Multimodal Methods in Business Studies and Education, 5 ECTS
Time and place: June 2026 (Timing: 8th June-12th June 2026), University of Oulu, Oulu, Finland (Face-to-face) Leaf Research Infrastructure (https://www.oulu.fi/en/research/research-infrastructures/leaf-research-infrastructure)
Learning goal and objectives:
The nature of social interactions in different business or learning contexts is getting more complex due to technological developments (e.g., emerging human-AI collaborations). This complexity necessitates the need for the interdisciplinary research mindset and methods, which provide contemporary multimodal views of exploring multidimensional complex human data. This course introduces and integrates individual modalities (e.g., physiological data; eye-tracking, heart rate, EDA; electrodermal activity, or video/audio data) to understand the social interactions in business or learning contexts (i.e., human-human and/or human-technology). This course offers a unique opportunity to collaborate with interdisciplinary teams, enhancing understanding of multimodal methods and research through diverse perspectives.
Learning objectives
· Adopting an interdisciplinary mindset
· Identifying and ideating interdisciplinary research problems
· Applying interdisciplinary multimodal methods at research infrastructures (e.g., LeaF)
· Learning about the ethical considerations related to the multimodal methods
· Understanding the research process related to multimodal methods
Schedule:
This is a 5-day course which collectively provides insights into an interdisciplinary mindset and the multimodal methods, emphasizing their potential use in your own research. Your learning will be supported by national and international leading scholars in their fields.
Day 1: Introduction to multimodal methods with interdisciplinary mindset (8.30-16.30),
Day 2: Detailed view of LeaF as space for multimodal data collection (8.30-16.30) Day 3: Ideating multimodal research in different disciplines (8.30-16.30)
Day 4: Multimodal data analysis and interpretation of results (8.30-16.30)
Day 5: Planning your research (8.30-16.00)
Instruction and examination:
Credits: 5 ECTS
Grading: Course evaluation is based on attendance and active participation in pre-assignment, course activities and post-course assignment.
Final grade: Five-level grading scale. In order to pass this course, all the aspects mentioned below should be completed:
▪ Submit pre-course assignment in the form of an individual report as per guidelines.
▪ Be physically present in all five days (all sessions)
▪ Participate actively during group discussions, peer-review tasks, and other assigned activities by teachers
▪ Submit post-course assignment in the form of an individual research plan. Post-course assignment is evaluated based on five-level grading scale. A grading criteria will be created and communicated students during the course.
Prerequisites: PhD students with motivation for interdisciplinary work.
Admittance: 25 students
25 PhD students are admitted to the course. This course is designed for doctoral researchers across various disciplines of business and education, including Management, International Business, Economics, Marketing, Business Analytics, Accounting, and Finance, as well as Educational Psychology and Educational Sciences. Students from fields other than business are admitted based on availability of seats in the course. Individual highly motivated doctoral students from EIASM/EDEN organizations outside Finland can participate based on availability of seats in the course. The course can also consider admitting highly motivated individual Master’s level students who can get the course accepted in the PhD studies later.
Application period: 1st November 2025-15th March 2026.
Notification of acceptance by e-mail 31st Mach 2026.
– Applicants will enroll to the course by submitting an application via given Webropol-link by March 15th, 2026.
– Applicants will be sent instructions for writing the pre-assignment when they are notified about course acceptance.
– The deadline for pre-assignment is on May 15th,
In case of any questions, please reach out to Eeva-Liisa Oikarinen (eeva-liisa.oikarinen@oulu.fi).
Instructors:
Due the interdisciplinary nature, the course has several experts and invited keynote speakers, which have been invited to facilitating the development of this course and sharing their expertise on specific topics. Below is listed the confirmed experts, their role and topics during the course. Final list of instructors, their roles and topics will be confirmed later.
Professor Magnus Söderlund is a professor of marketing and head of the consumer research unit. His research interests are often related to consumer marketing that utilizes experimental methods and how different marketing activities affect consumers, especially their satisfaction, more recently in virtual customer encounters. His studies have also used Face-reader analytics to analyze emotional reactions from video images and analyzed the emotional and cognitive elements of textual linguistic expression LIWC and their connections to customer satisfaction. He will introduce students to the potential related to these methodological approaches.
Professor Tapio Seppänen is a professor of biomedical engineering, and he is leading The Physiological Signal Analysis research team. The team’s expertise
includes biomedical engineering, digital signal processing, image analysis and machine learning algorithms. Research on biomedical signal analysis is focused on cardiovascular signal processing (multi-channel ECG and heart rate variability), cardio-respiratory signal processing, and autonomic nervous system signal processing. In exercise physiology domain, the focus of their research during the last 20 years has been to develop novel methods for analysis of cardiovascular function motivated by multimodal physiological signals and to apply those methods to the experimental physiology in healthy subjects and different patient populations. They have done research on affective computing in which algorithms for detecting human emotions from physiological signals have been in focus. Seppänen is providing one of the keynote lectures on the selected topics related to physiological signal analysis from multimodal perspective.
Dr. Haoyu Chen is a tenure-track Assistant Professor with the Center for Machine Vision and Signal Analysis (CMVS) at the University of Oulu, Finland. He is also a Research Fellow funded by the Research Council of Finland and a member of the European Laboratory for Learning and Intelligent Systems (ELLIS). Haoyu Chen received his Doctor’s and Master’s degrees in Computer Science and Engineering from the University of Oulu, Finland, in 2022 and 2017. His research interests include human behavior analysis, hybrid intelligence, and emotion AI. He has published more than 50 peer-reviewed papers, including top-tier venues such as CVPR, ICCV, ECCV, NeurIPS, IJCV, and ICML. His work on gesture recognition has received notable recognition, including the second prize of the IEEE Finland Jt. Chapter SP/CAS Best Paper Award, 2nd place in the Action Recognition Track of the ECCV 2020 VIPriors Challenges, etc. Dr. Chen has actively chaired workshops and challenges at various conferences, including HHAI 2024, IJCAI 2023, and IJCAI 2024. Outside academia, he is a co-founder of two AI startups based in Helsinki, Finland, focusing on implementing the latest AI technologies in real-world scenarios.
Dr. Jonna Malmberg works at the University of Oulu, in Learning and Learning Processes (LLP) Research Unit and is also member of Learning and Educational Technology (LET) Research Unit. She was appointed as an Assistant Professor (tenure track) in the GenZ strategic profiling theme Co-evolution of humans and new technologies in the emerging digital era. Jonna´s research is focuses on strategic and self-regulated learning in solo and collaborative learning settings. Also, Jonna explores how to support strategic and self-regulated learning with the use of adaptive technologies. Recently, she has been exploring how physiological data, such as electrodermal activity is connected to self-regulated learning in individual and collaborative learning settings and how to help learners to develop their learning skills.
Dr. Héctor J. Pijeira-Díaz is an Assistant Professor of “Learning and interaction processes and methods in technology-supported environments” at the Faculty of Education and Psychology at the University of Jyväskylä. His research interest focuses on the broad question of how technology can be leveraged to understand learning as a process. In the multidisciplinary fields of learning sciences, educational technology, and learning analytics, he has become specialized in psychophysiological approaches—especially concerning electrodermal activity (EDA)—and natural language processing (NLP). For the methodological innovations and contributions of his PhD thesis on EDA, he received the “Outstanding Multidisciplinary Doctoral Thesis” Eudaimonia Prize 2020 of the University of Oulu.
Dr. Justin Edwards is a postdoctoral researcher in the Learning and Educational Technology (LET) research lab in the Faculty of Education and Psychology. He investigates how people speak to one another and to machines. His research focuses on the design of artificial agents which proactively speak to people and how proactive agent speech impacts people’s ongoing tasks. His current research in the Triggers for collaborative learning regulation (TRIGGER) project aims to uncover how trigger events – challenging events that inhibit collaboration – can be detected by AI so that learners can receive support.
Dr. Eeva-Liisa Oikarinen has studied the dynamics of human-to-human marketing and especially the importance of human aspects in virtual customer service encounters. She has studied humor and its limits, playfulness and joking in various business interaction situations, such as in recruitment advertising, service encounters, and innovation management. Her research has been published in several leading business and service journals. Recently (2023-2024) Oikarinen has been responsible leader of the project, funded by Foundation for Economic Education with the aim of facilitating business interaction research in LeaF infrastructure in the University of Oulu. Oikarinen is a leader of emerging research group studying biomarketing and transformative bot-human companionships. Oikarinen has project management experience for innovative research openings (HURMOS-Humour tools for innovative business 2015-2017). She holds a previous master’s degree in biophysics with experience in the analysis of biosignals, which gives her fertile background in efforts to explain the interaction phenomena of marketing with biology.
Dr. Azzurra Morreale acts as an associate professor at LUT University, School of Business and Management, where she is also Head of Viipuri Lab since February 2021. She has been awarded the Title of Docent (Strategic financing, Economic behavior and Decision-making) in the same School for the period September 2021 – 31 August 2026. She received her Ph.D. in Industrial Engineering and Management from University of Palermo (Italy). She is also a member of CEEL (Cognitive and Experimental Economics Laboratory), Department of Economics, Management University of Trento (Italy). She has been a visiting scholar at the University of California Santa Cruz (USA), and she is a regular visiting scholar at University of Trento (Italy). She is particularly specialized in behavioral experimental and quantitative methods, and she has applied such methods to several financial and economics contexts (e.g., real options testing, crowdfunding, organizational exploration-exploitation dilemma, tax compliance, among others).
Dr. Egle Gedrimiene is a Data Management Specialist, Faculty of Education, University of Oulu. Her session covers ethical concerns and guidelines when collecting and using human data.
Antti Siipo is a manager in LeaF Research Infrastructure, University of Oulu. In his session students focus on research equipment which is available on LeaF Research Infrastructure.
Course coordinator and contact information:
Course convenors: Docent, Dr. Eeva-Liisa Oikarinen, Associate Professor Jonna Malmberg, Prof. Tapio Seppänen, Antti Siipo, and Mohsin Abdur Rehman.
– Course coordinator: Associate Professor Eeva-Liisa Oikarinen, eeva-liisa.oikarinen@oulu.fi
– Course assistant, Doctoral researcher, Mohsin Abdur Rehman,mohsin.abdurrehman@oulu.fi