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In laboratory courses, the assessment of exercises and assignments typically is treated as a simple, quantifiable approach. This approach however rarely includes qualitative factors, especially if the grading is being automatically performed by the system, and provides little to no feedback for the students to reflect on their work. The role of the laboratory in engineering education however is very critical and engineering students must possess knowledge that goes beyond mere theory, therefore a diverse and multidimensional assessment of laboratory students is a necessity. In this paper, an educational tool for laboratory students implementing automatic assessment based on artificial intelligence is being proposed, based on a pilot version that has been developed for MATLAB-related coursework. The highlights of the proposed tool is that it is based on a proven cognitive theory, it is easy to compile and or modify its contents, it is based on the same laboratory environment that the students are being trained in, it can include qualitative evaluation and it can save time that the educators would otherwise require to manually evaluate the exercises. [Partial funding for this research was provided by Greek national resources under the framework of the "Archimedes III: Funding of Research Groups in TEI of Athens" project of the "Education & Lifelong Learning" Operational Programme.] [For the complete proceedings, see ED557189.]

The building sector accounts for nearly half the energy consumption of Uzbekistan, with the residential energy consumption being much greater than that of even the most developed European countries. This is mainly attributed to the very low cost of energy in the region that, in combination with the lack of subsidies, offered no incentive for energy conservation measures. However, the price of energy has been rising at an alarming pace over the past few years, making building energy saving measures a nationwide concern. In this paper, we investigate the financially optimal insulation thickness for the most common external wall configurations using the two most commonly used building insulations materials in Tashkent, Uzbekistan, expanded polystyrene and mineral wool. Annual heating and cooling transmission loads are being calculated based on transient heat flow through the external walls and by using hourly climatic data. Additionally, we performed a financial analysis for each wall configuration and orientation, as well as for various thicknesses of insulation material. Depending on the wall type and orientation, the optimum insulation thickness was found to be between 3.75 cm and 11.0 cm. Furthermore, a sensitivity analysis indicates whether changes of the economic parameters affect the optimum insulation thickness. [ABSTRACT FROM AUTHOR]

In laboratory courses, the assessment of exercises and assignments typically is treated as a simple, quantifiable approach. This approach however rarely includes qualitative factors, especially if the grading is being automatically performed by the system, and provides little to no feedback for the students to reflect on their work. The role of the laboratory in engineering education however is very critical and engineering students must possess knowledge that goes beyond mere theory, therefore a diverse and multidimensional assessment of laboratory students is a necessity. In this paper, an educational tool for laboratory students implementing automatic assessment based on artificial intelligence is being proposed, based on a pilot version that has been developed for MATLAB-related coursework. The highlights of the proposed tool is that it is based on a proven cognitive theory, it is easy to compile and or modify its contents, it is based on the same laboratory environment that the students are being trained in, it can include qualitative evaluation and it can save time that the educators would otherwise require to manually evaluate the exercises. [ABSTRACT FROM AUTHOR]