.

show abstract

“…Initially, the evaluation of the system encompasses three key dimensions: user interaction, recommender system efficiency, and its impact on learning outcomes [50,51]. In light of this, a questionnaire employing a 10-point Likert scale was administered to students.…”

Section: Motivationmentioning

confidence: 99%

Enhancing Personalized Educational Content Recommendation through Cosine Similarity-Based Knowledge Graphs and Contextual Signals

Troussas,

Krouska,

Tselenti

et al. 2023

Information

Self Cite

View full text Add to dashboard Cite

The extensive pool of content within educational software platforms can often overwhelm learners, leaving them uncertain about what materials to engage with. In this context, recommender systems offer significant support by customizing the content delivered to learners, alleviating the confusion and enhancing the learning experience. To this end, this paper presents a novel approach for recommending adequate educational content to learners via the use of knowledge graphs. In our approach, the knowledge graph encompasses learners, educational entities, and relationships among them, creating an interconnected framework that drives personalized e-learning content recommendations. Moreover, the presented knowledge graph has been enriched with contextual signals referring to various learners’ characteristics, such as prior knowledge level, learning style, and current learning goals. To refine the recommendation process, the cosine similarity technique was employed to quantify the likeness between a learner’s preferences and the attributes of educational entities within the knowledge graph. The above methodology was incorporated in an intelligent tutoring system for learning the programming language Java to recommend content to learners. The software was evaluated with highly promising results.

show abstract

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

Cited by 13 publications

References 29 publications

Adapting to climate change through play? Didactically effective elements of a business simulation game

Adapting to climate change through play? Didactically effective elements of a business simulation game

Determination of the Rate of Penetration by Robust Machine Learning Algorithms Based on Drilling Parameters

Enhancing Personalized Educational Content Recommendation through Cosine Similarity-Based Knowledge Graphs and Contextual Signals

Contact Info

Product

Resources

About