2021
DOI: 10.11114/jets.v10i1.5396
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Integrating Evaluation as a Componential Element in the Development of the Course: The Case of Two Courses in the Faculty of Education (AUTH) during the Pandemic

Abstract: Evaluation, as a process, can positively contribute to the formation of better educational experiences for both instructors and students, as well as lay the foundations for the development of an evaluation culture in student participants. This article sets out to present the evaluation process carried out in two online courses at Aristotle University of Thessaloniki (AUTH) during the pandemic period, how it has constituted an integral component of each course and in what ways it has contributed to the students… Show more

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Cited by 2 publications
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“…Mcevoy D et al [11] proposed a data mining algorithm to support climate-adaptive urban development and empirically analyzed the impact of meteorological elements on urban haze. Masey et al [12] used data mining techniques based on bilinear transformation and ICEEMDAN framework to analyze the main reasons for the degradation of urban air quality from an economic point of view, which are the rapid development of urban economy, high-emission industrial and energy structure, and backward environmental protection technology, Korres M P et al [13] used the clustering algorithm in data mining technology to drill down and analyze the causes of haze formation and its impact on all sectors, and indirectly and directly give adjustment suggestions and optimization paths to achieve urban haze management at the source. In urban traffic management, Zhang Q [14] and Cali S [15] et al mined big data through the integration of intuitionistic fuzzy multi-criteria evaluation for marketing, supply, and purchasing decisions.…”
Section: Introductionmentioning
confidence: 99%
“…Mcevoy D et al [11] proposed a data mining algorithm to support climate-adaptive urban development and empirically analyzed the impact of meteorological elements on urban haze. Masey et al [12] used data mining techniques based on bilinear transformation and ICEEMDAN framework to analyze the main reasons for the degradation of urban air quality from an economic point of view, which are the rapid development of urban economy, high-emission industrial and energy structure, and backward environmental protection technology, Korres M P et al [13] used the clustering algorithm in data mining technology to drill down and analyze the causes of haze formation and its impact on all sectors, and indirectly and directly give adjustment suggestions and optimization paths to achieve urban haze management at the source. In urban traffic management, Zhang Q [14] and Cali S [15] et al mined big data through the integration of intuitionistic fuzzy multi-criteria evaluation for marketing, supply, and purchasing decisions.…”
Section: Introductionmentioning
confidence: 99%