Construction of Big Data Monitoring Platform for Teaching Quality under Intelligent Education

Retracted: Quality management in higher education: Developing the methodology on the basis of total quality management

“…Various methodologies for quality management of higher education have been proposed in the scientific literature. It is worth highlighting the basic ones, namely: the method of analysing hierarchies to determine the priority needs of consumers, develop strategies, plans and qualitative characteristics of the quality of education (Budiharso & Tarman, 2020); a comprehensive methodology for monitoring the quality of educational programmes (curricula) in higher educational institutions based on a survey of interested parties (Belash et al, 2015); a methodology based on comparative longitudinal studies, surveys and mixed methods of studying the quality of higher educational institutions (Leiber et al, 2015); agent‐oriented methodology, which provides for the development of a system for monitoring the quality of higher education and web mining as a method of collecting data on quality (Qin et al, 2020); data analysis methodology for assessing the quality of university departments’ performance in order to identify the level of efficiency and transparency of operation (Martín, 2006); contextualised methodology for assessing the quality of higher education based on 10 key interested parties’ questions (Nygaard & Belluigi, 2011); methodology for assessing the sustainability of a higher educational institution to characterise the functioning of the establishment in the context of the economic, environmental and social component (Madeira et al, 2011); methodology for recording data on students’ involvement in quality management (Coates, 2005); a methodology based on total quality management (TQM), evaluating principles and basic concepts in order to display the state of functioning of a higher educational institution in comparison with others over a certain period of time (Flores‐Molina, 2011; Kanji et al, 1999); a methodology based on multicriteria analysis and modelling of disaggregation of benefits, which takes into account the acceptance of the student in the labour market (Politis & Siskos, 2004). …”

“…• agent-oriented methodology, which provides for the development of a system for monitoring the quality of higher education and web mining as a method of collecting data on quality (Qin et al, 2020); • data analysis methodology for assessing the quality of university departments' performance in order to identify the level of efficiency and transparency of operation (Martín, 2006); • contextualised methodology for assessing the quality of higher education based on 10 key interested parties' questions (Nygaard & Belluigi, 2011); • methodology for assessing the sustainability of a higher educational institution to characterise the functioning of the establishment in the context of the economic, environmental and social component (Madeira et al, 2011); • methodology for recording data on students' involvement in quality management (Coates, 2005); • a methodology based on total quality management (TQM), evaluating principles and basic concepts in order to display the state of functioning of a higher educational institution in comparison with others over a certain period of time (Flores-Molina, 2011;Kanji et al, 1999); • a methodology based on multicriteria analysis and modelling of disaggregation of benefits, which takes into account the acceptance of the student in the labour market (Politis & Siskos, 2004).…”

Methodology for Ensuring Quality Management of Higher Education

“…Various methodologies for quality management of higher education have been proposed in the scientific literature. It is worth highlighting the basic ones, namely: the method of analyzing hierarchies to determine the priority needs of consumers, develop strategies, plans and qualitative characteristics of the quality of education (Budiharso et al, 2020); comprehensive methodology for monitoring the quality of educational programs (curricula) in higher educational institutions based on a survey of interested parties (Belash et al, 2015); methodology based on comparative longitudinal studies, surveys and mixed methods of studying the quality of higher educational institutions (Leiber et al, 2015); agent-oriented methodology, which provides for the development of a system for monitoring the quality of higher education and web mining as a method of collecting data on quality (Qin et al, 2020); data analysis methodology for assessing the quality of university departments' performance in order to identify the level of efficiency and transparency of operation (Martín, 2006); contextualized methodology for assessing the quality of higher education based on 10 key interested parties' questions (Nygaard and Belluigi, 2011); methodology for assessing the sustainability of a higher educational institution to characterize the functioning of the establishment in the context of the economic, environmental and social component (Madeira et al, 2011); methodology for recording data on students' involvement in quality management (Coates, 2005); methodology based on Total quality management (TQM), evaluating principles and basic concepts in order to display the state of functioning of a higher educational institution in comparison with others over a certain period of time (Kanji et al, 1999;Flores-Molina, 2011); methodology based on multicriteria analysis and modeling of disaggregation of benefits, which takes into account the acceptance of the student in the labor market (Politis and Siskos, 2004).…”

Simulation of intellectual system for evaluation of multilevel test tasks on the basis of fuzzy logic

“…A lot of studies in pedagogy are devoted to the issue of assessing knowledge. In particular: monitoring the quality of education (Cherednichenko and Yangolenko [7], He and He [16], Igbape and Idogho [19], Leontev et al [21], Li et al [22], Muhd Nor et al [25], Qin et al [30], Sorour et al [49], Wei [54], Zhi and Nan [56] and others); development of modern innovative technologies that are included in the knowledge assessment system (Anohina-Naumeca, Strautmane and Grundspenkis [2], Anohina-Naumeca and Grundspenkis [1], Gierłowski and Nowicki [13], Grundspenkis [14], Schmuck, Sima and Szöllosi [41], Szöllosi, Sima and Schmuck [50] and others); the use of a multi-point scale for assessing knowledge, abilities, and skills (Bespalko [5], Linn [23] and others); theoretical approaches to the assessment of students' knowledge, their development and improvement (Clotfelter, Ladd and Vigdor [8], Falchikov and Boud [11], Falchikov and Goldfinch [12], Host, Regnell and Wohlin [17], Hwang and Chang [18], Newble and Jaeger [27], Osadchyi et al [28], Rust, Price and Berry [39], Scouller [42], Topping [53], Wiliam et al [55] and others); evaluation of test results in an adaptive automated testing system, taking into account the ambiguity of the formulations of answers (Barker [3], Phankokkruad and Woraratpanya [29], Rudinskiy [38] and others). In [6] we substantiated the structural model of the neuro-fuzzy system of professional selection of students for training in IT specialties by studying the psychological characteristics, personal qualities and factual knowledge, skills and abilities of students as a unity of fuzzy and stochastic data base of t...…”