Instruction

Ever since No Child Left Behind in 2001 to the present, school accountability reform initiatives have concentrated on raising achievement. Critical to figuring out the relationship between instructional practice and student achievement is forming an awareness of the relationship from the perspective of school leaders—both principals and teachers—charged with improving student achievement. The study, a quantitative quasiexperimental design using the School Survey of Practices Associated with High Performance, representing instructional practices associated with improving student performance, collected survey data via social media from teachers, principals and other school leaders in Florida public schools.
The SSPAHP grouped instructional practices into five domains: effective leadership, curriculum, professional development, school culture, and ongoing use of data for school improvement, which served as the predictor variables. Achievement data from the Florida Standards Assessment for the schools mentioned by participants in the survey functioned as the criterion variable. While 130 surveys were collected, only 84 of the responses reflected schools that took part in the FSA and met the criteria for data analysis.

This phenomenological study explored the role of end-of-course examinations on teachers’ decision-making on curriculum and instruction through a comparative analysis of teachers who taught courses with end-of-course examinations and teachers who taught courses with locally created assessments (LCA). This study examined the experiences of nine teachers in a small school district located on the east-central coast of Florida.
The study’s theoretical framework drew on Bourdieu’s (1972/1977) tools of habitus, capital, practice, and fields to explain the role of education in the reproduction of social system. The study examined how standardized testing shaped teachers’ use of habitus and capital to determine their practice in their curriculum, instruction, relationships in different educational fields, morale, and perspectives on teacher evaluation.

Engagement with educational instruction and related materials is an important part of learning and contributes to test performance. There are various measures of engagement including self-reports, observations, pupil diameter, and posture. With the challenges associated with obtaining accurate engagement levels, such as difficulties with measuring variations in engagement, the present study used a novel approach to predict engagement from posture by using deep learning. Deep learning was used to analyze a labeled outline of the participants and extract key points that are expected to predict engagement. In the first experiment two short lectures were presented and participants were tested on a lecture to motivate engagement. The next experiment had videos that varied in interest to understand whether a more interesting presentation engages participants more, therefore helping participants achieve higher comprehension scores. In a third experiment, one video was presented to attempt to use posture to predict comprehension rather than engagement. The fourth experiment had videos that varied in level of difficulty to determine whether a challenging topic versus an easier topic affects engagement. T-tests revealed that the more interesting Ted Talk was rated as more engaging, and for the fourth study, the more difficult video was rated as more engaging. Comparing average pupil sizes did not reveal significant differences that would relate to differences in the engagement scores, and average pupil dilation did not correlate with engagement. Analyzing posture through deep learning resulted in three accurate predictive models and a way to predict comprehension. Since engagement relates to learning, researchers and educators can benefit from accurate engagement measures.