This four-part online course explores how researchers can leverage the latest capabilities of generative artificial intelligence (GenAI) to enhance their scholarly work. It is primarily tailored for doctoral students but will also be beneficial to anyone engaged in academic research, including established scholars and Master's students. The objective of the course is to develop foundational knowledge and awareness of current developments concerning GenAI's logic, capabilities and limitations, as well as the ethical and practical considerations and techniques associated with its use. Participants will receive practical guidance for integrating GenAI tools throughout various stages of their own research.

Session 1: Understanding and Using Generative AI Ethically in Research. This session will introduce the logic of generative AI and will explore the capabilities and implications of the latest generation of AI tools for academic research. It will also address the ethical considerations of using GenAI in research, including plagiarism, data fabrication, authorship, transparency, and reproducibility.

Session 2: Conducting a Literature Review with AI. Participants will learn how to leverage GenAI to identify key themes in existing research and streamline the literature review process. This includes searching for relevant literature, summarising and critically assessing key findings, and identifying a research gap. The session will address different types of literature reviews and the appropriateness of GenAI in each context.

Session 3: Using AI to Interact with Research Data and Sources. This session will focus on the application of GenAI in analysing and interacting with research data, with a particular emphasis on qualitative research. Topics will cover AI-assisted data exploration, pattern recognition, summarisation, and interpretation. The session will address potential biases that may emerge, underscoring the importance of human oversight in managing the generation of GenAI outputs and validating results.

Session 4: Enhancing Research Writing and Scholarly Communication through AI. Participants will learn how to utilise GenAI to identify shortcomings in a research manuscript and receive developmental editorial feedback to improve the text, format references, and create summaries for scholarly communication. They will also be introduced to GenAI tools for generating diagrams and visualisations. The session will examine current publisher guidelines regarding the use of AI in academic writing and will address the ethical implications related to authorship and plagiarism concerning AI-generated content.

Instructor

Costis Dallas is Professor and Head of the Department of Digital Cultures and Communication at the Faculty of Communication, Vilnius University. His research focuses on digital research methods in the human sciences, digital curation in the wild, the role of digital infrastructures in archaeological and humanities research, and heritage, memory, and identity practices on social media. He published over 50 peer-reviewed articles in journals and conference proceedings and co-edited Cultural Heritage Infrastructures in Digital Humanities (Routledge, 2017). His latest, co-authored peer-reviewed publications include “The Message Is the Agent: Nexus and Semiosphere in Social Media Communication”, “Difficult Heritage on Social Network Sites: An Integrative Review”, “An Ontology of Semiotic Activity and Epistemic Figuration of Heritage, Memory and Identity Practices on Social Network Sites’”, and “Battle or Ballet? Metaphors Archaeological Facebook Administrators Live By”. He holds a BA in History from the University of Ioannina, Greece, as well as MPhil and DPhil degrees from the University of Oxford and is an Emeritus Associate Professor at the Faculty of Information, University of Toronto.