The best way of ensuring you can use and modify existent online content is to search for Open Educational Resources (OER). Open educational resources (eduhack.eu) are “teaching, learning and research materials in any medium, digital or otherwise, that reside in the public domain or have been released under an open license that permits no-cost access, use, adaptation and redistribution by others with no or limited restrictions”. Several initiatives  exist that have  organized Open Educational Resources, for example OER Commons, Connexions, Khan Academy and Saylor.org. In these platforms you can search, browse, and evaluate resources, exploring some curated collections of full university courses, interactive mini-lessons and simulations, adaptations of existing open work, open textbooks, and so on.  

As an educational designer, you need to very critically evaluate online tools (eduhack.eu). Technologies are always inspired by values and principles that, whether explicitly  or not, may result in design choices and operational models that privilege certain worldviews, attitudes and even some groups of people over others. An example relating to analogue technologies would be the design of a pair of scissors easier to use for right-handed people than for left-handed people. Another example, referred to online technologies, are the algorithms which  shape the way we are exposed to information online and our own online experiences – (for a more detailed reflection you may see the review algorithms of oppression (eduhack.eu).  

ArtificiaI Intelligence (AI) tools are only as good as the data they are fed. Sensitive, personal data relating to individual students requires that university systems be technically robust and have effective data management. Although it is probably more of a power taken by the institution’s policy, it is useful for the teacher to be able to be critical of the tools proposed by the policy. It is important to be informed about the chosen methods of data collection and processing and to be extremely careful in how data, algorithms and artificial intelligence are used in teaching. Applying an ethical framework for this could be helpful (Cormack, 2021). This can be done in collaborating with current organizations such as the Institute for Ethical AI in education (IEAIED, 2021) and utilizing the Jisc code of practice for analytics (Sclater and Bailey, 2018). We must enable equality and diversity and acknowledge algorithmic biases in AI systems whereby certain groups of e-learners may be unfairly discriminated against. 

Always consider the pedagogical and learning effects in your design and choosing resources. As an example, among many others, see the 9 DeakinDesign principles:   

1. Holistic
2. Authentic
3. Active and collaborative
4. Integrated
5. Digital 
6. Course-wide
7. Inclusive
8. Feedback focused
9. Relational

Keep in mind that the learning resources chosen are amongst them consistent with the learning activities and with the communication tools that are used to contribute to the students’ learning needs. The adoption of a particular existent framework, model or toolkit may help to check and ensure the desired consistency. In practice, there are multiple of those frameworks, models and toolkits, so a critical reflection on them is needed. In this reflection it is a must to consider whether they are adapted to online learning and foster inclusion.