Data Science and AI in Context: Summary and Insights

Author : Alfred Spector

This paper explores how to deploy data science and data-driven AI, focusing on the broad collection of considerations beyond those of statistics and machine learning. Building on an analysis rubric introduced in a recent textbook by the author and three others, this paper summarizes some of the book’s key points and adds reflections on AI’s extraordinary growth and societal effects. The paper also discusses how to balance inevitable trade-offs and provides further thoughts on societal implications.

DOI : https://doi.org/10.1162/99608f92.cdebd845

Effects of Open Access. Literature study on empirical research 2010–2021

Authors : David Hopf, Sarah Dellmann, Christian Hauschke, Marco Tullney

Open access — the free availability of scholarly publications — intuitively offers many benefits. At the same time, some academics, university administrators, publishers, and political decision-makers express reservations. Many empirical studies on the effects of open access have been published in the last decade. This report provides an overview of the state of research from 2010 to 2021.

The empirical results on the effects of open access help to determine the advantages and disadvantages of open access and serve as a knowledge base for academics, publishers, research funding and research performing institutions, and policy makers.

This overview of current findings can inform decisions about open access and publishing strategies. In addition, this report identifies aspects of the impact of open access that are potentially highly relevant but have not yet been sufficiently studied.

URL : Effects of Open Access. Literature study on empirical research 2010–2021

DOI : https://doi.org/10.34657/13648

Academic Integrity and Artificial Intelligence in Higher Education (HE) Contexts: A Rapid Scoping Review

Authors : Beatriz Antonieta Moya, Sarah Elaine Eaton, Helen Pethrick, K. Alix Hayden, Robert Brennan, Jason Wiens, Brenda McDermott

Artificial Intelligence (AI) developments challenge higher education institutions’ teaching, learning, assessment, and research practices. To contribute timely and evidence-based recommendations for upholding academic integrity, we conducted a rapid scoping review focusing on what is known about academic integrity and AI in higher education. We followed the Updated Reviewer Manual for Scoping Reviews from the Joanna Briggs Institute (JBI) and the Preferred Reporting Items for Systematic reviews Meta-Analysis for Scoping Reviews (PRISMA-ScR) reporting standards.

Five databases were searched, and the eligibility criteria included higher education stakeholders of any age and gender engaged with AI in the context of academic integrity from 2007 through November 2022 and available in English. The search retrieved 2223 records, of which 14 publications with mixed methods, qualitative, quantitative, randomized controlled trials, and text and opinion studies met the inclusion criteria. The results showed bounded and unbounded ethical implications of AI.

Perspectives included: AI for cheating; AI as legitimate support; an equity, diversity, and inclusion lens into AI; and emerging recommendations to tackle AI implications in higher education. The evidence from the sources provides guidance that can inform educational stakeholders in decision-making processes for AI integration, in the analysis of misconduct cases involving AI, and in the exploration of AI as legitimate assistance. Likewise, this rapid scoping review signals key questions for future research, which we explore in our discussion.

URL : Academic Integrity and Artificial Intelligence in Higher Education (HE) Contexts: A Rapid Scoping Review

DOI : https://doi.org/10.55016/ojs/cpai.v7i3.78123

Challenges and strategies for open access in South Africa: A knowledge management approach

Authors : Kwame Kodua-Ntim, Madelein Fombad

This paper explores the challenges of open access in South Africa and draws from knowledge management concepts and principles to suggest strategies to enhance open access. A comprehensive analysis of the existing literature was undertaken to address these challenges.

A systematic review was undertaken to address the obstacles associated with open access using a well-defined search protocol. Some of the challenges were limited funding, inequality in access to technology, limited awareness, resistance from publishers, copyright issues, and lack of infrastructure.

The article suggests that knowledge management initiatives such as knowledge awareness of open access, knowledge sharing, leadership, rewards and incentives, and a positive culture will enhance open access.

URL : Challenges and strategies for open access in South Africa: A knowledge management approach

DOI : https://doi.org/10.1177/02666669241257188

Scientific discourse on YouTube: Motivations for citing research in comments

Authors : Sören Striewski, Olga Zagovora, Isabella Peters

YouTube is a valuable source of user-generated content on a wide range of topics, and it encourages user participation through the use of a comment system. Video content is increasingly addressing scientific topics, and there is evidence that both academics and consumers use video descriptions and video comments to refer to academic research and scientific publications.

Because commenting is a discursive behavior, this study will provide insights on why individuals post links to research publications in comments. For this, a qualitative content analysis and iterative coding approach were applied. Furthermore, the reasons for mentioning academic publications in comments were contrasted with the reasons for citing in scholarly works and with reasons for commenting on YouTube.

We discovered that the primary motives for sharing research links were (1) providing more insights into the topic and (2) challenging information offered by other commentators.

Arxiv : https://arxiv.org/abs/2405.12798

Research Data Management in the Croatian Academic Community: A Research Study

Author : Radovan Vrana

This paper presents the results of an empirical research study of Croatian scientists’ use and management of research data. This research study was carried out from 28 June 2023 until 31 August 2023 using an online questionnaire consisting of 28 questions. The answers of 584 respondents working in science were filtered out for further analysis. About three-quarters of the respondents used the research data of other scientists successfully. Research data were mostly acquired from colleagues from the same department or institution.

Roughly half of the respondents did not ask other scientists directly for their research data. Research data are important to the respondents mostly for raising the quality of research. Repeating someone else’s research by using their research data is still a problem. Less than one-third of the respondents provided full access to their research data mostly due to their fear of misuse.

The benefits of research data sharing were recognized but few of the respondents received any reward for it. Archiving research data is a significant problem for the respondents as they dominantly use their own computers prone to failure for that activity and do not think about long-term preservation. Finally, the respondents lacked deeper knowledge of research data management.

URL : Research Data Management in the Croatian Academic Community: A Research Study

DOI : https://doi.org/10.3390/publications12020016

Research Data Management in the Humanities: Challenges and Opportunities in the Canadian Context

Authors : Stefan Higgins, Lisa Goddard, Shahira Khair

In recent years, research funders across the world have implemented mandates for research data management (RDM) that introduce new obligations for researchers seeking funding. Although data work is not new in the humanities, digital research infrastructures, best practices, and the development of highly qualified personnel to support humanist researchers are all still nascent.

Responding to these changes, this article offers four contributions to how humanists can consider the role of “data” in their research and succeed in its management. First, we define RDM and data management plans (DMP) and raise some exigent questions regarding their development and maintenance.

Second, acknowledging the unsettled status of “data” in the humanities, we offer some conceptual explanations of what data are, and gesture to some ways in which humanists are already (and have always been) engaged in data work.

Third, we argue that data work requires conscious design—attention to how data are produced—and that thinking of data work as involving design (e.g., experimental and interpretive work) can help humanists engage more fruitfully in RDM.

Fourth, we argue that RDM (and data work, generally) is labour that requires compensation in the form of funding, support, and tools, as well as accreditation and recognition that incentivizes researchers to make RDM an integral part of their research.

Finally, we offer a set of concrete recommendations to support humanist RDM in the Canadian context.

URL : Research Data Management in the Humanities: Challenges and Opportunities in the Canadian Context

DOI : https://doi.org/10.16995/dscn.9956