Teaching
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AI in education
Here is a digest of my presentation on the perceived trustworthiness of AI and GPT tools and their use (and disuse) in higher education for a PIL webinar.
Intro to AI and LLMs, and some key terminology that we use loosely
Results of our first paper on LLM trustworthiness
Preliminary results of a study with GU and Chalmers students
Training in Higher Education Pedagogy
PIL 103 Teaching and Learning in Higher Education 3: Applied Analysis, University of Gothenburg, March 2024
PIL102 Teaching and Learning in Higher Education (badgr.com) University of Gothenburg, Mar 2023 (Also: PIL101)
PIL101 Microteaching (badgr.com) University of Gothenburg, Apr 2023
PIL101 Lesson plan (badgr.com) University of Gothenburg, May 2023
PIL101 Legal Module. University of Gothenburg, January 2024
PIL201 Supervision in Postgraduate Programmes, Universtity of Gothenburg, Nov 2023
Pedagogical Statement: my view on doctoral supervision
The role of the PhD supervisor is to make sure that students are ready to transition into the next stage of a research career: becoming an independent researcher (Åkerlind, 2015). In my opinion, there are three equally important approaches to this: (i) the external, by making sure the student is exposed to new ideas and communities, (ii) the constructive, not only enhancing research skills but also fostering inspiration towards research, and (iii) the realistic, concerned with ensuring that the PhD journey is well both research- and emotion-wise.
External approaches, such as helping students to publish their work and attend conferences and research events, are standardised to help students attain a set of skills up to par to their peers in other universities. These efforts also include build the student's confidence, so important in academic endeavours. There can be, of course, different schools of thought regarding the value of dissemination activities or participation in events. For example, I personaly believe that, for PhD students, it is more valuable to attend a conference (independently of its rank!) where interesting conversations with key researchers can be held, than publishing in a reputed journal. I believe that smaller venues are key for open dialogue about research directions, career expectations, and (sometimes tangential) topics that are key for the development of the students (Johansson, 2018).
On the other hand, the inner workings of a supervisor-student relationship can vary a lot. Åkerlind stated that supervisors should foster the development of the students, not only in terms of their hard skills but also fostering their personal development, e.g., inspire their enthusiasm towards research (Åkerlind, 2015). In my own supervision, this materialises in many formal and informal discussions with PhD students, supervised by me or not, about the beauty of the collective effort towards scientific progress. This is a concept easy to forget if a PhD journey is only a race against time with a number of set-in-stone measurable goals: more papers!, better ranked conferences!, more citations! I also try to invite senior researchers to these conversations, for they have often a different point of view (often more down-to-earth and pragmatic).
Which takes me to the third point: the realistic supervision. Schierenbeck states that the PhD supervisor should help the PhD student in "scaling down the ambitions" instead of addressing problems with too big of a scope (Schierenbeck, 2018). This is, of course, the best recommendation for a PhD student. However, in my opinion, PhD students should have a grace period every now and then (in the beginning of their journey and after each big submission, perhaps) to explore ideas, to diverge from their main line of research and converge in a topic to be discussed, and (if needed) to be discarded. That is research! Schierenbeck also discusses a similar issue, related to providing feedback: they suggest giving comments and criticism to the PhD student’s work should be addressed to achieving a result (in the case of a PhD, be it a paper, a presentation, or a thesis) that is "good enough" (Schierenbeck, 2018). I believe this is key in maintaining a balanced workplace for PhD students: their journey should be sufficient for them to grow into an independent researcher (Åkerlind, 2015) but, at the same time, should not be a weary obstacle race.
Frequent supervision meetings and short follow-up sessions can be very helpful to achieve help reduce stress of the student (Schierenbeck, 2018) and understand what is going well and what are the struggles. In my experience, the main obstacles for PhD students are not related to their research but the environment, that should be welcoming and inclusive but often is not. Sometimes, though, work itself is challenging: academics are and should always be subject to criticism, and acknowledging criticism and learning to appreciate it is part of a PhD student’s journey. Those troubled times can also be a time for the PhD supervisors to check up on their students’ overall feelings about their PhD journey and try to enhance the students’ enjoyment of and commitment to the doctoral experience, key for personal development as suggested by Åkerlind (Åkerlind, 2015).
References
(Åkerlind, 2015) Gerlese Åkerlind & Lynn McAlpine (2017) Supervising doctoral students: variation in purpose and pedagogy, Studies in Higher Education, 42:9, 1686-1698, DOI: 10.1080/03075079.2015.1118031
(Jackson, 2021) Jackson, D., Davidson, P. M., & Usher, K. (2021). Doctoral supervision as pedagogy. In Successful Doctoral Training in Nursing and Health Sciences: A Guide for Supervisors, Students and Advisors (pp. 17-32). Cham: Springer International Publishing.
(Johansson, 2018) Discussion between Erik and Peter Johansson.
(Schierenbeck, 2018) Discussion between Erik and Isabell Schierenbeck.
(Taylor, 2017) Taylor, S., Kiley, M., & Humphrey, R. (2017). A Handbook for Doctoral Supervisors (2nd ed.). Routledge. https://doi-org.ezproxy.ub.gu.se/10.4324/9781315559650
Teaching and supervision
Bachelor's and Master's thesis
Fazelidehkordi, Y., & Mahmoudifard, Amin. (2024). Assessing the Efficacy of GPT-4 in Test Generation: Comparing Against Human and Pynguin. Gothenburg University Publications Electronic Archive.
Anandan, S. (2024). RE Principles for Generative AI-enhanced Sustainability Assistants. Gothenburg University Publications Electronic Archive.
Galera, O. (2024). Heavy-duty truck simulator: a tool to plan charging and charger layouts. Chalmers Open Digital Repository.
Zsolnai, G., & Vidackovic, I. (2024). Exposing the gap between Automotive and Cloud Requirements Engineering Practices. Gothenburg University Publications Electronic Archive.
Andersson, J., & De Jesus, K. (2024). Heavy-duty truck simulator: a tool to plan charging and charger layouts. A study into the applicability of generative AI in software\\ development for advanced driver-assistance systems. Chalmers Open Digital Repository.
Liteanu, G.-V., & Korkmaz, N. (2023). Human Performance and VR Interfaces: A Study of Digital Twin Monitoring in AI-Driven Fleets of Vehicles. Gothenburg University Publications Electronic Archive.
Yasser, A., & Broberg, A. (2023). Digital Twins for Verification and Validation of CPS: Standardizing the Role of Requirements Engineering and AI with Digital twins. Gothenburg University Publications Electronic Archive.
Wang, Z., & Chang, Q. (2023). A Solution for 3D Visualization on Soil Surface Using Stereo Camera. Chalmers Open Digital Repository.
Ratushniak, O. (2023). Architecturally Significant Requirements and Design for Digital Twins of Semi-Autonomous Systems. Gothenburg University Publications Electronic Archive.
Petrov, S. (2023). Digital Twins and Sustainability: A Comprehensive Review of Limitations and Opportunities. To be published in the Chalmers Open Digital Repository.
Solé, Júlia. (2020). Integrating E-commerce into a Virtual Reality Entertainment Inflight Platform. Universitat Pompeu Fabra Digital Repository.
Mathematical Foundations for Software Engineering (GU)
The course introduces the students to basic mathematical and critical thinking skills needed for modeling, analysis and design, implementation, and testing of software applications. Students get in touch with mathematical foundations for software engineering (e.g. functions, relations, sets, graphs, logic, logarithms, geometry, number theory, statistics, basic proof techniques) that are required in subsequent courses throughout their studies of software engineering.
The course provides students with general ability to solve engineering problems.
Introduction to programming (UPF)
Python exercises (explained in Spanish): colab.research.google.com/drive/1PZpbiBaTwn_eEs_V2rmaD99if_Y7ZRvD
Google Colab used in class (all groups 2021-22):
S1 drive.google.com/file/d/15tIm7H3Av65lSYF-7zHCzS9k4_DTMS-o
L1 drive.google.com/file/d/1_niT1Lh9IGohdE-vVKiEYkUPSvzii_8V
S2 drive.google.com/file/d/1J2abV8-SgLsSvMb8sqZmOxdG2-0kbylZ
L2 colab.research.google.com/drive/1GwO25A71hF8AKauskVIE1shoTUajLfrQ
S3 drive.google.com/file/d/1UNFXdGpYfhGlbK82Wk0XWvSAVk7GerEh
L3 drive.google.com/file/d/1ydrhNh5-Eo-Xk7uFlmmV3pPlJEbO6G3R
Computer Graphics (UPF) and Advanced Visualisation (UPF)
These advanced 3D computer graphics project-based courses guided the students from the creation and transformation of primitives, to their integration on an interactive scene with multiple light sources (based on Phong and Gouraud algorithms). Students learn about many programming techniques and tips for the development of 3D graphics applications, e.g., computer games, medical imaging viz, etc.They also need to apply geometry, statistics, and algebra techniques they acquired throughout their studies of computer engineering.
In my YouTube Channel you can find videos about Computer Science, 2D videogame creation (Python + PyGame from scratch), etc. + other videos that are not Computer-Engineering-related. I am also mantaining a couple of interesting compilations/playlists that might be useful to you or your students. Feel free to take a look!
Recorded classes and Q&A sessions for Introduction to programming (labs and seminars, 2020) https://youtube.com/playlist?list=PLpkg5PEI-IvuATijFxgE6yJDo_EZCfNT9
Multimedia materials for the online summer school “Video games with Artificial Intelligence in Python” https://youtube.com/playlist?list=PLpkg5PEI-IvtrzydXhdobad5YEKnv3UBE
Multimedia materials (recorded interviews) for the “Bots: from video games to smart houses” course https://youtube.com/playlist?list=PLpkg5PEI-IvsgBTG8NLcLAPWvhby8WVqI
Multipurpose programming guide available online to review concepts (used in class) https://colab.research.google.com/drive/1PZpbiBaTwn_eEs_V2rmaD99if_Y7ZRvD
Introducció a la Programació
Academic year 2020-21
This course is taught in spanish and catalan! Alguns videos estan en anglès! Teniu els vídeos d'algunes classes que vam haver de fer en directe en aquesta playlist. També he penjat algunes explicacions de classe en format vídeos de 5 minutets per si us van bé.
Campus Júnior 2020
Videojuegos con Inteligencia Artificial en Python
Orientado a estudiantes desde tercero de ESO hasta primero de Bachillerato y Ciclos formativos de grado medio (CFGM). Proyecto final: un videojuego hecho en Python que usase una IA simple. Estoy muy contenta de los resultados aunque me hubiera gustado poder hacer el curso presencial en lugar de online...
Campus Júnior 2021
Bots: de Videojocs a Cases Intel·ligents
Organitzat per la Universitat Pompeu Fabra. Tot i que aquest any serà presencial, us deixo alguns enllaços a recursos que us poden ser útils per repassar o aprendre més. Us deixo també el link a la llista de reproducció amb els vídeos de classe (comentaris i explicacions d'experts en diversos àmbits).