nnovation of Business Models Through the Use of Competency-Based Education Platforms
The role of competency-based education (CBE) is gaining increasing attention in the digital age. According to Gartner, CBE is being considered as a possible breakthrough in redefining student learning with disruptive impacts on the institutional business model. The Harvard Business Review, however, reported that competencies themselves are not new. Some schools have been delivering competency-based education offline for decades, but without a technological enabler, the offline curriculum has not been able to take full advantage of what competencies have to offer.
Despite this growing relevance of CBE, no complete solution exists yet in the market. Therefore, the objective of this study is to assess potentially relevant CBE platforms by presenting the current advances in this field from prestigious consulting firms, such as Gartner, and publishers, such as the Harvard Business Review, as well as of other relevant players in this field.
This paper presents a list of solutions vendors that have popped up recently. Finally, the paper also presents two indicators that can help us understand the state of CBE in the market. The first one released by American Institute of Research refers to the factors that have helped or hindered the adoption of CBE in institutions, and the second one attests that most institutions are confident about the future of CBE.
Keywords: CBE, platform, education, competency, business model
Competency-based education (CBE) “is gaining momentum and being considered [as] a possible breakthrough in redefining student learning with disruptive impacts on the institutional business model” (Gartner, 2015).
The potential business impact of CBE is enormous. CBE has the potential to increase the scalability of learning while enhancing the skills gaps through personalization (Gartner, 2018a). Broadly speaking, CBE “identifies explicit learning outcomes when it comes to knowledge and the application of that knowledge” (Harvard Business Review, 2014).
According to Harvard Business Review (2014), “competencies themselves are nothing new. There are schools that have been delivering competency-based education offline for decades, but without a technological enabler, offline programs have not been able to take full advantage of what competencies have to offer.” Although no complete solution exists yet in the market, we need to assess potentially relevant CBE technology. This paper aims to describe the innovative initiatives that schools, and enterprises can adopt for their business models through the use of CBE platforms.
To fulfill the abovementioned objective, we conducted a thorough literature review. Papers published by consulting firms and publishers were analyzed. The paper is divided into the main aspects of competency-based education, which delves into the basics of Adaptative Learning Platform, the use of artificial intelligence in chatbot for education, barriers, and the future in CBE. It also opens a topic to present a small list of CBE vendors. The last section summarizes the main findings of the study and provides useful recommendations.
The overall objectives of this literature review section are to establish the significance of the general field of study of business models through the use of CBE platforms and to subsequently identify an area where a new contribution could be made.
CBE is a way of organizing instruction based on the learner’s acquisition or possession of specified competencies rather than on the seat time (Gartner, 2018a). CBE instructors seek to provide less shared and more individualized learning experiences in which learners learn at their own pace and then, after mastering a topic, move forward (Wiley Online Library, 2017). CBE platforms “support this instruction, with systems that allow students to advance through courses at their own pace, and with enhanced assessment functions to build and test their competencies” (Gartner, 2018a).
According to Soares (2012), “advances in cognitive science, software engineering, and human-computer interaction are all making it possible to use technology to create web-based education environments that both support the learning process at a granular level and assess student progress along the way.”
In this context, according to Gartner (2018a),
Emotion AI, Adaptive Learning Platforms and Artificial Intelligence Education Applications are ranked as transformational for their ability to bring education in a new form to learners. They build on vast amounts of data that can help make a direct, positive impact on learning for the individual student, thus contributing directly to the core mission education.
Figure 1. Priority matrix for education, 2018.
Adaptive learning platforms. Harvard Business Review (2019) stated that
over the past two decades the internet has reshaped our daily lives and the world of business – so it is not surprising that it is transforming how companies develop talent. The emergence of a ‘personal learning cloud’ makes it convenient and affordable for people to access new ways to learn.
This is now possible, thanks to adaptive learning, which is a “computer-based and/or online educational platform that modifies the presentation of material in response to student performance” (Dream Box, 2019).
the ultimate aim of adaptive learning in education is to enhance the learning experience and empower students. These changes will result in tangible results such as improved learning outcomes, higher retention rates and better graduation rates, all of which are necessary accountability measures in education.
“NASA also uses adaptive learning technology for simulation training and in safety models, and various branches of the U.S. military have also used it to train and educate soldiers for asymmetric warfare” (Dream Box, 2019).
Figure 2. Intelligent adaptive schema.
AI Chatbots in education applications. Students who attend the same class have different skills, interests, and abilities. Therefore, they need personal tutors who can provide one-on-one lectures (Srdanovic, 2017). Because of their conversation-based user interface, chatbots can become very much present in students’ interactions with information and contents, acting as intermediaries. In online learning environments, chatbots provide an element of interactivity (Bii, 2013). A recent Gartner (2018b) survey indicated that some higher education institutions are implementing AI technology with chatbots at different levels and forms. In education, chatbots can usually be distinguished into two types: those that do not have educational intentionality and those that have (Garcia, Fuertes, & Molas, 2018).
“Without educational intentionality: these are chatbots that are incorporated into teaching tasks of an administrative nature (student guidance and personal assistance) and of a support nature (to answer FAQs)” (Garcia et al., 2018).
“With educational intentionality: these are chatbots designed to foster teaching and learning directly (tutors that provide scaffolding for the learning process, exercise and practice programs for skills acquisition)” (Garcia et al., 2018).
Figure 3. Chatbot classification according to peer educational intentionality.
Note: Adapted from Garcia et al. (2018).
Indicators are, simply put, the ways we come to understand the inputs and outcomes of a program or project that we may or may not be able to observe directly (Kozma & Wagner, 2004). This section presents a small list of indicators that should help as a supportive tool when evaluating educational programs and projects.
Representative learning platform vendors. The figure below represents a few market vendors that offer higher education-based learning platforms.
Figure 4. Representative software vendors for proprietary platforms.
Barriers to CBE implementation. CBE may be a less conventional approach to teaching and learning, and program leaders may encounter local barriers to implementation on their campuses, ranging from institutional processes and infrastructure to stakeholders. The table below presents the factors that have helped or hindered the adoption of CBE among institutions:
Table 1. CBE adoption among institutions
Note: Adapted from American Institute of Research (2018c).
Future of CBE. According to the American Institute for Research (2018),
the future of CBE is likely to be influenced by the ability of schools and software providers to remove or bypass impediments to execution. However, the inclination of organizations to expand existing CBE programs or develop new ones plays an equally important role in CBE’s growth over time.
Exhibit 6. The intention of adoption of competency-based education, 2018.
Note: Adapted from American Institute for Research (2018).
The purpose of this paper is to present the findings of our study on the different aspects of the use of competency-based education platforms. The first part of the paper presented the basic concepts of competency-based education through the vision of important market consultants, publishers and specialists. At this point, were presented a big picture of emerging CBE technologies with a brief description of where these CBE technologies can be applied and how these trends allow institutions enhance their business models or even create new business opportunities. In this context, among the presented tendencies, it was highlighted opportunities of using tools like artificial intelligence and chatbots within the educational platform, as well as some of its functional aspects related to the chatbot’s intentionalities. The paper also presented a short list provided by Gartner with third party solutions to assist in future analysis and acquisition. Finally, the study concludes with the presentation of two indicators built by the American Institute of Research where it was possible to evaluate the main opportunities and barriers seen by schools regarding the adoption of CBE platforms. The second indicator suggested that there are increasing opportunities when adopting CBEs in institutions in an time windows of 2 to 4 years.
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