CoCreatingGFI is joining the national MNT conference in Trondheim, 5-6 May. Here, you can read our three conference contributions:
Co-creating course projects in introductory Meteorology and Oceanography – enhancing and building motivation through group supervision and collaboration with former students, Anna-Marie Strehl and Kjersti Birkeland Daae
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Co-create your own adventure, Kjersti Daae and Mirjam S. Glessmer
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Improving students’ programming skills through Collaborative Scientific Python, Julien-Pooya Weihs and Daniel Oddmund Lid
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Co-creating course projects in introductory Meteorology and Oceanography – enhancing and building motivation through group supervision and collaboration with former students
Anna-Marie Strehl & Kjersti Birkeland Daae
Abstract:
Small research projects aligned with a course are thought to help the students grasp theoretical concepts, apply skills that they acquired previously or during the course, and provide training in academic writing. The outcome of student projects, however, strongly depends on the effort that the students are willing to invest in their projects. We encourage students to take the lead in their own education and to learn from each other, and have tested three methods to support the students’ learning: The students design their own research question, we apply group supervision to support students during the execution of the research project, and we enable exchange with former students. By enabling students to choose a project topic of their interest, their motivation can be increased, inherently improving the learning outcome for the individual student. Group supervision facilitates learning beyond the individual projects and makes use of the individual strengths and knowledge of the students. Including more experienced students in the project development benefits both the current and former students and enables knowledge transfer across cohorts.
1) Introduction
Including practical assignments in courses is thought to support the students in their learning. Motivation for the task, however, is an important factor in determining the students’ actual learning outcome of assignments. While motivation can be facilitated by external factors such as rewards (e.g. grades), self-determination theory suggests that internal motivation is created by the need for or feeling of competence, relatedness, and autonomy (Deci and Ryan, 2000). Co-creation of teaching and learning (Bovill, 2020), which describes an interactive development of education where both students and teachers are involved in designing teaching and course work, is one approach implementing these three concepts in teaching.
We implemented three co-creation practices to enhance the students’ motivation and, subsequently, the learning outcome of an obligatory course assignment: (1) The students designed individual project research questions, (2) we supported the students through group supervision to both develop the project ideas further and to execute their assignments independently, (3) former students were actively involved in the development and execution of the students’ projects.
In the following, we will first introduce the assignment, then we will describe how the three practices were implemented. We present the outcomes of some individual projects as well as overall observations and discuss the impacts for the student’s motivation during the assignment, by relating the outcomes to the three essential components of self-determination theory, competence, relatedness, and autonomy.
2) Methods
In the course GEOF100 – Introduction to atmosphere, ocean, and climate, a project report is included in the course assessment, counting 30% of the final course grade. The students choose a research question, design and perform an experiment, and subsequently analyze the collected data to answer the research question. The project report resembles a scientific paper by following the IMRaD structure (Introduction, Method, Results, and Discussion). The discussion is supposed to contain a reflection of the learning outcome for the student in addition to the discussion of their results. The projects are executed individually, and each student submits his/her own report.
2.1) Letting students choose a research question
At the beginning of the semester, the teachers present an overview of the previous year’s student projects and a list of the available instrumentation. The students can use the overview to find inspiration for their own project and submit a research question they want to pursue within four weeks. The students can choose an example from the provided list, but they are strongly encouraged to be creative in designing their project and developing their own research questions.
2.2) Providing feedback and further developing the research project together
It is important for the successful execution of the research projects that each project is realistic to perform within the given time and that it aligns with the knowledge and skills students gain during the course. This is achieved by group supervision, where the teacher preferably sits down with 2-3 students at a time. We allow, however, individual supervision for students who prefer working alone. The groups are preferably chosen such that the topics within the group span a wide range of topics (e.g. from oceanography and meteorology). Due to the small number of students in the specific course, the group supervision aligned well with assigning groups of friends.
During group supervision we support the students in the choice of instrument and give advice on the choice of locations where we can expect to have an interesting outcome of the project. We would like to emphasize that the students and their peers are actively included in the decision-making process and that we provide scientific reasoning for our suggestions. We do, e.g., suggest to measure spatial variability in salinity content near a river estuary rather than in a harbor or at a local bathing spot.
2.3) Engaging former students in the execution of the research project
Some research projects are similar to projects that were performed in the previous year. Instead of prohibiting access to the former students’ reports, we actively encouraged an exchange between the current and former students by putting the students into contact with each other. We had two applicable student projects where, in both cases, the former students agreed to participate. The teacher did not interact further with these pairs of students, and they communicated independently.
3) Results
3.1) Choices of research questions
The degree of independence in the chosen research questions varies strongly amongst the students. Some of the chosen projects show little to no relation to any of the previously presented research questions (high degree of independence). However, most students choose to modify one of the presented research questions so that they can easily relate to the topic. Modifications include, e.g., the use of own equipment for carrying out the experiment (fishing rod, boat, buckets), the connection to a private hobby (sailing, paragliding, diving, hiking, kayaking, running, training, …), relation to daily-life activities (doing the laundry, taking a shower), or the integration of familiar locations (their parent’s home, a private cabin, etc.). Only a few students choose a research question from the list without modifying it.
In Examplebox 1, we provide examples of projects that were either developed independently or modified by the students. The extensive list illustrates that the students had sufficient input to creatively develop individual projects, giving them space for autonomously shaping their education. Connecting the project to previously acquired skills and knowledge acknowledges the students’ competence. Enabling both autonomy and competence through tailored student projects facilitates motivation to build on and expand previous knowledge.
3.2) Group supervision in action – create relatedness amongst students
The students engaged actively in the group supervision discussions. All students commented, posed questions, or suggested a solution or an improvement to at least one of their peers’ projects. Consequently, the students contributed to the development of at least two different projects (including their own one) with different research questions. In Examplebox 2, examples of problems and solutions that developed during the group supervision are given.
Problem: The instrument needs to float on the ocean’s surface for about two weeks.
Solution: A friend of mine owns a boat, we can ask him whether we can attach the instrument to the boat or whether he knows of a suitable floating dock.
Problem: The instruments need to be placed in different training centers and preferably start measuring at the same time.
Solution: Each of us can put one of the instruments at a different location and start the measurements.
Problem: The same instrument, of which we have only one available, needs to be used for different projects.
Solution: We can easily coordinate our measurements – and even compare them in our reports.
Examplebox 2- Problems and solutions that came up during group discussions
4) Discussion and Conclusions
We applied methods from the Co-creation approach (Bovill, 2020) to individual research projects of students in an introductory climate physics course. We guided the students to find their own project question, providing the feeling of autonomy. In group supervision sessions, the students successfully co-developed and improved each other’s projects, confirming their competence, creating the feeling of relatedness, and emphasizing their autonomy, as they found their own solutions. When applicable, we furthermore encouraged and enabled active exchange between former and current students, which supported all three elements of self-determination theory, relatedness, autonomy, and competence. We perceived high motivation amongst students and are currently investigating the students’ perspective on the impact of inner motivation on their perceived learning outcome.
References
Deci, E. L., Ryan, R. M., (2000), The “What” and “Why” of Goal Pursuits: Human Needs and the Self-Determination of Behavior, Psychological Inquiry 11, 4
Bovill, C., (2020), Co-creating Learning and Teaching – Towards Relational Pedagogy in Higher Education, Critical Practice in higher education
Co-create your own adventure
Kjersti Daae and Mirjam S. Glessmer
Abstract: We have run a 3-year project financed by the Norwegian Directorate for Higher Education and Skills, HK-dir, under the program for student active learning, on implementing student-staff collaborations to co-create learning at the Geophysical Institute, University of Bergen. Throughout the project, we have explored and learned new ways of implementing co-creation at multiple levels within a course. Here, we invite you to join our co-creation journey guided by the Mountain Code. We share ideas on how you can plan and carry out the journey together with the students.
Co-creation occurs “when staff and students work collaboratively with one another to create components of curricula and/or pedagogical approaches” (Bovill et al., 2016)
But what exactly does this mean? What components or approaches can we co-create, and what does co-creation look like within a higher education classroom? Although we have literally co-created fieldwork journeys with students (Daae et al., 2025), we will here welcome you to join us on a metaphoric co-creation journey through the landscape of opportunities guided by the Norwegian mountain code (Røde Kors, ND). The mountain code (dating back to 1952) is well-known in Norway; kids learn it early, and it is even printed on the wrapping of the popular hiking chocolate, Kvikk Lunsj!
Please consider the following rules to enjoy the co-creation adventure while ensuring you and your company stay safe.
1. Plan your trip and inform others about the route you have selected
Planning your journey of a higher education course means defining the course’s destination – the Intended Learning Outcomes (ILOs). As a teacher, you have the choice plan the destination alone, based on your experience and the guidelines from the study program board, or you can open up for combining a set of fixed ILOs with a list of, e.g., five optional ILOs where students select one or two, or leave one entirely open for students to choose themselves.
In addition to mapping out the destination, the teacher must plan and select the route or path they will follow to get there. The specific route entails the pedagogical approach, learning activities, and important checkpoints such as completed tasks or due dates for student hand-ins. Will your students be riding the bus of traditional lectures, or can they be actively engaged by walking the path of flipped classrooms or riding on a self-build vehicle, designing their own projects, towards the next checkpoint? And how could you involve students in planning the route? Could you invite students to choose some of the learning activities or even let them design one or two themselves?
Consider how many checkpoints your students require to reach the goal and where the checkpoints should be located. Are the checkpoints easy to reach and well-defined early in the course, or do the students risk falling into a bog of work overload from a piling-up of work in concurrent courses? Did students know about the checkpoints early enough, or is there a risk that they walk down too far on a tempting path of exploration to find their way to the next checkpoint in time?
Informing others about the selected route could mean discussing the course goal and content and the selected route with teachers giving courses for the same students that semester, as well as before and after. Together, you can adjust your journeys to avoid a simultaneous piling-up of workloads from multiple courses. You can also invite students to help set the deadlines and avoid workload conflicts. Knowing what the students are doing in other courses will also help you make references to or adapt your examples to the knowledge and skills they learn in other courses.
2. Adapt the planned routes according to ability and conditions
Before we can adapt the route, we must learn who our travel companions are and what needs they may have. How can we make sure that we include all students and give all of them a chance to reach their destination? Can you make the learning material more inclusive by, e.g., using shorter sentences in assignment instructions, using colorblind-friendly color schemes, being clear about required prior knowledge, or offering students to hand in voice recordings instead of written reports?
To get to know your students, ask them early on if they think the teacher should know anything about them to help them learn. Are there any students who are lacking the relevant background skills and competencies? Are there planned absences or schedule conflicts that will make it difficult to follow your idea of how the course should play out? It may feel unsafe for students to talk about their challenges early in the course or in front of a whole class. Providing multiple channels for students to respond to such questions safely and anonymously, for example, leaving a note in the teacher’s mailbox, writing in an anonymous online forum, communicating through the study administration, or inviting them to come see you in your office could help them build trust or share their concerns.
3. Pay attention to the weather and the avalanche warnings
Paying attention to the weather in a classroom could mean regularly checking in with the students and asking how they are doing. Are we, for example, moving too fast, or is anything outside the course taking up the student’s time and energy, like the geopolitical landscape or personal experiences? Teachers could ask and listen to the students directly to build trust (Glessmer, Persson & Forsyth, 2024) or use more anonymous feedback methods such as 1-minute papers, continue-start-stop notes, anonymous online discussion forums, talking to student representatives, or mid-term surveys like Teaching Analysis Polls (Kordts et al., 2025). From the feedback you receive, you can decide to adjust deadlines, spend more time on important topics that students struggle with, provide additional material, or allow students to choose different paths toward the next checkpoint.
4. Be prepared for bad weather and frost, even on short trips
Preparing for bad weather could mean that teachers familiarize themselves with typical misconceptions that prevent students from building new knowledge onto existing knowledge. If the teacher knows the down pits and unsheltered parts of the route, they can prepare resources and learning activities to help students in their sensemaking process or build a bridge that connects one piece of the trail with the next (Daae, Semper, Glessmer, 2024). Keeping an open line of communication with students to help them with their current struggles and letting them ask “no such thing as stupid” questions may help them stay on track. The teacher can also avoid having a too strict schedule and let students find a shelter to stay warm and dry while a storm of conflicting workloads passes.
Being prepared for bad weather can also mean establishing the space, time, norms, and trust to have difficult conversations before the situation arises where those need to be had (Venet, 2024).
5. Bring the necessary equipment so you can help yourself and others.
Some people like carrying books to read by the campfire, while others would like to listen to podcasts while hiking. Teachers typically recommend what students should bring along for the journey, i.e., what they should master and how they can prepare. But you are never guaranteed that students understand the importance of all items and bring them along.
Sometimes, students literally forget to bring raincoats to fieldwork journeys and become wet and cold, which is not ideal for learning. Could you bring some extra clothes to help them stay dry and warm? And could you offer resources like a metaphoric raincoat and sweater to keep students warm and dry on the metaphoric journey? A targeted, easy-to-understand compendium could be helpful.
Students could also get lost in a wetland full of stinging programming bugs, losing self-confidence and motivation to continue. Could you provide a guiding star (e.g., programming resources or tips on using Large Language Models) to safely navigate the buggy wetlands and enjoy the next leg of the trip? You may also consider trying out an activity bingo as a playful approach to a hidden curriculum packing list (Glessmer et al., 2023).
6. Choose safe routes. Recognize avalanche terrain and unsafe ice
Co-creating teaching and learning for a higher education course does not mean everything has to be up for debate. Offering students the opportunity to express their opinions and take responsibility for their learning is always good and builds positive relationships (Bovill, 2020). However, the teacher is the one who knows the route, the final destination, and which trails are not necessarily wise to follow. It may be fun to raft down the river instead of walking, but the river may have dangerous rapids, and if you choose to raft, you should know where to get out and carry the raft. There are dozens of ways to adapt any given method to your context and purpose that can be explored (Glessmer, Bovill, Daae, 2024). Ultimately, the teacher is responsible for explaining and defending a chosen route to the students, the study program board, and department leadership, so it might be necessary to prescribe some parts of the route to ensure everybody’s safe arrival at the destination.
7. Use a map and a compass. Always know where you are.
When you plan the course, you sketch out the map and set the route you will follow. However, the map’s resolution may not be sufficient to spot all steep parts of the path in advance. We may, therefore, need to move in the general direction of our goal and figure out the details along the way. When we first wrote about co-creation (Glessmer & Daae, 2021), we described integrating co-creation as tagging on independent short trips onto whatever journey a teacher was on. Now, we are considering much longer timescales and are negotiating with all our travel companions: students, technicians, admin, and others!
You will need a compass to orient and compare the map with the true landscape. Checking in on students regularly (as described under rule 3) gives you a compass to ensure they are on track and/or can follow the pace. A less obvious way to check in is to continuously encourage working in ways that enable sensemaking, confirm students’ progress, and provide formative feedback (Daae and Glessmer, 2022).
8. Don’t be ashamed to turn around
Sometimes, things don’t work according to plans or intentions. Don’t be afraid of turning around and/or skipping some parts of the travel. Perhaps there is a safer route you can take or wait out bad weather in a shelter along the way. And sometimes plans change along the way, which is ok, too! Perhaps the students make you aware of conditions that force you on a detour to, for example, pick up necessary concepts from previous courses.
9. Conserve your energy and seek shelter if necessary
Sometimes, the route is long and windy. How can you help your students conserve energy? Could you offer them a bus ride or a bicycle for parts of the journey? Consider the total workload of the course and adjust compulsory activities and expectations of student hand-ins if necessary. Could you make video recordings of lectures to allow students to watch at their own pace when they have time? Or could you provide material students can go through independently if they miss an active learning session?
Even with the means of transportation all sorted, there are still many ways that students can choose to travel together (collaborate) to save energy. On the lecture bus, they can do think-pair-shares, and on the skiing project, they might stick closely together or meet up at the bottom of the slope to check in on each other. Bringing together students from different cohorts can also be a great idea to learn from and with each other to conserve energy and build on each other’s knowledge (Daae et al., 2023; Strehl and Daae, 2025).
And sometimes, a little treat, like a good anecdote or comments to relevant news stories, before a steep uphill can motivate the students to start the climb.
10. Take chances – what if it works?
Rule 10 is not part of the official mountain code, and we will not be held responsible for anyone following this rule in a real mountain hike. This rule was made by one of the author’s grandfathers, who was an adventurer and who thought any list of rules should contain 10 rules. We believe this unofficial rule number 10 works well for our co-creation journey. Sometimes, you must take chances and dare to try something new to learn new ways of making the journey engaging for both the students and yourself. During our project, we tried many new things that we were not sure would work or that we initially thought we might not be allowed to do. One example is letting students vote for the weighting of different assessment elements toward the final grade. The students could vote for the final exam, counting between 50% and 90%, with the remaining weight distributed equally between two reports. The students were positive about discussing the assessment weighting and appreciated having a say in the decision.
Looking back, looking forward
Looking back at our journey, there are various ways of assessing whether and how well we reached the goal as a group or as individual students. How much did the students learn, and how could they demonstrate their learning? And is reaching the goal the only measure that matters? Courses that base their assessment on final exams only check where or how far the students reach, not what they experienced along the way. Implementing various partial assessments, where students could, e.g., help decide the weighting of the assessment elements, could increase the student motivation for multiple pieces of their travel and encourage them to enjoy both a view towards the horizon and closely observing a little bug on a blade of grass, and shift the focus away from just checking how far they reach.
Everybody loves telling the story of their adventures. Sometimes, snowstorms get deeper over time, or mountains less steep. We tell our story to inspire you to start your co-creation adventure – but do not follow our map blindly. We might have forgotten about the bogs of skeptical peers or the maze of administration. The legal avalanches might have gone off and taken the forest of choice with them. But it is an adventure worth starting, so have a nice trip!
Takk for turen!
We would like to thank students and teacher-peers for traveling with us. The project is funded by the Norwegian Directorate for Higher Education and Skills (HK-dir) under the program for student active learning, DIKU – AKTIV 2021/10219.
References
Bovill, C., Cook-Sather, A., Felten, P., Millard, L., & Moore-Cherry, N. (2016). Addressing potential challenges in co-creating learning and teaching: Overcoming resistance, navigating institutional norms and ensuring inclusivity in student–staff partnerships. Higher Education, 71, 195-208.
Bovill, C. (2020), Co-creating Learning and Teaching: Towards Relational Pedagogy in Higher Education. Critical Publishing, 96 pp, ISBN : 9781913063818
Daae, K., Steen-Larsen, H.C., and Glessmer, M. S. (2025). Students taking ownership in a jigsaw approach to fieldwork. In press for the book: Teaching Fieldwork in Geography, Earth and Environmental Sciences, by editors D. France, L. Batty and D. Swanton, Edward Elgar Publishing}
Daae, K., Semper, S., and Glessmer, M.S. (2024). Supporting sensemaking by introducing a connecting thread throughout a course. Oceanography 37(4), https://doi.org/10.5670/oceanog.2024.604
Daae, K., Årvik, A.D., Darelius, E., and Glessmer, M.S. (2023). Student guides: supporting learning from laboratory experiments through across-course collaboration. Nordic Journal of STEM Education, 7(1): 98-105. https://doi.org/10.5324/njsteme.v7i1.5093
Daae, K., and Glessmer, M.S. (2022). Collaborative sketching to support sensemaking: If you can sketch it, you can explain it. Oceanography, 35(2), https://doi.org/10.5670/oceanog.2022.208.
Glessmer, M. S., Persson, P., & Forsyth, R. (2024). Engineering students trust teachers who ask, listen, and respond. International Journal for Academic Development, 1–14. doi.org/10.1080/1360144X.2024.2438224
Glessmer, M.S., Bovill, C., and Daae, K. (2024). Adapting a teaching method to fit purpose and context. Oceanography, https://doi.org/10.5670/oceanog.2024.603.
Glessmer, M.S., Latuta, L., Saltalamacchia, F.and Daae, K. (2023). Activity bingo: Nudging students to make the most out of fieldwork. Oceanography, https://doi.org/10.5670/oceanog.2023.217.
Glessmer, M.S., and Daae, K. (2021). Co-creating learning in oceanography. Oceanography 34(4), https://doi.org/10.5670/oceanog.2021.405.
Kordts, R., de Vareilles, M., Daae, K., Gandrud, E., Årvik, A. D., and Glessmer, M. S. (2025). Teaching Analysis Poll (TAP) for Student Feedback. Oceanography (38/2), https://doi.org/10.5670/oceanog.2025.305.
Røde Kors, The Norwegian Mountain Code (2016), https://www.rodekors.no/globalassets/_vart-arbeid/beredskap/fjellvett/fjellvettreglene_engelsk.pdf (accessed 15.2.2025)
Strehl, A.M., and Daae, K., (2025), Co-creating course projects in introductory Meteorology and Oceanography – enhancing/building motivation through group supervision and collaboration with former students, Proceeding submitted to the MNT conference 2025
Venet, A. S. (2024). Becoming an Everyday Changemaker: Healing and Justice at School. Taylor & Francis.
Improving students’ programming skills through Collaborative Scientific Python
Julien-Pooya Weihs and Daniel Oddmund Lid
Abstract:
Scientific programming is an increasingly important part of the scientific curriculum and careers overall. However, students often struggle to see its uses and benefits, and where and how to begin learning it. At the same time, teachers face challenges in defining clear programming goals and creating new teaching materials that integrate the complexities of scientific programming.
To address these issues, a pilot course of five lectures over two weeks was created at the Geophysical Institute of the University of Bergen in Spring 2024. This course aimed to help students understand and practice the basics of scientific collaborative Python, focusing on common Python packages, standard scientific procedures, basic Git commands and collaborative tools. Designed with methods supported by didactics literature, the course emphasized active participation and group work, using real-world geophysical data. Pre- and post-course data were collected via surveys from 12 of the attending students.
We here present the main structure of the course, and the resources developed for it. We also share the reported positive impact on students’ reflections on the integrated Python-Git framework at the centre of the course.
Keywords: Programming education, Python, Git, Collaborative learning, Co-creation
1 Introduction
1.1 Context
1.1.1 Programming teaching and learning
Programming education poses challenges to both students and teaching staff. Discussions with students have revealed that they can lack experience with the programming routines required by their disciplinary courses, or lack the motivation to start learning programming, are not sure where to begin, and do not see the benefits of it overall. The too few assessments of programming tasks and sometimes absence of
programming during the exams render the motivation to learn low. Lecturers in the natural sciences reported that they often use a programming language in their research that does not coincidence with the programming language in their teaching, leading to a possible mismatch between research and instruction, and inducing teaching difficulties. In addition, programming is a complex topic to teach, with specific semantics, syntax and use cases, and programming goals are not always well defined in the curriculum. This results in teaching and learning programming in higher education to be one of the
cruxes of a modern degree in natural sciences, despite programming being a skill of very
high societal relevance and necessity in scientific careers.
A sustainable solution is hence needed, amongst others to introduce programming to the students in an incremental way, to help students with their related struggles, and to provide students with the associated professional skills (coding + data management).
1.1.2 The Git-VSC framework
Git (https://git-scm.com) is a cloud-based version control system that allows to track any history of changes to a file or project. Recording edits and updates, it also permits to revert a file or project to an earlier saved version of it. This makes it a transparent system for users and developers, showing throughout the development of a project which changes have been made to what by who, when and even why, as contributors can comment on each of their submitted changes. Every contributor to a project has a local copy of both the project and project history, and the changes to a group project are tracked between the local copies and the collaborative cloud-based version of the project.
A popular online platform for working on project development using Git is Github (https://github.com), and it allows multiple people to work simultaneously by tracking and organising their changes to all files of a same project. It is the most popular worldwide platform for developers (100 millions developers and over 386 millions repositories in 3/23), and is commonly used for open-source projects (40 millions
publically available repositories in 3/23). In the geosciences, a search across public repositories gave 1700 hits for ‘climate models’, 1000 hits for ‘oceanography’ and 2600 hits for ‘meteorology’ on the Github platform in 3/23.
Visual Studio Code (https://code.visualstudio.com) is a free and open-source code editor/interpreter/compiler with a wide range of features developed and maintained by a large community. It has been the most popular coding environment for users (74% of71000 respondents in 2022) and allows a full integration and synchronisation of projects with Github.
By introducing and using a combined Git-VSC environment to the students in our course, we provided them with a tool that is valued as a professional skill to master, that offers great collaborative possibilities, and supports integrating programming into any possible course. The use of Git also allows for full transparency on individual contributions in the workflow, and assures that shared documents are always up to date for everyone.
Research on using Git in programming (Zagalsky et al., 2015; Kertész, 2015; Feliciano et al., 2016; Glazunova, 2021) has shown that it improves collaboration, allows for effective version control, facilitates a platform for discussion between users, holds users accountable for their contributions, and allows students to develop technical skills at an industry-standard. However, it is also acknowledged that there is a steep learning curve for beginners unfamiliar with these environments, that the framework may not be
suitable for grading assignments, and that some students may be uncomfortable sharing their work.
1.2 Meaningful learning
Weurlander et al. (2009) present a theory of learning built upon 5 main pillars: context, motivation, connections, wholeness, and collaboration. Figure 1 presents a graphical representation of these intertwining constructs.
We value this theory for its multifaceted structure that overlaps with the main constructs from other popular theories of learning: collaboration integrates the socio-constructivist view that learning is the negotiation of norms and knowledge amongst peers, and can hence influence our sense of belonging to a group. Context and connections are closely tied with self-efficacy, when a learner realises the relevance and applicability of their knowledge and skills to their discipline. Motivation is commonly split into 2 mains axes: extrinsic, relating to external drivers, and intrinsic, relating to genuine interest. We used this framework when developing our course, being mindful to address each of these 5 pillars in the learning outcomes for the students.
Particularly, we put emphasis on students learning to learn (Blaschke, 2012), where the final goal is not the content but their development as a learner: capable of finding new approaches and information, and applying these in an effective manner. This can include utilising online resources, actively communicating with peers, and developing creative skills within the workflow. The learners undergoing such a process would become self-determined, gaining abilities to be effective and seeking out knowledge.
We lastly followed recommendations on teaching from discipline-based educational research (Singer et al., 2012; Deslauriers et al., 2019), namely, to encourage students’
active participation, to involve students in collaborative activities, and to supplement
instruction with tutorials.
1.3 Research Question
Considering the challenges of programming education, and designing a research-informed course on collaborative scientific programming, this project was driven by the following research question:
What are the students’ perception of the course on their programming learning?
2. Methods
2.1 The Collaborative Scientific Python Course
2.1.1 Course design
This first edition of our course was given as a pilot at the Geophysical Institute of the University of Bergen. The course was co-created by the authors, respectively a PhD student in geoscience education, and a master student in oceanography, taking advantage of two different disciplinary perspectives, with the following objectives:
- allowing the students to reach a certain fluency in working on collaborative projects using Git: download files, fork/branch projects, submit pull/merge requests, commit-push tracked changes, fetch-pull new versions, and run and manage projects with peers and collaborators.
- providing the students with an understanding and practice of basic scientific Python: discover and use Pandas, Matplotlib, Numpy, Cartopy, Scipy, be able to read-in, pre-process, analyse and visualise geophysical data, and groom and utilise these skills all along their studies and future careers.
To this end, the course featured activities using real-life data and focusing on scientific case-studies from meteorology and oceanography.
We iteratively designed a course-program that would focus on each element of the curriculum separately, before combining them in a group-project. We laid out a structure-skeleton, discussed what modules were essential, and in what order to best present them. By doing this weeks ahead of the course start, we had enough time to talk through each module, add activities, and revise the order and contents, if needed. During the course, and based on the progress of each day, we updated the content for the next day, either repeating previous elements that were deemed complex, or swapping modules to increase the coherence of the teaching flow. Every day, we would summarise the content of the previous day to help with the information retention.
The course was open to all students from all programs at the Geophysical Institute, and listed 15 attendees (course capped at 16 students, with 1 last-minute cancellation). The instruction was provided over 5 days during 2 weeks in the Spring 2024 semester, from 17:00 to 20:00, and offered free pizza and snacks to the students. No exam was used to assess the learning of this course, but the students prepared a final group presentation given to an invited climate expert from the Geophysical Institute.
2.1.2 Teaching structure
The curriculum was as follows:
Day 1 – Introduction (+ pre-course survey)
- theory and motivation behind meaningful learning & Git for programming.
- installation of Python, Visual Studio Code and Git infrastructure.
Day 2 – Scientific Python
- demonstration of use cases by invited researcher (in oceanography).
- practice and exercises.
- getting everyone past the minimal required programming level.
Days 3 & 4 – Git & Collaboration
- basic Git commands.
- scientific group project.
- collaborate in teams and between different teams.
Day 5 – Reflections (+ post-course survey)
- present and discuss results with a climate expert.
2.2 Student surveys
In order to capture the self-reported impact of the course on the students’ learning, we created pre- and post-course surveys inspired by the works of Boljat et al. (2019) and Van Staveren (2022), and answerable on a 5-points Likert-scale. Both surveys had in common a set of 10 questions targeting intrinsic, extrinsic and general motivation, self-efficacy, and belonging, and the post-course survey had an additional set of 10 questions to reflect on the course directly. An open-ended final question allowed the students to provide additional thoughts and comments for improvements of future editions of the course. Participation to the surveys was done on a voluntary basis, and 12 of the total 15 students responded to both the pre- and post-course surveys.
3 Results and Discussion
3.1 Course resources
An important result of this project was the creation of various teaching and educational resources, amongst which:
- Course slides for 5 lecture days.
- Python exercises and possible solutions.
- Pre- and post-course survey instruments.
- Link to GitHub repository with all resources.
All these resources are available upon request to the corresponding author. We would be glad to inspire fellow teaching practitioners to use and build up on these resources, both to improve the teaching material, but also to collect more educational data through the surveys, and hence contribute to a larger body of research and instruction in programming education.
3.2 Students’ responses
At the time of writing, the students survey data is being processed and analysed, and we here present only an excerpt of our preliminary results. Figure 2 displays the evolution of the pre- and post-course survey responses (first set of 10 questions).
Despite the very limited dataset of 12 students, we observe the following trends: the intrinsic movitation (+0.34 points on average) has the largest increase. Theories of learning often attribute one of the largest roles to this contruct in a learner’s drive and efficacy to learn.
General motivation (-0.23) and extinsic motivation (-0.02) are the two only constructs not gaining in score after the course. A explanation could reside in a slight transfer from extinsic (‘we need to study to pass the exam’) to intrinsic (‘programming is an interesting skill and activity’) motivation for the learners. Q5 in particular went from a score of 5.0 (pre) to 4.9 (post) and read ‘I believe that programming skills will be beneficial for my future career.’ Only 1 student answered ‘4’ instead of ‘5’ after the course, perhaps
indicating a slight reconsideration of future professional prospects.
Self-efficacy (+0.33) and belonging (+0.20) show clear trends, which is very positive despite the short format of this pilot, and motivates repetitions of the course in at least similar length formats.
4. Conclusion
This pilot course on collaborative scientific programming was successful and resulted in great satisfaction for the students taking it, as well as for us leading it. There is large educational potential for repetition and expansion of this project in various departments of natural sciences.
Acknowledgements
This project has been run within the HKDir-funded CoCreatingGFI project (https://cocreatinggfi.w.uib.no) at the Geophysical Institute of the University of Bergen. The authors warmly thank all participating students for their great energy and enthusiasm throughout the course.
References
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Boljat, I., Mladenović, M., & Jogun, N. M. (2019). Students’attitudes towards programming after the first year of implementing a new informatics curriculum in the elementary schools. In ICERI2019 Proceedings (pp. 9486-9495). IATED.
Deslauriers, L., McCarty, L. S., Miller, K., Callaghan, K., & Kestin, G. (2019). Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proceedings of the National Academy of Sciences, 116(39), 19251-19257.
Feliciano, J., Storey, M. A., & Zagalsky, A. (2016, May). Student experiences using GitHub in software engineering courses: a case study. In Proceedings of the 38th International Conference on Software Engineering Companion (pp. 422-431).
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Van Staveren, M. (2022). Integrating python into a physical chemistry lab. Journal of Chemical Education, 99(7), 2604-2609.
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Appendix: Questions in the student survey used in Figure 2
The questions were introduced with the following instructions for the LIKERT scale:
Please answer the questions using the following scale:
★ (1) – Strongly disagree
★★ (2) – Disagree
★★★ (3) – Neither agree nor disagree
★★★★ (4)- Agree
★★★★★ (5) – Strongly Agree
PRE- ans POST COURSE (10 QUESTIONS)
1. I like programming.
2. Programming is interesting.
3. I would like to continue learning programming in the future.
4. I would like more programming teaching in the next year.
5. I find programming easy.
6. Programming concepts and syntax are easy for me to learn.
7. I am confident that I could learn a new programming skill.
8. Programming makes me feel more like a geophysicist.
9. Collaborating in coding activities makes me feel more like a geophysicist.
10. I believe that programming skills will be beneficial for my future career