Analysis of Factors Affecting Lecturer Performance at a University during the COVID-19 Pandemic Using Logistic Regression and Genetic Algorithms

Autor/inn/en	Setyaningsih, Sri; Sukono, Sukono
Titel	Analysis of Factors Affecting Lecturer Performance at a University during the COVID-19 Pandemic Using Logistic Regression and Genetic Algorithms
Quelle	In: Cypriot Journal of Educational Sciences, 17 (2022) 2, S.542-561 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1305-905X
Schlagwörter	College Faculty; Teacher Effectiveness; COVID-19; Pandemics; Age Differences; Educational Attainment; Teacher Motivation; Teacher Attitudes; Technological Literacy; Educational Facilities; Foreign Countries; Teaching Experience; Job Satisfaction; Compensation (Remuneration); Teacher Supervision; Indonesia + Suchen Sie Ihr Suchwort? Fakultät; Effectiveness of teaching; Instructional effectiveness; Lehrerleistung; Unterrichtserfolg; Age; Difference; Age difference; Altersunterschied; Bildungsabschluss; Bildungsgut; Lehrerverhalten; Technisches Wissen; Bildungsstätte; Ausland; Labor; Labour; Satisfaction; Arbeit; Zufriedenheit; Abfindung; Kompensation; Lohnausgleich; Indonesien
Abstract	The COVID-19 pandemic has forced us to change all aspects of our lives, including higher education. As a result, lecturers get an impact in terms of technology literacy obligations. This situation certainly affects their performance in implementing the Tri Dharma of Higher Education. The purpose of this study is to analyze the factors that affect the performance of lecturers during the COVID-19 pandemic. These factors include age, education, motivation, satisfaction, perception of appreciation, supervision, learning facilities, and technological literacy. The method for collecting data was questionnaires and open interviews with 150 lecturer respondents at a university. Furthermore, the data obtained were analyzed using a logistic regression model, where the parameter estimation was conducted using a genetic algorithm. The estimation process is assisted by Matlab 7.0 software. The results of the analysis show that the factors of age, education, motivation, satisfaction, perception of supervision, learning facilities, and technological literacy have a significant effect on lecturer performance. This study implies that the University needs to consider significant factors for improving lecturers' performance so that teaching and learning activities can run effectively. (As Provided).
Anmerkungen	Birlesik Dunya Yenilik Arastirma ve Yayincilik Merkezi. Sht. Ilmiye Sakir Sokak, No: 9, Ortakoy, Lefkosa, 2681, Cyprus. e-mail: editor.cjes@gmail.com; Web site: https://un-pub.eu/ojs/index.php/cjes/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2022/4/11