We present an interactive spreadsheet that supports teaching essential concepts in classification using the logistic regression (LoR) model for binary classification. The interactive spreadsheet demonstrates the capabilities of LoR by integrating computation with visualization. Students will reinforce concepts like probabilities, maximum…

It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…

R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…

Adaptive E-learning platforms provide personalized learning process relying mainly on learning styles. The traditional approach to find learning styles depends on asking learners to self-evaluate their own attitudes and behaviors through surveys and questionnaires. This approach presents several weaknesses including the lack of self-awareness of…

This study explores and characterizes learners' participation patterns in MOOC forums, as well as the factors that correlate with learners' participation. Educational data mining and learning analytics methods were used to retrieve and analyze the learners' interpersonal interaction data, which had accumulated in the Coursera log files. The…

The purpose of this study was to analyze six English as a Foreign Language (EFL) learners' trajectories of discriminating near-synonyms in a data-driven learning task. Since the learners find it considerably difficult to learn subtle meaning differences of near-synonyms, corpus-based data-driven learning may provide an opportunity for them to…

Although massive open online courses (MOOCs) have attracted much worldwide attention, scholars still understand little about the specific elements that students find engaging in these large open courses. This study offers a new original contribution by using a machine learning classifier to analyze 24,612 reflective sentences posted by 5,884…

Attributes of teaching and learning contexts provide rich information about how students participate in learning activities. By tracking and analyzing snapshots of these attributes captured continuously throughout the duration of the learning activities, teachers can identify individual students who need special attention and apply different…

An important, yet largely unstudied problem in student data analysis is to detect "misconceptions" from students' responses to "open-response" questions. Misconception detection enables instructors to deliver more targeted feedback on the misconceptions exhibited by many students in their class, thus improving the quality of…

Determining what students think about science, technology, and society (STS) is of great importance. This also provides the basis for scientific literacy. As such, this study was conducted with a total of 102 senior students attending a university located in western Turkey. This study utilized the survey model as a research model and the…

Students' informal conversations on social media (e.g., Twitter, Facebook) shed light into their educational experiences--opinions, feelings, and concerns about the learning process. Data from such uninstrumented environments can provide valuable knowledge to inform student learning. Analyzing such data, however, can be challenging. The complexity…

The learning sciences community's interest in learning analytics (LA) has been growing steadily over the past several years. Three recent symposia on the theme (at the American Educational Research Association 2011 and 2012 annual conferences, and the International Conference of the Learning Sciences 2012), organized by Paulo Blikstein, led…

This paper extends the literature on grader variation and the role of moderation and socialisation processes in reducing this variation. It offers a fresh categorisation of academics' assessment beliefs and expectations, and uses this categorisation to analyse the interaction between implicit and explicit expectations in relation to grader…

In order to improve the understanding of educational needs among residents caring for the critically ill, narrative accounts of 19 senior physician trainees participating in level of care decision-making were analyzed. In this multicentre qualitative study involving 9 university centers in Canada, in-depth interviews were conducted in either…

This study investigates the possibility of analyzing educational data using the theory of rough sets which is mostly employed in the fields of data analysis and data mining. Data were collected using an open-ended conceptual understanding test of the living things administered to first-year high school students. The responses of randomly selected…