Creating a Metamodel for Predicting Learners’ Satisfaction by Utilizing an Educational Information System During COVID-19 Pandemic

Kanetaki, Zoe; Stergiou, Constantinos; Bekas, Georgios; Troussas, Christos; Sgouropoulou, Cleo

doi:10.3233/faia210085

Cited by 12 publications

(17 citation statements)

References 22 publications

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“…Subjective as it is, personal satisfaction is important mainly because, as shown by Kanetaki et al [67], it is linked to academic achievement; one, however, must not lose sight of the fact that this indicator is heavily subjective in nature. This pushes things into the direction of adaptability once more, predominantly within the context of one's intentionality regarding personal satisfaction; in other words, if one genuinely wishes to teach/learn as part of online education, the reality of personal satisfaction will be dependent on one's readiness to do one's best as educator/student.…”

Section: Hypothesis 5 (H5)mentioning

confidence: 99%

Effective Teaching during the COVID-19 Pandemic? Distance Learning and Sustainable Communication in Romania

et al. 2022

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Telecommuting in education field, enforced by Romanian Government measures as policy responses to COVID-19 pandemic, has had a tremendous effect both on teaching professionals and on students. This paper investigates the first group, namely the teachers and their perception of online education versus students’ academic performance during distance learning, with a particular focus on the negative factors impacting educational activities: objective ones, such as the limits of technology, and personal subjective ones, as in the phenomenon of negative affect. The study is based on quantitative research that assesses the relationship between personal subjective factors (skills, affect, difficulties in adapting, level of preparedness, professional satisfaction) and technological objective factors (inadequate electronic devices, faulty internet services), with a view to establishing if online education is genuinely sustainable as a valid educational system in the long run. 881 teachers from Romania were subjected to reflect on the effectiveness of online education during the pandemic, resulting in a correlational study with some interesting conclusions and directions highlighted as characteristic for a sustainable educational program. All in all, it can be concluded that when teachers become experienced in online teaching, the efficiency of online teaching is set to improve and when improvement happens, online teaching becomes sustainable as a proper method of training via online-facilitated means of communication.

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Section: Hypothesis 5 (H5)mentioning

confidence: 99%

Effective Teaching during the COVID-19 Pandemic? Distance Learning and Sustainable Communication in Romania

et al. 2022

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“…During the COVID-19 pandemic, limits to the adoption of these models occurred as some universities did not expect students to have access to printers at home (Becker, M. personal communication 9/28/ 2021). The literature shows that during the COVID-19 pandemic, the lack of printers in students' homes can be as high as 20% (Kanetaki et al, 2021). While this implementation is not perfect, most students had the resources and ability to construct these models with limited extra help from the faculty over various institutions (Table 1).…”

Section: Classroom Methodologymentioning

confidence: 99%

Groundwater origami: Folding paper models to visualize groundwater flow

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Dunkle

Kairies-Beatty

et al. 2022

Front. Environ. Sci.

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The training of geological scientists, more so than any other natural science, is dependent on how students learn to visualize and interpret complex three-dimensional problems at scales from micrometers to kilometers over time scales that span from seconds to centuries. Traditionally, our classrooms are at a disadvantage due to our standard two-dimensional use of whiteboards or slide decks. We are at an even bigger disadvantage when courses go to online education. While computer simulations and three-dimensional visualizations are used, they can lack the flexibility for students to perform free-form exploration. The novelty of this research is in the use of paper aquifer models and their implementation across seven academic institutions to provide three-dimensional physical examples for students to visualize subsurface geologic structure and quantify fluid flow through porous media. Students can cut, fold, and build three-dimensional hydrologic problems at home or in the classroom. Our methodology allows students to physically rotate their aquifer models to visualize cross-sectional areas, layer thicknesses, heterogeneity, and confining units. These foldable paper models provide a low barrier of entry for students to understand and quantify the relationships between water levels and geologic structure. Our experience using these models in both in-person and online classrooms highlights the advantages and disadvantages of these models. Results, although mostly anecdotal, suggest the paper models improve students’ learning and enhance their engagement with the material. The formal evaluations of pre- and post-model implementation show that low-scoring students had the most significant gains after being introduced to the paper aquifer models. At the same time, there was no change in the number of students in the highest scoring group. Our experience in the classroom points to new opportunities to engage with remote learners and tools for supporting flipped classroom activities. Our vision for the paper aquifer models is to provide the hydrologic community with an additional tool to help bridge the virtual classroom gap, engage students, and help them develop mastery of three-dimensional problem-solving.

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“…Forecasting grades in online educations systems represent a new challenge in the academic field, especially during pandemic circumstances [18,19], where in [20] an alternative term has been proposed "Emergency Remote Teaching" 1 and Remote Knowledge acquisition [21]. Researches have indicated specific factors that strongly affect students' academic performance under pandemic circumstances.…”

Section: Related Workmentioning

confidence: 99%

“…Visualising 3-Dimensional objects enables first year students to develop engineering specific skills. Other researchers [4,19,26] stated the link of Engineering education with the society, implementing assignments related to real world tasks and similar to students' future enrolment in their after-graduate employment. By exploring the topic of linking students' personal satisfaction and their level of academic achievements in CAD engineering courses during pandemic, researchers [19] revealed new parameters (variables) that affect students' achievements during lockdown periods.…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Machine Learning Model for Grade Prediction in Online Engineering Education

et al. 2022

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Facing the disruption caused by COVID-19 pandemic, the emergence of imposed and exclusive online learning revealed challenges for researchers worldwide, as of reforming curricula shortly and of collecting data accumulated by monitoring stu-dents’ commitment and academic performance. With this pool of data, this research explores grade prediction in a first-semester mechanical engineering CAD module, after testing the performance of the reform of specific curricula. A hybrid model has been created, based on 35 variables having been filtered out of statistical analysis and shown to be strongly correlated to students’ academic performance in the specif-ic online module during the first semester of the academic year 2020-2021. The hy-brid model consists of a Generalized Linear Model. It’s fitting errors are used as an extra predictor to an artificial neural network. The architecture of the neural network can be described by the following sizes: size of the input layer (36), size of the hidden layer (1) and size of the output layer (1). Since new factors are revealed to affect students’ academic achievements, the model has been trained in the 70% of the participants to predict the grade of the remaining 30%. The model has therefore been divided into three subsets, with a training set of 70% of the sample and one hidden layer predicting the test set (15%) and the validation set (15%). The final form of the trained hybrid model resulted in a coefficient of determination equal to 1 (R = 1). This means that the data fitting process resulted in a 100% success rate, in terms of associating the independent variables with the dependent variable (grade).

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Creating a Metamodel for Predicting Learners’ Satisfaction by Utilizing an Educational Information System During COVID-19 Pandemic

Cited by 12 publications

References 22 publications

Effective Teaching during the COVID-19 Pandemic? Distance Learning and Sustainable Communication in Romania

Effective Teaching during the COVID-19 Pandemic? Distance Learning and Sustainable Communication in Romania

Groundwater origami: Folding paper models to visualize groundwater flow

A Hybrid Machine Learning Model for Grade Prediction in Online Engineering Education

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