Teachers must be able to monitor students' behavior and identify valid cues in order to draw conclusions about students' actual engagement in learning activities. Teacher training can support (inexperienced) teachers in developing these skills by using videotaped teaching to highlight which indicators should be considered. However, this supposes…

With the increase in studies about artificial intelligence (AI) in the educational field, many scholars in the field believe that the role of teachers, school and leaders in education will change. In this regard, the purpose of this study is to examine what possible scenarios are there with the arrival of AI in education and what kind of…

Many recent studies have looked at the viability of applying recurrent neural networks (RNNs) to educational data. In most cases, this is done by comparing their performance to existing models in the artificial intelligence in education (AIED) and educational data mining (EDM) fields. While there is increasing evidence that, in many situations,…

There has been much research on the effectiveness of animated pedagogical agents in an educational context, however there is little research about how the emotions they display contribute to a learner's understanding of the lesson. The positivity principle suggests that learners should learn better from instructors with positive emotions compared…

Artificial intelligence (AI) is receiving a lot of attention in various fields. There is a need for educating students in AI technology. In this context, we have created a new type of carbon dioxide fountain by integrating AI with the well-established Arduino-carbon dioxide fountain experiment. This experiment consists of an Arduino…

Educational artificial intelligence (EAI) means an integration of artificial intelligence (AI) and educational science that is going to serve as an authoritative element of the education system in the future. However, limited bibliographic analysis study have been carried out with the purpose of conceptualising the advancements in this field of…

As we take advantage of new technologies that allow us to streamline the coding process of large qualitative datasets, we must consider whether human cognitive bias may introduce statistical bias in the process. Our research group analyzes large sets of student responses by developing computer models that are trained using human-coded responses…

There have been giant leaps in the field of education in the past 1-2 years. Schools and colleges are transitioning online to provide more resources to their students. The COVID-19 pandemic has provided students more opportunities to learn and improve themselves at their own pace. Online proctoring services (part of assessment) are also on the…

Assessment developers are increasingly using the developing technology of machine learning in transforming how to assess students in their science learning. I argue that these algorithmic models further embed the structures of inequality that are pervasive in the development of science assessments in how they legitimize certain language practices…

Commonly used machine learning applications seem to relate to big data. This article provides a gentle review of machine learning and shows why machine learning can be applied to small data too. An example of applying machine learning to screen irregularity reports is presented. In the example, the support vector machine and multinomial naïve…

Evaluators often find themselves in situations where resources to conduct thorough evaluations are limited. In this paper, we present a familiar instance where there is an overwhelming amount of open text to be analyzed under the constraints of time and personnel. In instances when timely feedback is important, the data are plentiful, and answers…

Early detection is key to intervening with students diagnosed with a specific learning disorder (SLD), which includes problems with spelling, grammar, punctuation, and clarity and organization of written expression, as a means of preventing potential negative consequences from this disorder. Deep convolutional neural networks (CNNs) perform better…

This dissertation presents a novel theory of event memory along with an associated computational model that embodies the claims of view which is integrated within a cognitive architecture. Event memory is a general-purpose storage for personal past experience. Literature on event memory reveals that people can remember events by both the…

Sensors and internet of things (IoTs) are ubiquitous in our modern day-to-day living. The past decade has been marked by the rapid emergence and proliferation of a myriad of small devices. Applications range from smart home devices that control cooking ranges to mobile phones, wearable devices that serve as fitness trackers and personalized…

"Reading the Machine: Digital Reading Practices and the Contemporary U.S. Novel," investigates how emerging information technologies--networked devices, software programs, and algorithmic protocols--redefine cultural forms of textual production and reception. Focusing on the longstanding literary form of the novel as a point of entry,…