Abstract
Observations from the online teaching of a robotics class during the CoViD-19 pandemic caused by SARS-CoV-2 also known as the Corona virus are presented. The online teaching of the course lead to an unexpected increase in the grade performance of the students – despite the fact that the exams were at the same level of difficulty as in the years before. There is some evidence that the asynchronous online teaching catered for some of the general interests and learning trends in generation-Z students. This paper addresses the question whether the general study performance of a student is a possible factor in whether the student profited more or less from the online version, i.e., whether there is a correlation between the improved course grade with the Grade Performance Average (GPA) of students.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Aristovnik, A., Kerzic, D., Ravselj, D., Tomazevic, N., Umek, L.: Impacts of the COVID-19 pandemic on life of higher education students: a global perspective. Sustainability 12(20), 8438 (2020)
Bai-Yun, C.: The effects of COVID-19 on international secondary assessment (2020). https://www.naric.org.uk/downloads/The%20Effects%20of%20COVID-19%20on%20International%20Secondary%20Assessment%20-%20UK%20NARIC.pdf
Birk, A., Dineva, E., Maurelli, F., Nabor, A.: A robotics course during COVID-19: Lessons learned and best practices for online teaching beyond the pandemic. Robotics 10(1), 5 (2021)
Buzzetto-More, N.A.: An examination of undergraduate student’s perceptions and predilections of the use of YouTube in the teaching and learning process. Interdiscip. J. e-Skills Lifelong Learn. 10, 17–32 (2014)
Carpenter, S.K., Witherby, A.E., Tauber, S.K.: On students’ (mis)judgments of learning and teaching effectiveness. J. Appl. Res. Mem. Cogn. 9(2), 137–151 (2020). http://www.sciencedirect.com/science/article/pii/S2211368120300024
Clayson, D.E.: Student evaluations of teaching: are they related to what students learn? A meta-analysis and review of the literature. J. Market. Educ. 31(1), 16–30 (2009). https://doi.org/10.1177/0273475308324086
Costello, E.: Opening up to open source: looking at how Moodle was adopted in higher education. Open Learn. J. Open Distance e-Learn. 28(3), 187–200 (2013). https://doi.org/10.1080/02680513.2013.856289
Crawford, J., et al.: COVID-19: 20 countries’ higher education intra-period digital pedagogy responses. J. Appl. Learn. Teach. 3(1), 1–20 (2020)
Davies, P.: What is evidence-based education? Br. J. Educ. Stud. 47(2), 108–121 (1999). https://doi.org/10.1111/1467-8527.00106
Dougiamas, M., Taylor, P.C.: Moodle: using learning communities to create an open source course management system. In: EdMedia. Association for the Advancement of Computing in Education (AACE) (2003)
IAU: Regional/national perspectives on the impact of COVID-19 on higher education (2020). https://www.iau-aiu.net/IMG/pdf/iau_covid-19_regional_perspectives_on_the_impact_of_covid-19_on_he_july_2020_.pdf
Ilag, Balu N.: Microsoft Teams Overview. In: Understanding Microsoft Teams Administration, pp. 1–36. Apress, Berkeley (2020). https://doi.org/10.1007/978-1-4842-5875-0_1
Linse, A.R.: Interpreting and using student ratings data: guidance for faculty serving as administrators and on evaluation committees. Stud. Educ. Eval. 54, 94–106 (2017). http://www.sciencedirect.com/science/article/pii/S0191491X16300232
Nicholas, A.J.: Preferred learning methods of the millennial generation. Int. J. Learn. Ann. Rev. 15(6), 27–34 (2008)
Pearson: The global learner survey (2020). https://www.pearson.com/content/dam/one-dot-com/one-dot-com/global/Files/news/gls/Pearson_Global-Learners-Survey_2020_FINAL.pdf
Perry, R.P., Smart, J.C.: The Scholarship of Teaching and Learning in Higher Education: An Evidence-Based Perspective. Springer, Dordrecht (2007). https://doi.org/10.1007/1-4020-5742-3
Poll, T.H.: Beyond Millennials: The Next Generation of Learners. Pearson, London (2018)
Schneider, M., Preckel, F.: Variables associated with achievement in higher education: a systematic review of meta-analyses. Psychol. Bull. 143(6), 565–600 (2017)
Slavin, R.E.: Evidence-based education policies: transforming educational practice and research. Educ. Res. 31(7), 15–21 (2002). https://doi.org/10.3102/0013189X031007015
Stroebe, W.: Why good teaching evaluations may reward bad teaching: on grade inflation and other unintended consequences of student evaluations. Perspect. Psychol. Sci. 11(6), 800–816 (2016). https://doi.org/10.1177/1745691616650284
Stroebe, W.: Student evaluations of teaching encourages poor teaching and contributes to grade inflation: a theoretical and empirical analysis. Basic Appl. Soc. Psychol. 42(4), 276–294 (2020). https://doi.org/10.1080/01973533.2020.1756817
Symonds, Q.: The coronavirus crisis and the future of higher education (2020). https://www.qs.com/portfolio-items/the-coronavirus-crisis-and-the-future-of-higher-education-report/
Symonds, Q.: International student survey - global opportunities in the new higher education paradigm (2020). https://info.qs.com/rs/335-VIN-535/images/QS_EU_Universities_Edition-International_Student_Survey_2020.pdf
Xu, D., Jaggars, S.S.: Performance gaps between online and face-to-face courses: differences across types of students and academic subject areas. J. High. Educ. 85(5), 633–659 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Birk, A., Dineva, E. (2022). Improved Students’ Performance in an Online Robotics Class During COVID-19: Do only Strong Students Profit?. In: Merdan, M., Lepuschitz, W., Koppensteiner, G., Balogh, R., Obdržálek, D. (eds) Robotics in Education. RiE 2021. Advances in Intelligent Systems and Computing, vol 1359. Springer, Cham. https://doi.org/10.1007/978-3-030-82544-7_13
Download citation
DOI: https://doi.org/10.1007/978-3-030-82544-7_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-82543-0
Online ISBN: 978-3-030-82544-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)