Open Recognition, Badges, and Microcredentials

Introduction: Why Learning Recognition Matters

Humans are continually learning. Every second, our senses take in 11 million bits of information (NPR, 2020). We naturally, and often unconsciously, use that information to reshape mental schemas, emotional frames, and behavioral patterns. We are constantly learning and growing, irrespective of and largely uncontrolled by any external system or instructional design.

Despite always learning, our learning often must be recognized in order to be useful in our lives. It is recognized by an employer when they believe us to be qualified for a particular job or promotion, or by a school admissions board when they judge that we have learned enough to qualify for higher education. There are also important informal recognitions of learning, such as when a peer recognizes our ability in a particular area and asks for our assistance, or when we recognize our own abilities and shortfalls and make decisions about what to focus on learning next. These informal recognitions motivate and inspire learners in interesting ways. Much of the field of instructional design relies on recognition of learning as part of analyzing learner needs, gaps in knowledge, objectives that should be learned, and the sequencing of learning that might be most helpful.

While most efforts to reform or improve education focus on improving educational content or the important relational communities that support learning (see West, 2023), it is equally important to consider the recognition that is part of any educational system. Similarly, in attempting to make education more open, we need to consider open recognition equally to open content and open pedagogies.

Learning has typically been recognized only in formal ways with grades, degrees, and certificates, and this often presents challenges in fully recognizing students’ learning. Consider the following hypothetical examples:

• Victoria, a brilliant student, completes 80% of her degree, but because of family health challenges requiring her assistance, she drops out of college. After many years and despite all that she has learned and the skills she has gained, she has no degree and no effective way to communicate to others what skills she has. Her years of learning are largely wasted, and she resigns herself to not being able to work in her chosen career.
• Maria, like 65,000 other computer science majors graduating each year in the United States, understands programming languages. However, she also has highly effective relational and communication skills. Her degree in computer science does not describe these important skills and her potential abilities as a bridge builder between programmers and other people within an organization.
• Robert had a personal interest in technical communication while earning his English-literature degree and sought out courses and internships in this area, developing skills in technical writing, graphic design, and media technologies. However, he did not formally earn a minor in technical writing, and thus his English degree does not communicate how Robert’s skillset is different from that of a typical English major.
• Vikram speaks a second language and lived abroad for several years. He continues to study this language through MOOCs (Massive Open Online Courses), language apps, and community meetups. He has received some digital certificates from these various places, but they do not transfer to his university. Consequently, they do not show up on his official learning record, and he is not allowed into advanced language courses. In addition, employers do not understand how he can actually use his language skills in a job.
• Ashanti learned several new technologies at the university, so she volunteered to lead a technology initiative at her school, where she teaches chemistry. However, her degree in secondary education does not explain what her technology skills are, and her principal would like some proof of her ability. She contacts her former professors, but they cannot remember what level of skill she had. She remembers that her professors complimented her on her work, but that positive feedback was never captured in a credential that she could keep and share with others. She can ask one of her professors to write a letter of recommendation, but it will be vague because he cannot remember her performance from several years ago.

These examples showcase several of many possible ways that the current educational credentialing system fails to communicate what students actually know and how they are each a unique person with distinctive abilities. Recently, though, technological innovations such as Open Badges, Verifiable Credentials, and Comprehensive Learner Records (West and Cheng, 2022) have opened the door to intriguing possibilities in this area. These digital credentials are similar technologies striving to accomplish the goal of greater transparency and better recognition of all learning a student achieves.

These alternative, digital credentials are novel in that they embed evidence of the actual learning in the credential itself. They can also represent learning of different types and scope. Some of these alternative credential options include microcredentials, Open Badges, nanocredentials, and nanodegrees. What these credentials have in common, though, is that they are different from traditional credentials because they are:

• data rich, embedding actual evidence of the learning permanently into the credential;
• based on open technology standards, allowing the credentials to be shared and exported/imported into different systems;
• micro, representing learning that is smaller than a degree or certificate program;
• flexible, representing learning from both formal (e.g., classes) and informal (e.g., self-learning, workshops) situations.

Despite these innovative new technologies, much of the discourse around these credentials has been uninspiring, as it has focused on how to use new tools to reinvent old systems. For example, it is popular to issue microcredentials for completed courses—which continues to only recognize learning as “valid” if completed at a university. New thinking is needed to consider how to use these internet technologies to more fully democratize education in society, recognizing learning from inside and outside formal schools and painting more complete and equitable pictures of everything a student has learned.

In this chapter, I first review the important role that credentials play in society, and I review some of these technological innovations that have emerged in this space in the past decade. I then discuss what research has found about when and how these technologies are helpful. In discussing all of this, I rely on a 3M (West and Cheng, 2022; adapted from Zawacki-Richter, 2009) model of how educational credential systems interface at micro (learner/personal), meso (institutional), and macro (societal) levels.

The Important Role of Credentials in Society

Educational institutions exist in society to meet various important needs, including preparing capable workers for society, resolving inequities, unifying a diverse population, preparing educated citizens who can more fully engage in our democracy, and helping individuals achieve their potential for self-actualization and fulfillment (see Feinberg and Soltis, 2004; Kober, 2007). In addition, schools exist for the blunt reason of producing degrees and other certifications—what Gallagher (2016) called “the foundation of the business model for most higher education institutions” (p. 3). In creating these credentials, schools meet a critical communication need by signaling to society about a particular student and their potential for various roles in society.

Besides signaling to employers about learners, there are two additional groups that educational credentials communicate to. First, they communicate to educators what kinds of teaching they should do. For example, if the credential represents an accumulation of knowledge, then instructors will likely teach through lecture as an efficient method of delivering information (Taglieri et al., 2017). If the credential represents the acquisition of skill, then using experiential learning strategies will more effectively develop these skills (Franco Valdez and Valdez Cervantes, 2018). Meanwhile, if the credential represents social skills, team-based learning and collaborative learning approaches will be used (Haberyan, 2007).

In addition, if the credential is designed based on an industrial model of sorting students into those who have “it” and those who do not, then this design communicates to teachers that their teaching should be a form of sorting. This leads teaching to become less focused on growth and equity and more focused on comparisons. It also discourages mastery grading or a “growth mindset” (Dweck, 2016) and relies instead on one-snapshot-in-time assessment. Finally, it creates artificial deadlines for learning, requiring students to learn within a set schedule, regardless of their personal situations or motivations. This disadvantages not only students who need more time to learn but also those who need less. Either way, students fall out of the “flow” of learning (Csikszentmihalyi, 1990) where learning is enjoyable and see learning instead as a chore.

In addition to communicating to employers and teachers, credentials also communicate to students about what they know, what matters, and who they are. In the previous example, traditional approaches to grading communicate to students whether they are “gifted,” “average,” or “struggling.” These perceptions powerfully affect them.

For these reasons, credentials are core to educational reform and even societal reform; as Gallagher (2016) explained, “Evolving the credential ecosystem is key to optimizing higher education” (p. 20).

Traditional Recognition of Learning

Traditionally, the emphasis in learning recognition has been top-down. In this approach, an institution is trusted to appropriately recognize whether and what a student has learned, and certify this learning. This recognition of learning appears in the form of grades, progress reports, competency dashboards, certificates, and degrees. However, this form of learning recognition is flawed for several reasons:

1. Lack of Equity — A top-down system breeds inequity as the power within society, as it relates to education, is controlled by few hands—in this case, usually universities. As all institutions can exhibit bias, this has the potential to exacerbate a lack of equity within society.
2. Lack of Access — When recognition of learning is controlled by a small segment within society, access to the benefits of learning recognition is then limited. Even though humans are constantly learning, only those who can get their learning recognized by the correct institution will be able to benefit from their learning.
3. Lack of Openness — Openness, as related to educational content, has been defined as the ability to reuse, retain, revise, remix, and redistribute (Wiley, 2015). Learning recognition can similarly be considered open only when a learner can retain their own learning data/credentials, reuse them for their own purposes, revise and remix them to better represent their own abilities, and redistribute them. This openness requires new technologies that take control of the recognition of learning away from institutions and instead share it equally with formal/informal learning institutions, as well as learners and communities.

Open Recognition: A New Standard

In 2012, the Mozilla Foundation released the Open Badges standard as a new potential technology to recognize learning wherever it happens. Since then, other technologies have also been created to similarly afford open recognition, including Blockcerts, Verifiable Credentials, and Comprehensive Learner Records. These technologies provide a similar potential, and are in many ways interoperable as they use open technical standards to make share data easy (for example, standards for Open Badges [https://openbadges.org/], Verifiable Credentials [https://www.w3.org/TR/vc-data-model/], and Comprehensive Learner Records [http://www.imsglobal.org/about/clr]). All of these technologies make it possible for anyone to recognize the learning of another, or even for a learner to recognize their own learning and codify it in a marker or credential that describes their ability.

While these technologies share many similarities in how they handle learner data, the practices surrounding how these technologies are used are very different and can vary widely from informal and even self-issued badges to formal microcredentials based on competency frameworks. Because of this, nomenclature becomes important: communities using these technologies for official, top-down credentials awarded by large institutions (e.g. universities, employers, and national organizations) typically refer to these as open microcredentials or certificates. Meanwhile, communities using these technologies for informal/non-formal learning, community-based recognition, or self-claiming recognition call these awards open badges or open recognition. The term open recognition appears to have emerged in the Bologna Open Recognition Declaration (2016) and later referenced in a document produced by the Joined Research Centre of the European Commission.

Later, Open Recognition was described as “a movement born from the practice of Open Badges, exploring and promoting practices, tools and policies enhancing and broadening the opportunities for everybody, individuals and communities to be recognised and contribute to the recognition of others.” (Mirva, 2020, see also http://www.openrecognition.org/bord/). While a fairly recent movement, it hearkens back to how learning was recognized within non-formalized learning communities. As Belshaw and Hilliger (2023) explained, “Open Recognition is similar to  “peer-to-peer validation and communal acknowledgement of skills and achievements, similar to how guilds or apprenticeships operated in the past” (para. 14).

A Unifying Open Recognition Standard

Proponents of open recognition see the movement as inclusive of open microcredentialing, certificates, and other top-down practices (see Figure 1). Simply, Open Recognition is the recognition of all learning, by any learner, acquired anywhere, at any time. This includes formal learning in school or through an employer-based system, non-formal (but intentional) learning such as MOOCs and other internet courses or community classes/lessons, or informal learning that arises unintentionally through daily activities (Council of Europe, 2023).

Figure 1.

Open recognition includes, but also extends, concepts like open badges and open credentials.

Image CC BY-ND Bryan Mathers

Thus, while there is overlap between the practice of microcredentials and open badges, they are also often used to mean different kinds of educational practices. However, they are all part of an Open Recognition framework that provides a method and technology for recognizing all types of learning. Figure 2 by the We Are Open Co-op visually depicts how these various types of learning recognition are related to each other on a spectrum from formal learning to informal learning, and from traditional/institutional-based recognition to non-traditional/community-based recognition.

Figure 2.

A depiction of how various types of credentials and badges are related to each other and represent options for formal, informal, and non-formal learning recognition, as well as recognition in traditional and non-traditional ways.

Or perhaps more simply put, open credentials may represent the award given at the end of an educational journey that is valued by outside entities, but open recognition also represents the very real recognition of performance that arises within communities and relationships (see Figure 3).

Image CC BY-ND Bryan Mathers

Open recognition provides an exciting pairing of technologies and practices “that could potentially disrupt the educational status quo” (Belshaw & Hilliger, 2023, para. 8) in a future where “universities and other institutions still play a role, but they are no longer the sole arbiters of who is ‘skilled’ and who is not. They are nodes in a broad ecosystem of learning and recognition that includes employers, co-ops, communities, and self-directed learners” (Belshaw & Hilliger, 2023, para. 2).

For instructional designers, policymakers, and instructors, it is important to acknowledge the nuanced differences in how we can recognize learning in order to make wise decisions about what type of recognition or credential we believe to be most important in a given setting. Whether awarding microcredentials in a formal educational setting, or open badges in an informal, community-based experience, all learning deserves to be recognized for the value it brings to individuals, families, and communities.

How Effective Are These Alternative, Open Credentials?

Our understanding remains limited as to how effective these various credentials are for supporting student learning, communicating learner ability, and supporting the vital roles of education within society. This limitation is largely because these credentials are still a recent innovation and also because full integration into educational systems is difficult, as it requires changing teaching strategies, data-management systems, and learner expectations.

Still, research has identified a few key findings (see West and Cheng, 2022 for a full review). For example, it appears that open micro/nanocredentials are helpful for motivating students, but often more for extrinsically motivated students than intrinsically motivated ones. They also can support improved learning when paired with appropriate pedagogies (such as personalized learning) or as part of encouraging student self-regulation of learning. For example, learners in a college chemical-laboratory course (N=559) mentioned that digital badges allowed them to receive personalized feedback. In this case, via the Passport badging platform developed by Purdue University, graders and teaching assistants wrote personalized feedback to students after the latter had submitted their work, and students could resubmit their work multiple times after incorporating feedback (Santos-Díaz et al., 2019).

However, despite these benefits, many challenges remain in integrating micro/nanocredentials into education, including how institutions should incorporate these alternative and open credentials into their digital/data systems, what the credentials should represent to groups within society, and how to develop rigor and trust in the credentials.

Despite these challenges, we do know that the usage of these credentials is growing rapidly. For example, it was estimated that from 2011 to 2018, between 15 and 24 million Open Badges had been issued (IMS Global, 2022; Mozilla, 2018), a number that grew to 43 million by 2020 (Abel and Surman, 2021).

This growth has led some organizations to believe that education and learning have been irrevocably disrupted. For example, the Education Design Lab, an early innovator in this space, reported that “within the decade, all but the most exclusive learning providers, old and new, will compete for students at the competency and experience level rather than at the degree level. That is the principal paradigm shift of the Learner Revolution” (deLaski and Lifland, 2020).

Others see this change as more complementary than revolutionary. As Gallagher (2019) argued, “Rather than sweeping away degrees, new types of online credentials—various certificates, MicroMasters, badges, and the like—are instead playing a complementary role, creating the building blocks for newer, more affordable degree programs” (para. 9). Regardless, this predicts a new role for credentials in 21st-century society, as we will transition to requiring greater transparency, better data on actual learning, and stronger communication of who learners and employees are and what they are capable of doing.

Integrating Micro/Nanocredentials at the Micro, Meso, and Macro Levels of Society

In order for these new, alternative credentials to achieve their potential, we need to rethink educational policy, systems, and strategies to better incorporate micro/nanocredentials. A useful framework for considering these systemic changes is the 3M model (West and Cheng, 2022, modified from Zawacki-Richter, 2009). In this model, shown in Figure 1, the authors propose considering educational innovations and their interface with society at the micro level, or at the level of individual students and faculty; at the meso level, where institutions such as universities and colleges reside; and at the macro level, which is the societal level.

Figure 1. 3M Model for Considering the Impacts of Open Credentials within Three Levels of Society

Improving Implementation at Micro Levels

At the most micro level of learning is the dyad of instructor and student. To improve implementation at this level, we need continued development of usable technologies to issue and receive micro/nanocredentials, greater training about what they are and what they represent, and scaffolding for users. First, while open data standards provide the promise of easily transferring credentials from one system to another, the process is still not as simple as it needs to be for mass adoption. Learners need simple systems that track their performance across systems and automatically collect their credentials.

Finally, we need to also support teachers and credential issuers in knowing how to teach with micro/nanocredentials. This may require universities to relinquish some control over the teaching at their institution to allow for the flexible nature of microcredentials. We will not see the benefit, however, until teachers have developed skills in teaching strategies to match these credentials, including how to maintain the experiential and social nature of learning in this process.

In summary, recommendations for improving microcredential implementation at the micro level could include the following:

• Create simple systems for collecting learners’ data across their varied learning experiences.
• Establish laws and safety systems for ensuring learners control their own data and when the data can be used as part of their learner profile.
• Teach learners how to use their data to craft their own professional profile and learning story.
• Support teachers in redesigning education to utilize these microcredentials.

Improving Implementation at Meso Levels

Gamrat and Bixler (2019) articulated four internal challenges that meso systems often face in developing open-badging systems: (a) the wide variety in how badges are designed; (b) the need for good assessment for open badges, and the reality that open badges are often trying to assess things that traditionally are difficult to evaluate (e.g., soft/career skills); (c) the complexity in designing badging systems visually and internally; and (d) the challenge of communicating the value proposition of the badges to others.

Addressing the first challenge is tricky, as school systems are typically designed to be very standardized. This has led to criticisms that campus micro/nanocredentials are overly standardized and represent a misunderstanding of micro/nanocredentials as tools for capturing a wide variety of experiences and learning. In addition, often the most meaningful learning experiences were not predicted ahead of time and could not have been predesigned. However, they are still meaningful and should be represented in a learner’s profile and verified by those who witnessed them (e.g., an instructor, supervisor, or peer).

If we are not careful, the effort to formalize all micro/nanocredentials could lead to a reification and replication of current educational processes—for example, replicating course grades as microcredentials, and minors as certificates—instead of allowing for true innovation where micro/nanocredentials could capture unexpected, but still meaningful, learning.

One potential solution may be for educational institutions to create systems for validated/predesigned credentials as well as systems for unplanned/unvalidated/informal credentials. For example, a university may decide to create university credentials that match their university’s mission, perhaps in areas such as service learning, multicultural awareness, citizenship, leadership, and collaboration. Simultaneously they could enable teachers, supervisors, and perhaps even peers to create university-branded (similar to official letterhead) community badges that act as signed, data-rich testimonials of what a person has been able to do. These could be created immediately, as needed, and issued on a case-by-case basis or even “claimed” by the learner themself before being validated by someone else. This kind of model would enable instructors to creatively develop new strategies for implementing micro/nanocredentials into their teaching.

Luckily, some instructional-design researchers have articulated processes to guide organizations in creating micro/nanocredentials. Stefaniak and Carey (2019) studied digital-badge programs at three different higher education institutions, and in addition to exploring their adoption patterns and successes, they developed a framework for successful badge-program implementation that provided insights into how to design the badges, how to choose/implement the platform, and how to implement the program once designed.

Also, Clements et al. (2020) wrote a referendum on how to “get started with open badges and open microcredentials” where they provide examples of various types of badges and badging systems, defined the sometimes-tricky and sometimes-technical vocabulary of open-badging systems, and articulated a process that new designers can use where you first design the system, then design the badges, then publish and implement the system, and finally work on marketing and communicating value.

Finally, the open recognition community has created an Open Recognition Toolkit that easily (and visually) guides learners, teachers, and designers through the process of creating open recognition systems. For more information, go to https://badge.wiki/wiki/Open_Recognition_Toolkit.

In summary, recommendations for improving microcredential implementation at the micro level could include the following:

• Create systems for validated/predesigned credentials as well as systems for unplanned/unvalidated/informal credentials, allowing for both types and communicating clearly to others which credentials were authorized by the university.
• Create institution-branded community badges that act as signed, data-rich testimonials by someone of what a person has been able to do, but without the need to be fully validated by the university.
• Develop assessments, rubrics, and guides within a university to help instructors and other credential issuers.
• Create design guides for practitioners that address why, who, and how to implement microcredentials effectively.

Improving Implementation at Macro Levels

Despite examples of many effective micro/nanocredential programs, projects, and courses, it remains a challenge to adopt this technology on a large-enough scale to transform educational systems within society. According to a review of 30 badge ecosystems, three competency-based digital-badge systems that received large funds from the Gates Foundation’s Project Mastery initiative all encountered technology, validity, and personnel challenges, resulting in two systems being suspended after pilot implementations and one being never implemented. None of the other competency-based systems thrived in the long-term (Hickey and Chartrand, 2020). Restricted financial support remains another challenge. Scholarships and financial aid are mostly only available for formal education programs. Learners have limited opportunities to apply for financial support to earn nontraditional credits in informal learning contexts.

To overcome these challenges, future endeavors need to

• expand the value and meaning of badges outside their original context (Pitt et al., 2019);
• align micro/nanocredentials with competency-based assessment (Haughton and Sign, 2019);
• provide guidelines for what types of experiences should be credited with credentials and how to design different credentials (Tzou and Horstman, 2015);
• establish frameworks for at least developing a shared understanding of micro/nanocredentials and open recognition (Stefaniak and Carey, 2019);
• develop standards to account for privacy concerns that remain a challenge when developing an open credential ecosystem (Reynolds, 2021); and
• mediate discussions on where and how metadata associated with these credentials should be created, stored, and shared.

Proposed Research Agenda for Open Recognition

It is clear that open micro/nanocredentials and other forms of open recognition have been effective in accomplishing some outcomes at the micro and meso levels, with other instances of challenges, unresolved issues, and mixed results. In addition, it is still uncertain how to integrate the concept of open recognition within macro systems. This presents many opportunities for researchers to further study the potential of these technologies and their effects on learners, teachers, institutions, and systems.

In reviewing the research, as an example, there are several gaps. First, there is a need for more research at each of the 3M levels: micro, meso, and macro. In their review of the current literature, West and Cheng (2022) reviewed the research published in the past decade at each of the 3M levels. They concluded that we still know little about the potential and pitfalls of open credentials. Instead, most of the literature reports personal reflections on use cases instead of actual research into effectiveness. Much of the research that does exist is on professional development, particularly for primary and secondary teachers.

In addition, a great deal of research focuses on applying microcredentials as part of a transition to a skills-economy mindset, with credentials recognizing discrete skills that are often technical in nature. In addition, open credentials can support research into Prior Learning Assessment and Recognition, which also focuses on a transition to a skills-economy. However, fewer research studies have investigated the applicability of open micro/nanocredentials in other domains. As an example, open credentials have the potential to recognize personal factors beyond just acquired skills—including interests, behaviors, self-directed learning, and the cascading of learning experiences that emerge from explorative learning. In addition, open recognition may have the potential to grow and build trust, identity, and connection within learning communities However, few studies exist on the challenges and benefits, or even the implementation, of this potential.

Conclusion

Open recognition practices have the potential to be a major disruptive innovation in education, particularly because public confidence in traditional educational credentials is waning. Levine and Van Pelt (2021) reported that only half of Americans now consider a college degree to be important and 60% believe graduates lack specific job skills. Meanwhile micro/nanocredentials are growing in popularity. For example, over 30 million people are now registered on edX for microdegree programs (Marcus, 2020), 43 million Open Badges were issued as of 2020 (see https://openbadges.org/), and an increasing number of universities are developing their own microcredentials (including 88% of universities in an Australian sample, according to McGreal and Olcott Jr., 2022).

These are challenges that open recognition is well positioned to address. First, open credentials can be earned inside colleges/universities but also in other organizations, allowing for more people to learn, grow, and earn credentials whether they choose to attend a university or not. Second, open credentials are uniquely positioned to report on specific skill/abilities precisely because they can be issued at the competency level rather than the course level. Finally, open credentials can recognize a variety of skills often forgotten in traditional education, such as social/soft/career skills. As Oblinger (2016) noted, “As the world has changed around us, our notions of what it means to be educated have evolved as well. Intellectual skills are a must in today’s world, but so too are interpersonal skills” (p. viii).

However, potential does not equal outcomes, especially in education. The history of education is fraught with failed innovations that never disrupted learning institutions as promised. One reason why this happens is that new ideas, strategies, and technologies are not considered at all three of the 3M levels of implementation. Without designing effective strategies for individual teachers and learners, it is unlikely that an innovation will be successful. But similarly, failure to reform the educational institutions and the interfaces with society at large will similarly cause an innovation to fail.

References

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Council of Europe. (2023). Formal, non-formal, and informal learning. https://www.coe.int/en/web/lang-migrants/formal-non-formal-and-informal-learning 

Gallagher, S. R. (2022). The future of university credentials: New developments at the intersection of higher education and hiring. Harvard Education Press.

MIRVA. (2020). Open recognition framework. https://mirva.openrecognition.org/wp-content/uploads/sites/3/2020/08/O1-Open-Recognit

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