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F(2,91) = 15.047, p =.000; R? = .249; Adjusted R* = .232 Multiple Regression with Total Student Engagement (SCEQ) as the Dependent Variable

Table 14 F(2,91) = 15.047, p =.000; R? = .249; Adjusted R* = .232 Multiple Regression with Total Student Engagement (SCEQ) as the Dependent Variable

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environment. In this model, student engagement consists of student skills, emotion, Problem Statement
environment. In this model, student engagement consists of student skills, emotion, Problem Statement
Student Age and Self-reported College Grade Point Average rogram. All students reported gender, ethnicity, and race. The majority of students were
Student Age and Self-reported College Grade Point Average rogram. All students reported gender, ethnicity, and race. The majority of students were
“Percentage of students with prior education equals more than 100% due to students with Student Gender, Ethnicity/race, Prior Education, Degree Program, n = 97
“Percentage of students with prior education equals more than 100% due to students with Student Gender, Ethnicity/race, Prior Education, Degree Program, n = 97
“Significant non-normality using one-sample Kolmogorov-Smimov Z tests (p < .001). Descriptive Statistics for Grit-S Scale, n = 97
“Significant non-normality using one-sample Kolmogorov-Smimov Z tests (p < .001). Descriptive Statistics for Grit-S Scale, n = 97
Descriptive Statistics for Student Course Engagement Questionnaire, n =97
Descriptive Statistics for Student Course Engagement Questionnaire, n =97
Descriptive Statistics for VAS Measuring Dependent Variables, n = 97
Descriptive Statistics for VAS Measuring Dependent Variables, n = 97
Bivariate Correlations among SCEQ and Engagement VAS and Subscales, n = 97 Table 6
Bivariate Correlations among SCEQ and Engagement VAS and Subscales, n = 97 Table 6
Independent sample ¢ tests were run to determine differences in total student Screening for Continuous Student Characteristics (Age and GPA) for Student Course
Independent sample ¢ tests were run to determine differences in total student Screening for Continuous Student Characteristics (Age and GPA) for Student Course
F(2,91) = 26.566, p = .000; R? = .369; Adjusted R? = .355 Multiple Regression with Skills Engagement (SCEQ) as the Dependent Variable omitting GPA as an independent variable. According to Table 13, 31% of the variance both were significant, grit was shown to have a stronger association with skills
F(2,91) = 26.566, p = .000; R? = .369; Adjusted R? = .355 Multiple Regression with Skills Engagement (SCEQ) as the Dependent Variable omitting GPA as an independent variable. According to Table 13, 31% of the variance both were significant, grit was shown to have a stronger association with skills
F(1,95) = 8.75, p = .004; R* = .084, Adjusted R? = .075 Multiple Regression with Emotion Engagement (SCEQ) as the Dependent Variable Table 14 (p < .01). In other words, students with higher total Grit scores demonstrated greater degree, and total Grit scores (p = .001), with total grit being the only significant
F(1,95) = 8.75, p = .004; R* = .084, Adjusted R? = .075 Multiple Regression with Emotion Engagement (SCEQ) as the Dependent Variable Table 14 (p < .01). In other words, students with higher total Grit scores demonstrated greater degree, and total Grit scores (p = .001), with total grit being the only significant
F(4,92) = 5.149, p = .001; R? = .183; Adjusted R? = .147 Multiple Regression with Participation/interaction Engagement as the Dependent
F(4,92) = 5.149, p = .001; R? = .183; Adjusted R? = .147 Multiple Regression with Participation/interaction Engagement as the Dependent
F(2,91) = 6.611, p = .002; R? = .127; Adjusted R” = .108 Multiple regression with performance engagement as the Dependent Variable Table 16
F(2,91) = 6.611, p = .002; R? = .127; Adjusted R” = .108 Multiple regression with performance engagement as the Dependent Variable Table 16
Multiple regression with VAS overall engagement as the Dependent Variable Table 18
Multiple regression with VAS overall engagement as the Dependent Variable Table 18
F(2,94) = 5.918, p = .004; R? = .112; Adjusted R? = .093 Multiple Regression Predicting Emotion VAS as the Dependent Variable Table 20
F(2,94) = 5.918, p = .004; R? = .112; Adjusted R? = .093 Multiple Regression Predicting Emotion VAS as the Dependent Variable Table 20
F(2,94) = 4.163, p = .019; R? = .081; Adjusted R? = .062 Multiple Regression with Participation/interaction VAS as the Dependent Variable
F(2,94) = 4.163, p = .019; R? = .081; Adjusted R? = .062 Multiple Regression with Participation/interaction VAS as the Dependent Variable
F(1,93) = 9.219, p = .003; R? = .091; Adjusted R? = .081 Multiple Regression with Performance VAS as the Dependent Variable
F(1,93) = 9.219, p = .003; R? = .091; Adjusted R? = .081 Multiple Regression with Performance VAS as the Dependent Variable
Summary of Specific Aim 3 Findings with and without GPA Variable
Summary of Specific Aim 3 Findings with and without GPA Variable
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