Processes and networks around digital learning materials

This blog post is a co-production of Ben Janssen (OpenEd Consult) and me. Nederlandse versie

The purpose of this series of blogs is to provide arguments that may be relevant when formulating a vision and policy for OERs. Vision and policy are necessary for adoption of OERs to be sustainable. Many OER initiatives start with an initial project grant but is not continued once the project is completed (Tlili et al, 2020; Annand, 2015). Paraphrasing, we might also say “Is there life after the project grant?”. In an advisory report for the OECD, David Wiley (2007) indicated that a distinction can be made between two issues regarding the sustainability of OER:

  1. How to sustain the production and sharing of OER?
  2. How to sustain the use and reuse of OER by end users?

Vision development and policy will have to address both issues.

In the previous blog, we have presented a framework for categorization of digital learning materials and the specific position of OER. In this blog, we will present two models: a process model for how instructors and students “deal” with digital learning materials and a model for the networks/contexts in which “users” of digital open educational resources operate. Vision and policy for OER will need to take both – the practices of users and the networks in which users operate – into account (Tlili et al, 2020).

A process model for using digital learning resources

In the zone Towards digital (open) educational resources of the Acceleration Plan a process model has been developed in order to get an idea of what the use of digital learning materials looks like in practice.

Their model was adapted to include semi-open and commercial learning resources, as well as the role of the student. The adaptations were made on the basis of observations and experiences in practice of the members of the zone.

The extended process model shows the activities an instructor and a student undertake in order to accomplish their optimal mix of learning resources. “Optimal mix” is defined as the mix of learning resources that, in the eyes of the instructor or student, most effectively supports his or her teaching and learning process that should lead to the achievement of the learning outcomes.

The process model distinguishes two scenarios:

  1. Scenario 1: the reading list. The instructor assembles what he/she considers to be an optimum mix for both the learning process to be supported by the student and for use in his/her educational process. The instructor determines which learning resources are compulsory and which are recommended additionally. The student uses these materials to compile his/her optimal mix. Communication about learning resources between the instructor and the student usually takes place via a list of required and optional learning materials (“the reading list”) compiled by the instructor.
  2. Scenario 2: the instruction. The instructor defines an assignment and usually provides a list of recommended literature (in some institutions also referred to as a reference list). Communication regarding learning resources between the instructor and the student is more diffuse than in scenario 1. Initially, there will be at least one instruction from the instructor to the student that will help guide the optimal mix of learning resources for the student (“the instruction”).

Scenario 1: the reading list

Figure 1 shows the process model for scenario 1.

Figure 1. Creation of optimal mix of learning materials, process model for scenario reading list. Click on the image to enlarge

An instructor will compile a mix of learning resources that best fits the learning outcomes to be achieved and his/her own educational process. That composition is visualised by the dotted shape in the diagram. The instructor searches for learning resources that can be either open or closed. Those resources can already be in his/her possession (in a private database, generally a hard drive), a local database (for example a departmental or institutional repository of learning resources, often a shared network drive), or in the “cloud”. In many cases, an instructor herself/himself will also create learning resources, which also includes mixes and adaptations of learning resources found elsewhere. The mix of learning resources will be subject to a quality control process, which may or may not be explicit. This quality control can also be carried out by people other than the instructor (for example, colleagues). Ultimately, the mix of learning resources will either be published (i.e. made available to students) or used in educational activities. In the latter case, those materials may not be made available to students. For example, a video that is shown in the lecture hall but that is not distributed further. It may also be the case that educational resources used in the educational activity become available to students. These might include copies of the slides that the instructor uses in the educational activity. Publishing the optimum mix of educational resources in any case involves specifying the titles of the educational resources (usually textbooks) that must be studied, whether or not it is compulsory (the reading list).

Experiences with the use of learning materials can be input for a quality check and possibly lead to adjustment of the optimal mix, during or after the course for which the optimal mix is composed. Consider, for example, a situation in which students during an educational activity indicate that they do not possess the prior knowledge that the instructor assumed was present. The instructor can then supplement the optimal mix with learning materials that fill in the knowledge gap. Feedback on the quality by students can also take place via a course evaluation (represented in the figure by the dotted arrow).

Based on the published mix of learning resources (including the reading list), the student will compile his/her own mix of learning resources. While studying or during an educational activity, the student can search for or create additional learning resources and add these to his/her optimal mix of learning resources. Quality control is expected to be implicit and based on the usefulness that the student experiences in achieving the formulated learning objectives. Think, for example, of the experiences the student has when doing exercises to master a certain mathematical concept. When the student is not able to do all the exercises, he or she will look for additional sources to gain knowledge that is apparently not yet present. Such practices are described in more detail in (Schuwer, Baas & De Ruijter, 2021).

A student may decide to publish parts of his or her mix for third parties. For example, making lecture notes available to fellow students in a study association.

Scenario 2: the instruction

Figure 2 shows the process model for scenario 2.

Figure 2 Creation of optimal mix of learning materials, process model for scenario instruction. Click on the image to enlarge

The activities correspond largely to those described in scenario 1. The teacher defines an assignment. If necessary, a list of recommended literature for carrying out the assignment is compiled and, if necessary, the teacher also produces teaching materials. All of this is published and made available to students (the instruction). What was written about quality control on the instructor’s side in scenario 1 also applies in this scenario. Based on the instructions, the student starts compiling his/her optimal mix of learning resources.

In this scenario, students can also publish their own (learning) materials (open or semi-open), both in local storage and in the “cloud”. The student will then also have access to local storage for materials in his/her optimal mix. This situation arises, for example, when students create and publish learning materials as part of their learning process. Such didactic forms of working characterize educational approaches such as Open Pedagogy and Open Educational Practices. Quality control of the materials to be published can be carried out by both the instructor and the student. Conversely, when an instructor and students jointly create and publish educational resources (shown by the green dotted shape in the figure), the student can also be part of the group that carries out a quality check for the instructor.

Not shown in the figure is the situation where learning materials created by a student during his/her learning process are added to the optimal mix by an instructor the next time the course is given.

A model for the networks of users of OER

Sharing and reuse of OER is done by individual instructors and students. Their actions are nevertheless influenced by the networks in which both categories of actors operate, in both a positive and a negative sense (as seen from the perspective of the adoption of OER). Vision and policy regarding OER will therefore also need to address those networks.

In this context, we distinguish two types of networks in which students and instructors function and which affect their views and activities regarding OER. First of all, every instructor and student is associated with at least one higher education institution. In addition, students and instructors work together in all kinds of contexts. When those relationships are institutional or semi-institutional, we refer to them as communities. Temporary collaborations, such as student workgroups that are formed for a course, are not included in our concept of communities.

Communities can exist within institutions, but also across institutions. Instructor communities can be discipline-oriented (for example, the Dutch Community of Practice Bachelor Nursing) or theme-oriented (for example, a community for educational video resources). There are also communities for supporting instructors and students in dealing with OER. Examples include the libraries’ Open Online Education working group or the various Special Interest Groups affiliated with SURF.

The following figure visualises the spheres of instructors, students, institutions and communities. It does not show the situation where an individual student or instructor is associated with more than one institution.

Click on the image to enlarge

In this figure, A, B and C are three institutions. The following situations can be distinguished:

  1. A community exists locally within an institution (1b in institution B or 1c in institution C). Examples: a course team within a department or a cross-faculty partnership of teaching staff in mathematics within one institution.
  2. A community of lecturers from two or more institutions (cross-institution community). In the figure, these are 2ab with institutions A and B and 2ac with institutions A and C respectively.
  3. Situation 3 at institution C shows the situation that instructors can be involved in more than one community.
  4. Community 4 at institution A consists of students. Example: a study association at a faculty.
  5. Community 5 is a cross-institutional community in which both instructors and students participate. An example is the so-called Centres of Expertise, in which students and instructors, but also researchers and entrepreneurs, work together to solve social challenges.

The example of community 5 illustrates that people other than teaching staff and students can also participate in communities. Support staff (educational experts, library staff and ICT experts) will often also be part of such communities.

Why these models?

In developing a vision and policy for the adoption of OER, it is important to focus on how and the context in which instructors and students create and use OER. Hodgkinson-Williams et al (2017:33) refer in this context to three kinds of dependencies:

  • the activity dependency
  • the context dependency
  • the concept dependency (the ideas and images people have).

In this contribution, we have outlined models for the first two types of dependencies: a process model for how instructors and students “deal” with digital learning resources and a concept model for the networks/context in which the “users” of digital open educational resources operate.

All kinds of factors play a role in activities and networks and these factors must also be addressed in an OER vision and policy. Examples include ownership of educational resources created (in part) by students or differing views regarding OER at institutions where instructors participate in a cross-institutional community. In a subsequent blog, we will clarify these and other issues and also formulate points of view from which a vision and policy for OERs can be drawn up.

Acknowledgements

The process model for assembling and using a mix of learning resources is based on an earlier version developed in the Acceleration Plan’s zone Towards Digital (Open) Educational Resources. The participants involved in formulating this model are to be thanked. In alphabetical order by surname, they are: Hans Beldhuis, Vincent de Boer, Cynthia van der Brugge, Michiel de Jong, Wouter Kleijheeg, Gerlien Klein, Gaby Lutgens, Marijn Post, Lieke Rensink, Arjan Schalken, Frederike Vernimmen – de Jong and Nicole Will.

References

Annand, D. (2015). Developing a sustainable financial model in higher education for open educational resources. The International Review of Research in Open and Distributed Learning16(5). https://doi.org/10.19173/irrodl.v16i5.2133

Hodgkinson-Williams, C., Arinto, P. B., Cartmill, T. & King, T. (2017). Factors influencing Open Educational Practices and OER in the Global South: Meta-synthesis of the ROER4D project. In C. Hodgkinson-Williams & P. B. Arinto (Eds.), Adoption and impact of OER in the Global South (pp. 27–67). DOI https://doi.org/10.5281/zenodo.1037088

Schuwer, R., Baas, M. & De Ruijter, A. (2021). De student gaat op zoek: de waarde van (open) leermaterialen voor het eigen leren. In: Baas, M., Jacobi, R., & Schuwer, R. (eds). Thema-uitgave hergebruik van open leermaterialen (pp 17-22). SURF, Nederland. https://communities.surf.nl/files/Artikel/download/Thema-uitgave%20hergebruik%20van%20leermaterialen_2mrt2021.pdf

Tlili, A., Nascimbeni, F., Burgos, D., Zhang, X., Huang, R., & Chang, T. (2020). The evolution of sustainability models for open educational resources: Insights from the literature and experts. Interactive Learning Environments, 1-16. https://doi.org/10.1080/10494820.2020.1839507

Wiley, D. (2007). On the Sustainability of Open Educational Resource Initiatives in Higher Education. Paper commissioned by the OECD’s Centre for Educational Research and Innovation (CERI) for the project on Open Educational Resources. http://www.oecd.org/education/ceri/38645447.pdf


This blog is contribution 3 in a series entitled A principled, pragmatic view of institutional OER policy. Previous contributions:

To be published:

  • Why are OER important? The value of OER from various perspectives
  • The need for a vision and policy regarding OER at both institutional and community of practice level
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