AEA365 | A Tip-a-Day by and for Evaluators

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Hello, my name is Michel Laurendeau, and I am a consultant wishing to share over 40 years of experience in policy development, performance measurement and evaluation of public programs. This is the fifth of seven (7) consecutive AEA365 posts discussing a stepwise approach to integrating performance measurement and evaluation strategies in order to more effectively support results-based management (RBM). In all post discussions, ‘program’ is meant to comprise government policies as well as broader initiatives involving multiple organizations.

This post discusses how the relation of performance measurement to results-based management should be articulated and incorporated into logic models.

Step 5 – Including the Management Cycle

Some logic models try to include management as a program activity leading to corporate results (e.g., ‘financial/operational sustainability’ and ‘protection of organization’) that are presented as program outcomes. Indeed, good management can help improve program delivery and thus contribute to program performance. However, that contribution is indirect and normally achieved through the ongoing oversight and control of program delivery (and the occasional revision of program design) with requisite adjustments to operational or strategic plans being informed by the ongoing measurement (or monitoring) and the periodic assessments of program performance (see Figure 5a).

Results-based management (RBM) then depends on the identification of relevant indicators and the availability of valid and reliable data to correctly inform players/stakeholders and adequately support management reporting and decision-making processes. The quality and use of performance measurement systems for governance is actually one of many elements of Management Accountability Frameworks (MAF) in the Canadian Federal Government, with other elements covering expectations regarding stewardship, policy and program development, risk management, citizen-focused service, accountability and people management. However, MAFs are the object of development and an assessment process that is totally separate from the one used for Performance Measurement Frameworks (PMF) based on delivery process models and/or logic models.

Indeed, the management cycle is relatively independent from actual program operations, with management standing in a relation of authority above program staff to provide oversight and control at each step of the delivery process (see Figure 4b in yesterday’s AEA365 post).

Trying to build the management cycle as a chain of results (or as a part of it) in a logic model is then totally inappropriate as it creates unnecessary confusion between management and program performance issues. Presenting the results of good management as program outcomes also blurs the distinction between efficiency (i.e., the internal capacity to deliver) and effectiveness (i.e., program impacts on target populations). Figure 5b below shows how to properly situate the management cycle in a logic model itself, essentially as an authoritative or facilitative process without direct causal links to specific program results.

This does not mean that management issues should be excluded from PMFs. Relevant indicators of management performance should also be identified for monitoring purposes whenever they are identified by management itself as internal factors or risks that do (or may) influence program delivery.

The next AEA365 post will discuss ways of addressing indicators and actual measures of performance.

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org . aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

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Hello, my name is Michel Laurendeau, and I am a consultant wishing to share over 40 years of experience in policy development, performance measurement and evaluation of public programs. This is the fourth of seven (7) consecutive AEA365 posts discussing a stepwise approach to integrating performance measurement and evaluation strategies in order to more effectively support results-based management (RBM). In all post discussions, ‘program’ is meant to comprise government policies as well as broader initiatives involving multiple organizations.

This post articulates the approach to the development of delivery process models that ventilate the individual activity-output sequences of a logic model in order to allow for the management oversight and control of program implementation.

Step 4 – Including Delivery Processes

Delivery process modelling can easily be accomplished by adapting a computer-assisted Integrated Definition (IDEF) methods developed in the ‘90s by the National Institute of Standards and Technologies (NIST). The IDEF 0 function modelling was initially based on authority links of controls ensuring that activities of multiple players are coordinated and undertaken only when proper authorities have been issued. In the IDEF 0 model, inputs and support mechanisms are used to perform operations and produce outputs through operations or transformation processes that are subjected to management controls and oversight (see Figure 4a). These nodes can be detailed further (by digging into the steps of each function) and/or sequenced to provide an exhaustive view of all program operations.

The delivery process model presented in Figure 4b is an adaptation of the IDEF 0 approach that is achieved by redefining operations and mechanisms as successive sub-activities supported by various players and stakeholders, with distinct products that are delivered at each step of production and that are subject to direct management authority (i.e. oversight and control). The final step is then the one that actually generates the product (or service) that is being identified as the output of a specific activity in the logic model.

In this modelling approach, inputs are not used to define consumed resources (e.g. funds and human resources), but rather to identify the mechanisms and sources of support for program delivery. Further, since delivery is done in a strict stepwise manner, the strong conditionality between sub-activities can actually be redefined as dependencies. The model also makes it possible to take into account internal and external factors/risks that can have an influence on delivery at each step of production.

The above model is essentially a working tool to help analysts validate their understanding of delivery processes. In performance measurement frameworks, the description of the process models can actually be limited to the sequence of operations and their related products in the narrative of each activity of the logic model, with a view to support the identification of indicators for monitoring purposes.

Figure 4b already suggests how to position the management cycle in relation with program delivery processes, and how best to articulate management issues from a program perspective. The next AEA365 post will address these features in greater detail.

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org . aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

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Hello, my name is Michel Laurendeau, and I am a consultant wishing to share over 40 years of experience in policy development, performance measurement and evaluation of public programs. This is the third of seven (7) consecutive AEA365 posts discussing a stepwise approach to integrating performance measurement and evaluation strategies in order to more effectively support results-based management (RBM). In all post discussions, ‘program’ is meant to comprise government policies as well as broader initiatives involving multiple organizations.

This post articulates how logic models should be structured when program designs include multiple strategic elements (or program activities) supporting a common objective.

Step 3 – Addressing Conditionality

Program interventions rarely rely on a single product or service to achieve intended results. In fact, program strategies are most often designed using multiple interventions from one or more players. In these situations, there normally exists some conditionality between separate program activities as they support and interact with each other. Addressed this way, the notion of conditions (also used in the TOC literature) allows structuring logic models by properly sequencing the multiple program interventions (i.e. converging results chains) deemed to contribute to a common final result that is specific to the program.

To an outside observer being exposed to multiple interventions, program activities may appear to be delivered in a sequential manner (from left to right) based on some observable results (e.g., outputs or immediate outcomes) until some final outcome is achieved (see Figure 3a). This would be the case of a person arriving at a hospital emergency or an employment centre and being subjected to a series of treatments or services.

However, from a program perspective, all activities are actually implemented in parallel with different clients and/or players. In the examples of the hospital emergency and the employment centre, it is the clients who are moving from left to right across activities as they are exposed to various program services. In programs that reach clients only indirectly (e.g., environmental programs or economic policies), it is rather the projects or client files that are shifting across activities while being processed and/or subjected to various program interventions.

Conditionality then allows taking into account the relationships between the strategic elements (or activities) of program interventions without the need to clutter the logic model with an exhaustive mapping and display of all possible interactions and feedback processes. Implicitly, all program activities are (or may be) influenced to some extent by previous activities situated at the left of the diagram (see Figure 3b). Thus, when conditionality exists and is properly taken into consideration, the positioning of program activities in the logic model becomes important for the description and understanding of the program theory of intervention (PTI).

The next AEA365 post will dwell further into program implementation and discuss how to best integrate delivery processes into logic models in order to effectively support management oversight and control.

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org . aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

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Hello, my name is Michel Laurendeau, and I am a consultant wishing to share over 40 years of experience in policy development, performance measurement and evaluation of public programs. This is the second of seven (7) consecutive AEA365 posts discussing a stepwise approach to integrating performance measurement and evaluation strategies in order to more effectively support results-based management (RBM). In all post discussions, ‘program’ is meant to comprise government policies as well as broader initiatives involving multiple organizations.

This post presents the approach to the development of result chains and their integration within a Theory of Change (TOC) from a program perspective.

Step 2 – Developing the Program Theory of Intervention (PTI)

Program interventions are best modeled using chains of results with a program delivery (activity – output) sequence followed by an outcome sequence linking outputs to the program’s intended result (final outcome). Most models use only two levels of outcomes, although some authors advocate using as many as five. However, three levels of outcomes would seem to be optimal as it allows properly linking chains of results to broader TOCs, with the link being made through factors (immediate outcomes) that influence behaviors (intermediate outcomes) in target populations, in order to resolve the specific societal issue (final outcome) that has given rise to the program (see Figure 2a).

 

In chains of results, outputs are the products delivered by the program (as well as services, through a push-pull approach) that reach target populations, marking the transition between the sequence controlled by the program (i.e. program control zone) and the sequence controlled by recipients (i.e., influence zone of the program).

Logic models developed using this approach help clarify how the program intervention is assumed to achieve its intended results (i.e., the nested program theory of intervention) under the conditions defined in the broader TOC (see Figure 2b).

Developed this way, logic models do resolve a number of issues:

  • The models provide a clear depiction of the chains of results and of the underlying working assumptions or hypotheses (i.e. salient causal links) of the program interventions and of their contribution to a common final result that is specific to the program;
  • The models provide the basis to identify comprehensive sets of indicators supporting ongoing performance measurement (i.e. monitoring) and periodic evaluations, from which a subset can be selected for reporting purposes;
  • Indicators can also cover external factor/risks that have (or may have) an ongoing influence on program results and that should be considered (i.e. included as control variables) in analyses to obtain more reliable assessments of program effectiveness.

However, developing a logic model that is a valid representation of program theories of interventions is easier said than done. The next AEA365 post will offer some suggestions for achieving that goal. Further, since logic models focus heavily on program outcomes, they provide very little information on delivery processes in support of management oversight and control. Subsequent posts will be discussing how program delivery can be meaningfully addressed and properly integrated in program theories of intervention.

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org . aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

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AEA365 Curator note: Today begins a special theme week with an extended (7 day) series on one topic by one contributing author. 

Hello, my name is Michel Laurendeau, and I am a consultant wishing to share over 40 years of experience in policy development, performance measurement and evaluation of public programs. This is the first of seven (7) consecutive AEA365 posts discussing a stepwise approach to integrating performance measurement and evaluation strategies in order to more effectively support results-based management (RBM). In all post discussions, ‘program’ is meant to comprise government policies and broader initiatives involving multiple organizations.

Step 1 of 7 – Developing the Theory of Change (TOC)

Effectively addressing an issue normally requires first understanding what you are dealing with. Models are generally used in evaluation to help clarify how program are meant to work and achieve intended results. However, much confusion exists between alternative approaches to modelling, each based on different ways of representing programs and the multiple underlying assumptions on which their interventions are based.

Top-down models, such as the one presented in Figure 1a, usually provide a narrow management perspective relying on inductive logic in order to select the evidence (based on existing knowledge and/or beliefs) that is necessary to support ex ante the strategic and operational planning of program interventions. Assumptions are then entirely about whether the program created necessary and/or sufficient conditions (as discussed in the TOC literature) for achieving intended results. In this context, the role of ex post evaluation is too often limited to focusing on program delivery and vindicating management’s contention that observed results depend to some (usually unknown) extent on existing program interventions.

As a research function, evaluation should also support (re)allocation decisions being made by senior government officials regarding the actual funding of public programs. However, this stronger evaluation role would involve reliably assessing individual program contributions to observed results in a given context, and require properly measuring real/actual program impacts while taking external factors into account.

The first difficulty in achieving this task is recognizing that Randomized Control Trials (RCT) are rarely able to completely eliminate the influence of all external factors, and that the statistical ‘black box’ approach it uses prevents reliably transposing (i.e., forecasting by extrapolating) observed results to situations with varying circumstances. Generalization is then limited to a narrow set of conditions formulated as broad assumptions about the context in which the program operates. Providing a more extensive base to reliably measure program effectiveness would entail, in a first step:

  1. developing more exhaustive Theories of Change (TOC) including all factors that created the need for program interventions and/or that likely have an influence on the issue or situation being addressed by the program; and,
  2. determining which factors/risks within the TOC are meant to be explicitly ‘managed’ by the program, with all others becoming external to the program intervention.

Figure 1b shows what a program logic model would normally look like at the end of this first step.

The next AEA365 post will articulate the approach to the development of the more detailed Program Theory of Intervention (PTI) that is imbedded within the broader TOC.

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org . aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

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Season’s Greetings and Happy Holidays loyal AEA365 readers! I’m Sheila B Robinson, Lead Curator and sometimes Saturday contributor with a few tips and tools for blogging in 2018. First off, content is king with blogging. Always. There’s no other rule as important as composing well-written, well-conceived content that is relevant and relatable to your audience.

Hot Tips: Here are a few up-to-date tips from 10 New Rules for Blogging Towards 2018, where author Yvette McKenzie advises:

1.) Long form is gaining traction.

…“longer reads” or long form content has been gaining traction for several years now. According to Kissmetrics, “Long-form content gets you more online visibility (social shares, links), more proof of your authority and industry expertise, and more material for altruistic community building and engagement.” It might not suit every type of post but long form content should be included as part of your broader blogging and content strategy.

2.) Consider a vlog or podcast.

…not everyone engages with blocks of text as a preferred medium. Many people prefer on-the-go content, including visuals like infographics, audio-only mediums such as podcasts or easily consumable videos. Generally speaking, a solid mix of these elements might gain you the best traction but knowing your audience and how they best engage should be what guides your strategy.

3.) Your audience always comes first.

…knowing your audience/s will always be crucial to your success. Blogs can be a great way to start a conversation, engage with an audience and to state your authority and expertise on a subject. Consider your audience first and try to “solve their problems” by providing the answers they are seeking. Putting your audience first will always be the cornerstone to successful blogging, so make audience data tracking something you incorporate often into your content strategy.

Next up, author Jasmine Demeester, in Blogging Trends 2018-2019 : Latest Blogging Trends agrees with using longform posts and video, and also offers this:

Cool Trick: Images, Graphics, Illustrations – – Creativeness still Ruling Blogging Trends 2018

Since readers now have a wide range of options, a blog would need much more beauty in 2018. By this, we mean that bloggers would have to spiffy up their platforms with beautiful illustrations, images, and anything that could immediately pull in a visitor…Flat designs like these are also more easily downloadable and integrated with any kind of content you have. Plus, they are immediately viewable by any first-time visitor. 

Don’t forget to check out AEA’s page of bloggers and tweeters!

Wishing all of you a happy, healthy 2018!

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on theaea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org . aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

Hello! We are Justin Sullivan, Libby Smith, and Kate Bentley from the Applied Research Center at the University of Wisconsin-Stout. When we attended Evaluation 2017, the AEA annual conference this year we knew we wanted to use the opportunity to get more active on Twitter. I (Libby) had avidly followed the conference hashtags in past years, but hadn’t jumped on the tweeting bandwagon. I knew that there was a growing community of evaluators on Twitter and we all wanted to be more connected to our peers and our field. With the help of our designer and social media manager, Kate Bentley, we devised a plan and dove in during the conference. We tweeted and followed others throughout the week. When we got back, we did what evaluators do…we pulled the data, analyzed it, and reported out!  Here is our infographic and some hot tips:

Click for larger image

Hot Tips:

  • You can scrape data from Twitter using R to analyze trends. This approach allows you to customize your search to focus on hashtags (#Eval17) or specific Twitter users. The resulting data set will include tweets, user names, and like and retweet data. You can also pull data to create a snapshot of what’s happening now or track trends over time.
  • Here is a step-by-step guide on how to connect R to Twitter to pull data. This guide is designed for first time R users. Learning how to code in R can be daunting; it comes with a steep learning curve. This guide includes a graphical user interface and code that you can simply copy and paste into R to get things going quickly. After working your way through this exercise, you will have a basic R skillset you can use to try other things.
  • When creating an infographic, it’s best to start by choosing a color palette using 4-6 colors. Choose colors that are complementary (think opposite sides of the color wheel) and suitable to your project. If you are working with an organization, use the palette they use for their branding.
  • The Noun Project has arguably the best icons on the web. You can search from over a million icons from thousands of authors. Licenses are available under Creative Commons, and there is both a free and paid version. These are high quality icons that will make your project stand out. Your icons should match the data you are presenting in content and context. Download a few icons and start thinking about how you plan to layout your content.
  • Use PowerPoint to start making infographics. It’s a simple interface with useful tools to move things around. Be sure to choose a catchy title, infuse a bit of variation in the size and scale of your icons, and try not to have too many repeating graph selections.

Thanks for reading and we look forward to seeing you at #Eval18!! You can find us on Twitter @arcevaluation and online at ARCevaluation.com.

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org . aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

We are Kelly Robertson and Lori Wingate, and we work at The Evaluation Center at Western Michigan University and EvaluATE, the National Science Foundation-funded evaluation resource center for Advanced Technological Education (ATE).

Rad Resource:

We’re excited to announce our new rad resource, the “Checklist of Program Evaluation Report Content.” We created this checklist to address a need for practical guidance about what should go in a traditional evaluation report—the most common means of communicating evaluation results. The checklist is strictly focused on the content of long-form technical evaluation reports (hence, the name). We see the checklist as complementary to the exciting work being done by others to promote the use of evaluation through alternative ways of organizing, formatting, and presenting data in evaluation reports. If you want guidance on how to make your great content look good, check out the new Evaluation Report Guidance by the Ewing Marion Kauffman Foundation and Evergreen Data.

How is our checklist on reporting different from others you may have come across?

  • It not only lists key elements of evaluation reports, but it also defines these elements and explains why they are relevant to an evaluation report.
  • Its focus is not on judging the quality of a report. Rather, our checklist is intended to support practitioners in making informed decisions about what should be included in an evaluation report.
  • It’s not tailored to a specific type of program or evaluand and is presented as a flexible guide rather than rigid specifications.

We hope multiple audiences find the checklist useful. For example, new evaluators may use it to guide them through the report writing process. More experienced evaluators may reference it to verify they did not overlook important content. Evaluators and their clients could use it to frame conversations about what should be included in a report.

Lesson Learned:

It takes a village to raise a great checklist. We received feedback from five evaluation experts, 13 of our peers at Western Michigan University, and 23 practitioners (all experts in their own right!). Their review and field testing were invaluable, and we are so grateful to everyone who provided input—and they’re all credited in the checklist.

Like checklists? See the WMU Evaluation Center’s Evaluation Checklists Project for more.

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org . aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

Dec/17

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Color Scripting by Wendy L. Tackett

I’m Wendy Tackett, the president of iEval, sometimes faculty member at Western Michigan University, and lifelong Disney fan!

Lessons Learned: You never know where you’re going to run into inspiration for your evaluation work, so keep your eyes, ears, and mind open. In 2015, I went to the D23 Expo in Anaheim, California. I went purely for myself, since I love Disney everything, and I never dreamed I would learn something that could be applicable to my evaluation practice.

In a session with the Pixar team, I learned about a technique created by Ralph Eggleston called color scripting. Color scripting is a type of story boarding, but Ralph would change the main colors of each panel to reflect the emotion the animated film was supposed to portray at that time. It helped the Pixar team understand what was going on in the film emotionally, and it also made it easier to create a musical score to enhance those emotions.

A few days later, I was taking notes on the engagement and enthusiasm of a large audience. I created some metrics on the spot including number of people on their mobile devices, number of people leaving the event, murmuring, applause, etc. Then inspiration hit me, and I used the color scripting idea to create a timeline of the event, highlighting who was presenting at different times, and coloring the data. The client felt it was an extremely useful overview of how the audience related to the event and the discussion that ensued really helped them figure out how to change the event for the next time.

Since then, my adaptation of color scripting has evolved, and my team has used it on different projects including professional development training, farmer’s markets, nutrition lessons, etc. Recently, we asked K-6th grade students what they learned at the end of each nutrition lesson, then analyzed the data by lesson topic, grade levels, and topic order. These graphs resulted in thoughtful conversations with the nutrition educators about what students think, the impact of specific lessons, and the progression of lessons. The color scripting graphs visually indicated the percentage of students expressing changes in knowledge (blues, the darker the blue – the more substantial the knowledge) or behavior (greens, the darker the green – the more substantial the behavior).

Hot Tip: When you learn (or create!) a new technique, try applying it in different contexts to 1) practice using it, 2) identify where it’s most meaningful in analyzing data, and 3) determine various ways clients will be able to use it.

Rad Resource: If you missed my presentation at AEA 2017 on Color Scripting and would like to download it, you can grab it and other presentations at iEval’s web site. In the presentation, there are detailed examples of how you can use Color Scripting. You can also grab the step-by-step directions on how to do Color Scripting!

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org . aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

No tags

Isidro Maya Jariego

I’m Isidro Maya Jariego, Associate Professor, Social Psychology Department of the Universidad de Sevilla (Spain). I’m participating in a project to promote the adoption of open educational resources (OER) and open educational practices (OEP) for improving the quality of education of universities in Egypt, Jordan, Morocco and Palestine. OpenMed is an international cooperation project co-funded by the Erasmus+ Capacity Building in Higher Education programme of the European Union.

Throughout project implementation, we observed that higher education institutions in the Middle East and North Africa (MENA) region face problems of massification, and occasionally cover large areas or rural extents of difficult accessibility. Massive Online Open Courses (MOOCs) and digital media allow facing these types of difficulties; at the same time, they offer opportunities for educational innovation.

This allowed us to observe the adjustment and incorporation of the project into four different national contexts.

Lessons Learned:

The degree of internationalization of the university is a good indicator of readiness to adopt OER and OEP. Universities that are bicultural, use a second language in teaching, have bilateral agreements with other universities outside the country, have a culturally diverse teaching staff or receive and send students in academic exchanges, tend to be more receptive to the incorporation of open educational resources.

During implementation of the OpenMed project we realized that participating universities and teachers were characterized by having a more international character than other local universities and teachers. Internationalization indirectly reports about readiness to adopt OER. It seems to be a self-reinforcing process: international experiences predispose for the incorporation of OEP and the incorporation of OEP contributes to the university’s internationalization.

https://www.researchgate.net/publication/320024153_Localising_Open_Educational_Resources_and_Massive_Open_Online_Courses

Hot Tip: Focus on organizational dynamics and local relevance. In southern Mediterranean countries there is usually a greater distance to the authority of the teacher, and the cohesion and harmony of the group have greater weight than the individual interests, in comparison with Europe and North America. However, beyond these cultural peculiarities, we have learned that organizational factors are key. Institutional constraints in each university (e.g, textbook use policies and incentives) are determinants of the likelihood of content reuse. On the other hand, in the reuse of content it is also opportune to incorporate locally relevant examples connected to local needs.

Hot Tip: Prevent exclusion of more local universities. Local universities that are less internationally connected, run the risk of being excluded from the processes of educational innovation and the incorporation of open education practices. These are universities somewhat disconnected from the elite of higher education institutions in the country. It is a high-risk group in terms of accessibility to quality education, which requires specific actions.

Rad Resources:

The OpenMed project has produced useful resources for planning to implement or evaluate a MENA region program:

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org . aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

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