06 SES 07 A, Space, Community & Distance
The review provides a systematic overview of the state of quantitative research on teaching and learning during school closures due to corona in Spring 2020. The review comprises 97 online surveys conducted between 24th of March 2020 and 11th of November 2020 and covering 255.955 cases (students, parents, teachers, school leaders). The analysis and synthesis of the findings was carried out along the “integrative model on distance education”. The review makes clear that central aspects of teaching and learning during corona-based school closures, such as distance learning characteristics (e.g. quality dimensions), student characteristics (e.g. self-sufficiency) and characteristics of home resources for learning (e.g. parental support) have already been the subject of many surveys. The school situation during the corona pandemic is therefore no longer an unexplored phenomenon. Rather, the scientific ethos of researchers in this field demands that the current state of research needs to be considered in their work. The review presented here is intended to facilitate this task by not only listing the existing surveys, but also synthesizing their central findings. In addition, the review provides a relevant information basis for decisions and action in politics, administration and school practice. At the same time, the review warns against an unreflected adoption of the findings by critically discussing the scientific quality of the surveys.
How does teaching and learning work during corona-based homeschooling from a theoretical point of view? Which aspects of teaching and learning come to the fore, which to the back? To guide our meta-review, we developed the "integrative framework model for distance learning".
The integrative framework model to distance learning is grounded in theoretical models of homework practices. These models postulate that parents’ learning support as well as the domestic resources for student learning in general (e.g., socioeconomic status of learners, equipment at home), strongly influence the quality and success of home learning processes. Trautwein et al.'s (2006) homework model is based, among other things, on various motivational theories, especially expectancy-value theory, and the supply-use model by Helmke (2009). In contrast to the supply-use model, Trautwein et al. (2006) attempt to describe more concretely the bundles of factors relevant to homework practice, namely parent role, student motivation, quality of homework practice, and student homework behavior. For example, Trautwein et al. (2006) postulate that characteristics of the learning environment, teachers, homework practice, students, and parental learning support influence learners' motivation to learn. Motivation, in turn, is hypothesized to be a predictor of students’ homework behavior, which is associated with student achievement.
Models of homework research, by virtue of their supply-use logic, seem to cover all the essential bundles of factors for distance education. What they lack is a view of the role of technology - especially digital media - in the teaching and learning process, which have only gained central importance in everyday school life as a result of school closures due to Corona. Therefore, we integrate theories of distance education (e.g., Wedemeyer 1981; Keegan 1986; Moore 2013) and e-education (e.g., Aparicio et al. 2016; Picciano 2017) into Trautwein et al.'s (2006) model of homework.
Systematic and unsystematic literature review The identification of the available 97 surveys was done in two steps: First, a systematic literature review was conducted. Second, surveys were identified through Google searches and by contacting the authors of surveys announced on the Internet. All the surveys included in our review had to... - represent a quantitative survey. - focus on descriptive descriptions of distance education during the spring 2020 school closures. - contain samples consisting of groups of actors in the education system (students, teachers, school administrators, parents, school administrators, etc.) with reference to primary education, lower secondary education or upper secondary education (excl. vocational education) in Germany, Austria or Switzerland. We used four research databases: Google Scholar, Scopus, EBSCOhost, FIS Education; and the following search terms: (corona OR "covid-19" OR "cov-19") AND (school OR schooling OR instruction OR learning) AND (survey) AND (Germany OR Austria OR Switzerland) AND (students OR pupils) -medical -therapy. To identify relevant surveys in the search hits, a three-step approach was taken: In the first step, it was checked whether the title contained indications for exclusion (such as "higher education", countries). If this was not the case, the same was checked for the abstract in the second step. If no reason for exclusion was identifiable here either, the full text (if accessible) was checked for fit with the review objective in a third step. After eliminating duplicates, steps 1 and 2 resulted in 25 search hits, of which a further five hits were excluded in the third step. Our unsystematic literature review via google search and direct contact of colleagues was far more successfully than the systematic review (due to the fact that hardly any research on distance education due to COVID-19 had already been published in peer-reviewd journals). In total we identified 97 relevant surveys. Qualitative content analysis To analyse and synthesize the findings of the 97 survey reports, we established a coding scheme. The top categories of this scheme were deductively derived from integrative Distance Education model (see the Theory Section). In the case of very extensive categories, subcategories were also derived inductively from the data material. This mainly concerned the quality characteristics of distance learning. To guide the content analysis, we set up a table with information on the definition of the category and anchor examples.
Selected findings Student achievement. The available surveys show that - according to the students' self-assessment - about one fifth to one half of the students expect negative effects of distance learning on their academic achievement. When parents are asked about their children's learning deficits, about one-third to two-thirds fear negative effects. Just over one-third of teachers also fear negative effect on student learning. Learning Effort. The state of research on student learning effort during distance education is characterized by high heterogeneity. The proportion of students spending less than 2 hours per day on learning activities varies from about one-fifth to slightly more than half of students, depending on the survey. In addition, in the student surveys, about one-third to half of the students report that their workload during distance learning was less than before the lockdown. These findings are largely consistent with those in the parent surveys. Students' independence. Slightly more than one-third of students have difficulty organizing their daily routines (e.g., getting up early). In addition, about a quarter to a third of the students report learning difficulties, concentration problems and excessive demands in self-directed learning. With regard to the use of digital media, between half and over 80% of the students think that they are well skilled. From the parents' perspective, in the majority of the surveys about a quarter to a third of the parents report that their children have difficulties with self-directed learning. This review results are supplemented by findings regarding technical equipment at home, parents learning support (time used, parents teaching skills, way of support, stress at home), instructional quality (share of learning time, amount of online teaching, cognitively activating learning tasks, individualisation and differentiation, feedback, …) and the impact of students social background an all the aspects mentioned.
Aparicio, M., Bacao, F., & Oliveira, T. (2016). An e-Learning Theoretical Framework. Educa-tional Technology & Society, 19(1), 292–307. Huber, S. G., & Helm, C. (2020a). COVID-19 and Schooling: Evaluation, Assessment and Accountability in Times of Crises—Reacting Quickly to Explore Key Issues for Policy, Practice and Research with the School Barometer. Educational Assessment, Evaluation and Accountability(32), 237–270. Keegan, D. (1986). The foundations of distance education. London: Croom Helm. Moore, M. G. (Hrsg.) (2013). Handbook of distance education. New York: Routledge. Trautwein, U., Lüdtke, O., Schnyder, I., & Niggli, A. (2006). Predicting homework effort: Support for a domain-specific, multilevel homework model. Journal of Educational Psy-chology, 98(2), 438–456. Wedemeyer, C. A. (1981). Learning at the back door: Reflections on non-traditional learning in the lifespan. Madison, WI: University of Wisconsin Press.
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