BA in
Communication Design (2003), MA in Multimedia Art (2007)
and PhD in Digital Media (2013) from the University of
Porto. In 2020, he completed a Post-Doctorate in Design
at the Faculty of Fine Arts of the University of Porto.
He is currently Associate (tenured) Professor at the
School of Design of the Polytechnic University of Cávado
and Ave (IPCA) and Director of the MA in Digital Design.
He is an Integrated Researcher of the Research Institute
for Design, Media and Culture (ID+), where he has
focused his research in the area of Communication Design
for Digital Media. He is currently Co-Principal
Investigator (Co-PI) of the project "HERIC 2D - Health
Risk Communication: Design and digital communication of
official public health sources to guide citizens in
pandemic situations" funded by FCT (Ref.
2022.06008.PTDC); was Principal Investigator (PI) of the
project "ECHO - Echoing the Communal Self: designing the
dissemination and replication of self-initiated
practices in underprivileged urban communities in a
post-pandemic world", funded by FCT
(EXPL/ART-DAQ/0037/2021); and has participated, as a
team member, in several funded research projects.
He is the Founder and Chair of DIGICOM - International
Conference on Design & Digital Communication
(http://digicom.ipca.pt). He is member of the editorial
board of several scientific journals and was co-editor
of more than several scientific publications in the area
of Communication Design, namely chapter books and
proceedings of international conferences.
He has won numerous awards, namely: 3 Graphis Gold Award
(2021, 2015 and 2014, USA); 2 Graphis Silver Award (2020
and 2014, USA); 1st prize - Mascot of the Oceanário of
Lisbon; 1st prize - Mascot of the Water Pavilion of
Porto; 1st prize - Porto Digital logo; 1st Prize "Winner
Online" in the contest Webdesign 2004, promoted by
ESTAL; and 1st Prize in the Contest "Papies 2006"
(category "Papies of the Internet). Some of his design
projects appear in over two dozen books on Communication
Design, published in Hong Kong, Germany, Spain, USA,
Austria, Netherlands, France, China and UK.
Title: Health Risk Communication: Design and Digital Communication of Official Public Health Sources to Guide Citizens in Pandemic Situations
Abstract: This project's main objective is to
improve the risk communication in Health in situations
of pandemic, by official public health institutions of
the Portuguese Government and State. To this end, it is
based on the experience of the COVID-19 pandemic, where
the aim is to evaluate and improve the communication and
design of the different websites of these institutions,
created to communicate and interact with citizens,
namely the Directorate-General for Health (DGS) and the
National Health Service (SNS24). In this communication
we will present the main results of the study carried
out in the area of Design. In particular, the aim is to
demonstrate the contribution of Interface Design and
Infographics in conveying public health information
through the development of best practice guidelines
tested on a prototype.
Acknowledgements: This work was founded by the
Portuguese Foundation for Science and Technology (FCT)
under the reference 2022.06008.PTDC.
Edwin P. Christmann earned his PhD at Old Dominion University and is professor in the curriculum and instruction/educational leadership department at Slippery Rock University. In addition, he is a professor in the Helms School of Government at Liberty University, where he is the Director of Research Methods. He is the program director of SRU’s EdD Program and has served as a contributing editor to the National Science Teachers Association’s middle schools journal, Science Scope, serves on the editorial review boards of several other research journals, and has authored the books Technology-Based Inquiry for Middle School and Beyond the Numbers: Making Sense of Statistics; and he has coauthored Interpreting Assessment Data: Statistical Techniques You Can Use, Designing Elementary Instruction and Assessment: Using the Cognitive Domain, Designing and Assessing IEP Instruction for Students with Mild Disabilities: Using the Cognitive Domain, and Designing Middle and High School Instruction and Assessment: Using the Cognitive Domain. In addition, he has written over 100 articles and is a frequent speaker at international conferences. He currently teaches graduate-level courses in measurement and assessments, science education, and statistics, which are built on the foundation of his math and science experiences.
Title: A Meta-Analytic Investigation of CAI on Mathematics Achievement
Abstract: This meta-analysis examined the research
question "What differences exist among the academic
achievement levels of mathematics students who were
exposed to computer-assisted instruction, and those who
were not exposed to this instruction?" Hence, a
comparison of the mathematics achievement between
students who received either traditional instruction or
traditional instruction supplemented with
computerassisted instruction (CAI) was conducted. From
the twenty-seven conclusions, an overall mean effect
size of 0.236 was calculated, indicating that, on
average, students receiving traditional instruction
supplemented with CAI attained higher academic
achievement than did 59.48 percent of those receiving
traditional instruction alone. Moreover, a .094
correlation between effect size years indicates that the
effect of CAI on mathematics achievement has slightly
increased during this period.
Mikie Nishiyama is an associate professor in the Postgraduate School of Tokyo Healthcare University and a Ph.D. candidate at the University of Tokyo. She has M.A.s in linguistics and language education from the University of London, Kyoto University, and the University of Tokyo. She is currently a director of the Japan Society of English for Research (J-SER). She teaches a graduate-level course in English for academic purposes and undergraduate-level English courses at Tokyo Healthcare University. Research interests include the use of AI translation and tools in foreign language writing. Her current research project is investigating the appropriate application of AI translation and tools in foreign language learners’ writing and the assessment of writing products.
Title: Exploring the Pedagogical Impact of Machine Translation on Foreign Language Writing: A Qualitative Analysis
Abstract: This presentation will discuss the findings from an ongoing qualitative content analysis of learners’ use of online machine translation (MT) in foreign language (FL) writing. The study aims to explore the pedagogical effects of MT use and the factors influencing its impact on FL writing. In the study, Japanese learners of English were taught how to use MT and were allowed to use it to complete English writing tasks during one semester at a university in Japan. At the end of the semester, semi-structured interviews were conducted to gather participants’ reflections on their experiences with MT in English writing. The interviews focused on: 1. how participants used MT; 2. what they noticed about their first and target languages; 3. how they felt about their English proficiency when using MT; 4. the long-term effects of using MT; 5. the instructor’s feedback on the use of MT; and 6. what they thought about MT use in FL writing. The interviews were analyzed through qualitative content analysis using NVivo 14, leading to the extraction of the following thematic categories: (1) MT as a useful tool for learning English; (2) modification of Japanese for easier translation; (3) differences in the role of MT by proficiency level; (4) development of autonomous learning skills; (5) increase in motivation for learning English; (6) trust in MT; and (7) resistance to over-reliance on MT. These findings highlight the potential benefits of MT as a tool to support learners in FL writing. By understanding learners’ responses to MT, educators can make more informed decisions about how to incorporate it effectively into FL writing instruction.
He is a
university faculty member at the Technological
University of the Philippines (TUP) and formerly serve
as Board of Director of the TUP under the Philippines
Commission of Higher Education. Currently he is a
research fellow at the University of Tokyo under the
MEXT program working research on the Human Resource
Development and sustainability in the field of
Engineering Education. His research focuses on Human
Resource Management and Development in multigenerational
cohorts, Technology Education, and Educational
Management.
Currently, he is working on research about educational
technology and behavioral intentions among secondary
students toward distinct allied field courses in Nuclear
Science, Technology, and Engineering. Recently, he was
invited to present his research findings at the United
Nations Scientific Conference in Vienna in November 2023
and July 2024 in Vienna, Austria, emphasizing the
importance of identifying the factors that influence the
next generation to pursue Science, Technology,
Engineering, and Mathematics (STEM) courses to meet
future workforce requirements towards its
sustainability.
Dr. Tomoki Sakakibara is junior associate professor in the Postgraduate School of Healthcare, Tokyo Healthcare University, and also teaches at the University of Tokyo. He received his Ph.D. in Language and Information Sciences from the Graduate School of Arts and Sciences at the University of Tokyo. He is also a diplomate of the English Education Program (UTEEP) and the Future Faculty Program (FFP) at the same institution. Dr. Sakakibara currently serves as a director of the Japan Society of English for Research (J-SER). His research interests center on literary texts from the Renaissance period, with a focus on the works of British author Robert Burton and French essayist Michel de Montaigne.
Title: Reviving Latin: How Generative AI Transforms Classical Language Learning
Abstract: In the digital era, the potential of
generative AI to revolutionize our interaction with
classical texts is profound. This speech explores the
transformative application of AI in reading and
interpreting texts written in Latin and those blending
classical and secular languages. Generative AI
transcends the traditional boundaries between modern and
classical studies, making Latin—often considered a
“dead” language—an interactive medium for expressing
thoughts and feelings. By turning Latin into a language
of active engagement rather than passive absorption, AI
enables deeper understanding and greater command of the
language. This approach not only enhances linguistic
competence but also broadens access to a vast repository
of human knowledge that has been largely untapped due to
the lack of enabling technology. In this way, digital
innovation fosters inclusion, allowing scholars and
learners to connect with classical texts in
unprecedented ways.
Dr. Ding, researcher of Hainan University. Her research interests include educational big data and learning analysis. She presided over six projects including two projects funded by NSFC, won the second prize of educational science research achievements in Zhejiang Province, and published more than 20 SSCI / SCI/CSSCI papers.
Title: Automatic Recognition of Students’ Collective Emotion and their Relationship with Classroom Interactions
Abstract: Classroom interaction analysis and the
students’ collective emotions recognition in class have
always been key research fields. It is difficult to
automatically track students’ collective emotional
dynamics using traditional methods like questionnaires,
electroencephalograms, and text sentiment analysis.
Furthermore, the impact of classroom interactions on
students’ collective emotional dynamics remains unknown.
We adopted deep learning algorithms to automatically and
simultaneously identify the overall performance of the
entire classes on each emotional dimension every three
seconds. Subsequently, we calculated the collective
emotional scores according to the PAD emotional status
score and calculation formula based on every students’
result in each emotional dimension. Meanwhile, the
entire classroom interaction sequences were coded,
analyzed, and visualized every three seconds. To explore
the impact of classroom interactions on students’
collective emotional dynamics, we aligned the data of
classroom interaction sequence with the emotional
dynamic sequence. Three classes—music, Chinese, and
math—were selected as case samples to understand the
association between classroom interactions and
collective emotion dynamics. Results shown that
introducing novel teaching elements enhances student
engagement and positively influences their collective
emotions. Frequent teacher encouragement further fosters
a positive emotional climate, while the types of
questions posed by teachers impact students differently.
These findings underscore the importance of innovative,
emotionally supportive teaching strategies in promoting
a more engaged and positive classroom environment.
