Background: Creativity is linked with educationally relevant constructs such as achievement, intelligence, and motivation. However, very few studies have explored longitudinal links between the constructs or the aetiology of individual differences in childhood creativity. Aims: The study addresses the gap in the literature of developmental studies…

Efforts have been made to promote children's interest in science, but little is known about how children's interest in science relates to other characteristics, such as science-specific curiosity, domain-general epistemic curiosity, and verbal intelligence. The current study examines how these factors relate to individual differences in children's…

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,…

In this thesis, we incorporate information theory into statistical signal processing and machine learning in order to achieve robust learning in presence of outliers (or generally in environments with non-Gaussian structure). In other words, by incorporating information theory especially when structure of environment is non-Gaussian, the…

We are currently in a century of data where massive amount of data are collected and processed every day, and machine learning plays a critical role in automatically processing the data and mining useful information from it for making decisions. Despite the wide and successful applications of machine learning in different fields, the robustness of…

Reduced empathy and alexithymic traits are common across the autism spectrum, but it is unknown whether this is also true for intellectually advanced adults with autism spectrum disorder. The aim of this study was to examine whether college students with autism spectrum disorder experience difficulties with empathy and alexithymia, and whether…

Intelligence typically is defined as consisting of "adaptation to the environment" or in related terms. Yet, it is not clear that "general intelligence" or g, traditionally conceptualized in terms of a general factor in a psychometrically-based hierarchical model of intelligence, provides an optimal way of defining intelligence…

Extensive research has established that successful learning from an example is conditional on an important learning activity: self-explanation. Moreover, a model for learning from examples suggests that self-explanation quality mediates effects of examples on learning outcomes (Atkinson et al. in Rev Educ Res 70:181-214, 2000). We investigated…

In this study, we built a personalized hybrid course recommendation system (PHCRS) that considers students' interests, abilities and career development. To meet students' individual needs, we adopted the five most widely used algorithms, including content-based filtering, popularity-based methods, item-based collaborative filtering, user-based…

Digital learning games are designed to foster both student learning and enjoyment. Given this goal, an interesting research topic is whether game mechanics that promote learning and those that promote enjoyment have different effects on students' experience and learning performance. We explored these questions in "Decimal Point," a…

Rapid developments in educational technology in higher education are intended to make learning more engaging and effective. At the same time, cognitive load theory stresses limitations of human cognitive architecture and urges educational developers to design learning tools that optimise learners' mental capacities. In a 2-month study we…

Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic achievements. This study proposes a new model based on machine learning algorithms to predict the final exam grades of undergraduate students, taking their midterm exam grades as the source data. The…

Previous attempts to explain teachers' educational effectiveness have mostly focused on personal traits, organizational commitment, pedagogical content knowledge or the passion for education, and so on. We want to highlight that social skills--competencies that enable teachers to interact effectively with others--might contribute to the teachers'…