Developing tools to support students and learning in a traditional or online setting is a significant task in today's educational environment. The initial steps toward enabling such technologies using machine learning techniques focused on predicting the student's performance in terms of the achieved grades. However, these approaches do not…

This study aimed to investigate what cultural meanings English language learners (ELLs) attributed to the selected digital photographs and how they interpreted these photographs at the intersection of 'my culture' and 'other culture' dichotomy. This qualitative study was carried out during the fall term of 2020-2021 at a state university in…

In this paper we show how we can utilize human-guided machine learning techniques coupled with a learning science practitioner interface (DataShop) to identify potential improvements to existing educational technology. Specifically, we provide an interface for the classification of underlying Knowledge Components (KCs) to better model student…

Machine learning algorithms have recently been used to predict students' performance in an introductory physics class. The prediction model classified students as those likely to receive an A or B or students likely to receive a grade of C, D, F or withdraw from the class. Early prediction could better allow the direction of educational…

Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…

High failure rates in introductory college science courses, including anatomy and physiology, are common at institutions across the country, and determining the specific factors that contribute to this problem is challenging. To identify students at risk for failure in introductory physiology courses at our open-enrollment institution, an online…

Are there consequences of calling objects by their names? Lupyan (2008) suggested that overtly labeling objects impairs subsequent recognition memory because labeling shifts stored memory representations of objects toward the category prototype (representational shift hypothesis). In Experiment 1, we show that processing objects at the basic…

We discuss the categorization of 20 quantum mechanics problems by physics professors and undergraduate students from two honours-level quantum mechanics courses. Professors and students were asked to categorize the problems based upon similarity of solution. We also had individual discussions with professors who categorized the problems. Faculty…

Bridgewater State University (BSU) is a public institution that falls under the Carnegie classification of Master's Colleges and Universities. BSU is committed to serving students in the New England region. This student population includes a sizeable number of underrepresented students. BSU is dealing with intense pressure to serve these students…

Many of the problems studied in cognitive science are inductive problems, requiring people to evaluate hypotheses in the light of data. The key to solving these problems successfully is having the right inductive biases--assumptions about the world that make it possible to choose between hypotheses that are equally consistent with the observed…

The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…