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ESCP Business School transforms itself by testing Adaptive Learning

As part of the School transformation plan, the Phygital Factory of ESCP Business School has launched this year a collaboration with the EdTech start-up Domoscio in order to implement an Adaptive Learning approach. ESCP newly Associated Dean of Learning Innovation: José Ramon Cobo in tandem with the school’s Chief Digital Officer: Anthony Hié, is moving forward in rethinking student pathways and experiences.

A “Phygital” transformation plan in line with students’ needs.

In 2019, ESCP Business School launched its “Phygital” transformation plan: “So’SCHOOL”, including some forty projects. All of them aim to transform the learning experience by offering new, bold and innovative digital services. A number of these projects are currently being driven by ESCP Business School’s digital & learning innovation cluster in a structure dedicated to experimentation: the Phygital Factory. It is within this framework that Domoscio and ESCP Business School have launched a collaboration on Adaptive Learning.
“As every teacher knows, there is no student equal to another. Each of them has its own characteristics, peculiarities, abilities and weaknesses, and broad-based learning approaches could be ineffective to embrace this complexity over the long term. Adaptive Learning is an educational system based on technology and data analysis, allowing teachers to track students’ performance and adjust methods and programs to each student’s needs.” Says José Ramon Cobo.
The objective of this collaboration is to deploy on test an Adaptive Learning solution on the Executive MBA, as it is a program with high attractiveness stakes. In addition, all of the project’s stakeholders – professors, academic managers and project team – are convinced that the individualization of the training experience will bring a real benefit to the program participants throughout their training and beyond.

An enhanced and individualized student experience, even for distance learning

According to Anthony Hié, “Adaptive learning is using the benefit of AI & bigdata for students to create the best possible online learning experience!”. With blended (physical and digital) and modular pedagogical activities, the challenge is to provide students with a tailor-made experience throughout their time at the school, allowing them to reach their learning objectives* in the best possible way. With Domoscio, the students’ learning data is processed using Artificial Intelligence technologies to determine their profile and pedagogical needs (known as Learning Analytics), and to build the most relevant learning path for them. Concretely, the students are enrolled in learning objectives according to their curriculum or wishes*. The Adaptive Learning system aims to find the best path for the student according to his or her profile. For this, two elements are essential.

• The implementation of a multimodal and continuous assessment strategy: among the types of data used by Adaptive Learning, assessment data is essential because it will measure the students’ mastery and progress towards their learning objectives throughout the course in order to estimate the skills gap. This data comes for example from positioning tests, online quizzes, grades… but also from the teacher’s evaluation of the skills that the student is able to apply in the context of projects.
• The implementation of a recommendation engine: once the students’ level has been positioned in relation to their learning objectives, Adaptive Learning can provide recommendations of pedagogical activities adapted to their individual needs. These recommendations will support the students in their progress by building a logical, optimal and blended path: it will thus be possible to alternate face-to-face courses or projects, virtual classrooms, MOOCs, micro-learning materials, digital remediation resources, etc.

In use, the interest of Adaptive Learning is even to implement a predictive approach: (1) depending on the experiences and profile of the students, we can group them into homogeneous groups; (2) for each group, we measure a posteriori the pedagogical impact of a resource on the students’ progress; (3) in this way, Artificial Intelligence can determine that if a student resembles the typical profile of a given group, then the learning material that worked well for that group will also work for that student.

Implications of adaptive learning for Business and Management Education

Nowadays, students have a diverse learning and knowledge background when attending a class. It comes naturally to think that progression in Higher Education institutions should not only consider scholars’ age and time spent in class but should be more focused on proficiency. In addition to give students the right time to maximize their efficiency and engagement, there are other significant implications in putting into practice Adaptive Learning. Think about how useful it would be for teachers to get real-time analytics about their class’ performance, emerging struggles and successful activities. Thanks to automated data analysis, they could promptly intervene on critical issues and adjust their method to solve them. Here are some opportunities of Adaptive Learning for ESCP Business School:

(1) Identifies competency gaps: across every discipline, identifying and remediating competency gaps is crucial. However, in many cases, students are not aware of the gaps in their understanding. Adaptive Learning uses a question-based approach (or situational questions, depending on the competence to evaluate) to understand what the students know and where the gaps are.

(2) Tailor-made focused training by providing focused attention to every individual student. It also offers personalized feedback to the students, which enables them to understand the concepts better;

(3) Adjusts to different learning styles: unlike the one-size-fits-all courses that could intimidate some groups of students, Adaptive Learning is suitable for all kinds of students, irrespective of whether they possess a beginner, intermediate, or advanced knowledge of the concepts;

(4) Updates when information changes: one of the crucial challenges when designing learning content is to provide the most up-to-date material. When a teacher introduces changes to the course, the system can differentiate between the material a student has already covered and new areas to master.

A first pilot launched in the first semester of 2021 on Executive Education

Initiated in June 2020, the collaboration between ESCP Business School and Domoscio first led to an audit of the existing tools, data and content in the ESCP course catalogue. Following this audit, ESCP Business School decided to implement a pilot project starting in Spring 2021 on Executive Education programs. As part of the pilot, the Domoscio Hub portal will be integrated into the learning system of the ESCP Executive Education branch and will allow to index a set of learning materials hosted on the different platforms used: Blackboard, FUN or Coursera, for example. The system implemented for this pilot will allow ESCP and Domoscio to validate the learning experience, involve teachers in these new methods and confirm the impacts of Adaptive Learning. Subsequently, in the event of a large-scale deployment, ESCP will be able to replicate the actions carried out on other programs. Adaptive Learning will then be integrated into the ESCP Phygital Factory. See you in the Summer of 2021 for the first results.

*A learning objective is a set of knowledge or skills that the learner must acquire with a given level of mastery.