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Statistics education is the practice of teaching and learning of statistics, along with the associated scholarly research.. Statistics is both a formal science and a practical theory of scientific inquiry, and both aspects are considered in statistics education.
Educational research refers to the systematic collection and analysis of evidence and data related to the field of education. Research may involve a variety of methods [ 1 ] [ 2 ] [ 3 ] and various aspects of education including student learning, interaction, teaching methods , teacher training, and classroom dynamics.
While the analysis of educational data is not itself a new practice, recent advances in educational technology, including the increase in computing power and the ability to log fine-grained data about students' use of a computer-based learning environment, have led to an increased interest in developing techniques for analyzing the large amounts of data generated in educational settings.
Dr. Wolfgang Greller and Dr. Hendrik Drachsler defined learning analytics holistically as a framework. They proposed that it is a generic design framework that can act as a useful guide for setting up analytics services in support of educational practice and learner guidance, in quality assurance, curriculum development, and in improving teacher effectiveness and efficiency.
Data-informed decision-making (DIDM) gives reference to the collection and analysis of data to guide decisions that improve success. [1] Another form of this process is referred to as data-driven decision-making, "which is defined similarly as making decisions based on hard data as opposed to intuition, observation, or guesswork."
Inquiry methods in SOTL include reflection and analysis, interviews and focus groups, questionnaires and surveys, content analysis of text, secondary analysis of existing data, quasi-experiments (comparison of two sections of the same course), observational research, and case studies, among others. As with all scholarly study, evidence depends ...
Research-informed teaching refers to the practice of linking research with teaching in Higher Education. Most universities in the world are organised into teaching and research divisions. Professors and lecturers will normally be contracted to do both and, in theory at least, course syllabi are structured around the teacher's research interests.
The most important distinction between the initial data analysis phase and the main analysis phase, is that during initial data analysis one refrains from any analysis that is aimed at answering the original research question. [109] The initial data analysis phase is guided by the following four questions: [110]