Journal of K-12 Educational Research 23 the chi-square test of independence was used with the variables of learning environment (personalized or traditional) and academic achievement (below the 80th percentile, at or above the 80th percentile). The data was analyzed for the whole second grade student population, students coded as academically at-risk, and students coded as economically disadvantaged. The results of the data analysis showed there was a significant relationship in both reading and math between personalized learning environments and high academic achievement for all student populations analyzed. While there was not significance in reading for average performance of 40th percentile or above for learning environments, there was a significant relationship between high academic achievement of 80th percentile or above and a personalized learning environment. In the area of math, there was a significant relationship between learning environment and student achievement at both the average range of above 40th percentile and above average range of above the 80th percentile. Table 1 shows statistical results for the research questions. Bolded p-values indicate significant results. The results of the current study conclude that there is a significant difference in student achievement between learning environments for all students in math. Students in personalized learning environments show a significant relationship in reading for high academic performance, but not for average performance. Implications The results of the current study have many similarities to previous studies conducted on personalized learning with strengths in math, success at the elementary level, and success with traditionally underperforming Table 1 Results of Analysis of Research Questions 1-12 Student Demographic N χ2 p Cramer's V RQ1: All Students (Avg, Achievement)– Reading 610 0.08 .784 .01 RQ2: All Students (Avg, Achievement)–Math 554 4.13 .042 .09 RQ3: At-Risk (Avg, Achievement)–Reading 430 1.90 .167 .07 RQ4: At-Risk (Avg, Achievement)–Math 379 5.00 .025 .12 RQ5: EcDis (Avg, Achievement)–Reading 552 < .01 .979 < .01 RQ6: EcDis (Avg, Achievement)–Math 498 5.80 .016 .11 RQ7: All Students (High Achievement)– Reading 610 6.5 .011 .10 RQ8: All Students (High Achievement)–Math 554 4.7 .030 .09 RQ9: At-Risk (High Achievement)–Reading 430 8.1 .005 .14 RQ10: At-Risk (High Achievement)–Math 379 7.8 .005 .14 RQ11: EcDis (High Achievement)–Reading 552 9.4 .002 .13 RQ12: EcDis (High Achievement)–Math 498 6.8 .009 .12 The results of the current study conclude that there is a significant difference in student achievement between learning environments for all students in math. Students in personalized learning environments show a significant relationship in reading for high academic performance, Table 1 Results of Analysis of Researched Questions 1-12
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