Abstract:

Formative assessment has proven an effective strategy to enhance learning achievements. Stepping ahead from the arid viewing of conventional classroom evaluation practices, the underlying principles and scope of formative assessment can help higher education (HE) learners to acquire transversal competencies.
There is evidence of student engagement with formative assessment processes. These include frequent and prospective feedback, peer and self-assessment, formative use of tests by error analysis, classroom dialogue, and critical reflection. We are aware of the effort to incorporate all these pedagogical elements in the university classroom, and that is why our research aims to design a formative assessment process aided by Artificial Intelligence (AI).
HE is undergoing a continuously changing context speeded up by digital transformation and the AI outbreak. Studies informing educators about how AI can be used in HE are essential at this moment because our students are already using it, which is starting to change the game rules and teaching-learning approaches.
Affordances of AI would help us to design AIFORA, an innovative tool to integrate formative assessment processes in HE. This tool would allow us to adapt challenge-based learning through modules: (i) diverse itineraries depending on dissimilar types of learners, (ii) student profiles based on their motivation level, tastes, and frustration tolerance, (iii) chatbots to give prompt feedback, (iv) rubrics, (v) tests with calibrate grading, (vi) portfolios, and (vii) complete competences reports. AIFORA aims at monitoring the acquisition of the transversal competencies: communication, teamwork, and learning to learn, by HE first-year degree learners.
Since the transition from Secondary School to HE is abrupt, early student support seems necessary to enable their success. University freshmen must acquire and develop the above-mentioned transversal competencies. The debate about how formative assessment may help HE students to meet the expected competencies, particularly transversal skills, is open. In this regard, the AIFORA tool is intended to help instructors to reconcile formative assessment and active learning drawing on AI benefits. We enumerate some AI desirable features, included in the AIFORA tool, that may help achieve this purpose.
In this work, we raise a question on how AI can also help instructors to follow up with learners, and reflect on a feasible way to apply the AI features to enhance a formative assessment process for first-year degree students. The purpose is to benefit from the AI functionalities to strengthen a more robust and fruitful evaluation approach that can impact significantly teaching and learning and compensate for the shortcomings implied by freshmen competencies.
We conclude that with the AI upheaval, the HE is to give a step forward to the education of the future, which is mainly digital, not only technologically, but also in how students study autonomously and communicate with instructors or among them. AI tools may transform and replace tutorial sessions but there is much field for improvement regarding online exams because of the capabilities of AI and digital media available. Some features and strategies have come to stay so it is time to reflect on the risks and challenges of AI and clarify how instructors take advantage of it.

Keywords:

Artificial intelligence, formative assessment, higher education, intelligent tutoring systems, transversal competencies, AIFORA.