01. Dezember 2023
Is it an exaggeration at this time in our world to suggest that we crave truth and authenticity? That both democracy and integrity currently suffer from the “toxic sludge” (Ressa, 2023) of mistruths and deception practiced by big tech, governments, and social media? As António Guterres of the United Nations warns, “Our world is becoming ‘unhinged’” (Guterres, 2023).
This dire macro assessment of our current 21st century world can equally be applied to the field of education as we enter an era of uncertainty brought about by artificial intelligence (AI), reduced funding, and shaky global economies. In this latter half of 2023, higher education scholarship is rife with research that attempts to deconstruct the effects of AI on learning and assessment.
This brief blog post’s intent is to discuss the unexplored and perhaps misunderstood potential of, not AI, but rather of a different learning tool, the recognition of prior learning (RPL) or prior learning assessment (PLAR), these being the most popular of the many names assigned to this protocol around the world. Long overlooked by much of the educational field, it will be even more overlooked now as AI takes the stage, front and centre. However, “too often, today’s AI technologies are used in ways that constrain learner agency, focus on ‘close-ended’ problems, and undervalue human connection and community” (Resnick, 2023). RPL, on the other hand, offers exactly the opposite.
Thus, I will dismiss AI upfront in this paragraph and turn this discussion to the topic at hand, RPL. AI is touted as having both positive and negative effects on educational processes, including assessment. It must be noted, however, that the gains potentially achieved with the introduction of AI pertain largely to increasing the accuracy of using technologies to conduct traditional testing protocols, processes that promote rote learning and recall, and cheating. That said, “the point at which technology can completely replace human teachers is still quite some way off, and humans will play a critical role in creating the best possible experience for everyone for many years to come” (Gilbert, 2023).
I should note here that although RPL processes are widely used in many countries around the world (and also feature many different labels in addition to PLAR and RPL), the perspective described here is primarily North American.
Authentic learning and authentic assessment co-exist compatibly in a constructivist learning environment. Authentic learning seeks to situate learners’ knowledge in the real world with an eye to application and connection (Herrington, Reeves & Oliver, 2014). Authentic assessment complements and arises from that approach, and both should contain these elements: collaboration and collegiality – among learners; and communication – among learners and between teacher and learners.
Group work, immediate and plentiful feedback, and a comfortable and safe learning environment go a long way toward ensuring the three “Cs” listed above. Authenticity, however, is a more difficult achievement. Authentic assessment encourages and rewards learner agency and counters, to varying degrees, the ills of rote learning and, importantly, cheating. Authentic assessment asks learners to respond to assignments from a personal or experiential space while making the necessary and relevant connections to the curriculum at hand. As such, the recognition of prior learning provides the ideal opportunity for learners to draw upon their experiential learning in an authentic practice while conforming to an institution-provided framework. RPL affords great value to both learners and institutions. Learners value, on a practical level, gaining recognition and program credit for the learning that they have already accomplished outside of a formal institution. In most cases, there is also a substantial cost benefit. Receiving acknowledgement of their prior experiential learning also boosts confidence and self-esteem.
Institutions offering RPL as a process benefit from attracting students who might otherwise not choose to slog through an entire program that asks them to learn material that they have already learned in the workplace and manifested over the years. Importantly, working with RPL awakens academics to the value of learning that has not come from their textbooks. Sadly, the latter has been difficult to accept for much of the higher education professoriate.
There are many possible reasons for the tepid acceptance of RPL in higher education; the remainder of this piece will deal with what I consider the most important one, that is the issue of academic quality, which, ostensibly, is always the prime concern of the academy. In constructing a rigorous RPL system, it is imperative to understand that the process is academic and not administrative; that is, RPL differs from transfer of credit or advanced credit in that it is not an appraisal of “work done” at another institution and subsequently applied to a student’s program. This administrative work is usually performed by the Registrar or university Registry.
On the contrary, a rigorous RPL process requires academic leadership and hands-on academic assessment. What is being assessed, by appropriate academic personnel, is the careful and methodical demonstration of learning by the applicant. Such a demonstration of learning is usually presented in a structured portfolio – an e-portfolio these days – following a template that requires a triad of parts: an autobiographical text that highlights the applicant’s relevant learning history; a series of carefully structured responses, called “learning statements,” to course or program outcomes, intended to show the applicant’s understanding of the learning outlined by those outcomes; and a presentation of data to support the purported learning. Such data may take the form of letters from appropriate personnel (supervisors, managers, not family or friends); documents outlining achievements; or products created by the applicant such as videos, scripts, media publications, etc. It is important to note that such documents are for evidential triangulation only and are not intended to, by themselves, serve as “proof” of learning.
The heart of the cognitive process in RPL lies in the learning statements which can be written in response to either course or program outcomes that are made available to applicants. These statements must be terse declaration of learning that are based on, often, Bloom’s Taxonomy, whereby levels of learning can be discerned. For example, “knowing” a fact sits at the bottom of the knowledge scale, while “creating” a connection or “evaluating” a supposition or a connection places very highly on the cognitive scale. The assessor, who ideally should be an expert in the academic area being contested, asks the following questions: " “At what level should this particular piece of knowledge be? Is it acceptable as just statement of fact? Should it demonstrate comprehension? Or should it demonstrate a synthesis of ideas?”
Obviously, this very stringent and detailed level of structure poses a challenge to the applicant. It is imperative, therefore, to have, within the institutional RPL process, a coach or mentor function that is filled by very skilled personnel who can guide applicants through the process as they prepare their portfolio. Between the RPL unit or department – however it is set up within the institution – and the academic assessors, the mentors, and the administrative office that receives and transcripts the results of the assessment, it is clear that a well-managed RPL process is an inclusive process with ample checks and balances along its academic journey. It is a pan-institutional effort and must be internally promoted and recognized as such.
In summary, the authenticity of this assessment protocol builds on individual students’ experiential learning and their resultant sense-making, applied within a framework that is set by the institution and validated by academic personnel. A rigorous RPL process brings applicants’ experiential learning to the fore and integrates it into curricular-based learning. In fact, a criticism of RPL by some of its advocates complains that, thus constructed, RPL is too restrictive and too dismissive of some experiential learning that could be considered worthy of acknowledgement. The author understands this view and is sympathetic, to a degree, while pragmatically respecting institutional concerns.
I have briefly outlined, above, a rationale for implementing an RPL process in institutions of higher education. It is not possible to describe here the many aspects of an entire process, and I recognize that processes will differ among practicing institutions in order to comply with institutional policy, mission, and resources. However, the value to learners is undeniable on both pedagogical and practical fronts.
 Some of the labels use for recognizing prior learning include Assessment of Prior Experiential Learning (APEL), Assessment of Prior Learning (APL), PLA (Prior Learning Assessment), RCC (Recognition of Current Competence), Recognition of Non-formal and Informal Learning (RNFIL), and Validation des Acquis des Experiences (VAE). There are others.
 In a holistic sense, recognizing learners’ prior learning can also be used in the workplace as “gap training” to complete a worker’s skill set. An effective skill-based program would identify critical gaps in a skill set and then adapt and integrate appropriate training using RPL protocols. Whereas universities apply RPL processes toward the attainment of a credential, usually an undergraduate degree, gap training identified by RPL is commonly conducted at technical schools or community colleges.
 Current literature suggests that the prime goal of many higher education institutions is to find employment for their graduates. This position is well documented in my forthcoming edited book, Portraits of Academic Life within Higher Education: From Hiring to Retiring (2024).
Gilbert, C. (2023): Trends in E-Assessment: Is AI the Future of Online Assessment? Cirrus. https://cirrusassessment.com/trends-in-e-assessment-is-ai-the-future-of-online-assessment/#:~:text=AI%20in%20online%20assessment&text=It%20can%20also%20assist%20with,setting%20better%2C%20more%20effective%20exams (letzter Aufruf am 28.11.2023).
Guterres, A. (2023): Secretary-General's address to the General Assembly. 78th Session of the United Nations General Assembly. https://www.un.org/sg/en/content/sg/speeches/2023-09-19/secretary-generals-address-the-general-assembly (letzter Aufruf am 28.11.2023).
Herrington, J.; Reeves, T. C; Oliver, R. (2014): Handbook of research on educational communications and technology. Springer, New York.
Resnick, M. (2023): AI and Creative Learning: Concerns, Opportunities, and Choices. Medium. https://mres.medium.com/ai-and-creative-learning-concerns-opportunities-and-choices-63b27f16d4d0 (letzter Aufruf am 28.11.2023).
Ressa, M. (2021): Nobel Lecture. The Nobel Foundation, Stockholm. https://www.nobelprize.org/prizes/peace/2021/ressa/lecture/ (letzter Aufruf am 28.11.2023).
Views expressed in this blog are those of the authors and do not necessarily reflect those of HRK. Your point of view is different, or you would like to discuss a topic? Then please send us your contribution to firstname.lastname@example.org.