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In Event: Cyberschooling and Social Isolation: New Literacy Opportunities for Vulnerable Populations
Socio-emotional learning in cyber schools: Results from a large quantitative study.
Objectives
The objective of this study was to determine the relationships between differing types of social interaction and cyber school students’ social and emotional learning skills.
Perspective
Scholars agree that social and emotional learning (SEL) should be an important part of K-12 education (Greenberg et al, 2003). The Collaborative for Academic, Social and Emotional Learning (CASEL) has five core proficiencies: Self-awareness, self-management, social awareness, relationship skills, and responsible decision-making skills (CASEL, 2013; Payton et al., 2000; Zins, Bloodworth, Weissberg & Walberg, 2007). However, cyber schools may struggle with helping students develop SEL skills. Communication can be impersonal because technology can become a barrier and substitute for person-to-person socialization (McFarlane, 2011; Hawkins et al, 2011, 2012; Murphy & Rodríguez-Manzanares, 2008; Picciano et al, 2010). However, teachers can develop caring relationships with students in interaction-rich online environments (Borup, Graham & Velasquez, 2013; Velasquez, Graham & Osguthorpe, 2013). Unfortunately, little research has been done on students’ SEL in cyber schools.
Method
The objective of this study was to determine the relationships between differing types of social interaction and cyber school students’ SEL skills. We employed a series of ordinary least squares (OLS) regression models and generalized ordered logistic (gologit) models to study these relationships. We obtained 2019-20 data from a cyber-school network operating in multiple states (n= 39,353), a unique data set with 65 variables. Our social interaction measurements included live, one-on-one lessons between teacher and student, live group lessons (teacher and students) and student average participation. SEL measures included measurements in the five core proficiencies mentioned above.
We conducted three models:
SELt_i=b_0+b_1 Social_i +ε_i (1)
SELt_i=b_0+b_1 Social_i+b_2 X_i +〖pastSELi+ε〗_i (2)
SELt_i=b_0+b_1 Social_i+b_2 X_i+b_3 〖S_ 〗_i+b_4 Social_i*S_i pastSELt_i+ε_i (3)
In the first model, we studied the association between the independent variable SEL and the dependent variable type of social interaction Socialfor student i. In the second model, we added student characteristics Xand student pastSEL. In the third model, we included interaction terms for specific groupings of students Sand types of social interactions.
Results
Students were reported as 55% female, 45% male, 66% white, 15% Latinx, 9% African American, 7% multi-race and 2% other, 18% special education (SPED), 45% free and reduced lunch (FARM). Data analysis is in progress.
Scholarly significance
This research is important because nothing is known about the effectiveness of current methods used by cyber schools to develop online students' SEL skills. Results from this study should point to the need to improve current methods and may direct future research into the connection between lower student achievement and SEL skills in cyber schools.