Understanding data analysis and interpreting data are key components of teaching interdisciplinary undergraduate students. We detail a semester-long research project that introduces students to long-term data sets, incorporates the use of widely available statistical analysis, and underscores an inquiry-based method of teaching climate change. Our…

Sentiment Analysis is a field of Natural Language Processing which aims at classifying the author's sentiment in text. This paper first describes a sentiment analysis model for students' comments about professor performance. The model achieved impressive results for comments collected from student surveys conducted at a private university in…

This publication describes the methods and procedures used for the 2008/18 Baccalaureate and Beyond Longitudinal Study (B&B:08/18). The B&B graduates, who completed the requirements for a bachelor's degree during the 2007-08 academic year, were first surveyed as part of the 2008 National Postsecondary Student Aid Study (NPSAS:08), and then…

Even under ideal conditions, teaching is tough work. Facing unrelenting pressure from administrators and parents and caught in a race against time to improve student outcomes, educators can easily become discouraged (or worse, burn out completely) without a robust coaching system in place to support them. For more than 20 years, perfecting such a…

A significant amount of research has gone into predicting student performance and many studies have been conducted to predict why students drop out. A variety of data including digital footprints, socio-economic data, financial data, and psychological aspects have been used to predict student performance at the test, course, or program level.…

This Equity Tool, intended to support when critically reading a research study/report, provides a brief introduction to key concepts and issues involved in using largescale research, calling attention to high profile controversies, and providing explicit linkages to desegregation areas (race, sex, nationality, religion). The first part (Table 1)…

This case study discusses how theory and deductive analysis can be used to better understand work-based learning (WBL). Based in a U.K. teacher education setting, it discusses a project which examined how novice teachers in English Further Education develop their professional knowledge and how their experiences might help understand WBL more…

Even with extensive retention research dating from the 1960s, community colleges still struggle to identify the reasons why students do not return to college. Data mining has allowed these retention models to evolve to identify new patterns among student populations and variables. The purpose of this study was to create a predictive model for…

Probabilistic reasoning underpins much of middle school students' future work in data analysis and inferential statistics. Unfortunately for many middle school students, probabilistic reasoning is not intuitive. One specific area in which students seem to struggle is determining the probability of compound events (Moritz and Watson 2000). Research…

Purpose: This paper explores the challenges of conducting qualitative research from ELT (English Language Teaching) Ph.D. candidates' perspectives. Design/methodology/approach: The participants of the study consisted of 30 Iranian Ph.D. students majoring in ELT. The semi-structured interview was employed to investigate the heart of experiences,…

Increasingly, students training in the biological sciences depend on a proper grounding in biological statistics, data science and experimental design. As biological datasets increase in size and complexity, transparent data management and analytical methods are essential skills for undergraduate biologists. We propose that using the software R…

The use of large, open-source data sets is ubiquitous in scientific research. Scientists--ranging from meteorologists to chemists to epidemiologists--are researching and investigating critical questions using data that they have not themselves collected. To contribute to the growing effort to bring data science into classrooms, the authors have…

Humans have always been lured by the idea that they can use data to understand a phenomenon and make predictions about it. Learning analytics, in this sense, promise to understand and optimize learning and the environments in which it occurs by collecting data from learners and learning contexts. In this regard, this study systematically examines…

With the impactful nature of the COVID-19 pandemic, this manuscript describes a teaching case for COVID-19 vaccinations to develop students' knowledge of analytics and supply chain management. The experiential learning activity is developed in the context of an undergraduate upper-level course on descriptive analytics and data visualization. The…

The development of digital technologies has created a market need for specialists working with the big data that is necessary for making management decisions. This study aims to identify the skills structure of the data analyst profession (DAP) in Russia. The authors used a program code written in Python to examine relevant vacancies extracted…