Transcription and translation into English. Sanjib Laobangdisa describes his experience during the 2022 Assam floods. The speaker is a worker who speaks Bengali, Hindi, Nagamese, and Assamese in addition to Dimasa. He is 46 years old at the time of recording.

Transcription and translation into English. Sneha Barman describes her experience during the 2022 Assam floods. The speaker is a student with a MA education who speaks Bengali, Hindi, and English in addition to Dimasa. She is 23 years old at the time of recording.

Presentation exploring the technical perspective of displaying CoRSAL content on social media.

Transcription and translation into English. Nayan Barman describes his experience during the 2022 Assam floods. The speaker is a worker with a high school education who speaks Bengali, Hindi, and English in addition to Dimasa. He is 59 years old at the time of recording.

Transcription and translation into English. Biswajit Barman describes his experience during the 2022 Assam floods. The speaker is a retired government worker who is 63 years old at the time of recording.

Transcription and translation into English. Bijoy Barman describes his experience during the 2022 Assam floods. The speaker is a government worker with a BA education who speaks Bengali, Hindi, and English in addition to Dimasa. He is 34 years old at the time of recording.

Transcription and translation into English. Usha Rani Barman describes her experience during the 2022 Assam floods. The speaker is a retired teacher who speaks Bengali, Hindi, and Assamese in addition to Dimasa. She is 70 years old at the time of recording.

Transcription and translation into English. Sabita Barman describes her experience during the 2022 Assam floods. The speaker is a housewife who is 56 years old at the time of recording.

This article provides a content analysis of studies from 2010 to 2020 aiming to disclose how artificial intelligence (AI) has been applied to the education sector and explore the potential research trends and challenges of AI in education. The content analysis shows that the research questions can be classified into development layer (classification, matching, recommendation, and deep learning), application layer (feedback, reasoning, and adaptive learning), and integration layer (affection computing, role-playing, immersive learning, and gamification).

In this enlightening discussion, Prof. Tadeusz Slupski of Poland, a visitor to Zangskar since November 1977, discusses the cultural shifts over the decades with a couple from Sani village. Slupski narrates the socio-cultural transformations he witnessed since his initial visit and invites the couple to expand on these changes from their firsthand experiences. They discuss the nuances of the architectural evolution of Zangskari houses, delving into traditional heating and lighting methods, recalling cherished olden poems, songs, and dances—emphasizing the "chham" (Chham) dance and costumes, and reminisce about traditional weddings marked by horseback marriage processions. Dr. Jamphel Sheyan, Assistant Professor of English at GMDC, skillfully interprets the conversation, bridging Zangskari and English. Recorded in Sani village, Ladakh Union Territory, India.

In this insightful discussion, Gyafo (King) Phuntsok Dawa, the King of Padum, answers the questions raised on Zangskar and its history by Dr. Tadeusz Slupski, a regular visitor to Zangskar since 1977. Gyafo Dawa delves into the rich heritage of his lineage and the Zangskari royal family. He recounts the pivotal moment in June 1948 when Zangskar faced invasion from Pakistani forces, prompting his father and the entire family, accompanied by Kushok Bakula Rimpoche, to seek refuge in Himachal Pradesh. Dr. Slupski further inquires about the demographics of Zangskar, leading the discussion towards the significant societal and cultural changes Zangskar has experienced over the past four and a half decades, since he first visited. Recorded in Old Padum village, Ladakh Union Territory, India.

This article proposes a method to model evacuation flows and reveal the patterns of evacuation flows at different spatial scales. First, the authors present a method to characterize evacuation flows at different geographic scales: the state level, considering evacuation flows across southern states affected by Irma; the urban/rural area level, and the county level. Then they demonstrate results on the predictability of evacuation flows in the most affected state, Florida, by using the following environmental factors: the destructive force of the hurricane, the socioeconomic context, and the evacuation policy issued for counties. The results presented in this paper can help decision makers to better understand population evacuation behaviors given certain environmental features, which in turn will aid in the design of efficient and informed preparedness and response strategies.

Article for a study aimed to develop understanding of the current state of metadata practices in digital collections of archival institutions in the Arabian Gulf region. It also explored perspectives (including attitudes and possible barriers) for development of large-scale regional portals that would facilitate discovery of Arab digital archives (including language collections) by aggregating metadata. It was presented at the 2nd International Workshop on Digital Language Archives held on June 30, 2023 as part of the ACM/IEEE Joint Conference on Digital Libraries 2023.

Article explores the training gap between the way these materials are organized and represented and the understanding of that data – and expectations towards the more functional ways of its organization and representation – by language preservation and revitalization researchers, and by members of language communities. Information resources collected by language archives have unique attributes of importance to their target user groups, and these attributes and their representation are not currently widely addressed by the formal training provided to information professionals. It was presented at the 2nd International Workshop on Digital Language Archives held on June 30, 2023 as part of the ACM/IEEE Joint Conference on Digital Libraries 2023.<

Poster on an analysis of publications from 2002-2021 on data literacy to identify relevant topics and trends. This is a part of preliminary work done to support a proposal for an Institute of Museum and Library Services (IMLS) grant. It was presented at the 2021 Association for Library and Information Science Education (ALISE) Annual Conference held virtually September 20-24, 2021.

Poster on a comparative analysis of data literacy competency frameworks. Seven competency frameworks were selected for in-depth analysis, and the results are compiled in a table. This work is part of an Institute of Museum and Library Services (IMLS) grant. It was presented at the 2022 Association for Library and Information Science Education (ALISE) Annual Conference held October 24-26, 2022.

This article analyzes item‐level metadata in three language archives by focusing on free‐text metadata: the Endangered Language Archive, Pacific Regional Archive for Digital Sources in Endangered Cultures, and the Archive of the Indigenous Languages of Latin America. The study identified categories of information included in Description metadata fields and the relative distribution of these categories.

This article is a review of literature for skills comprised within the Accreditation Board of Engineering and Technology (ABET) criteria determined 26 topics necessary for the entry-level and continued success of engineers. The findings suggest that although entry-level engineers have proficiency in all of these ABET required skills, the entry-level engineers were not meeting the level of importance expressed by the organization for 24 of these 26 skills.

This article presents a study that examined how three auditory lectures delivered at different speeds – normal (1.0x), fast (1.5x) and very fast (3.0x) speeds – affected graduate students’ attention, cognitive load, and learning.

Article uses 4E cognition as a framework to explore creativity in extreme environments. The article examines space arts as a case study through the history, present practices, and future possible arts in the context of humans beyond the Kármán boundary of the Earth’s atmosphere. This article is part of the research topic Creative Performance in Extreme Human Environments: Astronauts and Space

Article asserts that international students face unique challenges in pursuing higher education in a foreign country. To address these challenges and enhance their academic experience, higher education institutions are increasingly exploring the use of artificial intelligence (AI) applications. The research paper explores various AI applications, such as personalized learning experiences, adaptive testing, predictive analytics, and chatbots for learning and research.

Article describes how, since 2008, the End of Term Web Archive has been gathering snapshots of the federal web, consisting of the publicly accessible .gov and .mil websites. This paper describes the decisions made in the creation of these derivatives, the technologies used, and introduces the WARC Metadata Sidecar, which presents a useful approach for creating and storing auxiliary metadata for web archives.

Article describes how the End of Term (EOT) Web Archive Dataset presents a longitudinal dataset of the US federal web which includes publicly available .gov and .mil domains, created during the 2008, 2012, 2016, and 2020 presidential elections in the United States. The authors describe how based on the End of Term Web Archive, this dataset presents 461TB of WARC data and accompanying derivative files in WAT, WET, and CDX format.

Data management plan for the grant, "Collaborative Research: Diversifying Human-Centered Data Science through the Research and Design of Ethical Games." This project studies collaborative learning in a virtual setting for groups of peers with conflicting methodological cultures and diverse backgrounds. An additional artifact of this two-year, interdisciplinary project will be a prototype of an educational game, targeted towards the underrepresented communities and the greater public, that will bring more people into critical conversations about the roles of AI and data science in our society. The primary aim of this research is the production of novel theories in learning sciences regarding collaborative learning in the face of diverse backgrounds and cultural norms.