Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing…

Collaborative learning (CL) can be a powerful method for sharing understanding between learners. To this end, strategic regulation of processes, such as cognition and affect (including metacognition, emotion and motivation) is key. Decades of research on self-regulated learning has advanced our understanding about the need for and complexity of…

Education systems produce a large number of valuable data for all stakeholders. The processing of these educational data and making studies on the future of education based on the data reveal highly meaningful results. In this study, an insight was tried to be developed on the educational data collected from ninth-grade students by using data…

The aim of this paper is to survey recent research publications that use Soft Computing methods to answer education-related problems based on the analysis of educational data 'mined' mainly from interactive/e-learning systems. Such systems are known to generate and store large volumes of data that can be exploited to assess the learner, the system…

Humans are sensitive to the properties of individual items, and exemplar models are useful for capturing this sensitivity. I am a proponent of an extension of exemplar-based architectures that I briefly describe. However, exemplar models are very shallow architectures in which it is necessary to stipulate a set of primitive elements that make up…

This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent…

Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free statistical modeling of artificial intelligence, is a promising synthesis tool for discovering novel…

The ongoing datafication of our social reality has resulted in the emergence of new data-based business models. This development is also reflected in the education market. An increasing number of educational technology (EdTech) companies are entering the traditional education market with data-based teaching and learning solutions, and they are…

It is common to use anthropomorphic labels when talking about technology, for example describing some robots and phones as smart, thinking and talking. This article describes a workshop in which students considered ways that words such as 'hearing', 'smart' and 'intelligence' might change in meaning when they are used in the context of robotics…

Horror stories abound of colleges closed, faculty laid off, and liberal arts programs terminated. Families express concern about costs, students worry about debt, and society appears skeptical about whether a college education is worth it. In many of these reports, colleges and universities are to blame for their own failures. Academic programs…

This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent…

In "Cognitive Skills You Need for the 21st Century," Stephen Reed discusses a Future of Jobs report that contrasts trending and declining skills required by the workforce in the year 2022. Trending skills include analytical thinking and innovation, active learning strategies, creativity, reasoning, and complex problem solving. Part One…

Accurately predicting which students are best suited for graduate programs is beneficial to both students and colleges. In this paper, we propose a quantitative machine learning approach to predict an applicant's potential performance in the graduate program. Our work is based on a real world dataset consisting of MS in CS [Master of Science in…

Technology has been shown to reduce students' public speaking anxiety, enhance their delivery skills, and increase presentation self-efficacy. However, students can only garner benefits if technology designed for improving public speaking skills has been adopted and implemented. This study aims to analyze the relationship between students'…

Through co-occurrence analysis of 1139 documents (1964-2018) we identified discussions about the implementation of student teaching evaluation (SET). We found that: (1) Attention to SET originated in the US in the 1970s, spreading to German-speaking countries in the mid-1990s and continuing in China and Latin America in the early 2000s. (2) SET is…