Since 2010, gamification, a concept and practice, gained attention in academic research. Results of its effectiveness were mixed and often lacked the use of grounded models or frameworks. Dichev et al. (2019b) proposed the existence of demotivational factors and highlighted two distinct sets of motivational drivers--one linked to game elements and…

In education, machine learning (ML), especially deep learning (DL) in recent years, has been extensively used to improve both teaching and learning. Despite the rapid advancement of ML and its application in education, a few challenges remain to be addressed. In this thesis, in particular, we focus on two such challenges: (i) data scarcity and…

The emergence of digital-first assessments is prompting reconsideration of, and innovation in, aspects of psychometrics, test validation, and test use. Using the Duolingo English Test (DET) as an example, this three-paper series seeks to address issues concerning the estimation of classification consistency and the reporting of results for such…

Early childhood traumatic experiences place children at-risk for social, emotional, and behavioral impairments that contribute to poor educational outcomes. There is an increasing awareness that children with early traumatic exposure may need supplemental supports for academic success. These supports may be presented in the form of…

The increasing amount of available subjective text data in internet such as product reviews, movie critiques and social media comments provides golden opportunities for information retrieval researchers to extract useful information out of such datasets. Topic modeling and sentiment analysis are two widely researched fields that separately try to…

Instructional designers must design and develop online learning environments that present the content in a way that learners will find important and useful. Faculty and novice designers are being tasked to design and develop online learning environments without having the necessary knowledge or experience in instructional design in order to select…

As U.S federal government agencies have increased the use of the Internet to utilize technologies such as e-learning, U.S. federal government information systems have become more exposed to security vulnerabilities that may contribute to system attacks and system exploitation. U.S. federal government agencies are required to come up with their own…

Automation can mitigate issues when scaling and managing quality and identity in public discourse on the web. Discourse needs to be curated and filtered. Anonymous speech has to be supported while handling adversaries. Reliance on human curators or analysts does not scale and content can be missed. These scaling and management issues include the…

Quickly accessing the contents of a video is challenging for users, particularly for unstructured video, which contains no intentional shot boundaries, no chapters, and no apparent edited format. We approach this problem in the domain of lecture videos though the use of machine learning, to gather semantic information about the videos; and through…

Theory building is complex and ongoing. Theories need to be constantly tested and the underlying constructs explored, as knowledge of a field evolves. This study, which is in support of Moore's (1980, 1993) theory of transactional distance, is exploratory and descriptive, and focuses on one of the key variables in the theory dialogue. As…

This study sought to examine and extend the existing knowledge of IBSTPI competencies of instructional design (International Board of Standards for Training, Performance and Instruction, 2000), the instructional rubric standard expectations of Quality Matters (2010), the identified categories of online learning affordances (Kirschner, Strijbos,…

The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…