Teachers' use of student data to inform instruction is commonly accepted as sound educational practice, and this data use is only likely to grow as more data, as well as more-complex data, become increasingly available to educators. However, numerous studies reveal inconsistent data use among teachers and an overall lack of the preparation and…

Technology-based, open-ended learning environments (OELEs) can capture detailed information of students' interactions as they work through a task or solve a problem embedded in the environment. This information, in the form of log data, has the potential to provide important insights about the practices adopted by students for scientific inquiry…

Encouraging teachers to reflect on their instructional practices and course design has been shown to be an effective means of improving instruction and student learning. However, the process of encouraging reflection is difficult; reflection requires quality data, thoughtful analysis, and contextualized interpretation. Because of this, research on…

Intelligent assessment, the core of any AI-based educational technology, is defined as embedded, stealth and ubiquitous assessment which uses intelligent techniques to diagnose the current cognitive level, monitor dynamic progress, predict success and update students' profiling continuously. It also uses various technologies, such as learning…

Data-based individualization (DBI) is a process of collecting and analyzing data on students' response to intervention and then making intervention adaptations accordingly. Although this process can lead to better student outcomes, very few teachers are trained in the components of DBI, particularly in relation to behavior. Improving practice…

Trial-based functional analysis (TBFA) is an accurate and ecologically valid assessment of challenging behavior. Further, there is evidence to suggest that individuals with minimal exposure to behavior analytic assessment methodology (e.g., parents, teachers) can quickly be trained to conduct TBFAs in naturalistic settings (e.g., schools, homes).…

Preparing data-literate citizens and supporting future generations to effectively work with data is challenging. Engaging students in Knowledge Building (KB) may be a promising way to respond to this challenge because it requires students to reflect on and direct their inquiry with the support of data. Informed by previous studies, this research…

School attendance/absenteeism (SA/A) is a crucial indicator of health and development in youth but educational policies and health-based practices in this area rely heavily on a simple metric of physical presence or absence in a school setting. SA/A data suffer from problems of quality (reliability, construct validity, data integrity) and utility…

Abilities to interpret, analyze, and report data are in-demand job skills that many colleges and universities struggle to incorporate into the curriculum. The client-based project outlined in this study examines the experiential learning pedagogy used to teach students media analytics. This semester-long project encourages students to complete a…

This dissertation was prepared to determine if a correlation existed between a student's poverty level and an educational diagnosis of serious emotional disturbance. I hypothesize that students at or under the United States' definition of poverty are more likely to exhibit signs and symptoms of a serious emotional disturbance and therefore be…

Colorado has led the nation in supporting the success of all Coloradans, enacting bold policies, and continuing to build a Colorado for all. These efforts have all been informed by robust stakeholder engagement paired with data analysis. Various initiatives over the years have improved the state's ability to use data to inform these goals. With…

It is essential to save lives during emergencies not only in hospitals but also in colleges and universities. Failure to identify risks and take prompt action during catastrophes and emergency situations could result in the loss of life and property for the campus community. This research aims to explore the feasibility of using data analytics to…

Monitoring the fidelity with which implementers implement behavioral procedures is important, but individuals tasked with monitoring fidelity may have received little training. As a result, their data may be affected by variations in implementers' performance, such as the frequency of fidelity errors. To determine the extent to which the frequency…

Integrative data analyses have recently been shown to be an effective tool for researchers interested in synthesizing datasets from multiple studies in order to draw statistical or substantive conclusions. The actual process of integrating the different datasets depends on the availability of some common measures or items reflecting the same…

With ubiquitous computing, problems can be solved using more strategies than ever, though many strategies feature subpar performance. Here, we explored whether and how simple advice regarding when to use which strategy can improve performance. Specifically, we presented unfamiliar alphanumeric equations (e.g., A + 5 = F) and asked whether counting…