Learning at Scale

Roll, Ido; Russell, Daniel M.; Gašević, Dragan

doi:10.1007/s40593-018-0170-7

Cited by 41 publications

(13 citation statements)

References 27 publications

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“…In personalized and flexible learning, many AI researchers collect learners' choice and behavioral data to enhance learning experiences. These examples are Intelligent Tutoring (Roll et al 2018), predicting each student's grades to help teachers develop remedial actions or tailor career opportunities based on academic performance (Berendt et al 2017). Regarding flexibility and inclusivity, Ossiannilsson (2019) believes that it is not a challenge to find high-quality courses to learn in the era of the massive open online courses (MOOC); the challenges are in how to navigate between the abundance of similar courses.…”

Section: The Roles Benefits and Challenges Of Implementing Artificial Intelligence In Educationmentioning

confidence: 99%

Preliminary Research on the Social Attitudes toward AI’s Involvement in Christian Education in Vietnam: Promoting AI Technology for Religious Education

Tran

Nguyen

2021

Religions

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Artificial intelligence innovations, such as chatbots and specialized education suggestion tools, provide potential interactive and on-demand pedagogical engagement between non-Christians and Christians with Christianity. However, there is little empirical research on the readiness, acceptance, and adoption of religious education involvement of AI in a secular state such as Vietnam. This research addresses the literature gap by providing an entrepreneurial analysis and customer perspectives on the ideas of AI involvement in religious education. Specifically, the study explores whether the Vietnamese across different ages accept and have enough skills to adopt AI in Christian education innovation. The interview sample is 32 participants, selected based on their religious orientation (Christians and non-Christians) and age (Generation X, Generation Y, and Generation Z). Most respondents are open to AI application in religious education except for Church personnel. However, only Generation Z are fully prepared to adopt this innovation. Theoretically, the research customizes the Unified Theory of Acceptance and Use of Technology model into religious innovation context. Practically, this research acts as market research on the demand for AI’s religious innovation in Vietnam, an insight for future religious tech entrepreneurs.

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Section: The Roles Benefits and Challenges Of Implementing Artificial Intelligence In Educationmentioning

confidence: 99%

Preliminary Research on the Social Attitudes toward AI’s Involvement in Christian Education in Vietnam: Promoting AI Technology for Religious Education

Tran

Nguyen

2021

Religions

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“…This socio-cultural process of meaning-making is highly contextual and specific to learners' goals and environment. However, video interfaces rarely support these social activities that constitute the context of learning [10,33]. Drawing on this literature, we suggest that further attention to design is needed in order to explore ways in which people can participate and exchange ideas by deepening their engagement with and interpretation of shared resources.…”

Section: Background and Previous Workmentioning

confidence: 99%

"Can you believe [1:21]?!"

Yarmand

Yoon

Dodson

et al. 2019

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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As videos become increasingly ubiquitous, so is video-based commenting. To contextualize comments, people often reference specific audio/visual content within video. However, the literature falls short of explaining the types of video content people refer to, how they establish references and identify referents, how video characteristics (e.g., genre) impact referencing behaviors, and how references impact social engagement. We present a taxonomy for classifying video references by referent type and temporal specificity. Using our taxonomy, we analyzed 2.5K references with quotations and timestamps collected from public YouTube comments. We found: 1) people reference intervals of video more frequently than time-points, 2) visual entities are referenced more often than sounds, and 3) comments with quotes are more likely to receive replies but not more "likes". We discuss the need for in-situ dereferencing user interfaces, illustrate design concepts for typed referencing features, and provide a dataset for future studies.

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“…Online learning is the fastest growing areas of education worldwide because it provides access to educational opportunities in a flexible manner to students from diverse backgrounds and geographical regions who often can't access higher education by other means (Delaney & Fox, 2013;Roll, Russell, & Gašević, 2018). In Ireland, online higher education courses are less prevalent than in other jurisdictions such as Australia or the United States, but the number of students enrolling in online higher education courses in Ireland is growing, which is evident from the increase of online-only government sponsored Springboard degree courses, which grew from 10% of courses in 2011 to 15% in 2016 (HEA, 2016;HEA, 2018).…”

Section: Introductionmentioning

confidence: 99%

A balancing act: a window into online student engagement experiences

Farrell

Brunton

2020

Int J Educ Technol High Educ

168

121

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This article reports on a qualitative study which explored online student engagement experiences in a higher education institution. There are very few studies providing in-depth perspectives on the engagement experiences of online students. The project adopted a case study approach, following 24 online students over one academic year. The setting for the study was an undergraduate online Humanities programme at Dublin City University. The research question for the study was: What themes are central to online student engagement experiences? Data was collected from participant-generated learning portfolios and semi-structured interviews and analysed following a data-led thematic approach. The five central themes that make up the study’s findings highlight key issues of students’ sense of community, their support networks, balancing study with life, confidence, and their learning approaches. The findings of this study indicate that successful online student engagement was influenced by a number of psychosocial factors such as peer community, an engaging online teacher, and confidence and by structural factors such as lifeload and course design. One limitation of the study is that it is a relatively small, qualitative study, its findings provide insights into how online degrees can support online students to achieve successful and engaging learning experiences.

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Learning at Scale

Cited by 41 publications

References 27 publications

Preliminary Research on the Social Attitudes toward AI’s Involvement in Christian Education in Vietnam: Promoting AI Technology for Religious Education

Preliminary Research on the Social Attitudes toward AI’s Involvement in Christian Education in Vietnam: Promoting AI Technology for Religious Education

"Can you believe [1:21]?!"

A balancing act: a window into online student engagement experiences

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