In a range of settings, human operators make decisions with the assistance of automation, the reliability of which can vary depending upon context. Currently, the processes by which humans track the level of reliability of automation are unclear. In the current study, we test cognitive models of learning that could potentially explain how humans…

When text datasets are very large, manually coding line by line becomes impractical. As a result, researchers sometimes try to use machine learning algorithms to automatically code text data. One of the most popular algorithms is topic modeling. For a given text dataset, a topic model provides probability distributions of words for a set of…

We systematically compared two coding approaches to generate training datasets for machine learning (ML): (1) a holistic approach based on learning progression levels; and (2) a dichotomous, analytic approach of multiple concepts in student reasoning, deconstructed from holistic rubrics. We evaluated four constructed response assessment items for…

Among community college leaders and others interested in reforms to improve student success, there is growing interest in adopting machine learning (ML) techniques to predict credential completion. However, ML algorithms are often complex and are not readily accessible to practitioners for whom a simpler set of near-term measures may serve as…

Objective: This study examines how accurately a small set of short-term academic indicators can approximate long-term outcomes of community college students so that decision-makers can take informed actions based on those indicators to evaluate the current progress of large-scale reform efforts on long-term outcomes, which in practice will not be…

While many studies have demonstrated that conversational tutoring systems have a positive effect on learning, the amount of manual effort required to author, design, and tune dialogue behaviors remains a major barrier to widespread deployment and adoption of these systems. Such dialogue systems must not only understand student speech, but must…

Presents an information systems navigation approach using a combination of functionalities encountered in classification processes, Hypertext systems, and information retrieval systems. The first version of the SYRIUS system is described, with emphasis on the user's graphic interface which integrates these functionalities. (26 references) (EA)

A questionnaire was designed to aid the interested professional in describing, characteristics and analyzing his game, model, or simulation, and tested on a number of Department of Defense (DOD) games. An over-riding goal for the questionnaire was to produce a categorization scheme for games in general. The different sections of the questionnaire…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…

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…