Dissertations / Theses on the topic 'Technology student'

The purpose of this ethnographic research study was to investigate the effect of a Bring Your Own Technology (BYOT) policy on student engagement in a high school setting through classroom observations, cross-sectional surveys, and a focus group of technology teacher leaders. The qualitative and quantitative data gleaned from this study indicated no significant difference in student engagement levels when student-owned technology was used for instructional purposes, but student engagement increased with teacher support and efficacy with technology, student-directed learning, and utilization of Web 2.0 applications. The findings of this study will inform future decision making by school districts considering BYOT policies, assist teachers with technology-based instructional design, and contribute to the literature on student engagement with instructional technology.

This dissertation examines nontraditional online students’ perceptions of Tinto’s four student success conditions: expectations, support, assessment, and engagement. Expectations include those of the student, the faculty and the institution. Support includes academic, social, and financial support. Providing early and meaningful assessment and feedback to students is crucial during their educational career. The fourth success condition in Tinto’s model includes the involvement or engagement of students with their peers (and faculty) in both an academic and social contexts. Nontraditional student perceptions of each of these institutional conditions of success was uncovered through demographic survey, interviews, syllabi and website artifacts.This qualitative study provided a rich, detailed description of the lived experience of the nontraditional online student to add to the paucity of research on this understudied population. The three main themes emerged from the data: (a) nontraditional students identified in an asynchronous environment did not find the success conditions to be consistently present and reported that they would have benefitted from them if they had existed both academically and socially; (b) nontraditional students identified key elements for success, which included flexibility in their schedule and the opportunity to receive a degree from a reputable institution that would lead to career enhancement; (c) students reported developing a strong, positive academic relationship with their advisor. The advisor served as a substitute for faculty-student relationships and was the primary role for providing academic, social and financial support.

The student affairs profession is at a crossroads (Torres & Walbert, 2010) given digital technology’s growth and the academy’s administrative expansion (Bowen, 2013). Student affairs administrators must simultaneously respond to digital technology’s implications in students’ lives (Kirschner & Karpinski, 2010) and to new state and federal compliance mandates connected to their expanding campus roles (Dungy & Gordon, 2010). Student affairs leaders acknowledge that these competing priorities demand more nimble responses (Manning, Kinzie, & Schuh, 2013; McClennan & Stringer, 2009). Significant research (Barr, McClennan, & Sandeen, 2014; Elkins, 2015; Dungy & Gordon, 2010; Junco, 2014; Kuk, 2012; Torres & Walbert, 2010) highlights that student affairs administrator‘s digital technology use can augment traditional in-person co-curricular student experiences; yet, minimal research exists on how student affairs administrators utilize digital technology.

This qualitative, historical, interpretive study analyzed student affairs administrators’ digital technology use from 2005 to 2015. Three research questions and three sub-questions framed the research design, which utilized three data sources. The researcher conducted (N=16) interviews with student affairs professionals and educators. Elite interviews (N=5) were conducted with some of the earlier student affairs digital technology adopters, while (N=11) key informant interviews were conducted with administrators who started their professional careers in 2005. (N=206) documents, including conference presentations and publications, were collected through the Student Affairs Administrators in Higher Education (NASPA) and College Student Educators International (ACPA)’s websites. Data were analyzed in-case and across cases to highlight overall themes and a progressive timeline of how student affairs professionals used digital technology throughout their work. Using the futurology lens, the researcher envisioned how student affairs should use technology over the next ten years.

Analysis revealed that since 2005, student affairs administrators utilized digital technology to build capacity in their campus work, augment existing engagement efforts with students, faculty, and staff, and inspire change within and outside of their institution. Additionally, a historic timeline described how NASPA and ACPA provided limited, yet progressive, digital technology professional development education.

Student affairs administrators, professional organizations, and academy leaders leading digital technology implementation efforts might utilize the researcher’s recommendations as a starting point to catalyze the academy’s ongoing evolution.

Data models built for analyzing student data often obfuscate temporal relationships for reasons of simplicity, or to aid in generalization. We present a sequence model that is based on temporal relationships in heterogeneous student data as the basis for building predictive models to identify and understand students at risk. The properties of our sequence data model include temporal structure, segmentation, contextualization, and storytelling. To demonstrate the benefits of these properties, we have collected and analyzed 10 years of student data from the College of Computing at UNC Charlotte in a between-semester sequence model, and used data in an introductory course in computer science to build a within-semester sequence model. Our results for the two sequence models show that analytics based on the sequence data model can achieve higher predictive accuracy than non-temporal models with the same data. The sequence model not only outperforms non-temporal models to predict at risk students, but also provides interpretability by contextualizing the analytics with the context features in the data model. This ability to interpret and explore the analytics, enables the development of an interactive exploratory learning analytics framework to involve the domain experts in the process of knowledge discovery. To show this potential of the sequence model, we developed a dashboard prototype and evaluated the prototype during focus group with our college faculty, advisors, and leadership. As a result, the dashboard facilitates generating new hypotheses about student data, and enables the discovery of actionable knowledge for domain experts.

While much has been written about student engagement and its linkage to positive student outcomes—such as higher-order thinking, improved grades, and increased retention and graduation rates in traditional settings—little, if any, research has been done to connect student engagement and online student success. Learning Management Systems (LMSs) have the ability to measure student engagement by tracking frequency of logins, frequency of page visits, and frequency of discussion forum views, posts, and replies. Equally important, students who are aware of their levels of engagement compared to those levels measured by an LMS can self-monitor their progress and prevent the likelihood of failing a course. This initial exploratory study sought to determine whether relationships exist between students’ perceived level of engagement and students’ actual level of engagement as measured by an LMS, students’ perceived level of engagement and student success, and students’ actual level of engagement as measured by an LMS and student success. Correlation and regression analyses were performed to determine type and strength of relationships. Non-probability purposive sampling was used to recruit 38 respondents. Data showed that meaningful findings, which yielded statistically significant, modest or moderate positive partial relationships, occurred in the discussion forums. There were moderate positive relationships between students’ perceived level of engagement and frequency of discussion forum posts and replies, students’ perceived level of total engagement and student success, and students’ frequency of discussion forum views, posts, and replies, and student success. This initial exploratory study is useful in helping to refine future studies and learning more about student engagement levels in an online course and its relationship to positive student outcomes. Results can potentially help administrators and educators in making data-based decisions, and help students self-monitor engagement levels to improve student learning.

Too often, low socioeconomic school districts are associated with low performing students. The NCLB Act of 2001 dictates closure of the achievement gap by year 2014. Twenty-first century education must include instructional practices that use technology to enhance student learning. The non-experimental quantitative causal-comparative research study examined archival data from a Northwestern Arizona school district which included two dependent variables—the spring AIMS assessment and the spring ATI assessment. The statistical analysis used descriptive statistics to determine the effect of SRS on student academic achievement in mathematics. The data derived from 7th and 8th grade students to examine the ratio of the students’ scores in the highest category named Above, that included students’ scores which performed in the higher performance scale ranges on both assessments comparing the ratio of students’ scores in the Below category, that included students’ scores which performed in the lowest performance ranges on both assessments. Since the school district did not purchase the SRS technology until the 2010-2011 school year, the archival data from 2010 spring tests when students did not utilize SRS in the classroom was compared to the archival data from 2011 spring tests when students utilized SRS in the classroom environment. The data was compared horizontally from one year to the other: 7th grade to 7th grade and 8th grade to 8th grade on each test. In addition, the data was compared vertically from one year to the other: 7th grade to 8th grade on each test. The results of the research study can be used and replicated to help close the achievement gap.

This mixed-method research examines student achievement, student interaction and social elements to determine which elements support online course completion for students in a state virtual school. The quantitative goals seek to find a possible degree of convergence with the course completion average grade. Qualitative data from 10 high school students, their teachers, and quantitative data from their courses were gathered. Quantitative data from the learning management system (LMS) was reproduced, scrubbed of unwanted data, such as dropped students. Mixed method constant comparison was performed to determine a descriptive analysis of three variables: student achievement, student interaction, and social elements. Using the data gathered from the qualitative interviews, a yes or no was assigned to the students for behavioral, cognitive, and social skills. Using descriptive statistics, the skills were compared to the students' course grades. The results revealed a strong pattern match of data for Research Question 1. This data was indicative of the need for behavioral, cognitive, and social skills to complete an online course. Quantitative and teacher data were grouped by themes: asynchronous, administrative, and assessments; synchronous added for teacher data. A constant comparison of data correspondence was performed between the student course average grade, the access data, LMS theme data, and the course average final grade. The investigation of Research Question 2 indicated that the LMS's reporting module can determine interactions to support online course completion by providing average grade analysis along with access analysis and tool usage analysis.

Increasing technology intervention in rural schools is still a herculean task, especially with the lack of adequate infrastructures and limited resources. The purpose of this quantitative, causal comparative study was to determine the impact of technology interventions on student achievement in rural Nigerian schools. The study explored the differences in student achievement in mathematics and English between technology and nontechnology schools and established a relationship between teachers' level of technology implementation and student achievement. The convenience sample comprised 2,369 examination scores in mathematics and English of Senior Secondary Level 2 (SS2) students and purposive sampling of 34 teachers who participated in an online survey. Data were analyzed using multivariate analysis of variance (MANOVA), the level of technology implementation (LoTi) framework, and Pearson's correlation coefficient test. The results showed significant differences in student achievement between technology and nontechnology schools. However, the LoTi framework results indicated a low level of technology implementation in classroom instruction and no significant relationship between teachers' technology integration and student performance. Thus, the mere presence of technology seems to have more impact on student grades than the ways in which teachers use it. This study is resource material for stakeholders in education to ascertain the technology that worked best, teachers' professional development, and other infrastructures, prior to the deployment of technology interventions. The results could be useful for increasing teachers' technology integration and improving student performance, thereby leading to positive social change.

Student achievement has acted as the metric for school accountability and transparency. Administrators are becoming more innovative as they examine methods that will increase student achievement. However, research has shown little achievement gains in student achievement with regard to technology applications in schools. The theoretical framework of the digital divide guided this study. The original divide separated those who had technology and those who did not. The purpose of this study was to examine the differences in achievement scores between students who participated in a one-to-one technology program and students who participated in a traditional high school. The data generated for this study was from the New England Common Assessment Program (NECAP). This study examined 428 scores in mathematics and 429 scores each in reading and writing. To determine whether the one-to-one students outperformed the traditional students in mathematics, reading, and writing, the researcher conducted a t test. The t test indicated that no statistically significant difference existed between the achievement scores of the one-to-one students and those of the traditional student.