Identifying the assessment indicators which can facilitate the provision of personalized learning has been a long-term topic of discussion and debate. Several studies have emphasized on the important role that Information and Communication Technology solutions can play in closing this gap whereas, the recent pandemic outbreak, strengthened even more the necessity to introduce educational solutions capable for supporting Blended Learning scenarios. To tackle this obstacle, educators adopted various solutions including Learning Management System and Virtual Reality educational platforms. Recent reviews have revealed that examining students’ learning artifacts from a single solution, in isolation, may not be comprehensive enough to extract information and, therefore, provide holistic support for academic knowledge growth and skillset advancement. The introduction of multimodal assessments can potentially counter this issue and accordingly assist educators in providing personalised educational interventions. With that objective in mind, we propose an integrated Multimodal Learning Analytics (MMLA) framework which aims at orchestrating and classifying students’ personality traits, behavioral effects, academic performance, and practical skills simultaneously. The present work constitutes part of a wider effort which aims at providing Higher Education students with personalised and adaptive learning experiences to prepare and equip them with the qualities and the skills that the Industry 4.0 demands.