OEGlobal 2024

What happens when a long-standing commitment to open sharing of knowledge awakens to and begins to infuse responses to the stark reality of the climate emergency? What new learning practices are catalyzed, and how can this lead to a more just and livable world?

In this session, we’ll explore some ways that more timely, equitable and effective climate learning is being enabled by the methods and materials of open education; and also how open education practices can evolve to maximize the positive impacts of climate action efforts.

Substantial progress has been made on climate action and climate justice in recent years. But our “business as usual” trajectory of incremental change within existing systems still has us on track for warming of over 3C by 2100. This trajectory is less dire than the prospects of 4C+ that we faced a decade ago; but without much deeper transformations, we’re still on a path to trigger planetary tipping points, ecosystem collapses and mass disruptions of human society.

More must be done. And as a means of transformation, open practices have a key role to play.

These questions are playing out now in developing the Climate Project at MIT, an ambitious program announced in early 2024 to do bigger things faster and work more effectively with partners around the scientific and societal challenges of climate change.

In this session, we’ll highlight some of the ways that open knowledge practices are infusing climate work at MIT and in its collaborations, and ask what might be possible if a commitment to open knowledge practices spreads widely across climate action spaces.

At OE Global 2023, a workshop session began to consider an open climate knowledge community of practice. We discussed needs and opportunities, and identified some resources and programs that can serve as inspirations and a basis for future work. See workshop notes at https://bit.ly/oeglobal-climate-community.

One year later, where are we? How are open methods and materials making a difference for general public engagement and empowering k-12, post-secondary, workforce and professional learning about climate change and climate justice? Current and future generations are counting on us to make this everyone’s business.


Included in [Session 10A]: Practice and Policy in OE

References
Notes from OE Global’23 workshop on open climate knowledge: Accelerating Climate Action and Climate Justice Through Open Education.
OE Week 2024 event: Accelerating Climate Action and Climate Justice Through Open Education.
International Open Access Week 2022 webinar video: Learn Climate with Open MIT Resources.

Author Keywords
Lifelong and informal learning, Open educational practices, Open education policies and strategies, Social justice, Sustainability

Open Educational Resources (OER) have been discussed in Sweden as early as 2008 (Westman & Paulsson). Unfortunately, their adoption is still very limited due to a lack of understanding about their nature, how they can be used, and the opportunities they present (National Library of Sweden, 2022). In light of the UNESCO recommendation on OERs, the National Library of Sweden was tasked with developing national guidelines for open science by the Swedish Government. These were recently presented and include the use of OER (National Library of Sweden, 2024).

The national library's work on national guidelines was companied by The Association of Swedish Higher Education Institutions (SUHF) working group on OERs. SUHFs aim is to promote the sector interests to external actors and at strengthening internal cooperation. The task of the working group is to develop proposals for recommendations on what national OER coordination could look like and how educational institutions could create a long-term structure for the work. The OER working group reports first and foremost to the working group on open science, which put forward a roadmap for open science as early as 2021.

In line with the national recommendations for open science, SUHF updated their roadmap in the beginning of the year (SUHF, 2024) and includes now a section about OERs. The roadmap defines the responsibility of Swedish Higher Education institution to "actively work towards creating a sharing culture regarding educational resources by encouraging and promoting the creation, sharing, and use of open educational resources". In this presentation, a member of the OER working group presents the roadmap and its' accompanying guideline for the OER section, which tries to ensure that OERs are finally everybody's business in the Swedish Higher Education system.



Included in [Session 10A]: Practice and Policy in OE

References
Moore, M. G. (2022). From correspondence education to online distance education. In Handbook of Open, Distance and Digital Education (pp. 1-16). Singapore: Springer Nature Singapore.

National Library of Sweden (2022). Öppna lärresurser – en kartläggning och analys: Redovisning av uppdraget om öppna lärresurser, U2021/04163. Available at: https://urn.kb.se/resolve?urn=urn:nbn:se:kb:publ-691

National Library of Sweden (2024). Natio­nal guide­li­nes for promoting open science in Sweden. Available at: https://urn.kb.se/resolve?urn=urn:nbn:se:kb:publ-722.

SUHF (2024). Färdplan för öppen vetenskap (reviderad). Available at: https://suhf.se/app/uploads/2024/02/REK-2021-1-Fardplan-for-oppen-vetenskap-SUHF-Antagen-av-SUHFs-presidium-REVIDERAD-240201-1.pdf.

Westman, P., & Paulsson, J. (2008). Open Educational Resources in Swedish Higher Education. ScieCom Info, 4(23).

Author Keywords
Open Educational Resources, National policies, Sweden, UNESCO recommendation on OER, Higher Education

In 2021 California made the largest public investment in history in OER and Zero Textbook Cost degrees with a $115M grant program. Beginning in 2022, all California Community Colleges received funds to develop and implement ZTC pathways. As of 2024, colleges are developing hundreds of ZTC pathways to transform the student experience in the United States’ largest system of higher education, serving 2M+ students.

In this session, hear from leaders who are coordinating and supporting colleges in this historic work. What supports are provided to colleges? How are diversity, equity, and inclusion woven into support for colleges? What role do Open Pedagogy and Generative AI play? What is the sustainability plan for this massive undertaking? We will also consider how California got here and what it will mean when all colleges offer ZTC pathways.

The unique audience of OEGlobal presents an opportunity to consider how the ZTC movement in California can impact higher education in general. 



Included in [Session 10A]: Practice and Policy in OE

Author Keywords
Zero Textbook Cost degrees, Open Education policies and strategies, Community colleges

“An area of HE activity that is highly inequitable is the provision of expensive fully copyrighted print-based textbooks” (Cox, Masuku and Willmers: 2020).

Open educational resources (OER) have gained traction in many parts of the world, through their expression as open textbooks. South Africa is no exception when it comes to proclaiming their commitment to such open practice. The Open Learning Policy Framework for South African Post-School Education and Training commits higher education (HE) to such pursuits (Department: Higher Education and Training, 2017). As well as this national commitment, literature clearly demonstrates that open textbooks have the potential to disrupt the trajectory of exclusion in South African Higher Education by addressing issues of cost.

Open textbooks are also seen as a solution to variable quality of educational resources as well as addressing social injustice through increased access to learning materials (Cox et al., 2020; Hodgkinson-Williams & Arinto, 2017). The Digital Open Textbooks for Development (DOT4D) Project found that open textbooks “addressed economic, cultural, and political in justices faced by their students, issues not considered by traditional textbooks” (OER Africa, 2024). However, not much is known about the use of open textbooks in South African Higher education, especially in Accounting education and more specifically taxation education. Taxation is the focus of this study because of its content uniqueness to specific countries based on regional tax law.

In addition to the geographical uniqueness annual amendments to Tax Acts necessitate the continual updating of some content. Most universities in South Africa prescribe textbooks for undergraduate taxation modules (Department: Higher Education and Training, 2020). For all the reasons provided above and others reported in literature on open textbooks, this study aims to explore the use of open textbooks in Taxation. The challenge is that for the use of a taxation open textbooks to be sustainable, someone needs to take responsibility for updating for annual changes. Currently this function is performed by various commercial publishers who pay authors to do this.

The paper will report on a study focused on exploring the use of open textbooks in tax education. The paper will first report on a scoping review on the use of open textbooks in business education globally. The overarching question was: How are open textbooks used in business education? Following the scoping review, the study surveyed undergraduate taxation lecturers at South African universities to garner their perceptions regarding the use of open textbooks with the intention of introducing the use of open textbooks in tax education. The paper will report on the findings of this survey and more specifically identifying the challenges that need to be mitigated so that open textbooks or a sustainable alternative that speaks to increased access to learning materials and lower costs, can be introduced in the South African taxation education arena.



Included in [Session 10A]: Practice and Policy in OE

References
Cox, G., Masuku, B., & Willmers, M. (2020). Open textbooks and social justice: Open educational practices to address economic, cultural and political injustice at the University of Cape Town. Department: Higher Education and Training. (2017). Open Learning Policy Framework for Post-School Education and Training. (). https://www.gov.za/sites/default/files/gcis_document/201704/40772gon335.pdf Department: Higher education and Training. (2020). Students' Access to and Use of Learning Materials. Survey Report 2020. (). Pretoria: Department of Higher Education and Training. https://www.usaf.ac.za/wp-content/uploads/2021/02/DHET_SAULM-Report-2020.pdf Hodgkinson-Williams, C., & Arinto, P. (2017). Adoption and impact of OER in the Global South. African Minds. OER Africa. (2024). What are the benefits of open textbooks in the Global South? OER Africa. Retrieved 19 May 2024, from https://www.oerafrica.org/content/what-are-benefits-open-textbooks-global-south

Author Keywords
Open Textbooks, OER, Accounting (Taxation)Education, Higher Education

Since changing roles from CEO to Head of Research at Moodle, Martin has had a lot more time in the past year to go deeper into new technologies and especially to study how they might affect education in general.

This presentation will cover:

- the long-term trends he's seeing around education and where that will probably take us in the next ten years and more.
- the main trends for the future of the Moodle platform, particularly for incorporating AI
- A discussion about a potentially important OER project for Open Education Global, on which your feedback is sought.

Included in [Session 11A]: Artificial Intelligence

AI pervades various facets of society, including education. In the open education domain, the notion of open AI, distinct from the entity OpenAI, is attracting attention. However, the precise connotations of "open" in conjunction with "AI" remain subject to diverse interpretations, reflecting conceptual tensions and longstanding differences around concepts of “open” in respective domains.

In a blog post last year, prominent edtech expert David Wiley wrote, “when people talk about whether or not generative AI should be “open,” they could be talking about whether the foundation models should be open, whether the modified model weights that result from fine-tuning should be open, and/or whether the prompts (which includes templates, embeddings, etc.) should be open” (Wiley, 2023). In a similar direction, focusing on licensing for different aspects of AI technology, the Open Source Initiative are currently developing an “open-source AI” definition (Open Source Initiative, 2024). On the other hand, in broader literature, definitions of open education and open technology encompass a wide range of concepts, where “open” could mean: “ethical” (Holmes et al., 2022), “inclusive” and “innovative” (Bozkurt, 2023), “co-created” and “learner-driven” (Walberg and Thomas, 1972), “non-proprietary” (Berners-Lee, 2023), “decentralised” (Crowston and Howison, 2005), “accessible without barriers” (Knox, 2013), “available to join”, “shared”, “not tightly controlled” (Weller, 2020), “available in the public domain or under an open license” (UNESCO, 2022), “interpretable” and “visible” (Conati, Porayska-Pomsta, and Mavrikis, 2018), and many others.

This indicates that “open AI” and “open-source AI” are overlapping but not identical concepts. “Open-source AI” seems to be about the tangible aspects of systems, whereas “open AI” is broader and potentially includes context of how systems can be used, who can use them, and what for. Rather than trying to resolve these debates into a single taxonomy/typology, we propose a meronomic, holistic account of openness in AI education which explores the relationship between definitions with respect to part-whole relationships. This will facilitate diverse contributions and critical discussion.

In this panel session, participants will have the opportunity to engage in the panel discussion and ask questions regarding the dimensions of openness of AI in education.

The agenda includes:

• 10 minutes: introductions, pre-recorded 1-slide lightning presentations from experts, panel reactions
• 10 minutes: panel interaction and debate
• 15 minutes: Q&A with panel members based on thoughts submitted by the audience (with backup questions prepared by the moderators).
• 5 minutes: closing discussion and synthesis.

Experts who agreed to contribute so far include David Wiley, Anne-Marie Scott, Aras Bozkurt, Chrissi Nerantzi and Leo Havemann. Some of them might join virtually. They will be provided with prompts ahead of time for their initial statements. Robert Farrow, an experienced moderator, will chair the panel discussion. During the discussion, delegates will be able to contribute reflections and questions through a back channel and these will be integrated into the discussion.

Included in [Session 11A]: Artificial Intelligence

References

Berners-Lee, T. (2023). Frequently asked questions by the Press – Tim BL (w3.org). Available at https://www.w3.org/People/Berners-Lee/FAQ.html (Accessed: 2 May 2024)

Bozkurt, A. (2023). Generative AI, Synthetic Contents, Open Educational Resources (OER), and Open Educational Practices (OEP): A New Front in the Openness Landscape. Open Praxis, 15(3), pp. 178–184. DOI: https://doi.org/10.55982/openpraxis.15.3.579

Conati, C., Porayska-Pomsta, K. and Mavrikis, M., 2018. AI in Education needs interpretable machine learning: Lessons from Open Learner Modelling. arXiv preprint: https://arxiv.org/abs/1807.00154

Crowston, K. and Howison, J. (2005). The social structure of Free and Open Source software development. First Monday, Volume 10, Number 2 - 7 February 2005 Available at: https://firstmonday.org/ojs/index.php/fm/article/download/1207/1127 (Accessed: 2 May 2024)

Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S.B., Santos, O.C., Rodrigo, M.T., Cukurova, M., Bittencourt, I.I. and Koedinger, K.R. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, pp.1-23. DOI: https://doi.org/10.1007/s40593-021-00239-1

Knox, J. (2013). Five critiques of the open educational resources movement. Teaching in Higher Education, 18(8), pp. 821–832. DOI: https://doi.org/10.1080/13562517.2013.774354

Open Source Initiative (2024). The Open Source AI Definition – draft v. 0.0.8. Available at: https://opensource.org/deepdive/drafts/the-open-source-ai-definition-draft-v-0-0-8 (Accessed: 2 May 2024)

UNESCO (2022). Understanding Open Science. UNESDOC Digital Library. DOI: https://doi.org/10.54677/UTCD9302

Walberg, H.J. and Thomas, S.C. (1972). Open education: An operational definition and validation in Great Britain and United States. American Educational Research Journal, 9(2), pp.197-208. DOI: https://doi.org/10.3102/00028312009002197

Weller, M. (2020). 25 years of ed tech. Athabasca University Press. DOI: https://doi.org/10.15215/aupress/9781771993050.01

Wiley, D. (2023). An analogy for understanding what it means for generative AI to be “Open”. Open Content. https://opencontent.org/blog/archives/7289

Author Keywords
Open AI, Open-source AI, Artificial Intelligence, Open data, Open-source technical platforms

The burgeoning integration of Large Language Models (LLMs) such as ChatGPT into the fabric of Massive Open Online Courses (MOOCs) has highlighted a promising new direction for enhancing automated essay assessment processes. This research delves into the practical implementation of LLMs for evaluating student essays within MOOC frameworks, focusing primarily on exploring advanced prompt engineering strategies.

We investigate a spectrum of methodologies, including few-shot learning, Chain-of-Thought (CoT) prompting, and fine-tuning techniques, to discern the most effective strategies for harnessing the capabilities of LLMs in this educational domain. Drawing from the latest advancements in natural language processing (NLP), our study examines the ability of LLMs to deliver accurate, efficient, and scalable assessments of student submissions.

MOOCs typically host hundreds to thousands of students per course, presenting significant logistical challenges regarding assignment evaluation. The volume of essays that require assessment can be overwhelming for instructors, making it virtually impossible to provide detailed, timely feedback without technological assistance. The deployment of LLMs promises not only to enhance the grading efficiency and maintain consistency in evaluation standards across large cohorts.

The primary objective of this study is to explore the application of generative AI (GAI) in assisting with essay grading, utilizing open courses hosted at ewant, the largest MOOCs platform run by National Yang Ming Chiao Tung University (NYCU) in Taiwan . This course, "Required Credits for University Students - Emotional Education" is taught by Professor Chen Fei-Chuan at National Yunlin University of Science and Technology, Taiwan. Since its first delivery in 2015, this course has been offered 137 times, with nearly 20,000 students enrolled. From both qualitative and quantitative perspectives, this course represents an optimal choice for the study, offering substantial potential for further research and development. Assignments in this course predominantly involve open-ended questions without standard answers, encouraging students to reflect, discuss, share, and synthesize their personal experiences based on the knowledge acquired during the course. This type of unstructured assignment is better suited for introducing GAI than structured assignments in science and engineering courses with definitive answers.

This research aims to leverage a data-driven approach to develop a GAI system that replicates the grading standards and performance of the instructors or teaching assistants (graders), thereby assisting future educators in efficiently grading large volumes of written assignments. By analyzing the strengths and drawbacks of multiple prompt engineering and fine-tuning methods in automating essay evaluations, the study aims to establish a dataflow pipeline for AI-assisted essay grading, with the expectation of generalizing this process to other courses of a similar nature. Additionally, this research proposes recommendations for designing more effective and scalable automated essay assessment systems tailored for contemporary online education platforms.

Overall, this study aims to provide a comprehensive analysis of the potential of LLMs in transforming the landscape of essay assessment in MOOCs, thereby contributing valuable insights into the optimization of educational technologies in a GAI era.



Included in [Session 11A]: Artificial Intelligence

References
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in neural information processing systems, 33, 1877-1901.

Kojima, T., Gu, S. S., Reid, M., Matsuo, Y., & Iwasawa, Y. (2022). Large language models are zero-shot reasoners. Advances in neural information processing systems, 35, 22199-22213.

Min, S., Lyu, X., Holtzman, A., Artetxe, M., Lewis, M., Hajishirzi, H., & Zettlemoyer, L. (2022). Rethinking the role of demonstrations: What makes in-context learning work?. arXiv preprint arXiv:2202.12837.

Wei, J., Bosma, M., Zhao, V. Y., Guu, K., Yu, A. W., Lester, B., ... & Le, Q. V. (2021). Finetuned language models are zero-shot learners. arXiv preprint arXiv:2109.01652.

Wei, J., Wang, X., Schuurmans, D., Bosma, M., Xia, F., Chi, E., ... & Zhou, D. (2022). Chain-of-thought prompting elicits reasoning in large language models. Advances in Neural Information Processing Systems, 35, 24824-24837.

Author Keywords
Artificial Intelligence, Large Language Models, Prompt Engineering, Assessment, MOOCs